|
1
|
Demers J, Fagan WF, Potluri S, Calabrese JM. Testing-isolation interventions will likely be insufficient to contain future novel disease outbreaks. Math Biosci 2025; 384:109432. [PMID: 40158773 DOI: 10.1016/j.mbs.2025.109432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2024] [Revised: 02/24/2025] [Accepted: 03/19/2025] [Indexed: 04/02/2025]
Abstract
Rapid identification and isolation of infected individuals with diagnostic testing plays a critical role in combating invasions of novel human pathogens. Unfortunately, unprepared health agencies may struggle to meet the massive testing capacity demands imposed by an outbreaking novel pathogen, potentially resulting in a failure of epidemic containment as occurred with COVID-19. Despite the critical importance of understanding the likelihood of such an outcome, it remains unclear how the particular characteristics of a novel disease will impact the magnitude of resource constraints on controllability. Specifically, is the failure of testing-isolation unique to COVID-19, or is this a likely outcome across the spectrum of disease traits that may constitute future epidemics? Here, using a generalized mathematical model parameterized for seven different human diseases and variants, we show that testing-isolation strategies will typically fail to contain epidemic outbreaks at practicably achievable testing capacities. From this analysis, we identify three key disease characteristics that govern controllability under resource constraints; the basic reproduction number, mean latent period, and non-symptomatic transmission index. Interactions among these characteristics play prominent roles in both explaining controllability differences among diseases and enhancing the efficacy of testing-isolation in combination with transmission-reduction measures. This study provides broad guidelines for managing controllability expectations during future novel disease invasions, describing which classes of diseases are most amenable to testing-isolation strategies alone and which will necessitate additional transmission-reduction measures like social distancing.
Collapse
Affiliation(s)
- Jeffery Demers
- Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rosendorf (HZDR), Görlitz, Germany; Department of Biology, University of Maryland, College Park, MD, United States.
| | - William F Fagan
- Department of Biology, University of Maryland, College Park, MD, United States
| | - Sriya Potluri
- Department of Biology, University of Maryland, College Park, MD, United States; Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Justin M Calabrese
- Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rosendorf (HZDR), Görlitz, Germany; Department of Biology, University of Maryland, College Park, MD, United States; Department of Ecological Modelling, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany
| |
Collapse
|
|
2
|
Huang Q, Kang L, Wei X, Gong C, Xie H, Li M, Wang Y, Dong M, Huang F. Epidemiology and genetic diversity of common human coronaviruses in Beijing, 2015-2023: A prospective multicenter study. Int J Infect Dis 2025; 158:107926. [PMID: 40379085 DOI: 10.1016/j.ijid.2025.107926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2025] [Revised: 04/14/2025] [Accepted: 05/05/2025] [Indexed: 05/19/2025] Open
Abstract
OBJECTIVES To investigate the epidemiological and genetic features of common human coronaviruses (HCoVs) in Beijing in the context of the COVID-19 pandemic. METHODS We collected clinical samples from patients with acute respiratory tract infections (ARTIs) in 35 sentinel hospitals from 2015 to 2023. HCoVs were detected via multiple real-time PCR, and S gene sequencing and phylogenetic analysis were subsequently performed. RESULTS From 2015 to 2023, the combined detection rate of HCoVs was 1.55% (909/58,550). During the COVID-19 pandemic, a significant increase in HCoVs detection was observed (P < 0.001). Overall, the epidemic season of four HCoVs was from July to October, and each HCoV showed different epidemic seasons. Notably, HCoV-NL63 and HCoV-229E exhibited pronounced annual alternations in prevalence. The highest combined detection rates of HCoVs were in the ≥60 years age group (1.85%), followed by the 0-5 years age group (1.48%). HCoV-229E was more prevalent in patients with severe community-acquired pneumonia (sCAP) (P = 0.001). Phylogenetic analyses revealed that the four HCoVs were subjected to negative selection pressure, and multiple high-frequency amino acid site mutations were observed. HCoV-229E formed an emerging lineage after 2021. CONCLUSIONS This nine-year multicenter study in Beijing systematically elucidated that the four HCoVs exhibit distinct epidemiological characteristics, susceptible populations, and common mutations in amino acid sites, especially in the context of COVID-19. Therefore, continuous epidemiological surveillance and genetic characterization studies are imperative for predictive warning and timely identification of emerging coronavirus.
Collapse
Affiliation(s)
- Qi Huang
- School of Public Health, Capital Medical University, Beijing, China; Beijing Center for Disease Prevention and Control, Beijing Academy for Preventive Medicine, Beijing Institute of Tuberculosis Control Research and Prevention, Beijing, China
| | - Lu Kang
- Beijing Center for Disease Prevention and Control, Beijing Academy for Preventive Medicine, Beijing Institute of Tuberculosis Control Research and Prevention, Beijing, China; Beijing Research Center for Respiratory Infectious Diseases, Beijing, China
| | - Xiaofeng Wei
- Beijing Center for Disease Prevention and Control, Beijing Academy for Preventive Medicine, Beijing Institute of Tuberculosis Control Research and Prevention, Beijing, China; Beijing Research Center for Respiratory Infectious Diseases, Beijing, China
| | - Cheng Gong
- Beijing Center for Disease Prevention and Control, Beijing Academy for Preventive Medicine, Beijing Institute of Tuberculosis Control Research and Prevention, Beijing, China; Beijing Research Center for Respiratory Infectious Diseases, Beijing, China
| | - Hui Xie
- Beijing Center for Disease Prevention and Control, Beijing Academy for Preventive Medicine, Beijing Institute of Tuberculosis Control Research and Prevention, Beijing, China; Beijing Research Center for Respiratory Infectious Diseases, Beijing, China
| | - Maozhong Li
- Beijing Center for Disease Prevention and Control, Beijing Academy for Preventive Medicine, Beijing Institute of Tuberculosis Control Research and Prevention, Beijing, China; Beijing Research Center for Respiratory Infectious Diseases, Beijing, China
| | - Yiting Wang
- Beijing Center for Disease Prevention and Control, Beijing Academy for Preventive Medicine, Beijing Institute of Tuberculosis Control Research and Prevention, Beijing, China; Beijing Research Center for Respiratory Infectious Diseases, Beijing, China
| | - Mei Dong
- Beijing Center for Disease Prevention and Control, Beijing Academy for Preventive Medicine, Beijing Institute of Tuberculosis Control Research and Prevention, Beijing, China; Beijing Research Center for Respiratory Infectious Diseases, Beijing, China
| | - Fang Huang
- School of Public Health, Capital Medical University, Beijing, China; Beijing Center for Disease Prevention and Control, Beijing Academy for Preventive Medicine, Beijing Institute of Tuberculosis Control Research and Prevention, Beijing, China; Beijing Research Center for Respiratory Infectious Diseases, Beijing, China.
| |
Collapse
|
|
3
|
Mulondo J, Nayiga S, Nuwagaba W, Nayebare P, Namuganga JF, Ssewanyana I, Kamya MR, Nankabirwa JI. Optimizing the Use of SARS-CoV-2 Antigen Rapid Diagnostic Tests for the Timely Detection of and Response to COVID-19 in Schools and Markets in Uganda. Am J Trop Med Hyg 2025; 112:71-78. [PMID: 39591649 PMCID: PMC11965717 DOI: 10.4269/ajtmh.23-0758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 09/20/2024] [Indexed: 11/28/2024] Open
Abstract
The early detection and management of infections is crucial to control epidemics. We evaluated the feasibility and utility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigen rapid diagnostic tests (Ag-RDTs) for the timely detection of and response to coronavirus disease 2019 in high-risk border communities in Uganda. Between May and September 2022, monthly cross-sectional surveys were conducted in 11 schools and two markets in two border districts. Only baseline and end-line testing were also performed in matched control communities. Antigen rapid diagnostic test results and demographic and clinical data were collected, and contacts of patients were traced and tested. All patients were advised to self-isolate, and compliance was assessed on day 5. We enrolled 10,406 participants out of 10,472 screened individuals. The participants had a 1.3% test positivity rate, with schools recording higher, but non-significant, positivity rates than markets (1.4% versus 0.9%; P = 0.149). We tracked 556 contacts, and 536 (96.4%) agreed to test. The test positivity rate was significantly higher among contacts than the index participants (8.8% versus 1.3%; P <0.001). Only 55 (29.7%) of the index participants self-isolated effectively. Settings that received monthly testing had lower end-line positivity rates than controls (0.3% versus 1.4%; P = 0.001). Repeated SARS-CoV-2 Ag-RDT testing is feasible and could reduce SARS-CoV-2 infections. However, the participation in testing may have been enhanced by the compensation provided. Also, isolation was limited, which may reduce the impact of the intervention when rolled out on a large scale. Innovative strategies to increase the isolation of patients could improve the utility of early testing for transmission reduction during epidemics.
Collapse
Affiliation(s)
- Jerry Mulondo
- Infectious Diseases Research Collaboration, Kampala, Uganda
| | - Susan Nayiga
- Infectious Diseases Research Collaboration, Kampala, Uganda
| | | | | | | | | | - Moses R. Kamya
- Infectious Diseases Research Collaboration, Kampala, Uganda
- Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda
| | - Joaniter I. Nankabirwa
- Infectious Diseases Research Collaboration, Kampala, Uganda
- Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda
| |
Collapse
|
|
4
|
Gressani O, Torneri A, Hens N, Faes C. Flexible Bayesian estimation of incubation times. Am J Epidemiol 2025; 194:490-501. [PMID: 38988237 PMCID: PMC11815507 DOI: 10.1093/aje/kwae192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 05/14/2024] [Accepted: 07/03/2024] [Indexed: 07/12/2024] Open
Abstract
The incubation period is of paramount importance in infectious disease epidemiology as it informs about the transmission potential of a pathogenic organism and helps the planning of public health strategies to keep an epidemic outbreak under control. Estimation of the incubation period distribution from reported exposure times and symptom onset times is challenging as the underlying data is coarse. We developed a new Bayesian methodology using Laplacian-P-splines that provides a semiparametric estimation of the incubation density based on a Langevinized Gibbs sampler. A finite mixture density smoother informs a set of parametric distributions via moment matching and an information criterion arbitrates between competing candidates. Algorithms underlying our method find a natural nest within the EpiLPS package, which has been extended to cover estimation of incubation times. Various simulation scenarios accounting for different levels of data coarseness are considered with encouraging results. Applications to real data on coronavirus disease 2019, Middle East respiratory syndrome, and Mpox reveal results that are in alignment with what has been obtained in recent studies. The proposed flexible approach is an interesting alternative to classic Bayesian parametric methods for estimation of the incubation distribution.
Collapse
Affiliation(s)
- Oswaldo Gressani
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Data Science Institute Hasselt University, Hasselt BE-3500, Belgium
| | - Andrea Torneri
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Data Science Institute Hasselt University, Hasselt BE-3500, Belgium
| | - Niel Hens
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Data Science Institute Hasselt University, Hasselt BE-3500, Belgium
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaxinfectio, University of Antwerp, Antwerp BE-2000, Belgium
| | - Christel Faes
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Data Science Institute Hasselt University, Hasselt BE-3500, Belgium
| |
Collapse
|
|
5
|
McKendry R, Lemm NM, Papargyris L, Chiu C. Human Challenge Studies with Coronaviruses Old and New. Curr Top Microbiol Immunol 2024; 445:69-108. [PMID: 35181805 DOI: 10.1007/82_2021_247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Coronavirus infections have been known to cause disease in animals since as early as the 1920s. However, only seven coronaviruses capable of causing human disease have been identified thus far. These Human Coronaviruses (HCoVs) include the causes of the common cold, but more recent coronaviruses that have emerged (i.e. SARS-CoV, MERS-CoV and SARS-CoV-2) are associated with much greater morbidity and mortality. HCoVs have been relatively under-studied compared to other common respiratory infections, as historically they have presented with mild symptoms. This has led to a relatively limited understanding of their animal reservoirs, transmission and determinants of immune protection. To address this, human infection challenge studies with HCoVs have been performed that enable a detailed clinical and immunological analysis of the host response at specific time points under controlled conditions with standardised viral inocula. Until recently, all such human challenge studies were conducted with common cold HCoVs, with the study of SARS-CoV and MERS-CoV unacceptable due to their greater pathogenicity. However, with the emergence of SARS-CoV-2 and the COVID-19 pandemic during which severe outcomes in young healthy adults have been rare, human challenge studies with SARS-CoV-2 are now being developed. Two SARS-CoV-2 human challenge studies in the UK studying individuals with and without pre-existing immunity are underway. As well as providing a platform for testing of antivirals and vaccines, such studies will be critical for understanding the factors associated with susceptibility to SARS-CoV-2 infection and thus developing improved strategies to tackle the current as well as future HCoV pandemics. Here, we summarise the major questions about protection and pathogenesis in HCoV infection that human infection challenge studies have attempted to answer historically, as well as the knowledge gaps that aim to be addressed with contemporary models.
Collapse
Affiliation(s)
- Richard McKendry
- Department of Infectious Disease, Imperial College London, London, UK
| | - Nana-Marie Lemm
- Department of Infectious Disease, Imperial College London, London, UK
| | - Loukas Papargyris
- Department of Infectious Disease, Imperial College London, London, UK
| | - Christopher Chiu
- Department of Infectious Disease, Imperial College London, London, UK.
| |
Collapse
|
|
6
|
Wang G, Venegas FA, Rueda AM, Weerasinghe NW, Uggowitzer KA, Thibodeaux CJ, Moitessier N, Mittermaier AK. A naturally occurring G11S mutation in the 3C-like protease from the SARS-CoV-2 virus dramatically weakens the dimer interface. Protein Sci 2024; 33:e4857. [PMID: 38058248 PMCID: PMC10731504 DOI: 10.1002/pro.4857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 11/22/2023] [Accepted: 12/01/2023] [Indexed: 12/08/2023]
Abstract
The 3C-like protease (3CLpro ) is crucial to the replication of SARS-CoV-2, the causative agent of COVID-19, and is the target of several successful drugs including Paxlovid and Xocova. Nevertheless, the emergence of viral resistance underlines the need for alternative drug strategies. 3CLpro only functions as a homodimer, making the protein-protein interface an attractive drug target. Dimerization is partly mediated by a conserved glycine at position 11. However, some naturally occurring SARS-CoV-2 sequences contain a serine at this position, potentially disrupting the dimer. We have used concentration-dependent activity assays and mass spectrometry to show that indeed the G11S mutation reduces the stability of the dimer by 600-fold. This helps to set a quantitative benchmark for the minimum potency required of any future protein-protein interaction inhibitors targeting 3CLpro and raises interesting questions regarding how coronaviruses bearing such weakly dimerizing 3CLpro enzymes are capable of replication.
Collapse
Affiliation(s)
- Guanyu Wang
- Department of ChemistryMcGill UniversityMontrealQuebecCanada
| | | | - Andres M. Rueda
- Department of ChemistryMcGill UniversityMontrealQuebecCanada
| | | | | | | | | | | |
Collapse
|
|
7
|
Liu S, Hu M, Liu X, Liu X, Chen T, Zhu Y, Liang T, Xiao S, Li P, Ma X. Nanoparticles and Antiviral Vaccines. Vaccines (Basel) 2023; 12:30. [PMID: 38250843 PMCID: PMC10819235 DOI: 10.3390/vaccines12010030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 12/19/2023] [Accepted: 12/22/2023] [Indexed: 01/23/2024] Open
Abstract
Viruses have threatened human lives for decades, causing both chronic and acute infections accompanied by mild to severe symptoms. During the long journey of confrontation, humans have developed intricate immune systems to combat viral infections. In parallel, vaccines are invented and administrated to induce strong protective immunity while generating few adverse effects. With advancements in biochemistry and biophysics, different kinds of vaccines in versatile forms have been utilized to prevent virus infections, although the safety and effectiveness of these vaccines are diverse from each other. In this review, we first listed and described major pathogenic viruses and their pandemics that emerged in the past two centuries. Furthermore, we summarized the distinctive characteristics of different antiviral vaccines and adjuvants. Subsequently, in the main body, we reviewed recent advances of nanoparticles in the development of next-generation vaccines against influenza viruses, coronaviruses, HIV, hepatitis viruses, and many others. Specifically, we described applications of self-assembling protein polymers, virus-like particles, nano-carriers, and nano-adjuvants in antiviral vaccines. We also discussed the therapeutic potential of nanoparticles in developing safe and effective mucosal vaccines. Nanoparticle techniques could be promising platforms for developing broad-spectrum, preventive, or therapeutic antiviral vaccines.
