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Romano CJ, Tsukuda TN, Zhao R, Quint J, Jain S, Murray EL. Excess Deaths in California During the COVID-19 Pandemic, by Healthy Places Index Quartile, February 2020-April 2022. Public Health Rep 2025:333549251314409. [PMID: 40298079 PMCID: PMC12040852 DOI: 10.1177/00333549251314409] [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: 04/30/2025] Open
Abstract
OBJECTIVES Place-based disadvantage indices have been used to assess health disparities and allocate funding and health resources. We assessed excess mortality in California during the COVID-19 pandemic by Healthy Places Index (HPI) quartile, a disadvantage index used by the California Department of Public Health to structure COVID-19 response efforts. METHODS We estimated expected deaths from all causes during the COVID-19 pandemic by fitting a quasi-Poisson regression model to actual deaths that occurred from 2014 through 2019. We estimated ranges of excess deaths by calculating differences between actual deaths and (1) the average expected number of deaths and (2) the upper bound of the 95% prediction interval. The percentage of excess deaths equaled the number of excess deaths divided by the corresponding threshold. We reported estimates overall and across demographic groups, stratified by HPI quartile; quartile 4 indicated communities with the most advantaged social and environmental conditions. RESULTS From February 2020 through April 2022, the number of excess deaths in California ranged from 81 245 to 107 806, with 93 309 deaths attributed to COVID-19. The number of excess deaths decreased across quartiles, from 27 924 to 35 615 (20.5%-28.0%) in HPI quartile 1 to 7757 to 14 477 (4.6%-9.2%) in HPI quartile 4. The Hispanic or Latine population had a disproportionate percentage of excess deaths across all quartiles, whereas American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Pacific Islander, and White (all non-Hispanic) populations had percentage excess death estimates in quartile 2 that were similar to or higher than in quartile 1. CONCLUSIONS Health policies should supplement the use of place-based disparity measures with other measures that support groups at high risk for adverse health outcomes residing in more socially and environmentally advantaged communities.
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Affiliation(s)
| | | | - Rui Zhao
- California Department of Public Health, Richmond, CA, USA
| | - Joshua Quint
- California Department of Public Health, Richmond, CA, USA
| | - Seema Jain
- California Department of Public Health, Richmond, CA, USA
| | - Erin L. Murray
- California Department of Public Health, Richmond, CA, USA
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Fernandes F, Turra CM, França GVA, Castro MC. Mortality by Cause of Death in Brazil: A Research Note on the Effects of the COVID-19 Pandemic and Contribution to Changes in Life Expectancy at Birth. Demography 2025; 62:381-404. [PMID: 40136060 DOI: 10.1215/00703370-11862487] [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: 03/27/2025]
Abstract
We analyze and quantify the ways the COVID-19 pandemic affected other causes of death in Brazil in 2020 and 2021. We decompose age-standardized mortality rate time series for 2010-2021 into three additive components: trend, seasonal, and remainder. Given the long-term trend and historical seasonal variation, we assume that most of the impact of the COVID-19 pandemic will be left in the remainder. We use a regression model to test this assumption. We decompose the contributions of COVID-19 deaths (direct effect) and those of other causes (indirect effects) to the annual change in life expectancy at birth (e0) from 2017 to 2021. The COVID-19 pandemic not only increased rates for other causes of death but also decreased rates for some causes. Broadly, the remainders mirror the COVID-19 pandemic waves. The direct effects of the pandemic reduced e0 by 1.88 years in 2019-2020 and by 1.77 in 2020-2021. Indirect effects increased e0 by 0.44 in 2019-2020 and had virtually no effect on e0 in 2020-2021. Whether the trajectories of mortality rates and annual gains in e0 will return to prepandemic levels and their interregional gradients depend on whether a nonnegligible number of patients who recovered from COVID-19 will suffer premature mortality.
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Affiliation(s)
- Fernando Fernandes
- Department of Demography, Cedeplar, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Cássio M Turra
- Department of Demography, Cedeplar, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | - Marcia C Castro
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA, USA
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Barančok P, Dudek J, Ištokovičová P, Kandilaki D, Kotrč M, Löffler Ľ, Mišík M, Mužik R, Saal B, Vrbiková M, Zajac R, Selvek M, Pažitný P. The Role of COVID-19 in Excess Mortality in Slovakia: A Novel Approach Based on Healthcare Billing Records. Int J Public Health 2024; 69:1607537. [PMID: 39691547 PMCID: PMC11649408 DOI: 10.3389/ijph.2024.1607537] [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: 05/21/2024] [Accepted: 11/22/2024] [Indexed: 12/19/2024] Open
Abstract
Objectives Propose a methodology to identify COVID-19 associated deaths using healthcare billing records and evaluate its effectiveness by comparing the results with excess mortality data from 2020 to 2022 and confirmed COVID-19 deaths. Methods A retrospective quantitative analysis was conducted by merging healthcare billing records with cause of death data. The term "COVID-19 associated death" was defined as any death occurring within a defined timeframe following a confirmed contact with COVID-19. This category includes individuals who died directly due to COVID-19, with COVID-19 as a contributing factor, or as an aftermath of a COVID-19 infection, as well as those who died from other causes but had previously contracted COVID-19. This broader definition provides a more comprehensive measure of excess mortality compared to the officially confirmed COVID-19 deaths attributed to the virus. Results We identified 35,399 COVID-19 associated deaths during the 3-year pandemic in Slovakia compared to 21,395 confirmed COVID-19 deaths. Conclusion The identification of COVID-19 associated deaths with our methodology offers a more accurate explanation for the notably high excess mortality observed in Slovakia (31,789 deaths) during the pandemic, relative to the EU27. Given the high level of excess mortality, the officially confirmed deaths are likely underestimated, and the presented methodology provides a more precise measure of mortality. Additionally, healthcare billing records prove valuable in identifying these deaths at the individual patient level using claims data of health insurance companies, which is crucial for implementing targeted preventive measures and improving preparedness for future pandemics.
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Affiliation(s)
- Peter Barančok
- Institute for Healthcare Analyses, Ministry of Health, Bratislava, Slovakia
| | - Ján Dudek
- White Plume Technologies, Birmingham, AL, United States
| | - Petra Ištokovičová
- Institute for Healthcare Analyses, Ministry of Health, Bratislava, Slovakia
| | - Daniela Kandilaki
- Faculty of Management, Prague University of Economics and Business, Prague, Czechia
| | - Michal Kotrč
- Union Health Insurance Company, Bratislava, Slovakia
| | | | - Matej Mišík
- Institute for Healthcare Analyses, Ministry of Health, Bratislava, Slovakia
| | - Roman Mužik
- Dôvera Health Insurance Company, Bratislava, Slovakia
| | - Beáta Saal
- Dôvera Health Insurance Company, Bratislava, Slovakia
| | - Martina Vrbiková
- Reporting and Health Statistics, National Health Information Center, Bratislava, Slovakia
| | - Rudolf Zajac
- Independent Healthcare Consultant, Bratislava, Slovakia
| | - Martin Selvek
- Dôvera Health Insurance Company, Bratislava, Slovakia
| | - Peter Pažitný
- Faculty of Management, Prague University of Economics and Business, Prague, Czechia
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Archer A, White M, Quinn M, Wykoff R. Using Public Funeral and Obituary Listings to Identify Spikes in Excess Mortality in One Appalachian County. JOURNAL OF APPALACHIAN HEALTH 2024; 6:4-20. [PMID: 39534734 PMCID: PMC11552678 DOI: 10.13023/jah.0603.02] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/16/2024]
Abstract
Introduction Delays (10-22 months) in availability of official state and county-level mortality data could have significant public health consequences. The COVID-19 pandemic illuminated the need for health officials to access timely death data to identify unexpected increases in mortality in their communities. Purpose The purpose of this study is to determine if funeral home listings and/or newspaper obituaries could help identify excess mortality on the local level, prior to the availability of official death records. Methods To calculate excess mortality, four years (2017-2020) of data were collected from three sources: the state health department, online funeral home listings, and newspaper obituaries, all from Washington County, Tennessee. Simple linear regression was used to predict number of expected deaths by month for 2020 using 2017, 2018, and 2019 reported deaths, by data source. The percent difference of actual 2020 deaths from the expected deaths was then calculated by month and compared for each data source. Results Official COVID-19 state-reported death data accounted for only 50% of excess mortality estimated in 2020. Nearly 100 excess deaths occurred before the first reported death due to COVID-19. Trends in the percent difference between actual and expected funeral home listings and newspaper obituaries followed similar patterns as percent differences in actual v. expected state-reported mortality data. Implications Had funeral home listings and newspaper obituaries been used to identify excess mortality, health officials would have seen increases in mortality nearly five months prior to the first identified COVID-19 death. These publicly available tools could prove valuable to local health officials as an "early warning" sign of excess mortality.
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Dziadzko M, Belhassen M, Van Ganse E, Heritier F, Berard M, Marant-Micallef C, Aubrun F. Health Care Resource Use and Total Mortality After Hospital Admission for Severe COVID-19 Infections During the Initial Pandemic Wave in France: Descriptive Study. JMIR Public Health Surveill 2024; 10:e56398. [PMID: 39259961 PMCID: PMC11425017 DOI: 10.2196/56398] [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: 01/16/2024] [Revised: 06/28/2024] [Accepted: 07/21/2024] [Indexed: 09/13/2024] Open
Abstract
BACKGROUND Little is known about post-hospital health care resource use (HRU) of patients admitted for severe COVID-19, specifically for the care of patients with postacute COVID-19 syndrome (PACS). OBJECTIVE A list of HRU domains and items potentially related to PACS was defined, and potential PACS-related HRU (PPRH) was compared between the pre- and post-COVID-19 periods, to identify new outpatient care likely related to PACS. METHODS A retrospective cohort study was conducted with the French National Health System claims data (SNDS). All patients hospitalized for COVID-19 between February 1, 2020, and June 30, 2020 were described and investigated for 6 months, using discharge date as index date. Patients who died during index stay or within 30 days after discharge were excluded. PPRH was assessed over the 5 months from day 31 after index date to end of follow-up, that is, for the post-COVID-19 period. For each patient, a pre-COVID-19 period was defined that covered the same calendar time in 2019, and pre-COVID-19 PPRH was assessed. Post- or pre- ratios (PP ratios) of the percentage of users were computed with their 95% CIs, and PP ratios>1.2 were considered as "major HRU change." RESULTS The final study population included 68,822 patients (median age 64.8 years, 47% women, median follow-up duration 179.3 days). Altogether, 23% of the patients admitted due to severe COVID-19 died during the hospital stay or within the 6 months following discharge. A total of 8 HRU domains were selected to study PPRH: medical visits, technical procedures, dispensed medications, biological analyses, oxygen therapy, rehabilitation, rehospitalizations, and nurse visits. PPRs showed novel outpatient care in all domains and in most items, without specificity, with the highest ratios observed for the care of thoracic conditions. CONCLUSIONS Patients hospitalized for severe COVID-19 during the initial pandemic wave had high morbi-mortality. The analysis of HRU domains and items most likely to be related to PACS showed that new care was commonly initiated after discharge but with no specificity, potentially suggesting that any impact of PACS was part of the overall high HRU of this population after hospital discharge. These purely descriptive results need to be completed with methods for controlling for confusion bias through subgroup analyses. TRIAL REGISTRATION ClinicalTrials.gov NCT05073328; https://clinicaltrials.gov/ct2/show/NCT05073328.
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Affiliation(s)
- Mikhail Dziadzko
- Hospices Civils de Lyon, Hôpital de la Croix Rousse, Département d'Anesthésie-Réanimation, Douleur, Lyon, France
- Laboratoire RESHAPE, Université Claude Bernard Lyon 1, INSERM UMR 1290, Lyon, France
| | | | - Eric Van Ganse
- Laboratoire RESHAPE, Université Claude Bernard Lyon 1, INSERM UMR 1290, Lyon, France
- PELyon, Lyon, France
- Hospices Civils de Lyon, Hôpital de la Croix Rousse, Département de la Médecine Respiratoire, Lyon, France
| | - Fabrice Heritier
- Centre Hospitalier de Roanne, Département d'Anesthésie-Réanimation, Roanne, France
| | | | | | - Frederic Aubrun
- Hospices Civils de Lyon, Hôpital de la Croix Rousse, Département d'Anesthésie-Réanimation, Douleur, Lyon, France
- Laboratoire RESHAPE, Université Claude Bernard Lyon 1, INSERM UMR 1290, Lyon, France
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Fess LJ, Fell A, O'Toole S, D'Heilly P, Holzbauer S, Kollmann L, Markelz A, Morris K, Ruhland A, Seys S, Schiffman E, Wienkes H, Zirnhelt Z, Meyer S, Como-Sabetti K. COVID-19 Death Determination Methods, Minnesota, USA, 2020-2022 1. Emerg Infect Dis 2024; 30:1352-1360. [PMID: 38916546 PMCID: PMC11210668 DOI: 10.3201/eid3007.231522] [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: 06/26/2024] Open
Abstract
Accurate and timely mortality surveillance is crucial for elucidating risk factors, particularly for emerging diseases. We compared use of COVID-19 keywords on death certificates alone to identify COVID-19 deaths in Minnesota, USA, during 2020-2022, with use of a standardized mortality definition incorporating additional clinical data. For analyses, we used likelihood ratio χ2 and median 1-way tests. Death certificates alone identified 96% of COVID-19 deaths confirmed by the standardized definition and an additional 3% of deaths that had been classified as non-COVID-19 deaths by the standardized definition. Agreement between methods was >90% for most groups except children, although agreement among adults varied by demographics and location at death. Overall median time from death to filing of death certificate was 3 days; decedent characteristics and whether autopsy was performed varied. Death certificates are an efficient and timely source of COVID-19 mortality data when paired with SARS-CoV-2 testing data.
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Bonnet F, Grigoriev P, Sauerberg M, Alliger I, Mühlichen M, Camarda CG. Spatial Variation in Excess Mortality Across Europe: A Cross-Sectional Study of 561 Regions in 21 Countries. J Epidemiol Glob Health 2024; 14:470-479. [PMID: 38376764 PMCID: PMC11176282 DOI: 10.1007/s44197-024-00200-0] [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: 08/31/2023] [Accepted: 01/24/2024] [Indexed: 02/21/2024] Open
Abstract
OBJECTIVE To measure the burden of the COVID-19 pandemic in 2020 at the subnational level by estimating excess mortality, defined as the increase in all-cause mortality relative to an expected baseline mortality level. METHODS Statistical and demographic analyses of regional all-cause mortality data provided by the vital statistics systems of 21 European countries for 561 regions in Central and Western Europe. Life expectancy losses at ages 0 and 60 for males and females were estimated. RESULTS We found evidence of a loss in life expectancy in 391 regions, whilst only three regions exhibit notable gains in life expectancy in 2020. For 12 regions, losses of life expectancy amounted to more than 2 years and three regions showed losses greater than 3 years. We highlight geographical clusters of high mortality in Northern Italy, Spain and Poland, whilst clusters of low mortality were found in Western France, Germany/Denmark and Norway/Sweden. CONCLUSIONS Regional differences of loss of life expectancy are impressive, ranging from a loss of more than 4 years to a gain of 8 months. These findings provide a strong rationale for regional analysis, as national estimates hide significant regional disparities.
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Affiliation(s)
- Florian Bonnet
- French Institute for Demographic Studies (INED), 9 cours des Humanités, 93300, Aubervilliers, France.
| | - Pavel Grigoriev
- French Institute for Demographic Studies (INED), 9 cours des Humanités, 93300, Aubervilliers, France
| | - Markus Sauerberg
- Federal Institute for Population Research (BiB), Wiesbaden, Germany
| | - Ina Alliger
- Federal Institute for Population Research (BiB), Wiesbaden, Germany
| | | | - Carlo-Giovanni Camarda
- French Institute for Demographic Studies (INED), 9 cours des Humanités, 93300, Aubervilliers, France
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Rotondo-Trivette S, He XY, Samaan JS, Lv F, Truong E, Juels M, Nguyen A, Gao X, Zu J, Yeo YH, Ji FP, Melmed GY. Excess non-COVID-19-related mortality among inflammatory bowel disease decedents during the COVID-19 pandemic. World J Gastroenterol 2024; 30:2677-2688. [PMID: 38855149 PMCID: PMC11154683 DOI: 10.3748/wjg.v30.i20.2677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 01/10/2024] [Accepted: 02/22/2024] [Indexed: 05/27/2024] Open
Abstract
BACKGROUND The coronavirus disease 2019 (COVID-19) pandemic disrupted healthcare in the United States. AIM To investigate COVID-19-related and non-COVID-19-related death and characteristics associated with excess death among inflammatory bowel disease (IBD) decedents. METHODS We performed a register-based study using data from the National Vital Statistics System, which reports death data from over 99% of the United States population, from January 1, 2006 through December 31, 2021. IBD-related deaths among adults 25 years and older were stratified by age, sex, race/ethnicity, place of death, and primary cause of death. Predicted and actual age-standardized mortality rates (ASMRs) per 100000 persons were compared. RESULTS 49782 IBD-related deaths occurred during the study period. Non-COVID-19-related deaths increased by 13.14% in 2020 and 18.12% in 2021 [2020 ASMR: 1.55 actual vs 1.37 predicted, 95% confidence interval (CI): 1.26-1.49; 2021 ASMR: 1.63 actual vs 1.38 predicted, 95%CI: 1.26-1.49]. In 2020, non-COVID-19-related mortality increased by 17.65% in ulcerative colitis (UC) patients between the ages of 25 and 65 and 36.36% in non-Hispanic black (NHB) Crohn's disease (CD) patients. During the pandemic, deaths at home or on arrival and at medical facilities as well as deaths due to neoplasms also increased. CONCLUSION IBD patients suffered excess non-COVID-19-related death during the pandemic. Excess death was associated with younger age among UC patients, and with NHB race among CD patients. Increased death at home or on arrival and due to neoplasms suggests that delayed presentation and difficulty accessing healthcare may have led to increased IBD mortality.