Collapse
Affiliation(s)
- Sen Liu
- Guangzhou National Laboratory, Guangzhou International Bio-Island, Guangzhou 510005, China; (S.L.); (M.H.); (X.L.); (X.L.); (T.C.); (Y.Z.); (T.L.); (S.X.); (P.L.)
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
| | - Meilin Hu
- Guangzhou National Laboratory, Guangzhou International Bio-Island, Guangzhou 510005, China; (S.L.); (M.H.); (X.L.); (X.L.); (T.C.); (Y.Z.); (T.L.); (S.X.); (P.L.)
- State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou 511400, China
| | - Xiaoqing Liu
- Guangzhou National Laboratory, Guangzhou International Bio-Island, Guangzhou 510005, China; (S.L.); (M.H.); (X.L.); (X.L.); (T.C.); (Y.Z.); (T.L.); (S.X.); (P.L.)
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
| | - Xingyu Liu
- Guangzhou National Laboratory, Guangzhou International Bio-Island, Guangzhou 510005, China; (S.L.); (M.H.); (X.L.); (X.L.); (T.C.); (Y.Z.); (T.L.); (S.X.); (P.L.)
| | - Tao Chen
- Guangzhou National Laboratory, Guangzhou International Bio-Island, Guangzhou 510005, China; (S.L.); (M.H.); (X.L.); (X.L.); (T.C.); (Y.Z.); (T.L.); (S.X.); (P.L.)
- State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou 511400, China
| | - Yiqiang Zhu
- Guangzhou National Laboratory, Guangzhou International Bio-Island, Guangzhou 510005, China; (S.L.); (M.H.); (X.L.); (X.L.); (T.C.); (Y.Z.); (T.L.); (S.X.); (P.L.)
| | - Taizhen Liang
- Guangzhou National Laboratory, Guangzhou International Bio-Island, Guangzhou 510005, China; (S.L.); (M.H.); (X.L.); (X.L.); (T.C.); (Y.Z.); (T.L.); (S.X.); (P.L.)
- State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou 511400, China
| | - Shiqi Xiao
- Guangzhou National Laboratory, Guangzhou International Bio-Island, Guangzhou 510005, China; (S.L.); (M.H.); (X.L.); (X.L.); (T.C.); (Y.Z.); (T.L.); (S.X.); (P.L.)
| | - Peiwen Li
- Guangzhou National Laboratory, Guangzhou International Bio-Island, Guangzhou 510005, China; (S.L.); (M.H.); (X.L.); (X.L.); (T.C.); (Y.Z.); (T.L.); (S.X.); (P.L.)
| | - Xiancai Ma
- Guangzhou National Laboratory, Guangzhou International Bio-Island, Guangzhou 510005, China; (S.L.); (M.H.); (X.L.); (X.L.); (T.C.); (Y.Z.); (T.L.); (S.X.); (P.L.)
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
- State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou 511400, China
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
| |
Collapse
|
|
8
|
Rysava K, Tildesley MJ. Identification of dynamical changes of rabies transmission under quarantine: Community-based measures towards rabies elimination. PLoS Comput Biol 2023; 19:e1011187. [PMID: 38100528 PMCID: PMC10756519 DOI: 10.1371/journal.pcbi.1011187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 12/29/2023] [Accepted: 11/13/2023] [Indexed: 12/17/2023] Open
Abstract
Quarantine has been long used as a public health response to emerging infectious diseases, particularly at the onset of an epidemic when the infected proportion of a population remains identifiable and logistically tractable. In theory, the same logic should apply to low-incidence infections; however, the application and impact of quarantine in low prevalence settings appears less common and lacks a formal analysis. Here, we present a quantitative framework using a series of progressively more biologically realistic models of canine rabies in domestic dogs and from dogs to humans, a suitable example system to characterize dynamical changes under varying levels of dog quarantine. We explicitly incorporate health-seeking behaviour data to inform the modelling of contact-tracing and exclusion of rabies suspect and probable dogs that can be identified through bite-histories of patients presenting at anti-rabies clinics. We find that a temporary quarantine of rabies suspect and probable dogs provides a powerful tool to curtail rabies transmission, especially in settings where optimal vaccination coverage is yet to be achieved, providing a critical stopgap to reduce the number of human and animal deaths due to rabid bites. We conclude that whilst comprehensive measures including sensitive surveillance and large-scale vaccination of dogs will be required to achieve disease elimination and sustained freedom given the persistent risk of rabies re-introductions, quarantine offers a low-cost community driven solution to intersectoral health burden.
Collapse
Affiliation(s)
- Kristyna Rysava
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, United Kingdom
| | - Michael J. Tildesley
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, United Kingdom
| |
Collapse
|
|
9
|
Wang R, Han Y, Zhang R, Zhu J, Nan X, Liu Y, Yang Z, Zhou B, Yu J, Lin Z, Li J, Chen P, Wang Y, Li Y, Liu D, Shi X, Wang X, Zhang Q, Yang YR, Li T, Zhang L. Dissecting the intricacies of human antibody responses to SARS-CoV-1 and SARS-CoV-2 infection. Immunity 2023; 56:2635-2649.e6. [PMID: 37924813 DOI: 10.1016/j.immuni.2023.10.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 08/25/2023] [Accepted: 10/11/2023] [Indexed: 11/06/2023]
Abstract
The 2003 severe acute respiratory syndrome coronavirus (SARS-CoV-1) causes more severe disease than SARS-CoV-2, which is responsible for COVID-19. However, our understanding of antibody response to SARS-CoV-1 infection remains incomplete. Herein, we studied the antibody responses in 25 SARS-CoV-1 convalescent patients. Plasma neutralization was higher and lasted longer in SARS-CoV-1 patients than in severe SARS-CoV-2 patients. Among 77 monoclonal antibodies (mAbs) isolated, 60 targeted the receptor-binding domain (RBD) and formed 7 groups (RBD-1 to RBD-7) based on their distinct binding and structural profiles. Notably, RBD-7 antibodies bound to a unique RBD region interfaced with the N-terminal domain of the neighboring protomer (NTD proximal) and were more prevalent in SARS-CoV-1 patients. Broadly neutralizing antibodies for SARS-CoV-1, SARS-CoV-2, and bat and pangolin coronaviruses were also identified. These results provide further insights into the antibody response to SARS-CoV-1 and inform the design of more effective strategies against diverse human and animal coronaviruses.
Collapse
Affiliation(s)
- Ruoke Wang
- Comprehensive AIDS Research Center, Center for Global Health and Infectious Diseases Research, NexVac Research Center, Center for Infectious Diseases Research, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing 100084, China; Tsinghua-Peking Joint Center for Life Sciences, Beijing 100084, China
| | - Yang Han
- Department of Infectious Diseases, Peking Union Medical College Hospital, Beijing 100730, China; State Key Laboratory for Complex, Severe, and Rare Diseases, Peking Union Medical College Hospital, Beijing 100005, China
| | - Rui Zhang
- Comprehensive AIDS Research Center, Center for Global Health and Infectious Diseases Research, NexVac Research Center, Center for Infectious Diseases Research, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Jiayi Zhu
- CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, National Center for Nanoscience and Technology of China, CAS, Beijing 100190, China
| | - Xuanyu Nan
- CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, National Center for Nanoscience and Technology of China, CAS, Beijing 100190, China
| | - Yaping Liu
- Comprehensive AIDS Research Center, Center for Global Health and Infectious Diseases Research, NexVac Research Center, Center for Infectious Diseases Research, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Ziqing Yang
- Comprehensive AIDS Research Center, Center for Global Health and Infectious Diseases Research, NexVac Research Center, Center for Infectious Diseases Research, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Bini Zhou
- Key Laboratory of Bioorganic Phosphorus Chemistry and Chemical Biology, Department of Chemistry, Tsinghua University, Beijing 100084, China
| | - Jinfang Yu
- The Ministry of Education Key Laboratory of Protein Science, Beijing Advanced Innovation Center for Structural Biology, Beijing Frontier Research Center for Biological Structure, Collaborative Innovation Center for Biotherapy, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Zichun Lin
- The Ministry of Education Key Laboratory of Protein Science, Beijing Advanced Innovation Center for Structural Biology, Beijing Frontier Research Center for Biological Structure, Collaborative Innovation Center for Biotherapy, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Jinqian Li
- Comprehensive AIDS Research Center, Center for Global Health and Infectious Diseases Research, NexVac Research Center, Center for Infectious Diseases Research, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Peng Chen
- Comprehensive AIDS Research Center, Center for Global Health and Infectious Diseases Research, NexVac Research Center, Center for Infectious Diseases Research, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Yangjunqi Wang
- CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, National Center for Nanoscience and Technology of China, CAS, Beijing 100190, China
| | - Yujie Li
- Key Laboratory of Bioorganic Phosphorus Chemistry and Chemical Biology, Department of Chemistry, Tsinghua University, Beijing 100084, China
| | - Dongsheng Liu
- Key Laboratory of Bioorganic Phosphorus Chemistry and Chemical Biology, Department of Chemistry, Tsinghua University, Beijing 100084, China
| | - Xuanling Shi
- Comprehensive AIDS Research Center, Center for Global Health and Infectious Diseases Research, NexVac Research Center, Center for Infectious Diseases Research, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Xinquan Wang
- The Ministry of Education Key Laboratory of Protein Science, Beijing Advanced Innovation Center for Structural Biology, Beijing Frontier Research Center for Biological Structure, Collaborative Innovation Center for Biotherapy, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Qi Zhang
- Comprehensive AIDS Research Center, Center for Global Health and Infectious Diseases Research, NexVac Research Center, Center for Infectious Diseases Research, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Yuhe R Yang
- CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, National Center for Nanoscience and Technology of China, CAS, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Taisheng Li
- Department of Infectious Diseases, Peking Union Medical College Hospital, Beijing 100730, China; State Key Laboratory for Complex, Severe, and Rare Diseases, Peking Union Medical College Hospital, Beijing 100005, China.
| | - Linqi Zhang
- Comprehensive AIDS Research Center, Center for Global Health and Infectious Diseases Research, NexVac Research Center, Center for Infectious Diseases Research, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing 100084, China; Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China; Institute of Biomedical Health Technology and Engineering, Shenzhen Bay Laboratory, Shenzhen 518132, China.
| |
Collapse
|
|
10
|
Kilpatrick AM. Ecological and Evolutionary Insights About Emerging Infectious Diseases from the COVID-19 Pandemic. ANNUAL REVIEW OF ECOLOGY, EVOLUTION, AND SYSTEMATICS 2023; 54:171-193. [DOI: 10.1146/annurev-ecolsys-102320-101234] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2025]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic challenged the workings of human society, but in doing so, it advanced our understanding of the ecology and evolution of infectious diseases. Fluctuating transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) demonstrated the highly dynamic nature of human social behavior, often without government intervention. Evolution of SARS-CoV-2 in the first two years following spillover resulted primarily in increased transmissibility, while in the third year, the globally dominant virus variants had all evolved substantial immune evasion. The combination of viral evolution and the buildup of host immunity through vaccination and infection greatly decreased the realized virulence of SARS-CoV-2 due to the age dependence of disease severity. The COVID-19 pandemic was exacerbated by presymptomatic, asymptomatic, and highly heterogeneous transmission, as well as highly variable disease severity and the broad host range of SARS-CoV-2. Insights and tools developed during the COVID-19 pandemic could provide a stronger scientific basis for preventing, mitigating, and controlling future pandemics.
Collapse
Affiliation(s)
- A. Marm Kilpatrick
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, California, USA
| |
Collapse
|
|
11
|
Yan Q, Shan S, Zhang B, Sun W, Sun M, Luo Y, Zhao F, Guo X. Monitoring the Relationship between Social Network Status and Influenza Based on Social Media Data. Disaster Med Public Health Prep 2023; 17:e490. [PMID: 37721020 DOI: 10.1017/dmp.2023.117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/19/2023]
Abstract
BACKGROUND This article aims to analyze the relationship between user characteristics on social networks and influenza. METHODS Three specific research questions are investigated: (1) we classify Weibo updates to recognize influenza-related information based on machine learning algorithms and propose a quantitative model for influenza susceptibility in social networks; (2) we adopt in-degree indicator from complex networks theory as social media status to verify its coefficient correlation with influenza susceptibility; (3) we also apply the LDA topic model to explore users' physical condition from Weibo to further calculate its coefficient correlation with influenza susceptibility. From the perspective of social networking status, we analyze and extract influenza-related information from social media, with many advantages including efficiency, low cost, and real time. RESULTS We find a moderate negative correlation between the susceptibility of users to influenza and social network status, while there is a significant positive correlation between physical condition and susceptibility to influenza. CONCLUSIONS Our findings reveal the laws behind the phenomenon of online disease transmission, and providing important evidence for analyzing, predicting, and preventing disease transmission. Also, this study provides theoretical and methodological underpinnings for further exploration and measurement of more factors associated with infection control and public health from social networks.
Collapse
Affiliation(s)
- Qi Yan
- Management School, Tianjin Normal University, Tianjin, China
| | - Siqing Shan
- School of Economics and Management, Beihang University, Beijing, China
- Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operation, Beijing, China
| | - Baishang Zhang
- Development Research Center of State Administration for Market Regulation of the PR China, Beijing, China
| | - Weize Sun
- School of Economics and Management, Beihang University, Beijing, China
- Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operation, Beijing, China
| | - Menghan Sun
- School of Economics and Management, Beihang University, Beijing, China
- Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operation, Beijing, China
| | - Yiting Luo
- School of Economics and Management, Beihang University, Beijing, China
- Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operation, Beijing, China
| | - Feng Zhao
- School of Economics and Management, Beihang University, Beijing, China
- Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operation, Beijing, China
| | - Xiaoshuang Guo
- School of Economics and Management, Beihang University, Beijing, China
- Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operation, Beijing, China
| |
Collapse
|
|
12
|
Nojiri S, Kawakami Y, Nakamoto D, Kuroki M, Nishizaki Y. Case fatality rate considering the lag time from the onset of COVID-19 infection to related death from 2020 to 2022 in Japan. IJID REGIONS 2023; 8:36-48. [PMID: 37361016 PMCID: PMC10149354 DOI: 10.1016/j.ijregi.2023.04.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 04/24/2023] [Accepted: 04/25/2023] [Indexed: 06/28/2023]
Abstract
Importance On an ecological scale, the lag time between coronavirus disease 2019 (COVID-19) infection and related fatality has varied between epidemic waves and prefectures in Japan. The variability in lag time across areas of Japan during the seven distinct waves can help derive a more appropriate estimation of the weekly confirmed case fatality rate (CFR) of COVID-19. Objective To estimate the 7-day moving average CFR across area block levels in Japan from February 2020 to July 2022 using the lag time between COVID-19 infection and related fatality. Main outcomes and measures The 7-day moving average CFR of COVID-19 for area blocks in Japan considering the lag time between infection and death (total and subgroup analysis of elderly). Results Lag time was found to vary substantially among prefectures in Japan from the first wave to the seventh wave of the COVID-19 epidemic. The estimated 7-day moving average CFR based on the lag time reflects the Japanese COVID-19 pandemic and related policy interventions (e.g. vaccination of elderly people) rather than other standard CFR estimations. Conclusions and relevance The variation in estimated lag time across prefectures in Japan for different epidemic waves indicates that it is inadequate to use the clinical results of the period from the start of infection to death for evaluation of the ecological scale of the CFR. Moreover, the lag time between infection and related fatality was found to be either shorter or longer than the clinically reported period. This revealed that preliminary reports of CFR may be overestimated or underestimated, even if they consider the lag based on clinical reports.
Collapse
Affiliation(s)
- Shuko Nojiri
- Clinical Translational Science, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Medical Technology Innovation Centre, Juntendo University, Tokyo, Japan
| | - Yuta Kawakami
- Clinical Translational Science, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Faculty of Engineering, Yokohama National University, Kanagawa, Japan
| | - Daisuke Nakamoto
- Clinical Translational Science, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Manabu Kuroki
- Faculty of Engineering, Yokohama National University, Kanagawa, Japan
| | - Yuji Nishizaki
- Clinical Translational Science, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Medical Education, Juntendo University Graduate School of Medicine, Tokyo, Japan
| |
Collapse
|
|
13
|
He J, Guo X, Pan C, Cheng G, Zheng M, Zi Y, Cui H, Li X. High-output soft-contact fiber-structure triboelectric nanogenerator and its sterilization application. NANOTECHNOLOGY 2023; 34:385403. [PMID: 37339612 DOI: 10.1088/1361-6528/acdfd5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 06/20/2023] [Indexed: 06/22/2023]
Abstract
Infectious diseases are spreading rapidly with the flow of the world's population, and the prevention of epidemic diseases is particularly important for public and personal health. Therefore, there is an urgent need to develop a simple, efficient and non-toxic method to control the spread of bacteria and viruses. The newly developed triboelectric nanogenerator (TENG) can generate a high voltage, which inhibits bacterial reproduction. However, the output performance is the main factor limiting real-world applications of TENGs. Herein, we report a soft-contact fiber-structure TENG to avoid insufficient friction states and to improve the output, especially at a high rotation speed. Rabbit hair, carbon nanotubes, polyvinylidene difluoride film and paper all contain fiber structures that are used to guarantee soft contact between the friction layers and improve the contact state and abrasion problem. Compared with a direct-contact triboelectric nanogenerator, the outputs of this soft-contact fiber-structure TENG are improved by about 350%. Meanwhile, the open-circuit voltage can be enhanced to 3440 V, which solves the matching problems when driving high-voltage devices. A TENG-driven ultraviolet sterilization system is then developed. The bactericidal rate of this sterilization system can reach 91%, which significantly reduces the risk of disease spread. This work improves a forward-looking strategy to improve the output and service life of the TENG. It also expands the applications of self-powered TENG sterilization systems.
Collapse
Affiliation(s)
- Jianwei He
- College of Materials Science and Engineering, Ocean University of China, Qingdao 266100, People's Republic of China
| | - Xuhua Guo
- College of Materials Science and Engineering, Ocean University of China, Qingdao 266100, People's Republic of China
| | - Caofeng Pan
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, People's Republic of China
| | - Gang Cheng
- Key Lab for Special Functional Materials of Ministry of Education, School of Materials Science and Engineering, Henan University, Kaifeng, 475004, People's Republic of China
| | - Mingli Zheng
- Key Lab for Special Functional Materials of Ministry of Education, School of Materials Science and Engineering, Henan University, Kaifeng, 475004, People's Republic of China
| | - Yunlong Zi
- Sustainable Energy and Environment Thrust, Hong Kong University of Science and Technology, Guangzhou, 510000, People's Republic of China
| | - Hongzhi Cui
- College of Materials Science and Engineering, Ocean University of China, Qingdao 266100, People's Republic of China
| | - Xiaoyi Li
- College of Materials Science and Engineering, Ocean University of China, Qingdao 266100, People's Republic of China
- Key Lab for Special Functional Materials of Ministry of Education, School of Materials Science and Engineering, Henan University, Kaifeng, 475004, People's Republic of China
| |
Collapse
|
|
14
|
Fellows IE, Handcock MS. Modeling of networked populations when data is sampled or missing. METRON 2023; 81:21-35. [PMID: 37284420 PMCID: PMC10199300 DOI: 10.1007/s40300-023-00246-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 03/22/2023] [Indexed: 06/08/2023]
Abstract
Networked populations consist of inhomogeneous individuals connected via relational ties. The individuals typically vary in multivariate attributes. In some cases primary interest focuses on individual attributes and in others the understanding of the social structure of the ties. In many circumstances both are of interest, as is their relationship. In this paper we consider this last, most general, case. We model the joint distribution of social ties and individual attributes when the population is only partially observed. Of central interest is when the population is surveyed using a network sampling design. A second situation is when data about a subset of the ties and/or the individual attributes is unintentionally missing. Exponential-family random network models (ERNM)s are capable of specifying a joint statistical representation of both the ties of a network and individual attributes. This class of models allow the nodal attributes to be modeled as stochastic processes, expanding the range and realism of exponential-family approaches to network modeling. In this paper we develop a theory of inference for ERNMs when only part of the network is observed, as well as specific methodology for partially observed networks, including non-ignorable mechanisms for network-based sampling designs. In particular, we consider data collected via contact tracing, of considerable importance to infectious disease epidemiology and public health.
Collapse
Affiliation(s)
| | - Mark S. Handcock
- Department of Statistics, University of California, Los Angeles, Los Angeles, CA 90095-1554 USA
| |
Collapse
|
|
15
|
Putter JS, Seghatchian J. T-cell lymphocytopenia: an omnipresent predictor of morbidity and mortality in consequence of SARS-CoV disease and influenza A infections. Cytokine 2023; 165:156163. [PMID: 36989654 PMCID: PMC9933323 DOI: 10.1016/j.cyto.2023.156163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 02/01/2023] [Accepted: 02/11/2023] [Indexed: 02/18/2023]
Abstract
We proposed T-cell lymphocytopenia as a strategic predictor of serious coronavirus and influenza infections. Our preeminent goal was to determine whether a degree of T-cell lymphopenia would identify a distinct threshold cell count to differentiate between severe and non-severe infections. We codified an Index Severity Score to exploit an association between T-cell cytopenia and the grade of disease activity. Principal result A T-cell count of 560 cells/uL or below signified a trend towards advanced disease. Key findings and conclusions The T-cell threshold >560 cells/uL discriminated 85.7% specificity of the lesser viral infections and <=560 cells/uL identified 100% sensitivity of severe infections or death. The positive predictive value of this threshold test was 92.9%.
T-cell apoptosis and sequestration are two of the primary mechanisms of T-cell lymphodepletion. There is potential for the T-cell threshold at <=560 cells/uL to become a standard to differentiate disease severity. Future research should explore correlations between the T-cell threshold, medical outcomes of treatment, Cytokine Release Syndromes, cytokine levels, inflammatory and coagulation markers.
Collapse
Affiliation(s)
- Jeffrey S. Putter
- Medical Biomechanics Inc., 100 E. San Marcos Blvd. #400, North San Diego County, CA 92069 United States of America,Corresponding author
| | - Jerard Seghatchian
- International Consultancyin modern precision personalized blood component therapies. London, England UK
| |
Collapse
|
|
16
|
Ahumada M, Ledesma-Araujo A, Gordillo L, Marín JF. Mutation and SARS-CoV-2 strain competition under vaccination in a modified SIR model. CHAOS, SOLITONS, AND FRACTALS 2023; 166:112964. [PMID: 36474823 PMCID: PMC9715496 DOI: 10.1016/j.chaos.2022.112964] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 10/27/2022] [Accepted: 11/27/2022] [Indexed: 05/07/2023]
Abstract
The crisis caused by the COVID-19 outbreak around the globe raised an increasing concern about the ongoing emergence of variants of the virus that may evade the immune response provided by vaccines. New variants appear due to mutation, and as the cases accumulate, the probability of the emergence of a variant of concern increases. In this article, we propose a modified susceptible, infected, and recovered (SIR) model with waning immunity that captures the competition of two strain classes of an infectious disease under the effect of vaccination with a highly contagious and deadlier strain class emerging from a prior strain due to mutation. When these strains compete for a limited supply of susceptible individuals, changes in the efficiency of vaccines may affect the behaviour of the disease in a non-trivial way, resulting in complex outcomes. We characterise the parameter space including intrinsic parameters of the disease, and using the vaccine efficiencies as control variables. We find different types of transcritical bifurcations between endemic fixed points and a disease-free equilibrium and identify a region of strain competition where the two strain classes coexist during a transient period. We show that a strain can be extinguished either due to strain competition or vaccination, and we obtain the critical values of the efficiency of vaccines to eradicate the disease. Numerical studies using parameters estimated from publicly reported data agree with our theoretical results. Our mathematical model could be a tool to assess quantitatively the vaccination policies of competing and emerging strains using the dynamics in epidemics of infectious diseases.
Collapse
Affiliation(s)
- M Ahumada
- Departamento de Física, Universidad Técnica Federico Santa María, Casilla 110 V, Valparaíso, Chile
| | - A Ledesma-Araujo
- Departamento de Física, Facultad de Ciencia, Universidad de Santiago de Chile, Usach, Av. Víctor Jara 3493, Estación Central, Santiago, Chile
| | - L Gordillo
- Departamento de Física, Facultad de Ciencia, Universidad de Santiago de Chile, Usach, Av. Víctor Jara 3493, Estación Central, Santiago, Chile
| | - J F Marín
- Departamento de Física, Facultad de Ciencia, Universidad de Santiago de Chile, Usach, Av. Víctor Jara 3493, Estación Central, Santiago, Chile
| |
Collapse
|
|
17
|
Murakami T, Sakuragi S, Deguchi H, Nakata M. Agent-based model using GPS analysis for infection spread and inhibition mechanism of SARS-CoV-2 in Tokyo. Sci Rep 2022; 12:20896. [PMID: 36463351 PMCID: PMC9719469 DOI: 10.1038/s41598-022-25480-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 11/30/2022] [Indexed: 12/04/2022] Open
Abstract
Analyzing the SARS-CoV-2 pandemic outbreak based on actual data while reflecting the characteristics of the real city provides beneficial information for taking reasonable infection control measures in the future. We demonstrate agent-based modeling for Tokyo based on GPS information and official national statistics and perform a spatiotemporal analysis of the infection situation in Tokyo. As a result of the simulation during the first wave of SARS-CoV-2 in Tokyo using real GPS data, the infection occurred in the service industry, such as restaurants, in the city center, and then the infected people brought back the virus to the residential area; the infection spread in each area in Tokyo. This phenomenon clarifies that the spread of infection can be curbed by suppressing going out or strengthening infection prevention measures in service facilities. It was shown that pandemic measures in Tokyo could be achieved not only by strong control, such as the lockdown of cities, but also by thorough infection prevention measures in service facilities, which explains the curb phenomena in real Tokyo.
Collapse
Affiliation(s)
- Taishu Murakami
- MRI Research Associates, Inc., 2-10-3 Nagata-cho, Chiyoda-ku, Tokyo, 100-0014, Japan
| | - Shunsuke Sakuragi
- MRI Research Associates, Inc., 2-10-3 Nagata-cho, Chiyoda-ku, Tokyo, 100-0014, Japan.
| | - Hiroshi Deguchi
- Faculty of Commerce and Economics, Chiba University of Commerce, 1-3-1 Konodai, Ichikawa-shi, Chiba, 272-8512, Japan
| | - Masaru Nakata
- MRI Research Associates, Inc., 2-10-3 Nagata-cho, Chiyoda-ku, Tokyo, 100-0014, Japan
| |
Collapse
|
|
18
|
Langel SN, Garrido C, Phan C, Travieso T, Kirshner H, DeMarco T, Ma ZM, Reader JR, Olstad KJ, Sammak RL, Shaan Lakshmanappa Y, Roh JW, Watanabe J, Usachenko J, Immareddy R, Pollard R, Iyer SS, Permar S, Miller LA, Van Rompay KKA, Blasi M. Dam-Infant Rhesus Macaque Pairs to Dissect Age-Dependent Responses to SARS-CoV-2 Infection. Immunohorizons 2022; 6:851-863. [PMID: 36547390 PMCID: PMC10538284 DOI: 10.4049/immunohorizons.2200075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 11/18/2022] [Indexed: 12/24/2022] Open
Abstract
The global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its associated coronavirus disease (COVID-19) has led to a pandemic of unprecedented scale. An intriguing feature of the infection is the minimal disease in most children, a demographic at higher risk for other respiratory viral diseases. To investigate age-dependent effects of SARS-CoV-2 pathogenesis, we inoculated two rhesus macaque monkey dam-infant pairs with SARS-CoV-2 and conducted virological and transcriptomic analyses of the respiratory tract and evaluated systemic cytokine and Ab responses. Viral RNA levels in all sampled mucosal secretions were comparable across dam-infant pairs in the respiratory tract. Despite comparable viral loads, adult macaques showed higher IL-6 in serum at day 1 postinfection whereas CXCL10 was induced in all animals. Both groups mounted neutralizing Ab responses, with infants showing a more rapid induction at day 7. Transcriptome analysis of tracheal airway cells isolated at day 14 postinfection revealed significant upregulation of multiple IFN-stimulated genes in infants compared with adults. In contrast, a profibrotic transcriptomic signature with genes associated with cilia structure and function, extracellular matrix composition and metabolism, coagulation, angiogenesis, and hypoxia was induced in adults compared with infants. Our study in rhesus macaque monkey dam-infant pairs suggests age-dependent differential airway responses to SARS-CoV-2 infection and describes a model that can be used to investigate SARS-CoV-2 pathogenesis between infants and adults.
Collapse
Affiliation(s)
- Stephanie N Langel
- Center for Global Health and Diseases, Department of Pathology, Case Western Reserve University School of Medicine, Cleveland, OH
| | - Carolina Garrido
- Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC
| | - Caroline Phan
- Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC
| | - Tatianna Travieso
- Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC
| | - Helene Kirshner
- Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC
| | - Todd DeMarco
- Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC
| | - Zhong-Min Ma
- California National Primate Research Center, University of California, Davis, Davis, CA
| | - J Rachel Reader
- California National Primate Research Center, University of California, Davis, Davis, CA
| | - Katherine J Olstad
- California National Primate Research Center, University of California, Davis, Davis, CA
| | - Rebecca L Sammak
- California National Primate Research Center, University of California, Davis, Davis, CA
| | | | - Jamin W Roh
- Center for Immunology and Infectious Diseases, University of California, Davis, Davis, CA
- Graduate Group in Immunology, University of California, Davis, Davis, CA
| | - Jennifer Watanabe
- California National Primate Research Center, University of California, Davis, Davis, CA
| | - Jodie Usachenko
- California National Primate Research Center, University of California, Davis, Davis, CA
| | - Ramya Immareddy
- California National Primate Research Center, University of California, Davis, Davis, CA
| | - Rachel Pollard
- Center for Immunology and Infectious Diseases, University of California, Davis, Davis, CA
| | - Smita S Iyer
- California National Primate Research Center, University of California, Davis, Davis, CA
- Center for Immunology and Infectious Diseases, University of California, Davis, Davis, CA
- Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, Davis, CA
| | - Sallie Permar
- Department of Pediatrics, New York-Presbyterian Hospital/Weill Cornell Medical Center, New York, NY; and
| | - Lisa A Miller
- California National Primate Research Center, University of California, Davis, Davis, CA
- Department of Anatomy, Physiology, and Cell Biology, School of Veterinary Medicine, University of California, Davis, Davis, CA
| | - Koen K A Van Rompay
- California National Primate Research Center, University of California, Davis, Davis, CA
| | - Maria Blasi
- Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC
| |
Collapse
|
|
19
|
Quantitatively evaluate the impact of domestic aviation control measures on the spread of COVID-19 in China. Sci Rep 2022; 12:17600. [PMID: 36266307 PMCID: PMC9584274 DOI: 10.1038/s41598-022-21355-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 09/26/2022] [Indexed: 01/13/2023] Open
Abstract
To quantitatively evaluate the impact of domestic aviation control measures on the spread of COVID-19 in China. The number of international flights from March to September 2019 simulated the number of flights from March to September 2020 without implementing aviation control measures. In addition, the proportion of asymptomatic persons and the delay in case reporting were adjusted to estimate the prevalence of each country during the same period and calculate the estimated imported cases. The estimated imported cases were assigned each day with weight, and the estimated daily reported cases were obtained based on the actual daily number of domestic cases in China. Effective Reproduction Number ([Formula: see text]) was calculated based on delayed distribution, Basic Reproductive Number ([Formula: see text]) distribution, and generation time distribution were reported in previous studies. Gaussian Process was used to estimate the effect of time-varying on [Formula: see text], and the estimated [Formula: see text] was compared with the actual [Formula: see text]. The estimated imported cases increased significantly compared with the actual number of imported cases. The estimated imported cases were mainly concentrated in North America and Europe from March to April and gradually increased in many East Asian countries from May to September. The difference between predicted [Formula: see text] and actual [Formula: see text] was statistically significant. The estimated imported cases and the estimated [Formula: see text] have increased compared to the actual situation. This paper quantitatively proves that Chinese aviation control measures significantly suppress the COVID-19 epidemic, which is conducive to promoting and applying this measure.