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Affiliation(s)
- Sarah Rotondo-Trivette
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States
| | - Xin-Yuan He
- Department of Infectious Disease, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, Shaanxi Province, China
| | - Jamil S Samaan
- Karsh Division of Gastroenterology and Hepatology Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States
| | - Fan Lv
- School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an 710049, Shaanxi Province, China
| | - Emily Truong
- Karsh Division of Gastroenterology and Hepatology Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States
| | - Michaela Juels
- David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, United States
| | - Anthony Nguyen
- David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, United States
| | - Xu Gao
- Department of Infectious Disease, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, Shaanxi Province, China
- Division of Gastroenterology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, Shaanxi Province, China
| | - Jian Zu
- School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an 710049, Shaanxi Province, China
| | - Yee Hui Yeo
- Karsh Division of Gastroenterology and Hepatology Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States
| | - Fan-Pu Ji
- Department of Infectious Disease, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, Shaanxi Province, China
- National and Local Joint Engineering Research Center of Biodiagnosis and Biotherapy, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, Shaanxi Province, China
- Key Laboratory of Surgical Critical Care and Life Support (Xi’an Jiaotong University), Ministry of Education, Xi’an 710004, Shaanxi Province, China
| | - Gil Y Melmed
- Karsh Division of Gastroenterology and HepatologyDepartment of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States
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Bonnet F, Grigoriev P, Sauerberg M, Alliger I, Mühlichen M, Camarda CG. Spatial disparities in the mortality burden of the covid-19 pandemic across 569 European regions (2020-2021). Nat Commun 2024; 15:4246. [PMID: 38762653 PMCID: PMC11102496 DOI: 10.1038/s41467-024-48689-0] [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: 12/18/2023] [Accepted: 05/08/2024] [Indexed: 05/20/2024] Open
Abstract
Since its emergence in December 2019, the COVID-19 pandemic has resulted in a significant increase in deaths worldwide. This article presents a detailed analysis of the mortality burden of the COVID-19 pandemic across 569 regions in 25 European countries. We produce age and sex-specific excess mortality and present our results using Age-Standardised Years of Life Lost in 2020 and 2021, as well as the cumulative impact over the two pandemic years. Employing a forecasting approach based on CP-splines that considers regional diversity and provides confidence intervals, we find notable losses in 362 regions in 2020 (440 regions in 2021). Conversely, only seven regions experienced gains in 2020 (four regions in 2021). We also estimate that eight regions suffered losses exceeding 20 years of life per 1000 population in 2020, whereas this number increased to 75 regions in 2021. The contiguity of the regions investigated in our study also reveals the changing geographical patterns of the pandemic. While the highest excess mortality values were concentrated in the early COVID-19 outbreak areas during the initial pandemic year, a clear East-West gradient appeared in 2021, with regions of Slovakia, Hungary, and Latvia experiencing the highest losses. This research underscores the importance of regional analyses for a nuanced comprehension of the pandemic's impact.
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Affiliation(s)
- Florian Bonnet
- French Institute for Demographic Studies (INED), Aubervilliers, France.
| | - Pavel Grigoriev
- Federal Institute for Population Research (BiB), Wiesbaden, Germany
| | - Markus Sauerberg
- Federal Institute for Population Research (BiB), Wiesbaden, Germany
| | - Ina Alliger
- Federal Institute for Population Research (BiB), Wiesbaden, Germany
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10
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Campos MAG, Cutrim ÉAM, Cutrim ÉMM, de Oliveira JVP, de Oliveira EJSG, Pontes DDB, de Figueiredo JA, Silva GEB. Accuracy of the Verbal Autopsy questionnaire in the diagnosis of COVID-19 deaths in a Brazilian capital. Rev Inst Med Trop Sao Paulo 2024; 66:e33. [PMID: 38747854 PMCID: PMC11095245 DOI: 10.1590/s1678-9946202466033] [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: 01/17/2024] [Accepted: 03/27/2024] [Indexed: 05/19/2024] Open
Abstract
The Verbal Autopsy (VA) is a questionnaire about the circumstances surrounding a death. It was widely used in Brazil to assist in postmortem diagnoses and investigate excess mortality during the Coronavirus Disease 2019 (COVID-19) pandemic. This study aimed to determine the accuracy of investigating acute respiratory distress syndrome (ARDS) using VA. This is a cross-sectional study with prospective data collected from January 2020 to August 2021 at the Death Verification Service of Sao Luis city, Brazil. VA was performed for suspected COVID-19 deaths, and one day of the week was randomly chosen to collect samples from patients without suspected COVID-19. Two swabs were collected after death and subjected to reverse transcription-polymerase chain reaction (RT-PCR) for SARS-CoV-2 detection. Of the 250 cases included, the VA questionnaire identified COVID-19-related ARDS in 67.2% (52.98% were positive for COVID-19). The sensitivity of the VA questionnaire was 0.53 (0.45-0.61), the specificity was 0.75 (0.64-0.84), the positive predictive value was 0.81 (0.72-0.88), and the negative predictive value was 0.44 (0.36-0.53). The VA had a lower-than-expected accuracy for detecting COVID-19 deaths; however, because it is an easily accessible and cost-effective tool, it can be combined with more accurate methods to improve its performance.
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Affiliation(s)
- Marcos Adriano Garcia Campos
- Universidade Estadual Paulista, Faculdade de Medicina de Botucatu, Hospital das Clínicas, Botucatu, São Paulo, Brazil
| | | | - Érico Murilo Monteiro Cutrim
- Universidade Estadual Paulista, Faculdade de Medicina de Botucatu, Hospital das Clínicas, Botucatu, São Paulo, Brazil
| | | | | | | | | | - Gyl Eanes Barros Silva
- Universidade Federal do Maranhão, Faculdade de Medicina, São Luís, Maranhão, Brazil
- Universidade de São Paulo, Faculdade de Medicina de Ribeirão Preto, Departamento de Patologia e Medicina Legal, Ribeirão Preto, São Paulo, Brazil
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11
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Ziakas PD, Mylonakis E. Public interest trends for COVID-19 and pandemic trajectory: A time-series analysis of US state-level data. PLOS DIGITAL HEALTH 2024; 3:e0000462. [PMID: 38471136 DOI: 10.1371/journal.pdig.0000462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Accepted: 02/06/2024] [Indexed: 03/14/2024]
Abstract
Google Trends provides spatiotemporal data for user-specific terms scaled from less than 1 (lowest relative popularity) to 100 (highest relative popularity) as a proxy for the public interest. Here we use US state-level data for COVID-19 to examine popularity trends during the pandemic evolution. We used "coronavirus" and "covid" search terms and set the period up from January 1st, 2020, to November 12, 2022. We measured the agreement on web rankings between states using the nonparametric Kendall's W (0 for no concordance to 1 for perfect agreement). We compiled state-level weekly data on COVID-19 incidence and mortality and scaled state curves from 0 to 100 through a min-max normalization process. We used a dynamic time-warping algorithm to calculate similarities between the popularity, mortality, and incidence of COVID-19. The methodology is a pattern recognition process between time series by distance optimization. The similarity was mapped from 0 to 1, with 1 indicating perfect similarity and 0 indicating no similarity. The peak in popularity was in March 2020, succeeded by a decline and a prolonged period of fluctuation around 20%. Public interest rose briefly at the end of 2021, to fall to a low activity of around 10%. This pattern was remarkably consistent across states (Kendal's W 0.94, p < 0.001). Web search trends were an impression of contagion growth: Overall, popularity-mortality trajectories yielded higher similarity indices (median 0.78; interquartile range 0.75-0.82) compared to popularity-incidence trajectories (median 0.74; interquartile range 0.72-0.76, Wilcoxon's exact p<0.001). The popularity-mortality trajectories had a very strong similarity (>0.80) in 19/51 (37%) regions, as opposed to only 4/51 (8%) for popularity-incidence trajectories. State-level data show a fading public concern about COVID-19, and web-search popularity patterns may reflect the COVID-19 trajectory in terms of cases and mortality.