Collapse
|
|
20
|
Wang Y, Qing F, Li H, Wang X. Timely and effective media coverage's role in the spread of Corona Virus Disease 2019. MATHEMATICAL METHODS IN THE APPLIED SCIENCES 2022; 47:MMA8732. [PMID: 36247227 PMCID: PMC9537968 DOI: 10.1002/mma.8732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 06/04/2022] [Accepted: 09/03/2022] [Indexed: 06/16/2023]
Abstract
For all humanity, the sudden outbreak of Corona Virus Disease 2019 has been an important problem. Timely and effective media coverage is considered to be one of the effective approaches to control the spread of epidemic in early stage. In this paper, a Sentiment-enabled Susceptible-Exposed-Infected-Recovered (SEIR) model is established to reveal the relationship between the propagation of the epidemic and media coverage. The authors take the positive and negative media coverage into consideration when implementing the Sentiment-enabled SEIR model. This model is constructed by parameterizing the number of current confirmed cases, cumulative cured cases, cumulative deaths, and media coverage. The numerical simulation and sensitivity analysis are conducted based on the Sentiment-enabled SEIR model. The numerical analysis confirms the rationality of the Sentiment-enabled SEIR model. The sensitivity analysis shows that positive media coverage acts a pivotal part in reducing the figure for confirmed cases. Negative media coverage has an effect on the figure for confirmed cases is not as significant as that of positive media coverage, but it is not negligible.
Collapse
Affiliation(s)
- Yan Wang
- State Key Laboratory of Media Convergence and CommunicationCommunication University of ChinaBeijingChina
- School of Data Science and Media IntelligenceCommunication University of ChinaBeijingChina
| | - Feng Qing
- State Key Laboratory of Media Convergence and CommunicationCommunication University of ChinaBeijingChina
- School of Data Science and Media IntelligenceCommunication University of ChinaBeijingChina
| | - Haozhan Li
- State Key Laboratory of Media Convergence and CommunicationCommunication University of ChinaBeijingChina
- School of Data Science and Media IntelligenceCommunication University of ChinaBeijingChina
| | - Xuteng Wang
- Department of primary educationYantai Preschool Education CollegeYantaiChina
| |
Collapse
|
|
21
|
Jackson CH, Tom BD, Kirwan PD, Mandal S, Seaman SR, Kunzmann K, Presanis AM, De Angelis D. A comparison of two frameworks for multi-state modelling, applied to outcomes after hospital admissions with COVID-19. Stat Methods Med Res 2022; 31:1656-1674. [PMID: 35837731 PMCID: PMC9294033 DOI: 10.1177/09622802221106720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
We compare two multi-state modelling frameworks that can be used to represent dates of events following hospital admission for people infected during an epidemic. The methods are applied to data from people admitted to hospital with COVID-19, to estimate the probability of admission to intensive care unit, the probability of death in hospital for patients before and after intensive care unit admission, the lengths of stay in hospital, and how all these vary with age and gender. One modelling framework is based on defining transition-specific hazard functions for competing risks. A less commonly used framework defines partially-latent subpopulations who will experience each subsequent event, and uses a mixture model to estimate the probability that an individual will experience each event, and the distribution of the time to the event given that it occurs. We compare the advantages and disadvantages of these two frameworks, in the context of the COVID-19 example. The issues include the interpretation of the model parameters, the computational efficiency of estimating the quantities of interest, implementation in software and assessing goodness of fit. In the example, we find that some groups appear to be at very low risk of some events, in particular intensive care unit admission, and these are best represented by using 'cure-rate' models to define transition-specific hazards. We provide general-purpose software to implement all the models we describe in the flexsurv R package, which allows arbitrarily flexible distributions to be used to represent the cause-specific hazards or times to events.
Collapse
Affiliation(s)
| | - Brian Dm Tom
- 47959MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Peter D Kirwan
- 47959MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Public Health England, London, UK
| | | | - Shaun R Seaman
- 47959MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Kevin Kunzmann
- 47959MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Anne M Presanis
- 47959MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Daniela De Angelis
- 47959MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Public Health England, London, UK
| |
Collapse
|
|
22
|
Suman TY, Keerthiga R, Remya RR, Jacintha A, Jeon J. Assessing the Impact of Meteorological Factors on COVID-19 Seasonality in Metropolitan Chennai, India. TOXICS 2022; 10:toxics10080440. [PMID: 36006119 PMCID: PMC9414974 DOI: 10.3390/toxics10080440] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 07/27/2022] [Accepted: 07/29/2022] [Indexed: 12/10/2022]
Abstract
Meteorological factors may influence coronavirus disease 2019 (COVID-19) transmission. Due to the small number of time series studies, the relative importance of seasonality and meteorological factors is still being debated. From March 2020 to April 2021, we evaluated the impact of meteorological factors on the transmission of COVID-19 in Chennai, India. Understanding how the COVID-19 pandemic spreads over the year is critical to developing public health strategies. Correlation models were used to examine the influence of meteorological factors on the transmission of COVID-19. The results revealed seasonal variations in the number of COVID-19-infected people. COVID-19 transmission was greatly aggravated by temperature, wind speed, nitric oxide (NO) and barometric pressure (BP) during summer seasons, whereas wind speed and BP aggravated COVID-19 transmission during rainy seasons. Furthermore, PM 2.5, NO and BP aggravated COVID-19 transmission during winter seasons. However, their relationships fluctuated seasonally. Our research shows that seasonal influences must be considered when developing effective interventions.
Collapse
Affiliation(s)
- Thodhal Yoganandham Suman
- Department of Environmental Engineering, Changwon National University, Changwon 51140, Gyeongsangnam-do, Korea;
- School of Smart and Green Engineering, Changwon National University, Changwon 51140, Gyeongsangnam-do, Korea
- Ecotoxicology Division, Centre for Ocean Research, Sathyabama Institute of Science and Technology, Chennai 600119, Tamil Nadu, India;
| | - Rajendiran Keerthiga
- College of Pharmaceutical Sciences, Southwest University, Chongqing 400716, China;
| | - Rajan Renuka Remya
- Centre for Material Engineering and Regenerative Medicine, Bharath Institute of Higher Education and Research, Selaiyur, Chennai 600126, Tamil Nadu, India;
| | - Amali Jacintha
- Ecotoxicology Division, Centre for Ocean Research, Sathyabama Institute of Science and Technology, Chennai 600119, Tamil Nadu, India;
| | - Junho Jeon
- Department of Environmental Engineering, Changwon National University, Changwon 51140, Gyeongsangnam-do, Korea;
- School of Smart and Green Engineering, Changwon National University, Changwon 51140, Gyeongsangnam-do, Korea
- Correspondence:
| |
Collapse
|
|
23
|
Phillips JC, Moret MA, Zebende GF, Chow CC. Phase transitions may explain why SARS-CoV-2 spreads so fast and why new variants are spreading faster. PHYSICA A 2022; 598:127318. [PMID: 35431416 PMCID: PMC9004254 DOI: 10.1016/j.physa.2022.127318] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 10/26/2021] [Indexed: 05/11/2023]
Abstract
The novel coronavirus SARS CoV-2 responsible for the COVID-19 pandemic and SARS CoV-1 responsible for the SARS epidemic of 2002-2003 share an ancestor yet evolved to have much different transmissibility and global impact 1. A previously developed thermodynamic model of protein conformations hypothesized that SARS CoV-2 is very close to a new thermodynamic critical point, which makes it highly infectious but also easily displaced by a spike-based vaccine because there is a tradeoff between transmissibility and robustness 2. The model identified a small cluster of four key mutations of SARS CoV-2 that predicts much stronger viral attachment and viral spreading compared to SARS CoV-1. Here we apply the model to the SARS-CoV-2 variants Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1) and Delta (B.1.617.2)3 and predict, using no free parameters, how the new mutations will not diminish the effectiveness of current spike based vaccines and may even further enhance infectiousness by augmenting the binding ability of the virus.
Collapse
Affiliation(s)
- J C Phillips
- Department of Physics and Astronomy, Rutgers University, Piscataway, NJ 08854, United States of America
| | | | - Gilney F Zebende
- Department of Physics, State University of Feira de Santana, BA, Brazil
| | - Carson C Chow
- Mathematical Biology Section, NIDDK, NIH, Bethesda, Md 20892, United States of America
| |
Collapse
|
|
24
|
Makadzange AT, Gundidza P, Lau C, Dietrich J, Beta N, Myburgh N, Elose N, Ndhlovu C, James W, Stanberry L. Attitudes to Vaccine Mandates among Late Adopters of COVID-19 Vaccines in Zimbabwe. Vaccines (Basel) 2022; 10:1090. [PMID: 35891254 PMCID: PMC9316741 DOI: 10.3390/vaccines10071090] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 06/30/2022] [Accepted: 07/03/2022] [Indexed: 12/05/2022] Open
Abstract
Despite sufficient supply, <25% of the population in sub-Saharan Africa has received at least one dose of COVID-19 vaccine. Vaccine mandates have previously been effective in increasing vaccine uptake. Attitudes to COVID-19 vaccine mandates and vaccines for children in African populations are not well understood. We surveyed late-adopters presenting for COVID-19 vaccination one year after program initiation in Zimbabwe. Logistic regression models were developed to evaluate factors associated with attitudes to mandates. In total, 1016 adults were enrolled; 690 (67.9%) approved of mandating vaccination for use of public spaces, 686 (67.5%) approved of employer mandates, and 796 (78.3%) approved of mandating COVID-19 vaccines for schools. Individuals of lower economic status were twice as likely as high-income individuals to approve of mandates. Further, 743 (73.1%) participants indicated that they were extremely/very likely to accept vaccines for children. Approval of vaccine mandates was strongly associated with perceptions of vaccine safety, effectiveness, and trust in regulatory processes that approved vaccines. Vaccine hesitancy is an important driver of low vaccine coverage in Africa and can be mitigated by vaccine mandates. Overall, participants favored vaccine mandates; however, attitudes to mandates were strongly associated with level of education and socioeconomic status.
Collapse
Affiliation(s)
- Azure Tariro Makadzange
- Charles River Medical Group, 155 King George Avenue, Avondale, Harare, Zimbabwe; (P.G.); (N.B.); (N.E.); (C.N.)
| | - Patricia Gundidza
- Charles River Medical Group, 155 King George Avenue, Avondale, Harare, Zimbabwe; (P.G.); (N.B.); (N.E.); (C.N.)
| | - Charles Lau
- RTI International, 3040 East Cornwallis Road, Research Triangle Park, Research Triangle, NC 27709, USA;
| | - Janan Dietrich
- Perinatal HIV Research Unit (PHRU), Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2000, South Africa;
- African Social Sciences Unit of Research and Evaluation (ASSURE), a Division of the Wits Health Consortium, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2000, South Africa
- Health Systems Research Unit, South African Medical Research Council, Bellville 7530, South Africa
| | - Norest Beta
- Charles River Medical Group, 155 King George Avenue, Avondale, Harare, Zimbabwe; (P.G.); (N.B.); (N.E.); (C.N.)
| | - Nellie Myburgh
- Wits Vaccines & Infectious Diseases Analytics (VIDA) Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2000, South Africa;
| | - Nyasha Elose
- Charles River Medical Group, 155 King George Avenue, Avondale, Harare, Zimbabwe; (P.G.); (N.B.); (N.E.); (C.N.)
| | - Chiratidzo Ndhlovu
- Charles River Medical Group, 155 King George Avenue, Avondale, Harare, Zimbabwe; (P.G.); (N.B.); (N.E.); (C.N.)
- Internal Medicine Unit, Faculty of Health Sciences, University of Zimbabwe, Harare, Zimbabwe
| | - Wilmot James
- Institute for Social and Economic Research and Policy, Columbia University, IAB 118th Street, New York, NY 10025, USA;
| | - Lawrence Stanberry
- Vaccine Information Network, Columbia University, 533 W 218th St., New York, NY 10032, USA;
- Department of Pediatrics, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| |
Collapse
|
|
25
|
Abou Ghayda R, Lee KH, Han YJ, Ryu S, Hong SH, Yoon S, Jeong GH, Yang J, Lee HJ, Lee J, Lee JY, Effenberger M, Eisenhut M, Kronbichler A, Solmi M, Li H, Jacob L, Koyanagi A, Radua J, Park MB, Aghayeva S, Ahmed MLCB, Al Serouri A, Al‐Shamsi HO, Amir‐Behghadami M, Baatarkhuu O, Bashour H, Bondarenko A, Camacho‐Ortiz A, Castro F, Cox H, Davtyan H, Douglas K, Dragioti E, Ebrahim S, Ferioli M, Harapan H, Mallah SI, Ikram A, Inoue S, Jankovic S, Jayarajah U, Jesenak M, Kakodkar P, Kebede Y, Kifle M, Koh D, Males VK, Kotfis K, Lakoh S, Ling L, Llibre‐Guerra J, Machida M, Makurumidze R, Mamun MA, Masic I, Van Minh H, Moiseev S, Nadasdy T, Nahshon C, Ñamendys‐Silva SA, Yongsi BN, Nielsen HB, Nodjikouambaye ZA, Ohnmar O, Oksanen A, Owopetu O, Parperis K, Perez GE, Pongpirul K, Rademaker M, Rosa S, Sah R, Sallam D, Schober P, Singhal T, Tafaj S, Torres I, Torres‐Roman JS, Tsartsalis D, Tsolmon J, Tuychiev L, Vukcevic B, Wanghi G, Wollina U, Xu R, Yang L, Zaidi Z, Smith L, Shin JI. The global case fatality rate of coronavirus disease 2019 by continents and national income: A meta-analysis. J Med Virol 2022; 94:2402-2413. [PMID: 35099819 PMCID: PMC9015248 DOI: 10.1002/jmv.27610] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 12/20/2021] [Accepted: 01/18/2022] [Indexed: 02/05/2023]
Abstract
The aim of this study is to provide a more accurate representation of COVID-19's case fatality rate (CFR) by performing meta-analyses by continents and income, and by comparing the result with pooled estimates. We used multiple worldwide data sources on COVID-19 for every country reporting COVID-19 cases. On the basis of data, we performed random and fixed meta-analyses for CFR of COVID-19 by continents and income according to each individual calendar date. CFR was estimated based on the different geographical regions and levels of income using three models: pooled estimates, fixed- and random-model. In Asia, all three types of CFR initially remained approximately between 2.0% and 3.0%. In the case of pooled estimates and the fixed model results, CFR increased to 4.0%, by then gradually decreasing, while in the case of random-model, CFR remained under 2.0%. Similarly, in Europe, initially, the two types of CFR peaked at 9.0% and 10.0%, respectively. The random-model results showed an increase near 5.0%. In high-income countries, pooled estimates and fixed-model showed gradually increasing trends with a final pooled estimates and random-model reached about 8.0% and 4.0%, respectively. In middle-income, the pooled estimates and fixed-model have gradually increased reaching up to 4.5%. in low-income countries, CFRs remained similar between 1.5% and 3.0%. Our study emphasizes that COVID-19 CFR is not a fixed or static value. Rather, it is a dynamic estimate that changes with time, population, socioeconomic factors, and the mitigatory efforts of individual countries.
Collapse
Affiliation(s)
- Ramy Abou Ghayda
- Urology InstituteUniversity Hospitals, Case Western Reserve UniversityClevelandOhioUSA
| | - Keum Hwa Lee
- Department of PediatricsYonsei University College of MedicineSeoulRepublic of Korea
| | - Young Joo Han
- Hospital Medicine CenterHaeundae Paik Hospital, Inje University College of MedicineBusanRepublic of Korea
| | - Seohyun Ryu
- Yonsei University College of MedicineSeoulRepublic of Korea
| | - Sung Hwi Hong
- Yonsei University College of MedicineSeoulRepublic of Korea
| | - Sojung Yoon
- Yonsei University College of MedicineSeoulRepublic of Korea
| | - Gwang Hum Jeong
- College of Medicine, Gyeongsang National UniversityJinjuRepublic of Korea
| | - Jae Won Yang
- Department of NephrologyYonsei University Wonju College of MedicineWonjuRepublic of Korea
| | - Hyo Jeong Lee
- Yonsei University College of MedicineSeoulRepublic of Korea
| | - Jinhee Lee
- Department of PsychiatryYonsei University Wonju College of MedicineWonjuRepublic of Korea
| | - Jun Young Lee
- Department of NephrologyYonsei University Wonju College of MedicineWonjuRepublic of Korea
| | - Maria Effenberger
- Department of Internal Medicine I, Gastroenterology, Hepatology, Endocrinology & MetabolismMedical University InnsbruckInnsbruckAustria
| | - Michael Eisenhut
- Luton & Dunstable University Hospital NHS Foundation TrustLutonUK
| | - Andreas Kronbichler
- Department of Internal Medicine IV, Nephrology and HypertensionMedical University InnsbruckInnsbruckAustria
| | - Marco Solmi
- Department of PsychiatryUniversity of OttawaOntarioCanada
- Department of Mental HealthThe Ottawa HospitalOntarioCanada
- Ottawa Hospital Research Institute (OHRI) Clinical Epidemiology Program University of OttawaOttawaOntarioCanada
- School of Epidemiology and Public Health, Faculty of MedicineUniversity of OttawaOttawaCanada
| | - Han Li
- University of Florida College of MedicineGainesvilleFloridaUSA
| | - Louis Jacob
- Faculty of MedicineUniversity of Versailles Saint‐Quentin‐en‐YvelinesVersaillesFrance
- Research and Development UnitParc Sanitari Sant Joan de Déu, CIBERSAMSant Boi de LlobregatBarcelonaSpain
| | - Ai Koyanagi
- Research and Development UnitParc Sanitari Sant Joan de Déu, CIBERSAMSant Boi de LlobregatBarcelonaSpain
- ICREABarcelonaSpain
| | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain
- Department of Psychosis StudiesInstitute of Psychiatry, Psychology, and Neuroscience, King's College LondonLondonUK
- Department of Clinical NeuroscienceCentre for Psychiatric Research, Karolinska InstitutetStockholmSweden
| | - Myung Bae Park
- Department of Gerontology Health and WelfarePai Chai UniversityDaejeonRepublic of Korea
| | - Sevda Aghayeva
- Department of GastroenterologyAzerbaijan Medical University School of MedicineBakuAzerbaijan
| | - Mohamed L. C. B. Ahmed
- Research Unit in Epidemiology and Diversity of Microorganisms, Department of BiologyUniversity of Nouakchott Al AasriyaNouakchottMauritania
| | | | - Humaid O. Al‐Shamsi
- College of MedicineUniversity of SharjahSharjahUnited Arab Emirates
- Burjeel Cancer Institute, Burjeel Medical CityAbu DhabiUnited Arab Emirates
| | - Mehrdad Amir‐Behghadami
- Iranian Center of Excellence in Health Management (IceHM)School of Management and Medical Informatics, Tabriz University of Medical SciencesTabrizIran
- Student Research Committee (SRC), Tabriz University of Medical SciencesTabrizIran
- Road Traffic Injury Research Center, Iranian International Safe Community Support CenterTabriz University of Medical SciencesTabrizIran
| | - Oidov Baatarkhuu
- School of MedicineMongolian National University of Medical SciencesUlan BatorMongolia
| | - Hyam Bashour
- Department of Family and Community MedicineFaculty of Medicine, Damascus UniversityDamascusSyria
| | | | - Adrian Camacho‐Ortiz
- Servicio de InfectologíaHospital Universitario “Dr José Eleuterio González”, Universidad Autónoma de Nuevo LeónMonterreyMexico
| | - Franz Castro
- Department of Research and Health Technology AssessmentGorgas Memorial Institute for Health StudiesPanama CityPanama
| | - Horace Cox
- Ministry of Health GuyanaGeorgetownGuyana
| | - Hayk Davtyan
- Tuberculosis Research and Prevention Center NGOYerevanArmenia
| | - Kirk Douglas
- Centre for Biosecurity Studies, University of the West Indies, Cave HillSt. MichaelBarbados
| | - Elena Dragioti
- Department of Health, Medicine and Caring SciencesPain and Rehabilitation Centre, Linkoping UniversityLinkopingSweden
| | - Shahul Ebrahim
- Faculty of MedicineUniversity of Sciences, Techniques, and TechnologyBamakoMali
| | - Martina Ferioli
- IRCCS Azienda Ospedaliero‐Universitaria di Bologna, Respiratory and Critical Care UnitS. Orsola‐Malpighi HospitalBolognaItaly
| | - Harapan Harapan
- Medical Research UnitSchool of Medicine Universitas Syiah KualaBanda AcehIndonesia
| | - Saad I. Mallah
- School of Medicine, Royal College of Surgeons in Ireland‐BahrainBusaiteenKingdom of Bahrain
| | - Aamer Ikram
- National Institute of HealthIslamabadPakistan
| | - Shigeru Inoue
- Department of Preventive Medicine and Public HealthTokyo Medical UniversityTokyoJapan
| | - Slobodan Jankovic
- Department of Pharmacology and Toxicology, Faculty of Medical SciencesUniversity of KragujevacKragujevacSerbia
| | - Umesh Jayarajah
- Postgraduate Institute of Medicine, University of ColomboColomboSri Lanka
| | - Milos Jesenak
- Department of Pediatrics, Jessenius Faculty of Medicine in MartinComenius University in BratislavaMartinSlovakia
| | - Pramath Kakodkar
- School of Medicine, National University of Galway IrelandGalwayIreland
| | - Yohannes Kebede
- Department of Health, Behavior, and Society, Faculty of Public HealthJimma UniversityJimmaEthiopia
| | - Meron Kifle
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical MedicineUniversity of OxfordOxfordUK
| | - David Koh
- Saw Swee Hock School of Public Health, National University of SingaporeSiangapore
| | - Visnja K. Males
- Division of Endocrinology, Diabetes and Metabolic Disease in SplitClinical Hospital Centre Split, School of Medicine Split, Šoltanska 1SplitCroatia
| | - Katarzyna Kotfis
- Department Anaesthesiology, Intensive Therapy and Acute IntoxicationsPomeranian Medical UniversitySzczecinPoland
| | - Sulaiman Lakoh
- College of Medicine and Allied Health Sciences, University of Sierra LeoneFreetownSierra Leone
| | - Lowell Ling
- Department of Anaesthesia and Intensive CareThe Chinese University of Hong KongShatin, Hong Kong SARChina
| | | | - Masaki Machida
- Department of Preventive Medicine and Public HealthTokyo Medical UniversityTokyoJapan
| | - Richard Makurumidze
- Department of Community Medicine, Department of Primary Care SciencesUniversity of Zimbabwe, Faculty of Medicine and Health SciencesHarareZimbabwe
| | - Mohammed A. Mamun
- Department of Public Health and InformaticsJahangirnagar UniversitySavarDhakaBangladesh
- Department of Public HealthDaffodil International UniversityDhakaBangladesh
- CHINTA Research BangladeshDhakaBangladesh
| | - Izet Masic
- Academy of Medical Sciences of Bosnia and HerzegovinaSarajevoBosnia and Herzegovina
| | - Hoang Van Minh
- Center for Population Health Sciences, Hanoi University of Public HealthHanoiVietnam
| | - Sergey Moiseev
- Sechenov First Moscow State Medical UniversityMoscowRussia
| | - Thomas Nadasdy
- Department of Dermatology“St. Parascheva” Clinical Hospital of Infectious DiseasesGalatiRomania
| | - Chen Nahshon
- Department of Gynecologic Surgery and OncologyCarmel Medical CenterHaifaIsrael
| | - Silvio A. Ñamendys‐Silva
- Instituto Nacional de Cancerología, Instituto Nacional de Ciencias Médicas y Nutrición Salvador ZubiránMexico CityMexico
| | - Blaise N. Yongsi
- Institute for Training & Research in Population Studies (IFORD), The University of Yaoundé IISoaCameroon
| | - Henning B. Nielsen
- Department of Anaesthesia and Intensive CareZealand University Hospital RoskildeRoskildeDenmark
| | | | - Ohnmar Ohnmar
- Department of Medical Research (Lower Myanmar)Myanmar Health MinistryYangonMyanmar
| | | | - Oluwatomi Owopetu
- Department of Community MedicineUniversity College HospitalIbadanNigeria
| | | | | | - Krit Pongpirul
- Department of Preventive Medicine, Faculty of MedicineChulalongkorn UniversityBangkokThailand
| | - Marius Rademaker
- Waikato Clinical School, Auckland University Medical SchoolHamiltonNew Zealand
| | - Sandro Rosa
- College of Pharmacy, Federal Fluminense University, NiteróiRio de JaneiroBrazil
- Pharmacy DivisionNational Institute of Industrial PropertyRio de JaneiroRio de JaneiroBrazil
| | - Ranjit Sah
- National Public Health LaboratoryKathmanduNepal
| | - Dina Sallam
- Department of Pediatrics & pediatric nephrology, Faculty of MedicineAin Shams UniversityCairoEgypt
| | - Patrick Schober
- Department of AnesthesiologyAmsterdam University Medical Centers, Vrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Tanu Singhal
- Kokilaben Dhirubhai Ambani Hospital and Medical Research InstituteMumbaiIndia
| | - Silva Tafaj
- University Hospital Shefqet NdroqiTiranaAlbania
| | | | | | | | - Jadamba Tsolmon
- Mongolian National University of Medical SciencesUlaanbaatarMongolia
| | | | - Batric Vukcevic
- Faculty of MedicineUniversity of MontenegroPodgoricaMontenegro
| | - Guy Wanghi
- Unit of Physiology, Department of Basic Sciences, Faculty of MedicineUniversity of KinshasaKinshasaDemocratic Republic of the Congo
| | - Uwe Wollina
- Department of Dermatology and AllergologyStädtisches Klinikum DresdenDresdenGermany
| | - Ren‐He Xu
- Centre of Reproduction, Development and Aging, Faculty of Health Sciences, Institute of Translational MedicineUniversity of MacauTaipaMacauChina
| | - Lin Yang
- Department of Cancer Epidemiology and Prevention ResearchAlberta Health ServicesCalgaryCanada
- Departments of Oncology and Community Health SciencesUniversity of CalgaryCalgaryCanada
| | - Zoubida Zaidi
- Faculty of MedicineUniversity Ferhat AbbasSetifAlgeria
| | - Lee Smith
- The Cambridge Centre for Sport and Exercise Sciences, Anglia Ruskin UniversityCambridgeUK
| | - Jae Il Shin
- Department of PediatricsYonsei University College of MedicineSeoulRepublic of Korea
| |
Collapse
|
|
26
|
Measuring the unknown: An estimator and simulation study for assessing case reporting during epidemics. PLoS Comput Biol 2022; 18:e1008800. [PMID: 35604952 PMCID: PMC9166360 DOI: 10.1371/journal.pcbi.1008800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 06/03/2022] [Accepted: 04/20/2022] [Indexed: 11/19/2022] Open
Abstract
The fraction of cases reported, known as 'reporting', is a key performance indicator in an outbreak response, and an essential factor to consider when modelling epidemics and assessing their impact on populations. Unfortunately, its estimation is inherently difficult, as it relates to the part of an epidemic which is, by definition, not observed. We introduce a simple statistical method for estimating reporting, initially developed for the response to Ebola in Eastern Democratic Republic of the Congo (DRC), 2018-2020. This approach uses transmission chain data typically gathered through case investigation and contact tracing, and uses the proportion of investigated cases with a known, reported infector as a proxy for reporting. Using simulated epidemics, we study how this method performs for different outbreak sizes and reporting levels. Results suggest that our method has low bias, reasonable precision, and despite sub-optimal coverage, usually provides estimates within close range (5-10%) of the true value. Being fast and simple, this method could be useful for estimating reporting in real-time in settings where person-to-person transmission is the main driver of the epidemic, and where case investigation is routinely performed as part of surveillance and contact tracing activities.
Collapse
|
|
27
|
Guimarães Sousa S, Kleiton de Sousa A, Maria Carvalho Pereira C, Sofia Miranda Loiola Araújo A, de Aguiar Magalhães D, Vieira de Brito T, Barbosa ALDR. SARS-CoV-2 infection causes intestinal cell damage: Role of interferon’s imbalance. Cytokine 2022; 152:155826. [PMID: 35158258 PMCID: PMC8828414 DOI: 10.1016/j.cyto.2022.155826] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 02/02/2022] [Accepted: 02/04/2022] [Indexed: 12/12/2022]
Abstract
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the causative agent of the newly emerging lung disease pandemic COVID-19. This viral infection causes a series of respiratory disorders, and although this virus mainly infects respiratory cells, the small intestine can also be an important site of entry or interaction, as enterocytes highly express in angiotensin-2 converting enzyme (ACE) receptors. There are countless reports pointing to the importance of interferons (IFNs) with regard to the mediation of the immune system in viral infection by SARS-CoV-2. Thus, this review will focus on the main cells that make up the large intestine, their specific immunology, as well as the function of IFNs in the intestinal mucosa after the invasion of coronavirus-2.
Collapse
|
|
28
|
Pan J, Zhu W, Tian J, Liu Z, Xu A, Yao Y, Wang W. Vaccination as an alternative to non-drug interventions to prevent local resurgence of COVID-19. Infect Dis Poverty 2022; 11:36. [PMID: 35346382 PMCID: PMC8959078 DOI: 10.1186/s40249-022-00960-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 03/14/2022] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
While a COVID-19 vaccine protects people from serious illness and death, it remains a concern when and how to lift the high-cost and strict non-pharmaceutical interventions (NPIs). This study examined the joint effect of vaccine coverage and NPIs on the control of local and sporadic resurgence of COVID-19 cases.
Methods
Between July 2021 and January 2022, we collected the large-scale testing information and case number of imported COVID-19 patients from the website of the National Health Commission of China. A compartment model was developed to identify the level of vaccine coverage that would allow safe relaxation of NPIs, and vaccination strategies that can best achieve this level of coverage. We applied Monte Carlo simulation 50 000 times to remove random fluctuation effects and obtain fitted/predicted epidemic curve based on various parameters with 95% confidence interval at each time point.
Results
We found that a vaccination coverage of 50.4% was needed for the safe relaxation of NPIs, if the vaccine effectiveness was 79.3%. The total number of incidence cases under the key groups firstly strategy was 103 times higher than that of accelerated vaccination strategy. It needed 35 months to fully relax NPIs if the key groups firstly strategy was implemented, and 27 months were needed with the accelerated vaccination strategy. If combined the two strategies, only 8 months are needed to achieve the vaccine coverage threshold for the fully relaxation of NPIs. Sensitivity analyses results shown that the higher the transmission rate of the virus and the lower annual vaccine supply, the more difficult the epidemic could be under control. When the transmission rate increased 25% or the vaccination effectiveness rate decreased 20%, 33 months were needed to reduce the number of total incidence cases below 1000.
Conclusions
As vaccine coverage improves, the NPIs can be gradually relaxed. Until that threshold is reached, however, strict NPIs are still needed to control the epidemic. The more transmissible SARS-CoV-2 variant led to higher resurgence probability, which indicates the importance of accelerated vaccination and achieving the vaccine coverage earlier.
Graphical Abstract
Collapse
|
|
29
|
Morozova OV, Novikova NA, Epifanova NV, Novikov DV, Mokhonov VV, Sashina TA, Zaytseva NN. [Detection SARS-CoV-2 ( Coronaviridae: Coronavirinae: Betacoronavirus: Sarbecovirus) in children with acute intestinal infection in Nizhny Novgorod during 2020-2021]. Vopr Virusol 2022; 67:69-76. [PMID: 35293190 DOI: 10.36233/0507-4088-95] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 03/15/2022] [Indexed: 12/15/2022]
Abstract
INTRODUCTION The novel coronavirus infection COVID-19 is a major public health problem worldwide. Several publications show the presence of gastrointestinal (GI) symptoms (nausea, vomiting, and diarrhea) in addition to respiratory disorders.The aim of this study was the monitoring of RNA of COVID-19 pathogen, coronavirus SARS-CoV-2 (Coronaviridae: Coronavirinae: Betacoronavirus; Sarbecovirus) in children hospitalized with acute intestinal infection (AII), with following molecular-genetic characterization of detected strains. MATERIAL AND METHODS Fecal samples of children with AII hospitalized in infectious hospital of Nizhny Novgorod (Russia) in the period from 01.07.2020 to 31.10.2021 were used as material for the study. Viral RNA detection was performed by real-time polymerase chain reaction (RT-PCR). The nucleotide sequence of S-protein gene fragment was determined by Sanger sequencing. RESULTS AND DISCUSSION SARS-CoV-2 genetic material was detected in 45 out of 2476 fecal samples. The maximum number of samples containing RNA of the virus occurred in November 2020 (detection rate of 12.2%). In 20.0% of cases, SARS-CoV-2 RNA was detected in combination with rota-, noro-, and adenoviruses. 28 nucleotide sequences of S-protein gene fragment complementary DNA (cDNA) were determined. Phylogenetic analysis showed that the studied SARS-CoV-2 strains belonged to two variants. Analysis of the S-protein amino acid sequence of the strains studied showed the absence of the N501Y mutation in the 2020 samples, which is a marker for variants with a high epidemic potential, called variants of concern (VOC) according to the World Health Organization (WHO) definition (lines Alpha B.1.1.7, Beta B.1.351, Gamma P.1). Delta line variant B.1.617.2 was identified in two samples isolated in September 2021. CONCLUSION The detection of SARS-CoV-2 RNA in the fecal samples of children with AII, suggesting that the fecal-oral mechanism of pathogen transmission may exist, determines the necessity to optimize its monitoring and to develop an algorithm of actions with patients with signs of AII under the conditions of a novel coronavirus infection pandemic.