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Affiliation(s)
- Panayiotis D Ziakas
- Department of Medicine, Brown University, Providence, Rhode Island, United States of America
| | - Eleftherios Mylonakis
- Department of Medicine, Houston Methodist Hospital, Houston, Texas, United States of America
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Cristelli MP, Fortaleza CMCB, Pereira JFCA, Taddeo JB, Viana LA, Requião-Moura LR, Chow CYZ, Nakamura MR, Tedesco-Silva H, Medina-Pestana J. Excess mortality among kidney transplant recipients: Impact of COVID-19-related deaths during the pandemic. Transpl Infect Dis 2024; 26:e14204. [PMID: 38010722 DOI: 10.1111/tid.14204] [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: 07/07/2023] [Revised: 11/11/2023] [Accepted: 11/14/2023] [Indexed: 11/29/2023]
Abstract
BACKGROUND Because COVID-19 has been associated with high lethality rates among kidney transplant recipients (KTR), but also with a severe disruption and delays in overall healthcare, this study aims to evaluate the excess mortality in the pandemic era among KTR in a high-volume Brazilian transplant center. METHODS This study used data from a single center that provides follow-up on all its transplant recipients. The population of interest included all the patients who were transplanted between August 31, 1983 and December 31, 2022 and who were live from January 1, 2014. Using the "AutoRegressive Integrated Moving Average" forecasting algorithm, the expected mortality for the pandemic era (2020-2022) was modeled from the pre-pandemic era (2014-2019). RESULTS There were 12 077 KTRs at risk of dying in the entire observation period. In the pre-pandemic era, there were 21 deaths per 1000 patients at risk. In the pandemic era, there were 1429 observed deaths (rate of 47 deaths per 1000 patients at risk) versus the expected 587 deaths, resulting in an absolute number of 842 excess deaths, or an observed-to-expected ratio of 2.4, or an absolute rate of 26 deaths in excess per 1000 patients at risk. The excess deaths exhibited a temporal pattern mirroring that of the surges in new cases and lethality rates of COVID-19. COVID-19-related deaths drove 94% of excess mortality in the pandemic era. CONCLUSION In this large cohort of KTR under centralized follow-up, more than twofold excess mortality was primarily driven by COVID-19-related deaths, highlighting the vulnerability of this population to the most severe presentation of SARS-CoV-2 infection.
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Affiliation(s)
| | | | | | | | | | - Lucio Roberto Requião-Moura
- Hospital do Rim, Fundação Oswaldo Ramos, São Paulo, Brazil
- Nephrology Division, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Charles Yea Zen Chow
- Hospital do Rim, Fundação Oswaldo Ramos, São Paulo, Brazil
- Nephrology Division, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Monica Rika Nakamura
- Hospital do Rim, Fundação Oswaldo Ramos, São Paulo, Brazil
- Nephrology Division, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Helio Tedesco-Silva
- Hospital do Rim, Fundação Oswaldo Ramos, São Paulo, Brazil
- Nephrology Division, Universidade Federal de São Paulo, São Paulo, Brazil
| | - José Medina-Pestana
- Hospital do Rim, Fundação Oswaldo Ramos, São Paulo, Brazil
- Nephrology Division, Universidade Federal de São Paulo, São Paulo, Brazil
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13
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Bonnet F, Camarda CG. Estimating subnational excess mortality in times of pandemic. An application to French départements in 2020. PLoS One 2024; 19:e0293752. [PMID: 38241216 PMCID: PMC10798530 DOI: 10.1371/journal.pone.0293752] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 10/18/2023] [Indexed: 01/21/2024] Open
Abstract
The COVID-19 pandemic's uneven impact on subnational regions highlights the importance of understanding its local-level mortality impact. Vital statistics are available for an increasing number of countries for 2020, 2021, and 2022, facilitating the computation of subnational excess mortality and a more comprehensive assessment of its burden. However, this calculation faces two important methodological challenges: it requires appropriate mortality projection models; and small populations imply considerable, though commonly neglected, uncertainty in the estimates. We address both issues using a method to forecast mortality at the subnational level, which incorporates uncertainty in the computation of mortality measures. We illustrate our approach by examining French départements (NUTS 3 regions, or 95 geographical units), and produce sex-specific estimates for 2020. This approach is highly flexible, allowing one to estimate excess mortality during COVID-19 in most demographic scenarios and for past pandemics.
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Affiliation(s)
- Florian Bonnet
- Institut national d’études démographiques (INED), Aubervilliers, France
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14
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Habibdoust A, Seifaddini M, Tatar M, Araz OM, Wilson FA. Predicting COVID-19 new cases in California with Google Trends data and a machine learning approach. Inform Health Soc Care 2024; 49:56-72. [PMID: 38353707 DOI: 10.1080/17538157.2024.2315246] [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: 04/10/2024]
Abstract
BACKGROUND Google Trends data can be a valuable source of information for health-related issues such as predicting infectious disease trends. OBJECTIVES To evaluate the accuracy of predicting COVID-19 new cases in California using Google Trends data, we develop and use a GMDH-type neural network model and compare its performance with a LTSM model. METHODS We predicted COVID-19 new cases using Google query data over three periods. Our first period covered March 1, 2020, to July 31, 2020, including the first peak of infection. We also estimated a model from October 1, 2020, to January 7, 2021, including the second wave of COVID-19 and avoiding possible biases from public interest in searching about the new pandemic. In addition, we extended our forecasting period from May 20, 2020, to January 31, 2021, to cover an extended period of time. RESULTS Our findings show that Google relative search volume (RSV) can be used to accurately predict new COVID-19 cases. We find that among our Google relative search volume terms, "Fever," "COVID Testing," "Signs of COVID," "COVID Treatment," and "Shortness of Breath" increase model predictive accuracy. CONCLUSIONS Our findings highlight the value of using data sources providing near real-time data, e.g., Google Trends, to detect trends in COVID-19 cases, in order to supplement and extend existing epidemiological models.
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Affiliation(s)
- Amir Habibdoust
- Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri, USA
| | | | - Moosa Tatar
- Department of Pharmaceutical Health Outcomes and Policy, University of Houston College of Pharmacy, Houston, Texas, USA
| | - Ozgur M Araz
- College of Business, University of Nebraska- Lincoln, Lincoln, Nebraska, USA
| | - Fernando A Wilson
- Matheson Center for Health Care Studies, University of Utah, Salt Lake City, Utah, USA
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA
- Department of Economics, University of Utah, Salt Lake City, Utah, USA
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15
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Valgañón P, Lería U, Soriano-Paños D, Gómez-Gardeñes J. Socioeconomic determinants of stay-at-home policies during the first COVID-19 wave. Front Public Health 2023; 11:1193100. [PMID: 37475770 PMCID: PMC10354257 DOI: 10.3389/fpubh.2023.1193100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 06/19/2023] [Indexed: 07/22/2023] Open
Abstract
Introduction The COVID-19 pandemic has had a significant impact on public health and social systems worldwide. This study aims to evaluate the efficacy of various policies and restrictions implemented by different countries to control the spread of the virus. Methods To achieve this objective, a compartmental model is used to quantify the "social permeability" of a population, which reflects the inability of individuals to remain in confinement and continue social mixing allowing the spread of the virus. The model is calibrated to fit and recreate the dynamics of the epidemic spreading of 42 countries, mainly taking into account reported deaths and mobility across the populations. Results The results indicate that low-income countries have a harder time slowing the advance of the pandemic, even if the virus did not initially propagate as fast as in wealthier countries, showing the disparities between countries in their ability to mitigate the spread of the disease and its impact on vulnerable populations. Discussion This research contributes to a better understanding of the socioeconomic and environmental factors that affect the spread of the virus and the need for equitable policy measures to address the disparities in the global response to the pandemic.
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Affiliation(s)
- Pablo Valgañón
- Department of Condensed Matter Physics, University of Zaragoza, Zaragoza, Spain
- GOTHAM Lab - Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, Zaragoza, Spain
| | - Unai Lería
- Department of Condensed Matter Physics, University of Zaragoza, Zaragoza, Spain
| | - David Soriano-Paños
- GOTHAM Lab - Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, Zaragoza, Spain
- Institute Gulbenkian of Science (IGC), Oeiras, Portugal
| | - Jesús Gómez-Gardeñes
- Department of Condensed Matter Physics, University of Zaragoza, Zaragoza, Spain
- GOTHAM Lab - Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, Zaragoza, Spain
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16
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Toh KB, Runge M, Richardson RA, Hladish TJ, Gerardin J. Design of effective outpatient sentinel surveillance for COVID-19 decision-making: a modeling study. BMC Infect Dis 2023; 23:287. [PMID: 37142984 PMCID: PMC10158704 DOI: 10.1186/s12879-023-08261-5] [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: 10/24/2022] [Accepted: 04/17/2023] [Indexed: 05/06/2023] Open
Abstract
BACKGROUND Decision-makers impose COVID-19 mitigations based on public health indicators such as reported cases, which are sensitive to fluctuations in supply and demand for diagnostic testing, and hospital admissions, which lag infections by up to two weeks. Imposing mitigations too early has unnecessary economic costs while imposing too late leads to uncontrolled epidemics with unnecessary cases and deaths. Sentinel surveillance of recently-symptomatic individuals in outpatient testing sites may overcome biases and lags in conventional indicators, but the minimal outpatient sentinel surveillance system needed for reliable trend estimation remains unknown. METHODS We used a stochastic, compartmental transmission model to evaluate the performance of various surveillance indicators at reliably triggering an alarm in response to, but not before, a step increase in transmission of SARS-CoV-2. The surveillance indicators included hospital admissions, hospital occupancy, and sentinel cases with varying levels of sampling effort capturing 5, 10, 20, 50, or 100% of incident mild cases. We tested 3 levels of transmission increase, 3 population sizes, and conditions of either simultaneous transmission increase or lagged increase in the older population. We compared the indicators' performance at triggering alarm soon after, but not prior, to the transmission increase. RESULTS Compared to surveillance based on hospital admissions, outpatient sentinel surveillance that captured at least 20% of incident mild cases could trigger an alarm 2 to 5 days earlier for a mild increase in transmission and 6 days earlier for a moderate or strong increase. Sentinel surveillance triggered fewer false alarms and averted more deaths per day spent in mitigation. When transmission increase in older populations lagged the increase in younger populations by 14 days, sentinel surveillance extended its lead time over hospital admissions by an additional 2 days. CONCLUSIONS Sentinel surveillance of mild symptomatic cases can provide more timely and reliable information on changes in transmission to inform decision-makers in an epidemic like COVID-19.