Collapse
Affiliation(s)
- O V Morozova
- FSBI «Academician I.N. Blokhina Nizhny Novgorod Scientific Research Institute of Epidemiology and Microbiology» of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor)
| | - N A Novikova
- FSBI «Academician I.N. Blokhina Nizhny Novgorod Scientific Research Institute of Epidemiology and Microbiology» of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor)
| | - N V Epifanova
- FSBI «Academician I.N. Blokhina Nizhny Novgorod Scientific Research Institute of Epidemiology and Microbiology» of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor)
| | - D V Novikov
- FSBI «Academician I.N. Blokhina Nizhny Novgorod Scientific Research Institute of Epidemiology and Microbiology» of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor)
| | - V V Mokhonov
- FSBI «Academician I.N. Blokhina Nizhny Novgorod Scientific Research Institute of Epidemiology and Microbiology» of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor)
| | - T A Sashina
- FSBI «Academician I.N. Blokhina Nizhny Novgorod Scientific Research Institute of Epidemiology and Microbiology» of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor)
| | - N N Zaytseva
- FSBI «Academician I.N. Blokhina Nizhny Novgorod Scientific Research Institute of Epidemiology and Microbiology» of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor)
| |
Collapse
|
|
30
|
Silverstein NJ, Wang Y, Manickas-Hill Z, Carbone C, Dauphin A, Boribong BP, Loiselle M, Davis J, Leonard MM, Kuri-Cervantes L, Meyer NJ, Betts MR, Li JZ, Walker BD, Yu XG, Yonker LM, Luban J. Innate lymphoid cells and COVID-19 severity in SARS-CoV-2 infection. eLife 2022; 11:e74681. [PMID: 35275061 PMCID: PMC9038195 DOI: 10.7554/elife.74681] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 03/11/2022] [Indexed: 11/21/2022] Open
Abstract
Background Risk of severe COVID-19 increases with age, is greater in males, and is associated with lymphopenia, but not with higher burden of SARS-CoV-2. It is unknown whether effects of age and sex on abundance of specific lymphoid subsets explain these correlations. Methods Multiple regression was used to determine the relationship between abundance of specific blood lymphoid cell types, age, sex, requirement for hospitalization, duration of hospitalization, and elevation of blood markers of systemic inflammation, in adults hospitalized for severe COVID-19 (n = 40), treated for COVID-19 as outpatients (n = 51), and in uninfected controls (n = 86), as well as in children with COVID-19 (n = 19), recovering from COVID-19 (n = 14), MIS-C (n = 11), recovering from MIS-C (n = 7), and pediatric controls (n = 17). Results This observational study found that the abundance of innate lymphoid cells (ILCs) decreases more than 7-fold over the human lifespan - T cell subsets decrease less than 2-fold - and is lower in males than in females. After accounting for effects of age and sex, ILCs, but not T cells, were lower in adults hospitalized with COVID-19, independent of lymphopenia. Among SARS-CoV-2-infected adults, the abundance of ILCs, but not of T cells, correlated inversely with odds and duration of hospitalization, and with severity of inflammation. ILCs were also uniquely decreased in pediatric COVID-19 and the numbers of these cells did not recover during follow-up. In contrast, children with MIS-C had depletion of both ILCs and T cells, and both cell types increased during follow-up. In both pediatric COVID-19 and MIS-C, ILC abundance correlated inversely with inflammation. Blood ILC mRNA and phenotype tracked closely with ILCs from lung. Importantly, blood ILCs produced amphiregulin, a protein implicated in disease tolerance and tissue homeostasis. Among controls, the percentage of ILCs that produced amphiregulin was higher in females than in males, and people hospitalized with COVID-19 had a lower percentage of ILCs that produced amphiregulin than did controls. Conclusions These results suggest that, by promoting disease tolerance, homeostatic ILCs decrease morbidity and mortality associated with SARS-CoV-2 infection, and that lower ILC abundance contributes to increased COVID-19 severity with age and in males. Funding This work was supported in part by the Massachusetts Consortium for Pathogen Readiness and NIH grants R37AI147868, R01AI148784, F30HD100110, 5K08HL143183.
Collapse
Affiliation(s)
- Noah J Silverstein
- Program in Molecular Medicine, University of Massachusetts Medical SchoolWorcesterUnited States
- Medical Scientist Training Program, University of Massachusetts Medical SchoolWorcesterUnited States
- Massachusetts Consortium on Pathogen ReadinessBostonUnited States
| | - Yetao Wang
- Program in Molecular Medicine, University of Massachusetts Medical SchoolWorcesterUnited States
- Massachusetts Consortium on Pathogen ReadinessBostonUnited States
| | - Zachary Manickas-Hill
- Massachusetts Consortium on Pathogen ReadinessBostonUnited States
- Ragon Institute of MGH, MIT and HarvardCambridgeUnited States
| | - Claudia Carbone
- Program in Molecular Medicine, University of Massachusetts Medical SchoolWorcesterUnited States
| | - Ann Dauphin
- Program in Molecular Medicine, University of Massachusetts Medical SchoolWorcesterUnited States
| | - Brittany P Boribong
- Massachusetts General Hospital, Mucosal Immunology and Biology Research CenterBostonUnited States
- Massachusetts General Hospital, Department of PediatricsBostonUnited States
- Harvard Medical SchoolBostonUnited States
| | - Maggie Loiselle
- Massachusetts General Hospital, Mucosal Immunology and Biology Research CenterBostonUnited States
| | - Jameson Davis
- Massachusetts General Hospital, Mucosal Immunology and Biology Research CenterBostonUnited States
| | - Maureen M Leonard
- Massachusetts General Hospital, Mucosal Immunology and Biology Research CenterBostonUnited States
- Massachusetts General Hospital, Department of PediatricsBostonUnited States
- Harvard Medical SchoolBostonUnited States
| | - Leticia Kuri-Cervantes
- Department of Microbiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Institute for Immunology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Nuala J Meyer
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of MedicinePhiladelphiaUnited States
| | - Michael R Betts
- Department of Microbiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Institute for Immunology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Jonathan Z Li
- Massachusetts Consortium on Pathogen ReadinessBostonUnited States
- Department of Medicine, Brigham and Women’s HospitalBostonUnited States
| | - Bruce D Walker
- Massachusetts Consortium on Pathogen ReadinessBostonUnited States
- Ragon Institute of MGH, MIT and HarvardCambridgeUnited States
- Howard Hughes Medical InstituteChevy ChaseUnited States
- Department of Biology and Institute of Medical Engineering and Science, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Xu G Yu
- Massachusetts Consortium on Pathogen ReadinessBostonUnited States
- Ragon Institute of MGH, MIT and HarvardCambridgeUnited States
- Department of Medicine, Brigham and Women’s HospitalBostonUnited States
| | - Lael M Yonker
- Massachusetts General Hospital, Mucosal Immunology and Biology Research CenterBostonUnited States
- Massachusetts General Hospital, Department of PediatricsBostonUnited States
- Harvard Medical SchoolBostonUnited States
| | - Jeremy Luban
- Program in Molecular Medicine, University of Massachusetts Medical SchoolWorcesterUnited States
- Massachusetts Consortium on Pathogen ReadinessBostonUnited States
- Ragon Institute of MGH, MIT and HarvardCambridgeUnited States
- Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Medical SchoolWorcesterUnited States
- Broad Institute of Harvard and MITCambridgeUnited States
| |
Collapse
|
|
31
|
Canale MP, Menghini R, Martelli E, Federici M. COVID-19-Associated Endothelial Dysfunction and Microvascular Injury: From Pathophysiology to Clinical Manifestations. Card Electrophysiol Clin 2022; 14:21-28. [PMID: 35221082 PMCID: PMC8556628 DOI: 10.1016/j.ccep.2021.10.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Coronavirus-19 disease (COVID-19) affects more people than previous coronavirus infections and has a higher mortality. Higher incidence and mortality can probably be explained by COVID-19 causative agent's greater affinity (about 10-20 times) for angiotensin-converting enzyme 2 (ACE2) receptor compared with other coronaviruses. Here, the authors first summarize clinical manifestations, then present symptoms of COVID-19 and the pathophysiological mechanisms underlying specific organ/system disease. The worse clinical outcome observed in COVID-19 patients with diabetes may be in part related to the increased ADAM17 activity and its unbalanced interplay with ACE2. Therefore, strategies aimed to inhibit ADAM17 activity may be explored to develop new effective therapeutic approaches.
Collapse
Affiliation(s)
- Maria Paola Canale
- Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy; Center for Atherosclerosis, Policlinico Tor Vergata, Rome, Italy
| | - Rossella Menghini
- Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy
| | - Eugenio Martelli
- Department of General and Specialist Surgery "P. Stefanini", Sapienza University of Rome, Italy; Division of Vascular Surgery, S. Anna and S. Sebastiano Hospital, Caserta, Italy
| | - Massimo Federici
- Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy; Center for Atherosclerosis, Policlinico Tor Vergata, Rome, Italy.
| |
Collapse
|
|
32
|
Possible Therapeutic Intervention Strategies for COVID-19 by Manipulating the Cellular Proteostasis Network. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1352:125-147. [PMID: 35132598 DOI: 10.1007/978-3-030-85109-5_8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
INTRODUCTION The recent outbreak of coronavirus infection by SARS-CoV-2 that started from the Wuhan Province of China in 2019 has spread to most parts of the world infecting millions of people. Although the case fatality rate of SARS-CoV-2 infection is less than the previous epidemics by other closely related coronaviruses, due to its high infectivity, the total number of SARS-CoV-2 infection-associated disease, called Covid-19, is a matter of global concern. Despite drastic preventive measures, the number of Covid-19 cases are steadily increasing, and the future course of this pandemic is highly unpredictable. The most concerning fact about Covid-19 is the absence of specific and effective preventive or therapeutic agents against the disease. Finding an immediate intervention against Covid-19 is the need of the hour. In this chapter, we have discussed the role of different branches of the cellular proteostasis network, represented by Hsp70-Hsp40 chaperone system, Ubiquitin-Proteasome System (UPS), autophagy, and endoplasmic reticulum-Unfolded Protein Response (ER-UPR) pathway in the pathogenesis of coronavirus infections and in the host antiviral defense mechanisms. RESULTS Based on scientific literature, we present that pharmacological manipulation of proteostasis network can alter the fate of coronavirus infections and may help to prevent the resulting pathologies like Covid-19.
Collapse
|
|
33
|
Kaur R, Singh S, Singh TG, Sood P, Robert J. Covid-19: pharmacotherapeutic insights on various curative approaches in terms of vulnerability, comorbidities, and vaccination. Inflammopharmacology 2022; 30:1-21. [PMID: 34981320 PMCID: PMC8722419 DOI: 10.1007/s10787-021-00904-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 11/30/2021] [Indexed: 12/15/2022]
Abstract
A novel coronavirus disease (COVID-19), caused by a severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), was discovered in Wuhan, China, in December 2019, and the world has suffered from a pandemic. As of 22nd March 2020, at least 185 countries worldwide had been affected by COVID-19. SARS-CoV-2, leading to COVID-19 pneumonia, infects cells through ACE-2 receptors. The disease has different clinical signs and symptoms, including chills, high fever, dyspnea, and cough. Other symptoms including haemoptysis, myalgia, diarrhoea, expectoration, and fatigue may also occur. The rapid rise in confirmation cases is severe in preventing and controlling COVID-19. In this review, the article will explore and evaluate the insights into how COVID influences patients with other comorbid conditions such as cardiovascular disease, diabetes, Parkinson's, and how conditions Urolithiasis, anosmia, and anuria may develop after infection. The virus mutates and the variants are now prevalent in the present scenario where the world stands in eradicating the pandemic by looking into the development of vaccines by several countries and how the vaccination can temporarily help prevent COVID spread.
Collapse
Affiliation(s)
- Rupinder Kaur
- Chitkara College of Pharmacy, Chitkara University, Punjab, 140401, India
| | - Shareen Singh
- Chitkara College of Pharmacy, Chitkara University, Punjab, 140401, India
| | | | - Pragati Sood
- Chitkara College of Pharmacy, Chitkara University, Punjab, 140401, India
| | - Jiki Robert
- Chitkara College of Pharmacy, Chitkara University, Punjab, 140401, India
| |
Collapse
|
|
34
|
The Hybrid Incidence Susceptible-Transmissible-Removed Model for Pandemics : Scaling Time to Predict an Epidemic's Population Density Dependent Temporal Propagation. Acta Biotheor 2022; 70:10. [PMID: 35092515 PMCID: PMC8800439 DOI: 10.1007/s10441-021-09431-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Accepted: 11/01/2021] [Indexed: 11/07/2022]
Abstract
The susceptible-transmissible-removed (STR) model is a deterministic compartment model, based on the susceptible-infected-removed (SIR) prototype. The STR replaces 2 SIR assumptions. SIR assumes that the emigration rate (due to death or recovery) is directly proportional to the infected compartment’s size. The STR replaces this assumption with the biologically appropriate assumption that the emigration rate is the same as the immigration rate one infected period ago. This results in a unique delay differential equation epidemic model with the delay equal to the infected period. Hamer’s mass action law for epidemiology is modified to resemble its chemistry precursor—the law of mass action. Constructing the model for an isolated population that exists on a surface bounded by the extent of the population’s movements permits compartment density to replace compartment size. The STR reduces to a SIR model in a timescale that negates the delay—the transmissible timescale. This establishes that the SIR model applies to an isolated population in the disease’s transmissible timescale. Cyclical social interactions will define a rhythmic timescale. It is demonstrated that the geometric mean maps transmissible timescale properties to their rhythmic timescale equivalents. This mapping defines the hybrid incidence (HI). The model validation demonstrates that the HI-STR can be constructed directly from the disease’s transmission dynamics. The basic reproduction number (\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$${\mathcal{R}}_0$$\end{document}R0) is an epidemic impact property. The HI-STR model predicts that \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$${\mathcal{R}}_0 \propto \root \mathfrak{B} \of {\rho_n}$$\end{document}R0∝ρnB where \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$\rho_n$$\end{document}ρn is the population density, and \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$${\mathfrak{B}}$$\end{document}B is the ratio of time increments in the transmissible- and rhythmic timescales. The model is validated by experimentally verifying the relationship. \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$${\mathcal{R}}_0$$\end{document}R0’s dependence on \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$\rho_n$$\end{document}ρn is demonstrated for droplet-spread SARS in Asian cities, aerosol-spread measles in Europe and non-airborne Ebola in Africa.
Collapse
|
|
35
|
Ghanbari A, Khordad R, Ghaderi-Zefrehei M. Non-extensive thermodynamic entropy to predict the dynamics behavior of COVID-19. PHYSICA. B, CONDENSED MATTER 2022; 624:413448. [PMID: 34611380 PMCID: PMC8483613 DOI: 10.1016/j.physb.2021.413448] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 09/28/2021] [Indexed: 05/05/2023]
Abstract
The current world observations in COVID-19 are hardly tractable as a whole, making situations of information to be incompleteness. In pandemic era, mathematical modeling helps epidemiological scientists to take informing decisions about pandemic planning and predict the disease behavior in the future. In this work, we proposed a non-extensive entropy-based model on the thermodynamic approach for predicting the dynamics of COVID-19 disease. To do so, the epidemic details were considered into a single and time-dependent coefficients model. Their four constraints, including the existence of a maximum point were determined analytically. The model was worked out to give a log-normal distribution for the spread rate using the Tsallis entropy. The width of the distribution function was characterized by maximizing the rate of entropy production. The model predicted the number of daily cases and daily deaths with a fairly good agreement with the World Health Organization (WHO) reported data for world-wide, Iran and China over 2019-2020-time span. The proposed model in this work can be further calibrated to fit on different complex distribution COVID-19 data over different range of times.