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Affiliation(s)
- Kok Ben Toh
- Department of Preventive Medicine, Institute for Global Health, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
| | - Manuela Runge
- Department of Preventive Medicine, Institute for Global Health, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Reese Ak Richardson
- Department of Chemical and Biological Engineering, Northwestern University, Chicago, IL, USA
| | - Thomas J Hladish
- Department of Biology, University of Florida, Gainesville, FL, USA
- Emerging Pathogen Institute, University of Florida, Gainesville, FL, USA
| | - Jaline Gerardin
- Department of Preventive Medicine, Institute for Global Health, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
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17
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Fantin R, Barboza-Solís C, Hildesheim A, Herrero R. Excess mortality from COVID 19 in Costa Rica: a registry based study using Poisson regression. LANCET REGIONAL HEALTH. AMERICAS 2023; 20:100451. [PMID: 36852399 PMCID: PMC9945505 DOI: 10.1016/j.lana.2023.100451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 01/16/2023] [Accepted: 02/03/2023] [Indexed: 02/25/2023]
Abstract
Background Official death toll related to COVID-19 has been considerably underestimated in reports from some Latin American countries. This study aimed to analyze the mortality associated with the COVID-19 pandemic in Costa Rica between March 2020 and December 2021. Methods A registry based study based on 2017-2021 data from the National Institute of Statistics and Census was designed (N = 128,106). Excess deaths were defined by the WHO as "the difference in the total number of deaths in a crisis compared to those expected under normal conditions"; and were estimated using a Poisson regression, and mortality and years of potential life lost (YPLL) rates were calculated. Findings The COVID-19 pandemic represented 15% of the deaths in Costa Rica between March 2020 and December 2021. The mortality rate related to COVID-19 was 83 per 100,000 person-years. Between March and July 2020 (low-incidence period), observed number of deaths was 9%-lower than expected, whereas it was 15% and 24% higher than expected between July 2020 and March 2021 (high incidence period - no vaccination), and between March 2021 and December 2021 (high incidence period - progressive vaccination) respectively. Between July 2020 and December 2021, excess deaths observed and COVID-19 deaths reported were comparable (7461 and 7620 respectively). Nevertheless, there were more deaths than expected for conditions that predispose to COVID-19 deaths. YPLL and mortality rates increased with age, but significant excess deaths were observed in all age-groups older than 30-39 years. No large differences were noted by districts' socioeconomic characteristics although excess death rate was lower in rural compared to urban areas. Interpretation Reporting of deaths was only slightly underestimated. In the pre-vaccination period, mortality rate and YPLL rates increased with age, being highest in people aged 60 years or older and justifying the decision to initially prioritize vaccination of older individuals. Funding The study was supported by the University of Costa Rica and the Agencia Costarricense de Investigaciones Biomédicas - Fundación Inciensa.
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Affiliation(s)
- Romain Fantin
- Centro Centroamericano de Población, Universidad de Costa Rica, San Pedro, Costa Rica,Agencia Costarricense de Investigaciones Biomédicas – Fundación Inciensa, San José, Costa Rica,Facultad de Odontología, Universidad de Costa Rica, San Pedro, Costa Rica,Corresponding author. Agencia Costarricense de Investigaciones Biomédicas – Fundación Inciensa, San José, Costa Rica
| | | | - Allan Hildesheim
- Agencia Costarricense de Investigaciones Biomédicas – Fundación Inciensa, San José, Costa Rica
| | - Rolando Herrero
- Agencia Costarricense de Investigaciones Biomédicas – Fundación Inciensa, San José, Costa Rica
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18
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Lu D, Dhanoa S, Cheema H, Lewis K, Geeraert P, Merrick B, Vander Leek A, Sebastianski M, Kula B, Chaudhuri D, Basmaji J, Agrawal A, Niven D, Fiest K, Stelfox HT, Zuege DJ, Rewa OG, Bagshaw SM, Lau VI. Coronavirus disease 2019 (COVID-19) excess mortality outcomes associated with pandemic effects study (COPES): A systematic review and meta-analysis. Front Med (Lausanne) 2022; 9:999225. [PMID: 36590965 PMCID: PMC9800609 DOI: 10.3389/fmed.2022.999225] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 12/02/2022] [Indexed: 12/23/2022] Open
Abstract
Background and aim With the Coronavirus Disease 2019 (COVID-19) pandemic continuing to impact healthcare systems around the world, healthcare providers are attempting to balance resources devoted to COVID-19 patients while minimizing excess mortality overall (both COVID-19 and non-COVID-19 patients). To this end, we conducted a systematic review (SR) to describe the effect of the COVID-19 pandemic on all-cause excess mortality (COVID-19 and non-COVID-19) during the pandemic timeframe compared to non-pandemic times. Methods We searched EMBASE, Cochrane Database of SRs, MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Cochrane Controlled Trials Register (CENTRAL), from inception (1948) to December 31, 2020. We used a two-stage review process to screen/extract data. We assessed risk of bias using Newcastle-Ottawa Scale (NOS). We used Critical Appraisal and Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. Results Of 11,581 citations, 194 studies met eligibility. Of these studies, 31 had mortality comparisons (n = 433,196,345 participants). Compared to pre-pandemic times, during the COVID-19 pandemic, our meta-analysis demonstrated that COVID-19 mortality had an increased risk difference (RD) of 0.06% (95% CI: 0.06-0.06% p < 0.00001). All-cause mortality also increased [relative risk (RR): 1.53, 95% confidence interval (CI): 1.38-1.70, p < 0.00001] alongside non-COVID-19 mortality (RR: 1.18, 1.07-1.30, p < 0.00001). There was "very low" certainty of evidence through GRADE assessment for all outcomes studied, demonstrating the evidence as uncertain. Interpretation The COVID-19 pandemic may have caused significant increases in all-cause excess mortality, greater than those accounted for by increases due to COVID-19 mortality alone, although the evidence is uncertain. Systematic review registration [https://www.crd.york.ac.uk/prospero/#recordDetails], identifier [CRD42020201256].
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Affiliation(s)
- David Lu
- Faculty of Medicine and Dentistry, Alberta Health Services, University of Alberta, Edmonton, AB, Canada
| | - Sumeet Dhanoa
- Faculty of Medicine and Dentistry, Alberta Health Services, University of Alberta, Edmonton, AB, Canada
| | - Harleen Cheema
- Faculty of Medicine and Dentistry, Alberta Health Services, University of Alberta, Edmonton, AB, Canada
| | - Kimberley Lewis
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada
- Division of Critical Care Medicine, Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - Patrick Geeraert
- Faculty of Medicine and Dentistry, Alberta Health Services, University of Alberta, Edmonton, AB, Canada
| | - Benjamin Merrick
- Faculty of Medicine and Dentistry, Alberta Health Services, University of Alberta, Edmonton, AB, Canada
| | - Aaron Vander Leek
- Faculty of Medicine and Dentistry, Alberta Health Services, University of Alberta, Edmonton, AB, Canada
| | - Meghan Sebastianski
- Alberta Strategy for Patient-Oriented Research Knowledge Translation Platform, University of Alberta, Edmonton, AB, Canada
| | - Brittany Kula
- Division of Infectious Disease, Department of Medicine, Faculty of Medicine and Dentistry, Alberta Health Services, University of Alberta, Edmonton, AB, Canada
| | - Dipayan Chaudhuri
- Division of Critical Care Medicine, Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - John Basmaji
- Division of Critical Care, Department of Medicine, Western University, London, ON, Canada
| | - Arnav Agrawal
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada
- Division of General Internal Medicine, Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - Dan Niven
- Department of Critical Care Medicine, Cumming School of Medicine, Alberta Health Services, University of Calgary, Calgary, AB, Canada
| | - Kirsten Fiest
- Department of Critical Care Medicine, Cumming School of Medicine, Alberta Health Services, University of Calgary, Calgary, AB, Canada
| | - Henry T. Stelfox
- Department of Critical Care Medicine, Cumming School of Medicine, Alberta Health Services, University of Calgary, Calgary, AB, Canada
| | - Danny J. Zuege
- Department of Critical Care Medicine, Cumming School of Medicine, Alberta Health Services, University of Calgary, Calgary, AB, Canada
| | - Oleksa G. Rewa
- Department of Critical Care Medicine, Faculty of Medicine and Dentistry, Alberta Health Services, University of Alberta, Edmonton, AB, Canada
- School of Public Health, University of Alberta, Edmonton, AB, Canada
| | - Sean M. Bagshaw
- Department of Critical Care Medicine, Faculty of Medicine and Dentistry, Alberta Health Services, University of Alberta, Edmonton, AB, Canada
- School of Public Health, University of Alberta, Edmonton, AB, Canada
| | - Vincent I. Lau
- Department of Critical Care Medicine, Faculty of Medicine and Dentistry, Alberta Health Services, University of Alberta, Edmonton, AB, Canada
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19
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Roldan-Hernandez L, Graham KE, Duong D, Boehm AB. Persistence of Endogenous SARS-CoV-2 and Pepper Mild Mottle Virus RNA in Wastewater-Settled Solids. ACS ES&T WATER 2022; 2:1944-1952. [PMID: 36380769 PMCID: PMC8938836 DOI: 10.1021/acsestwater.2c00003] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Limited information is available on the decay rate of endogenous SARS-CoV-2 and pepper mild mottle virus (PMMoV) RNA in wastewater and primary settled solids, potentially limiting an understanding of how transit or holding times within wastewater infrastructure might impact RNA measurements and their relationship to community COVID-19 infections. In this study, primary settled solids samples were collected from two wastewater treatment plants in the San Francisco Bay Area. Samples were thoroughly mixed, aliquoted into subsamples, and stored at 4, 22, and 37 °C for 10 days. The concentrations of SARS-CoV-2 (N1 and N2 targets) and PMMoV RNA were measured using an RT-ddPCR. Limited decay (<1 log10 reduction) was observed in the detection of viral RNA targets at all temperature conditions, suggesting that SARS-CoV-2 and PMMoV RNA can be highly persistent in solids. First-order decay rate constants ranged from 0.011 to 0.098 day-1 for SARS-CoV-2 RNA and from 0.010 to 0.091 day-1 for PMMoV RNA depending on the temperature conditions. A slower decay was observed for SARS-CoV-2 RNA in primary settled solids compared to previously reported decay in wastewater influent. Further research is needed to understand if solid content and wastewater characteristics might influence the persistence of viral RNA targets.