Collapse
Affiliation(s)
- Ahmad Ghanbari
- Department of Physics, College of Science, Yasouj University, Yasouj, 75918-74934, Iran
| | - Reza Khordad
- Department of Physics, College of Science, Yasouj University, Yasouj, 75918-74934, Iran
| | | |
Collapse
|
|
36
|
Adla K, Dejan K, Neira D, Dragana Š. Degradation of ecosystems and loss of ecosystem services. One Health 2022. [DOI: 10.1016/b978-0-12-822794-7.00008-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
|
|
37
|
Smirnov NN. Infection evolution and spreading models in non-uniform biological systems. INFECTION, GENETICS AND EVOLUTION : JOURNAL OF MOLECULAR EPIDEMIOLOGY AND EVOLUTIONARY GENETICS IN INFECTIOUS DISEASES 2022; 97:105174. [PMID: 34864200 DOI: 10.1016/j.meegid.2021.105174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Revised: 11/20/2021] [Accepted: 11/29/2021] [Indexed: 06/13/2023]
Abstract
The paper investigates peculiarities of infection evolution and spreading models in non-uniform biological systems of individuals (humans, animals, plants) using the approach of mathematical modeling. The effects of different characteristic features are revealed. A robust tool for prediction of infection evolution (growth and spreading) under different external conditions is developed accounting for spatial non-uniformity of governing parameters.
Collapse
Affiliation(s)
- N N Smirnov
- Moscow M.V. Lomonosov State University, Moscow 119991, Russia.
| |
Collapse
|
|
38
|
Nascimento GC, Santos GM, Moura SRB, de Carvalho ARB, da Silva Andrade L, Moura LKB, Mendes F, Moreira MASP, Moura MEB. Bibliometric Analysis Of Research on Coronavirus Infection and Patient Safety in Health Care. Open Nurs J 2021. [DOI: 10.2174/1874434602115010373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Objective:
The study aimed at analyzing the international scientific publications on coronavirus infection and patient safety in health care.
Methods:
This research is a bibliometric study carried out by searching published articles in theISIWebofKnowledge/WebofScience database and analyzing the results through bibliometric analysis software HistCite. The selected time frame was between 1970 and 2020, and we used the following descriptors: “coronavirus infection” OR “severe acute respiratory syndrome” OR “COVID-19/SARS-CoV-2”.
Results: We found 5,434 publications in 1,491 different journals; they are written by 18,274 authors linked to 4,064 institutions, which are located in 104 countries. In the citations analysis, the h-index was 155, and the average of citations each article received was 30.79.
Conclusion:
During the studied period, the Web of Science database showed two peaks of publications on coronavirus infections.The first comprised 768 articles published between 2003 and 2004 when a new coronavirus caused an outbreak of severe acute respiratory failure. The second consisted of 576 articles published between 2019 and 2020, during the period of the COVID-19 pandemic COVID-19. The knowledge on coronavirus infection should be widely shared so that new studies can be designed and the world scientific community can contribute to improving patient safety in healthcare and preventing new pandemics of severe acute respiratory infection caused by coronaviruses.
Collapse
|
|
39
|
Yadav SK, Zhao S, Akhter Y. Response to Comments on "Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: a data-driven analysis in the early phase of the outbreak". Int J Infect Dis 2021; 115:70-71. [PMID: 34879227 PMCID: PMC8645260 DOI: 10.1016/j.ijid.2021.12.310] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 12/01/2021] [Indexed: 11/04/2022] Open
Affiliation(s)
- Subhash Kumar Yadav
- Department of Statistics, School of Physical and Decision Sciences, Babasaheb Bhimrao Ambedkar University, Lucknow 226025, India.
| | - Shi Zhao
- JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China
| | - Yusuf Akhter
- Department of Biotechnology, School of Life Sciences, Babasaheb Bhimrao Ambedkar University, Lucknow 226025, India.
| |
Collapse
|
|
40
|
Gudigar A, Raghavendra U, Nayak S, Ooi CP, Chan WY, Gangavarapu MR, Dharmik C, Samanth J, Kadri NA, Hasikin K, Barua PD, Chakraborty S, Ciaccio EJ, Acharya UR. Role of Artificial Intelligence in COVID-19 Detection. SENSORS (BASEL, SWITZERLAND) 2021; 21:8045. [PMID: 34884045 PMCID: PMC8659534 DOI: 10.3390/s21238045] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 11/26/2021] [Accepted: 11/26/2021] [Indexed: 12/15/2022]
Abstract
The global pandemic of coronavirus disease (COVID-19) has caused millions of deaths and affected the livelihood of many more people. Early and rapid detection of COVID-19 is a challenging task for the medical community, but it is also crucial in stopping the spread of the SARS-CoV-2 virus. Prior substantiation of artificial intelligence (AI) in various fields of science has encouraged researchers to further address this problem. Various medical imaging modalities including X-ray, computed tomography (CT) and ultrasound (US) using AI techniques have greatly helped to curb the COVID-19 outbreak by assisting with early diagnosis. We carried out a systematic review on state-of-the-art AI techniques applied with X-ray, CT, and US images to detect COVID-19. In this paper, we discuss approaches used by various authors and the significance of these research efforts, the potential challenges, and future trends related to the implementation of an AI system for disease detection during the COVID-19 pandemic.
Collapse
Affiliation(s)
- Anjan Gudigar
- Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India; (A.G.); (S.N.); (M.R.G.); (C.D.)
| | - U Raghavendra
- Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India; (A.G.); (S.N.); (M.R.G.); (C.D.)
| | - Sneha Nayak
- Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India; (A.G.); (S.N.); (M.R.G.); (C.D.)
| | - Chui Ping Ooi
- School of Science and Technology, Singapore University of Social Sciences, Singapore 599494, Singapore;
| | - Wai Yee Chan
- Department of Biomedical Imaging, Faculty of Medicine, University of Malaya, Kuala Lumpur 50603, Malaysia;
| | - Mokshagna Rohit Gangavarapu
- Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India; (A.G.); (S.N.); (M.R.G.); (C.D.)
| | - Chinmay Dharmik
- Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India; (A.G.); (S.N.); (M.R.G.); (C.D.)
| | - Jyothi Samanth
- Department of Cardiovascular Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal 576104, India;
| | - Nahrizul Adib Kadri
- Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia; (N.A.K.); (K.H.)
| | - Khairunnisa Hasikin
- Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia; (N.A.K.); (K.H.)
| | - Prabal Datta Barua
- Cogninet Brain Team, Cogninet Australia, Sydney, NSW 2010, Australia;
- School of Business (Information Systems), Faculty of Business, Education, Law & Arts, University of Southern Queensland, Toowoomba, QLD 4350, Australia
- Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia;
| | - Subrata Chakraborty
- Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia;
- Faculty of Science, Agriculture, Business and Law, University of New England, Armidale, NSW 2351, Australia
| | - Edward J. Ciaccio
- Department of Medicine, Columbia University Medical Center, New York, NY 10032, USA;
| | - U. Rajendra Acharya
- School of Engineering, Ngee Ann Polytechnic, Singapore 599489, Singapore;
- Department of Biomedical Informatics and Medical Engineering, Asia University, Taichung 41354, Taiwan
- International Research Organization for Advanced Science and Technology (IROAST), Kumamoto University, Kumamoto 860-8555, Japan
| |
Collapse
|
|
41
|
Saidi O, Malouche D, Saksena P, Arfaoui L, Talmoudi K, Hchaichi A, Bouguerra H, Romdhane HB, Hsairi M, Ouhichi R, Souteyrand Y, Alaya NB. Impact of contact tracing, respect of isolation, and lockdown in reducing the number of cases infected with COVID-19. Case study: Tunisia's response from March 22 to May 4, 2020. Int J Infect Dis 2021; 113:26-33. [PMID: 33578008 PMCID: PMC7872851 DOI: 10.1016/j.ijid.2021.02.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 12/29/2020] [Accepted: 02/02/2021] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Coronavirus disease 2019 (COVID-19) has spread rapidly across the world. Tunisia reacted early to COVID-19, resulting in a low number of infections during the first wave of the pandemic. This study was performed to model the effects of different interventions on the evolution of cases and to compare these with the Tunisian experience. METHODS A stochastic transmission model was used to quantify the reduction in number of cases of COVID-19 with the interventions of contact tracing, compliance with isolation, and a general lockdown. RESULTS In the model, increasing contact tracing from 20% to 80% after the first 100 cases reduced the cumulative number of infections (CNI) by 52% in 1 month. Similarly, increased compliance with isolation from 20% to 80% after the first 100 cases reduced the CNI by 45%. These reductions were smaller if the interventions were implemented after 1000 cases. A general lockdown reduced the CNI by 97% after the first 100 cases. Tunisia implemented its general lockdown after 75 cases were confirmed, which reduced the cumulative number of infected cases by 86% among the general population. CONCLUSIONS This study shows that the early application of critical interventions contributes significantly to reducing infections and the evolution of COVID-19 in a country. Tunisia's early success with the control of COVID-19 is explained by its quick response.
Collapse
Affiliation(s)
| | - Dhafer Malouche
- Higher School of Statistics and Data Analysis, University of Carthage, Tunisia
| | | | | | | | - Aicha Hchaichi
- National Observatory for New and Emerging Diseases (NONED), Tunisia
| | - Hend Bouguerra
- National Observatory for New and Emerging Diseases (NONED), Tunisia
| | | | - Mohamed Hsairi
- Tunisian Society of Epidemiologists, Faculty of Medicine Tunis, University El Manar, Tunisia
| | | | | | - Nissaf Ben Alaya
- National Observatory for New and Emerging Diseases (NONED), Tunisia
| |
Collapse
|
|
42
|
Acute Respiratory Distress Syndrome: Focus on Viral Origin and Role of Pulmonary Lymphatics. Biomedicines 2021; 9:biomedicines9111732. [PMID: 34829961 PMCID: PMC8615541 DOI: 10.3390/biomedicines9111732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 11/01/2021] [Accepted: 11/17/2021] [Indexed: 11/30/2022] Open
Abstract
Acute respiratory distress syndrome (ARDS) is a serious affection of the lung caused by a variety of pathologies. Great interest is currently focused on ARDS induced by viruses (pandemic influenza and corona viruses). The review describes pulmonary changes in ARDS and specific effects of the pandemic viruses in ARDS, and summarizes treatment options. Because the known pathogenic mechanisms cannot explain all aspects of the syndrome, the contribution of pulmonary lymphatics to the pathology is discussed. Organization and function of lymphatics in a healthy lung and in resorption of pulmonary edema are described. A future clinical trial may provide more insight into the role of hyaluronan in ARDS but the development of promising pharmacological treatments is unlikely because drugs play no important role in lymphedema therapy.
Collapse
|
|
43
|
Alshengeti A, Alahmadi H, Barnawi A, Alfuraydi N, Alawfi A, Al-Ahmadi A, Sheikh M, Almaghthawi A, Alnakhli Z, Rasheed R, Ibrahim A, Sobhi A, Al Shahrani D, Kordy F. Epidemiology, clinical features, and outcomes of coronavirus disease among children in Al-Madinah, Saudi Arabia: A retrospective study. INTERNATIONAL JOURNAL OF PEDIATRICS AND ADOLESCENT MEDICINE 2021; 9:136-142. [PMID: 35663790 PMCID: PMC9152574 DOI: 10.1016/j.ijpam.2021.11.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 10/12/2021] [Accepted: 11/02/2021] [Indexed: 12/24/2022] Open
Abstract
Background and Objective Coronavirus disease (COVID-19) is milder with favorable outcomes in children than in adults. However, detailed data regarding COVID-19 in children from Saudi Arabia are scarce. This study aimed to describe COVID-19 among children in Al-Madinah, Saudi Arabia. Methods This retrospective observational study included children <14 years old hospitalized with COVID-19 between May 1, 2020 and July 31, 2020. Clinical data, COVID-19 disease severity, and outcomes were collected. The total number of presenting symptoms and signs were computed by counting those recorded upon presentation. The Kruskal-Wallis non-parametric test was used to compare the number of symptoms and signs across all levels of COVID-19 severity. Result Overall, 106 patients met the inclusion criteria; their ages ranged from 2 weeks to 13 years. Most patients were ≤12 months of age (43.4%). Bronchial asthma was the most common comorbidity (9.4%). Among 99 symptomatic patients, fever was the most common symptom (84.8%); seven patients (7%) were diagnosed with febrile seizure. Most COVID-19 cases were mild (84%); one patient (0.94%) was in critical condition and one patient (0.94%) met the Multisystem Inflammatory Syndrome in children criteria. The mean number of symptoms and signs in children with severe or critical COVID-19 was significantly higher than that in children with mild cases or non-severe pneumonia (P < .001). One patient died owing to COVID-19 (0.94%). Conclusions COVID-19 mortality in children is rare; however, while most children exhibit mild disease with favorable outcomes, children with chronic lung disease may be at higher risk for severe disease.
Collapse
Affiliation(s)
- Amer Alshengeti
- Department of Pediatrics, College of Medicine, Taibah University, Al-Madinah, Saudi Arabia
- Infectious Disease Division, Department of Pediatrics, Madinah Maternity and Children Hospital, Al-Madinah, Saudi Arabia
- Infection Prevention and Control Department, Prince Mohammad Bin Abdulaziz Hospital, Ministry of National Guard-Health Affairs, Al-Madinah, Saudi Arabia
- Corresponding author. Department of Pediatrics, College of Medicine, Taibah University, Al-Madinah, Saudi Arabia.
| | - Hatem Alahmadi
- Infectious Disease Division, Department of Pediatrics, Madinah Maternity and Children Hospital, Al-Madinah, Saudi Arabia
| | - Ashwaq Barnawi
- Infectious Disease Division, Department of Pediatrics, Madinah Maternity and Children Hospital, Al-Madinah, Saudi Arabia
| | - Nouf Alfuraydi
- Infectious Disease Division, Department of Pediatrics, Madinah Maternity and Children Hospital, Al-Madinah, Saudi Arabia
| | - Abdulsalam Alawfi
- Department of Pediatrics, College of Medicine, Taibah University, Al-Madinah, Saudi Arabia
| | - Arwa Al-Ahmadi
- Department of Pediatrics, Madinah Maternity and Children Hospital, Al-Madinah, Saudi Arabia
| | - Mohammad Sheikh
- Department of Pediatrics, Madinah Maternity and Children Hospital, Al-Madinah, Saudi Arabia
| | - Amani Almaghthawi
- Department of Pediatrics, Madinah Maternity and Children Hospital, Al-Madinah, Saudi Arabia
| | - Zahera Alnakhli
- Department of Pediatrics, Madinah Maternity and Children Hospital, Al-Madinah, Saudi Arabia
| | - Raghad Rasheed
- Department of Pediatrics, Madinah Maternity and Children Hospital, Al-Madinah, Saudi Arabia
| | - Amany Ibrahim
- Department of Pediatrics, Saudi German Hospital, Al-Madinah, Saudi Arabia
- Diabetes Endocrine and Metabolic Pediatric Unit (DEMPU), Pediatric Department, Cairo University, Cairo, Egypt
| | - Ahmed Sobhi
- Department of Pediatrics, Saudi German Hospital, Al-Madinah, Saudi Arabia
- Pediatric Department, Cairo University, Cairo, Egypt
| | | | - Faisal Kordy
- Infectious Disease Division, Department of Pediatrics, Madinah Maternity and Children Hospital, Al-Madinah, Saudi Arabia
| |
Collapse
|
|
44
|
Liu T, Feng M, Wen Z, He Y, Lin W, Zhang M. Comparison of the Characteristics of Cytokine Storm and Immune Response Induced by SARS-CoV, MERS-CoV, and SARS-CoV-2 Infections. J Inflamm Res 2021; 14:5475-5487. [PMID: 34720596 PMCID: PMC8550203 DOI: 10.2147/jir.s329697] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 09/30/2021] [Indexed: 12/12/2022] Open
Abstract
Cytokine storm (CS) is a significant cause of death in patients with severe coronavirus pneumonia. Excessive immune-inflammatory reaction, many inflammatory cell infiltration, and extreme increase of proinflammatory cytokines and chemokines lead to acute lung injury and acute respiratory distress syndrome (ARDS). This review compares the characters of cytokine storms and immune responses caused by three highly pathogenic and infectious coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome-coronavirus (MERS-CoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and analyzes the possible mechanisms to guide clinical treatment in the future.