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Affiliation(s)
- Laura Roldan-Hernandez
- Department
of Civil and Environmental Engineering, Stanford University, 473 Via Ortega, Stanford 94305, California, United States
| | - Katherine E. Graham
- Department
of Civil and Environmental Engineering, Stanford University, 473 Via Ortega, Stanford 94305, California, United States
| | - Dorothea Duong
- Verily
Life Sciences, San Francisco, California 94080, United States
| | - Alexandria B. Boehm
- Department
of Civil and Environmental Engineering, Stanford University, 473 Via Ortega, Stanford 94305, California, United States
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20
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Rossen LM, Nørgaard SK, Sutton PD, Krause TG, Ahmad FB, Vestergaard LS, Mølbak K, Anderson RN, Nielsen J. Excess all-cause mortality in the USA and Europe during the COVID-19 pandemic, 2020 and 2021. Sci Rep 2022; 12:18559. [PMID: 36329082 PMCID: PMC9630804 DOI: 10.1038/s41598-022-21844-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 10/04/2022] [Indexed: 11/06/2022] Open
Abstract
Both the USA and Europe experienced substantial excess mortality in 2020 and 2021 related to the COVID-19 pandemic. Methods used to estimate excess mortality vary, making comparisons difficult. This retrospective observational study included data on deaths from all causes occurring in the USA and 25 European countries or subnational areas participating in the network for European monitoring of excess mortality for public health action (EuroMOMO). We applied the EuroMOMO algorithm to estimate excess all-cause mortality in the USA and Europe during the first two years of the COVID-19 pandemic, 2020-2021, and compared excess mortality by age group and time periods reflecting three primary waves. During 2020-2021, the USA experienced 154.5 (95% Uncertainty Interval [UI]: 154.2-154.9) cumulative age-standardized excess all-cause deaths per 100,000 person years, compared with 110.4 (95% UI: 109.9-111.0) for the European countries. Excess all-cause mortality in the USA was higher than in Europe for nearly all age groups, with an additional 44.1 excess deaths per 100,000 person years overall from 2020-2021. If the USA had experienced an excess mortality rate similar to Europe, there would have been approximately 391 thousand (36%) fewer excess deaths in the USA.
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Affiliation(s)
- Lauren M Rossen
- National Center for Health Statistics, Centers for Disease Control and Prevention, 3311 Toledo Road, Hyattsville, MD, 20782, USA.
| | - Sarah K Nørgaard
- Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Copenhagen, Denmark
| | - Paul D Sutton
- National Center for Health Statistics, Centers for Disease Control and Prevention, 3311 Toledo Road, Hyattsville, MD, 20782, USA
| | - Tyra G Krause
- Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Copenhagen, Denmark
| | - Farida B Ahmad
- National Center for Health Statistics, Centers for Disease Control and Prevention, 3311 Toledo Road, Hyattsville, MD, 20782, USA
| | - Lasse S Vestergaard
- Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Copenhagen, Denmark
| | - Kåre Mølbak
- Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Copenhagen, Denmark
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Robert N Anderson
- National Center for Health Statistics, Centers for Disease Control and Prevention, 3311 Toledo Road, Hyattsville, MD, 20782, USA
| | - Jens Nielsen
- Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Copenhagen, Denmark
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21
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Takahashi S, Nakazawa E, Ichinohe S, Akabayashi A, Akabayashi A. Wearable Technology for Monitoring Respiratory Rate and SpO 2 of COVID-19 Patients: A Systematic Review. Diagnostics (Basel) 2022; 12:diagnostics12102563. [PMID: 36292252 PMCID: PMC9600544 DOI: 10.3390/diagnostics12102563] [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: 09/26/2022] [Revised: 10/19/2022] [Accepted: 10/19/2022] [Indexed: 11/25/2022] Open
Abstract
With the significant numbers of sudden home deaths reported worldwide due to coronavirus disease 2019 (COVID-19), wearable technology has emerged as a method for surveilling this infection. This review explored the indicators of COVID-19 surveillance, such as vitals, respiratory condition, temperature, oxygen saturation (SpO2), and activity levels using wearable devices. Studies published between 31 December 2019, and 8 July 2022, were obtained from PubMed, and grey literature, reference lists, and key journals were also searched. All types of articles with the keywords “COVID-19”, “Diagnosis”, and “Wearable Devices” were screened. Four reviewers independently screened the articles against the eligibility criteria and extracted the data using a data charting form. A total of 56 articles were on monitoring, of which 28 included SpO2 as a parameter. Although wearable devices are effective in the continuous monitoring of COVID-19 patients, further research on actual patients is necessary to determine the efficiency and effectiveness of wearable technology before policymakers can mandate its use.
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Affiliation(s)
- Shizuko Takahashi
- Department of Biomedical Ethics, Faculty of Medicine, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
- Sanno Medical Center, 8-5-35 Akasaka, Minato-ku, Tokyo 107-0052, Japan
| | - Eisuke Nakazawa
- Department of Biomedical Ethics, Faculty of Medicine, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Sakurako Ichinohe
- Department of Biomedical Ethics, Faculty of Medicine, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Aru Akabayashi
- Department of Biomedical Ethics, Faculty of Medicine, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
- Department of Biochemistry and Biophysics, School of Medicine and Dentistry Center for RNA Biology, University of Rochester, 601 Elmwood Avenue, Rochester, NY 14642, USA
| | - Akira Akabayashi
- Department of Biomedical Ethics, Faculty of Medicine, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
- Division of Medical Ethics, School of Medicine, New York University, 227 East 30th Street, New York, NY 10016, USA
- Correspondence: or ; Fax: +81-35-841-3319
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22
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da Silva SJR, do Nascimento JCF, Germano Mendes RP, Guarines KM, Targino Alves da Silva C, da Silva PG, de Magalhães JJF, Vigar JRJ, Silva-Júnior A, Kohl A, Pardee K, Pena L. Two Years into the COVID-19 Pandemic: Lessons Learned. ACS Infect Dis 2022; 8:1758-1814. [PMID: 35940589 PMCID: PMC9380879 DOI: 10.1021/acsinfecdis.2c00204] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible and virulent human-infecting coronavirus that emerged in late December 2019 in Wuhan, China, causing a respiratory disease called coronavirus disease 2019 (COVID-19), which has massively impacted global public health and caused widespread disruption to daily life. The crisis caused by COVID-19 has mobilized scientists and public health authorities across the world to rapidly improve our knowledge about this devastating disease, shedding light on its management and control, and spawned the development of new countermeasures. Here we provide an overview of the state of the art of knowledge gained in the last 2 years about the virus and COVID-19, including its origin and natural reservoir hosts, viral etiology, epidemiology, modes of transmission, clinical manifestations, pathophysiology, diagnosis, treatment, prevention, emerging variants, and vaccines, highlighting important differences from previously known highly pathogenic coronaviruses. We also discuss selected key discoveries from each topic and underline the gaps of knowledge for future investigations.
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Affiliation(s)
- Severino Jefferson Ribeiro da Silva
- Laboratory of Virology and Experimental Therapy (LAVITE), Department of Virology, Aggeu Magalhães Institute (IAM), Oswaldo Cruz Foundation (Fiocruz), 50670-420 Recife, Pernambuco, Brazil.,Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON M5S 3M2, Canada
| | - Jessica Catarine Frutuoso do Nascimento
- Laboratory of Virology and Experimental Therapy (LAVITE), Department of Virology, Aggeu Magalhães Institute (IAM), Oswaldo Cruz Foundation (Fiocruz), 50670-420 Recife, Pernambuco, Brazil
| | - Renata Pessôa Germano Mendes
- Laboratory of Virology and Experimental Therapy (LAVITE), Department of Virology, Aggeu Magalhães Institute (IAM), Oswaldo Cruz Foundation (Fiocruz), 50670-420 Recife, Pernambuco, Brazil
| | - Klarissa Miranda Guarines
- Laboratory of Virology and Experimental Therapy (LAVITE), Department of Virology, Aggeu Magalhães Institute (IAM), Oswaldo Cruz Foundation (Fiocruz), 50670-420 Recife, Pernambuco, Brazil
| | - Caroline Targino Alves da Silva
- Laboratory of Virology and Experimental Therapy (LAVITE), Department of Virology, Aggeu Magalhães Institute (IAM), Oswaldo Cruz Foundation (Fiocruz), 50670-420 Recife, Pernambuco, Brazil
| | - Poliana Gomes da Silva
- Laboratory of Virology and Experimental Therapy (LAVITE), Department of Virology, Aggeu Magalhães Institute (IAM), Oswaldo Cruz Foundation (Fiocruz), 50670-420 Recife, Pernambuco, Brazil
| | - Jurandy Júnior Ferraz de Magalhães
- Laboratory of Virology and Experimental Therapy (LAVITE), Department of Virology, Aggeu Magalhães Institute (IAM), Oswaldo Cruz Foundation (Fiocruz), 50670-420 Recife, Pernambuco, Brazil.,Department of Virology, Pernambuco State Central Laboratory (LACEN/PE), 52171-011 Recife, Pernambuco, Brazil.,University of Pernambuco (UPE), Serra Talhada Campus, 56909-335 Serra Talhada, Pernambuco, Brazil.,Public Health Laboratory of the XI Regional Health, 56912-160 Serra Talhada, Pernambuco, Brazil
| | - Justin R J Vigar
- Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON M5S 3M2, Canada
| | - Abelardo Silva-Júnior
- Institute of Biological and Health Sciences, Federal University of Alagoas (UFAL), 57072-900 Maceió, Alagoas, Brazil
| | - Alain Kohl
- MRC-University of Glasgow Centre for Virus Research, Glasgow G61 1QH, United Kingdom
| | - Keith Pardee
- Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON M5S 3M2, Canada.,Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON M5S 3G8, Canada
| | - Lindomar Pena
- Laboratory of Virology and Experimental Therapy (LAVITE), Department of Virology, Aggeu Magalhães Institute (IAM), Oswaldo Cruz Foundation (Fiocruz), 50670-420 Recife, Pernambuco, Brazil
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23
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Zhang Y, Chang HH, Iuliano AD, Reed C. Application of Bayesian spatial-temporal models for estimating unrecognized COVID-19 deaths in the United States. SPATIAL STATISTICS 2022; 50:100584. [PMID: 35013705 PMCID: PMC8730676 DOI: 10.1016/j.spasta.2021.100584] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 12/23/2021] [Accepted: 12/24/2021] [Indexed: 05/10/2023]
Abstract
In the United States, COVID-19 has become a leading cause of death since 2020. However, the number of COVID-19 deaths reported from death certificates is likely to represent an underestimate of the total deaths related to SARS-CoV-2 infections. Estimating those deaths not captured through death certificates is important to understanding the full burden of COVID-19 on mortality. In this work, we explored enhancements to an existing approach by employing Bayesian hierarchical models to estimate unrecognized deaths attributed to COVID-19 using weekly state-level COVID-19 viral surveillance and mortality data in the United States from March 2020 to April 2021. We demonstrated our model using those aged ≥ 85 years who died. First, we used a spatial-temporal binomial regression model to estimate the percent of positive SARS-CoV-2 test results. A spatial-temporal negative-binomial model was then used to estimate unrecognized COVID-19 deaths by exploiting the spatial-temporal association between SARS-CoV-2 percent positive and all-cause mortality counts using an excess mortality approach. Computationally efficient Bayesian inference was accomplished via the Polya-Gamma representation of the binomial and negative-binomial models. Among those aged ≥ 85 years, we estimated 58,200 (95% CI: 51,300, 64,900) unrecognized COVID-19 deaths, which accounts for 26% (95% CI: 24%, 29%) of total COVID-19 deaths in this age group. Our modeling results suggest that COVID-19 mortality and the proportion of unrecognized deaths among deaths attributed to COVID-19 vary by time and across states.
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Affiliation(s)
- Yuzi Zhang
- Department of Biostatistics and Bioinformatics, The Rollins School of Public Health of Emory University, 1518 Clifton Rd. N.E., Atlanta, GA 30322, USA
| | - Howard H Chang
- Department of Biostatistics and Bioinformatics, The Rollins School of Public Health of Emory University, 1518 Clifton Rd. N.E., Atlanta, GA 30322, USA
| | - A Danielle Iuliano
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Carrie Reed
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
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24
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Chen YH, Stokes AC, Aschmann HE, Chen R, DeVost S, Kiang MV, Koliwad S, Riley AR, Glymour MM, Bibbins-Domingo K. Excess natural-cause deaths in California by cause and setting: March 2020 through February 2021. PNAS NEXUS 2022; 1:pgac079. [PMID: 35832865 PMCID: PMC9272175 DOI: 10.1093/pnasnexus/pgac079] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 05/27/2022] [Indexed: 02/06/2023]
Abstract
Excess mortality has exceeded reported deaths from Covid-19 during the pandemic. This gap may be attributable to deaths that occurred among individuals with undiagnosed Covid-19 infections or indirect consequences of the pandemic response such as interruptions in medical care; distinguishing these possibilities has implications for public health responses. In the present study, we examined patterns of excess mortality over time and by setting (in-hospital or out-of-hospital) and cause of death using death certificate data from California. The estimated number of excess natural-cause deaths from 2020 March 1 to 2021 February 28 (69,182) exceeded the number of Covid-19 diagnosed deaths (53,667) by 29%. Nearly half, 47.4% (32,775), of excess natural-cause deaths occurred out of the hospital, where only 28.6% (9,366) of excess mortality was attributed to Covid-19. Over time, increases or decreases in excess natural non-Covid-19 mortality closely mirrored increases or decreases in Covid-19 mortality. The time series were positively correlated in out-of-hospital settings, particularly at time lags when excess natural-cause deaths preceded reported Covid-19 deaths; for example, when comparing Covid-19 deaths to excess natural-cause deaths in the week prior, the correlation was 0.73. The strong temporal association of reported Covid-19 deaths with excess out-of-hospital deaths from other reported natural-cause causes suggests Covid-19 deaths were undercounted during the first year of the pandemic.
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Affiliation(s)
- Yea-Hung Chen
- Department of Epidemiology and Biostatistics, University of California, 550 16th St, San Francisco, CA 94158, USA
| | - Andrew C Stokes
- Department of Global Health, Boston University School of Public Health, Boston, MA 02118, USA
| | - Hélène E Aschmann
- Department of Epidemiology and Biostatistics, University of California, 550 16th St, San Francisco, CA 94158, USA
| | - Ruijia Chen
- Department of Epidemiology and Biostatistics, University of California, 550 16th St, San Francisco, CA 94158, USA
| | - Shelley DeVost
- Department of Epidemiology and Biostatistics, University of California, 550 16th St, San Francisco, CA 94158, USA
| | - Mathew V Kiang
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Palo Alto, CA 94304, USA
| | - Suneil Koliwad
- Department of Medicine, and Diabetes Center, University of California, San Francisco, CA 94117, USA
| | - Alicia R Riley
- Department of Sociology, University of California, Santa Cruz, CA 95064, USA
| | - M Maria Glymour
- Department of Epidemiology and Biostatistics, University of California, 550 16th St, San Francisco, CA 94158, USA
| | - Kirsten Bibbins-Domingo
- Department of Epidemiology and Biostatistics, University of California, 550 16th St, San Francisco, CA 94158, USA
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25
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Vladescu C, Ciutan M, Rafila A. In-hospital admissions and deaths in the context of the COVID-19 pandemic, in Romania. Germs 2022; 12:169-179. [PMID: 36504608 PMCID: PMC9719376 DOI: 10.18683/germs.2022.1320] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 03/16/2022] [Accepted: 04/04/2022] [Indexed: 12/15/2022]
Abstract
Introduction The COVID-19 pandemic context led to a relevant burden on essential sectors of society; hospital sector capacity is tested in this period. Methods A cross-sectional study of admissions in hospitals reporting DRG data for 2018-2020. Trend analysis of admissions and deaths in hospitals was carried out for identifying annual patterns and deviations from the 2010-2020 trend. Data aggregated by year, month, diagnosis, death in hospital. Graph analysis for time and diagnosis comparisons and correlation identifying associations. Results There is an annual change in admission and death patterns recorded in Romanian hospitals. An important contraction in number of acute hospital admissions was recording during the COVID-19 pandemic; patients' hesitancy to seek healthcare and limited capacity to treat patients other than COVID-19 patients due to legal regulations limiting the admissions number could explain this pattern of admission only for serious condition or emergency surgery. In Romania excess deaths in second half 2020 was generally greater than COVID-19 deaths. Overall, excess mortality between March and December 2020 was more than double than reported COVID-19 deaths. The same mortality pattern persists, but with significant decreases for some diagnoses. Conclusions The Romanian healthcare system has been challenged due to COVID-19 pandemic, leading to temporary reorganization of hospitals with consequences on all acute care diagnostics and therapeutic pathways. It is a challenge to identify causes of reduced inpatient treatment rates and to provide evidence on hospital activity for understanding future optimal management of patients with COVID-19, but also with other acute and chronic conditions.