Collapse
Affiliation(s)
- Tong Liu
- Department of Medicine, Xizang Minzu University, Xianyang, Shaanxi, People’s Republic of China
| | - Meng Feng
- School of Basic Medicine, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, People’s Republic of China
| | - Zexin Wen
- Department of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian, People’s Republic of China
| | - Yijie He
- Department of Medicine, Xizang Minzu University, Xianyang, Shaanxi, People’s Republic of China
| | - Wei Lin
- School of Basic Medicine, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, People’s Republic of China
| | - Min Zhang
- Department of Medicine, Xizang Minzu University, Xianyang, Shaanxi, People’s Republic of China
| |
Collapse
|
|
45
|
Li Y, Tang XX. Abnormal Airway Mucus Secretion Induced by Virus Infection. Front Immunol 2021; 12:701443. [PMID: 34650550 PMCID: PMC8505958 DOI: 10.3389/fimmu.2021.701443] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 09/06/2021] [Indexed: 12/23/2022] Open
Abstract
The airway mucus barrier is a primary defensive layer at the airway surface. Mucins are the major structural components of airway mucus that protect the respiratory tract. Respiratory viruses invade human airways and often induce abnormal mucin overproduction and airway mucus secretion, leading to airway obstruction and disease. The mechanism underlying the virus-induced abnormal airway mucus secretion has not been fully studied so far. Understanding the mechanisms by which viruses induce airway mucus hypersecretion may open new avenues to treatment. In this article, we elaborate the clinical and experimental evidence that respiratory viruses cause abnormal airway mucus secretion, review the underlying mechanisms, and also discuss the current research advance as well as potential strategies to treat the abnormal airway mucus secretion caused by SARS-CoV-2.
Collapse
Affiliation(s)
- Yao Li
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xiao Xiao Tang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.,Guangzhou Laboratory, Bio-island, Guangzhou, China
| |
Collapse
|
|
46
|
Elsaid M, Nasef MA, Huy NT. R 0 of COVID-19 and its impact on vaccination coverage: compared with previous outbreaks. Hum Vaccin Immunother 2021; 17:3850-3854. [PMID: 34612165 DOI: 10.1080/21645515.2020.1865046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
Abstract
Background: Vaccination has been known to reduce morbidity and mortality of infectious diseases since the emergence of the 1st vaccine in the 18th century. That's why global efforts are directed toward finding a vaccine for COVID-19 in order to eliminate its threat.The current pandemic of COVID-19 has changed the world affecting all fields significantly as a result of the preventive measures including locking down, social distancing, obligatory mask wearing, stopping flights, etc. The medical field is clearly the most significantly affected starting from altering most of the research efforts toward the new virus passing through the inadequate number of physicians as well as unavailable intensive care unit (ICU) beds. In order to break the restricted preventive measures, we need to minimize the newly infected cases which can be achieved by reaching adequate herd immunity. Moreover, calculating the basic reproduction number (R0) of COVID-19 is crucial to estimate the herd immunity threshold (Ic).Methods: In this review, we searched PubMed for studies that mentioned the R0 of COVID_19, SARS, and MERS as well as measles, Zika and dengue virus to calculate the herd immunity threshold and the minimal vaccination coverage.Results: The value of R0 could vary for the same disease and consequently the herd immunity threshold as well as the vaccination coverage. The R0 of COVID-19 ranged widely through various articles from 1.4 to 6.68. As a result, the herd immunity threshold would range from 28.57% to 85.03%. However, the vaccination coverage depends also on the effectiveness of the vaccine which is still unknown.Conclusion: The calculations of vaccination coverage include many variables such as the R0 of the disease, Ic that depends on that value as well as sensitivity and specificity of the vaccine itself.
Collapse
Affiliation(s)
- Mohamed Elsaid
- Faculty of Medicine, Misr University for Science and Technology, Cairo, Egypt
| | | | - Nguyen Tien Huy
- School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan.,Institute of Research and Development, Duy Tan University, Da Nang, Vietnam
| |
Collapse
|
|
47
|
Duah M, Li L, Shen J, Lan Q, Pan B, Xu K. Thymus Degeneration and Regeneration. Front Immunol 2021; 12:706244. [PMID: 34539637 PMCID: PMC8442952 DOI: 10.3389/fimmu.2021.706244] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 08/16/2021] [Indexed: 01/08/2023] Open
Abstract
The immune system’s ability to resist the invasion of foreign pathogens and the tolerance to self-antigens are primarily centered on the efficient functions of the various subsets of T lymphocytes. As the primary organ of thymopoiesis, the thymus performs a crucial role in generating a self-tolerant but diverse repertoire of T cell receptors and peripheral T cell pool, with the capacity to recognize a wide variety of antigens and for the surveillance of malignancies. However, cells in the thymus are fragile and sensitive to changes in the external environment and acute insults such as infections, chemo- and radiation-therapy, resulting in thymic injury and degeneration. Though the thymus has the capacity to self-regenerate, it is often insufficient to reconstitute an intact thymic function. Thymic dysfunction leads to an increased risk of opportunistic infections, tumor relapse, autoimmunity, and adverse clinical outcome. Thus, exploiting the mechanism of thymic regeneration would provide new therapeutic options for these settings. This review summarizes the thymus’s development, factors causing thymic injury, and the strategies for improving thymus regeneration.
Collapse
Affiliation(s)
- Maxwell Duah
- Department of Hematology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou Medical University, Xuzhou, China.,Blood Diseases Institute, Xuzhou Medical University, Xuzhou, China
| | - Lingling Li
- Department of Hematology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou Medical University, Xuzhou, China.,Blood Diseases Institute, Xuzhou Medical University, Xuzhou, China
| | - Jingyi Shen
- Department of Hematology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou Medical University, Xuzhou, China.,Blood Diseases Institute, Xuzhou Medical University, Xuzhou, China
| | - Qiu Lan
- Department of Hematology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou Medical University, Xuzhou, China.,Blood Diseases Institute, Xuzhou Medical University, Xuzhou, China
| | - Bin Pan
- Department of Hematology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou Medical University, Xuzhou, China.,Blood Diseases Institute, Xuzhou Medical University, Xuzhou, China
| | - Kailin Xu
- Department of Hematology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou Medical University, Xuzhou, China.,Blood Diseases Institute, Xuzhou Medical University, Xuzhou, China
| |
Collapse
|
|
48
|
Singh P, Chauhan SS, Pandit S, Sinha M, Gupta S, Gupta A, Parthasarathi R. The dual role of phytochemicals on SARS-CoV-2 inhibition by targeting host and viral proteins. J Tradit Complement Med 2021; 12:90-99. [PMID: 34513611 PMCID: PMC8424525 DOI: 10.1016/j.jtcme.2021.09.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 09/05/2021] [Accepted: 09/06/2021] [Indexed: 12/26/2022] Open
Abstract
Background The severe acute respiratory syndrome-2019 has affected more than 190 million people around the world and caused severe crises throughout the globe. Due to rapid mutation in the viral genome, its became important to simultaneously improvise the host immunity while targeting viral proteins to reduce the severity of infection. Aim The current computational work focuses on multi-level rigorous screening of 47 medicinal plant-based phytochemicals for discovering effective phytochemical inhibitors against the host and viral targets. Experimental procedure A total of 586 phytochemicals were analyzed in detail based on their drug-likeness, pharmacological properties, and structure-based activity against the viral proteins (Spike glycoprotein, Papain-like protease, and Main protease) and host proteins (ACE2, Importin-subunit α-5, and β-1). Phytochemicals showing higher binding affinity with the dual capacity to target both the categories of proteins were further analyzed by profiling of their chemical reactivity using Density-Functional Theory (DFT) based quantum chemical methods. Finally, detailed molecular dynamics simulations were performed to analyze the interactions of the complexes. Results and conclusion The results revealed that the selected phytochemicals from Andrographis paniculata, Aconitum heterophyllum, Costus speciosus and Inula racemosa may have the capacity to act with prominent affinity towards the host and viral proteins. Therefore, the combination of active phytochemicals of these plants may prove to be more beneficial and can be used for developing the potential phytotherapeutic intervention.
COVID-19 caused severe crisis throughout the globe. Current drug discovery efforts are targeting SARS-CoV-2 viral and host proteins using repurposed drugs. Screening of 586 phytochemicals from 47 medicinal plants against both the host as well as viral targets. Phytochemicals probably acts by inhibiting specific targets, thus help in reducing SARS-CoV-2 infection.
Collapse
Affiliation(s)
- Prakrity Singh
- CSIR- Indian Institute of Toxicology Research, Vishvigyan Bhavan, 31, Mahatma Gandhi Marg, Lucknow, 226001, Uttar Pradesh, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, Uttar Pradesh, India
| | - Shweta Singh Chauhan
- CSIR- Indian Institute of Toxicology Research, Vishvigyan Bhavan, 31, Mahatma Gandhi Marg, Lucknow, 226001, Uttar Pradesh, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, Uttar Pradesh, India
| | - Shraddha Pandit
- CSIR- Indian Institute of Toxicology Research, Vishvigyan Bhavan, 31, Mahatma Gandhi Marg, Lucknow, 226001, Uttar Pradesh, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, Uttar Pradesh, India
| | - Meetali Sinha
- CSIR- Indian Institute of Toxicology Research, Vishvigyan Bhavan, 31, Mahatma Gandhi Marg, Lucknow, 226001, Uttar Pradesh, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, Uttar Pradesh, India
| | - Shristee Gupta
- CSIR- Indian Institute of Toxicology Research, Vishvigyan Bhavan, 31, Mahatma Gandhi Marg, Lucknow, 226001, Uttar Pradesh, India
| | - Anshika Gupta
- CSIR- Indian Institute of Toxicology Research, Vishvigyan Bhavan, 31, Mahatma Gandhi Marg, Lucknow, 226001, Uttar Pradesh, India
| | - Ramakrishnan Parthasarathi
- CSIR- Indian Institute of Toxicology Research, Vishvigyan Bhavan, 31, Mahatma Gandhi Marg, Lucknow, 226001, Uttar Pradesh, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, Uttar Pradesh, India
| |
Collapse
|
|
49
|
Budwong A, Auephanwiriyakul S, Theera-Umpon N. Infectious Disease Relational Data Analysis Using String Grammar Non-Euclidean Relational Fuzzy C-Means. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:8153. [PMID: 34360446 PMCID: PMC8346127 DOI: 10.3390/ijerph18158153] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 07/27/2021] [Accepted: 07/28/2021] [Indexed: 11/29/2022]
Abstract
Statistical analysis in infectious diseases is becoming more important, especially in prevention policy development. To achieve that, the epidemiology, a study of the relationship between the occurrence and who/when/where, is needed. In this paper, we develop the string grammar non-Euclidean relational fuzzy C-means (sgNERF-CM) algorithm to determine a relationship inside the data from the age, career, and month viewpoint for all provinces in Thailand for the dengue fever, influenza, and Hepatitis B virus (HBV) infection. The Dunn's index is used to select the best models because of its ability to identify the compact and well-separated clusters. We compare the results of the sgNERF-CM algorithm with the string grammar relational hard C-means (sgRHCM) algorithm. In addition, their numerical counterparts, i.e., relational hard C-means (RHCM) and non-Euclidean relational fuzzy C-means (NERF-CM) algorithms are also applied in the comparison. We found that the sgNERF-CM algorithm is far better than the numerical counterparts and better than the sgRHCM algorithm in most cases. From the results, we found that the month-based dataset does not help in relationship-finding since the diseases tend to happen all year round. People from different age ranges in different regions in Thailand have different numbers of dengue fever infections. The occupations that have a higher chance to have dengue fever are student and teacher groups from the central, north-east, north, and south regions. Additionally, students in all regions, except the central region, have a high risk of dengue infection. For the influenza dataset, we found that a group of people with the age of more than 1 year to 64 years old has higher number of influenza infections in every province. Most occupations in all regions have a higher risk of infecting the influenza. For the HBV dataset, people in all regions with an age between 10 to 65 years old have a high risk in infecting the disease. In addition, only farmer and general contractor groups in all regions have high chance of infecting HBV as well.
Collapse
Affiliation(s)
- Apiwat Budwong
- Department of Computer Engineering, Faculty of Engineering, Graduate School, Chiang Mai University, Chiang Mai 50200, Thailand;
| | - Sansanee Auephanwiriyakul
- Department of Computer Engineering, Faculty of Engineering, Excellence Center in Infrastructure Technology and Transportation Engineering, Biomedical Engineering Institute, Chiang Mai University, Chiang Mai 50200, Thailand
| | - Nipon Theera-Umpon
- Department of Electrical Engineering, Faculty of Engineering, Biomedical Engineering Institute, Chiang Mai University, Chiang Mai 50200, Thailand;
| |
Collapse
|
|
50
|
Berber E, Sumbria D, Çanakoğlu N. Meta-analysis and comprehensive study of coronavirus outbreaks: SARS, MERS and COVID-19. J Infect Public Health 2021; 14:1051-1064. [PMID: 34174535 PMCID: PMC8214867 DOI: 10.1016/j.jiph.2021.06.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 05/31/2021] [Accepted: 06/10/2021] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Zoonotic coronaviruses have caused several endemic and pandemic situations around the world. SARS caused the first epidemic alert at the beginning of this century, followed by MERS. COVID-19 appeared to be highly contagious, with human-to-human transmission by aerosol droplets, and reached nearly all countries around the world. A plethora of studies were performed, with reports being published within a short period of time by scientists and medical physicians. It has been difficult to find the relevant data to create an overview of the situation according to studies from accumulated findings and reports. In the present study we aimed to perform a comprehensive study in the context of the case fatality ratios (CFRs) of three major human Coronavirus outbreaks which occurred during the first twenty years of 21st century. METHODS In this study, we performed meta-analyses on SARS, MERS and COVID-19 outbreak events from publicly available records. Study analyses were performed with the help of highly reputable scientific databases such as PubMed, WOS and Scopus to evaluate and present current knowledge on zoonotic coronavirus outbreaks, starting from 2000 to the end of 2020. RESULTS A total of 250,194 research studies and records were identified with specific keywords and synonyms for the three viruses in order to cover all publications. In the end, 41 records were selected and included after applying several exclusion and inclusion criteria on identified datasets. SARS was found to have a nearly 11% case fatality ratio (CFR), which means the estimated number of deaths as a proportion of confirmed positive cases; Taiwan was the country most affected by the SARS outbreak based on the CFR analysis. MERS had CFRs of 35.8 and 26 in Saudi Arabia during the 2012 and 2015 outbreaks, respectively. COVID-19 resulted in a 2.2 CFR globally, and the USA reported the highest mortality ratio in the world in the end of first year of COVID-19 pandemic. CONCLUSION Some members of the Coronaviridae family can cause highly contagious and devastating infections among humans. Within the last two decades, the whole world has witnessed several deadly emerging infectious diseases, which are most commonly zoonotic in nature. We conclude that pre-existing immunity during the early stages of a pandemic might be important, but case control and management strategies should be improved to decrease CFRs. Finally, we have addressed several concerns in relation to outbreak events in this study.
Collapse
Affiliation(s)
- Engin Berber
- University of Tennessee, Department of Biomedical and Diagnostic Sciences, College of Veterinary Medicine, Knoxville, TN, USA; Erciyes University, College of Veterinary Medicine, Department of Virology, Kayseri, Turkey.
| | - Deepak Sumbria
- University of Tennessee, Department of Biomedical and Diagnostic Sciences, College of Veterinary Medicine, Knoxville, TN, USA; Dr. Yashwant Singh Parmar University of Horticulture and Forestry, Department of Silviculture and Agroforestry, College of Forestry, Solan, Himachal Pradesh, India
| | - Nurettin Çanakoğlu
- Muğla Sıtkı Koçman University, Milas Faculty of Veterinary Science, Department of Virology, Muğla, Turkey
| |
Collapse
|