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Affiliation(s)
- Cristian Vladescu
- Prof. Dr., MD, PhD, National School of Public Health Management and Professional Development, No. 31 Vaselor Street, Bucharest, Romania and University Titu Maiorescu Bucharest, Romania
| | - Marius Ciutan
- Dr. Marius Ciutan, National School of Public Health Management and Professional Development Bucharest, No. 31 Vaselor Street, Bucharest, Romania,Corresponding author: Marius Ciutan,
| | - Alexandru Rafila
- Prof. Dr., MD, PhD, Alexandru Rafila, National Institute for Infectious Diseases “Prof. Dr. Matei Balș”, No. 1 Dr. Calistrat Grozovici street, Bucharest, Romania and Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
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26
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Paglino E, Lundberg DJ, Cho A, Wasserman JA, Raquib R, Luck AN, Hempstead K, Bor J, Elo IT, Preston SH, Stokes AC. Excess all-cause mortality across counties in the United States, March 2020 to December 2021. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022. [PMID: 35547848 DOI: 10.1101/2022.06.29.222770652022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Official Covid-19 death counts have underestimated the mortality impact of the Covid-19 pandemic in the United States. Excess mortality, which compares observed deaths to deaths expected in the absence of the pandemic, is a useful measure for assessing the total effect of the pandemic on mortality levels. In the present study, we produce county-level estimates of excess mortality for 3,127 counties between March 2020 and December 2021. We fit two hierarchical linear models to county-level death rates from January 2015 to December 2019 and predict expected deaths for each month during the pandemic. We compare observed deaths to these estimates to obtain excess deaths for each county-month. An estimated 936,911 excess deaths occurred during 2020 and 2021, of which 171,168 (18.3%) were not assigned to Covid-19 on death certificates as an underlying cause of death. Urban counties in the Far West, Great Lakes, Mideast, and New England experienced a substantial mortality disadvantage in 2020, whereas rural counties in these regions had higher mortality in 2021. In the Southeast, Southwest, Rocky Mountain, and Plains regions, there was a rural mortality disadvantage in 2020, which was exacerbated in 2021. The proportion of excess deaths assigned to Covid-19 was lower in 2020 (76.3%) than in 2021 (87.0%), suggesting that a larger fraction of excess deaths was assigned to Covid-19 later in the pandemic. However, in rural areas and in the Southeast and Southwest a large share of excess deaths was still not assigned to Covid-19 during 2021. SIGNIFICANCE Deaths during the Covid-19 pandemic have been primarily monitored through death certificates containing reference to Covid-19. This approach has missed more than 170,000 deaths related to the pandemic between 2020 and 2021. While the ascertainment of Covid-19 deaths improved during 2021, the full effects of the pandemic still remained obscured in some regions. County-level estimates of excess mortality are useful for studying geographic inequities in the mortality burden associated with the pandemic and identifying specific regions where the full mortality burden was significantly underreported (i.e. Southeast). They can also be used to inform resource allocation decisions at the federal and state levels and encourage uptake of preventive measures in communities with low vaccine uptake.
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27
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Geeraedts F, Luttje M, Visschedijk J, van Hattem M, Hasper HJ, Kohnen R, Loman R, de Goede R, Jansen D, Hess D, Al Naiemi N. Low-Threshold Testing for SARS-CoV-2 (COVID-19) in Long-Term Care Facilities Early in the First Pandemic Wave, the Twente Region, the Netherlands: A Possible Factor in Reducing Morbidity and Mortality. J Appl Gerontol 2022; 41:1802-1811. [PMID: 35543170 PMCID: PMC9127376 DOI: 10.1177/07334648221093050] [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] [Indexed: 01/08/2023] Open
Abstract
During the first wave of the COVID-19 pandemic, there was a shortage of
SARS-CoV-2 diagnostic tests, and testing patients with mild symptoms
(low-threshold testing) was not recommended in the Netherlands. Despite these
guidelines, to protect those who were most at risk, low-threshold testing was
advocated and offered to the majority of long-term care institutions in the
Twente region. In this manner, 144 healthcare workers and
96 residents tested SARS-CoV-2-positive and were isolated before the same
service was provided nationwide by public health services. Strikingly, excess
mortality rate in the Twente region 1 month after the
introduction of this strategy was found to be 62%–89% lower than that in
neighboring regions, which may be explained by this divergent testing strategy.
In an emerging pandemic, early implementation of a liberal testing policy may be
more effective than restricted testing in settings with a high death rate.
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Affiliation(s)
- Felix Geeraedts
- Laboratory for Medical Microbiology and Public Health, Hengelo, the Netherlands
| | - Mariska Luttje
- Carintreggeland Nursing Homes and Home Care, Hengelo, the Netherlands
| | - Jan Visschedijk
- Carintreggeland Nursing Homes and Home Care, Hengelo, the Netherlands
| | | | - Henk-Jan Hasper
- Trivium Meulenbelt Zorg Nursing Homes and Home Care, Almelo, the Netherlands
| | - Roy Kohnen
- Livio Nursing Homes and Home Care, Enschede, the Netherlands
| | - Rene Loman
- Zorggroep Sint Maarten Nursing Homes and Home Care, Denekamp, the Netherlands
| | - Rudi de Goede
- Liberein Nursing Homes and Home Care, Enschede, the Netherlands
| | - Desiré Jansen
- De Posten Nursing Homes and Home Care, Enschede, the Netherlands
| | - Dorine Hess
- Laboratory for Medical Microbiology and Public Health, Hengelo, the Netherlands
| | - Nashwan Al Naiemi
- Laboratory for Medical Microbiology and Public Health, Hengelo, the Netherlands
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28
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Glance LG, Chandrasekar EK, Shippey E, Stone PW, Dutton R, McCormick PJ, Shang J, Lustik SJ, Wu IY, Eaton MP, Dick AW. Association Between the COVID-19 Pandemic and Disparities in Access to Major Surgery in the US. JAMA Netw Open 2022; 5:e2213527. [PMID: 35604684 PMCID: PMC9127559 DOI: 10.1001/jamanetworkopen.2022.13527] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 04/04/2022] [Indexed: 12/17/2022] Open
Abstract
Importance Racial minority groups account for 70% of excess deaths not related to COVID-19. Understanding the association of the Centers for Medicare & Medicaid Services' (CMS's) moratorium delaying nonessential operations with racial disparities will help shape future pandemic responses. Objective To evaluate the association of the CMS's moratorium on elective operations during the first wave of the COVID-19 pandemic among Black individuals, Asian individuals, and individuals of other races compared with White individuals. Design, Setting, and Participants This cross-sectional study assessed a 719-hospital retrospective cohort of 3 470 905 adult inpatient hospitalizations for major surgery between January 1, 2018, and October 31, 2020. Exposure The first wave of COVID-19 infections between March 1, 2020, and May 31, 2020. Main Outcomes and Measures The main outcome was the association between changes in monthly elective surgical case volumes and the first wave of COVID-19 infections as a function of patient race, evaluated using negative binomial regression analysis. Results Among 3 470 905 adults (1 823 816 female [52.5%]) with inpatient hospitalizations for major surgery, 70 752 (2.0%) were Asian, 453 428 (13.1%) were Black, 2 696 929 (77.7%) were White, and 249 796 (7.2%) were individuals of other races. The number of monthly elective cases during the first wave was 49% (incident rate ratio [IRR], 0.49; 95% CI, 0.486-0.492; P < .001) compared with the baseline period. The relative reduction in unadjusted elective surgery cases for Black (unadjusted IRR, 0.99; 95% CI, 0.97-1.01; P = .36), Asian (unadjusted IRR, 1.08; 95% CI, 1.03-1.14; P = .001), and other race individuals (unadjusted IRR, 0.97; 95% CI, 0.95-1.00; P = .05) during the surge period compared with the baseline period was very close to the change in cases for White individuals. After adjustment for age, sex, comorbidities, and surgical procedure, there was still no evidence that the first wave of the pandemic was associated with disparities in access to elective surgery. Conclusions and Relevance In this cross-sectional study, the CMS's moratorium on nonessential operations was associated with a 51% reduction in elective operations. It was not associated with greater reductions in operations for racial minority individuals than for White individuals. This evidence suggests that the early response to the pandemic did not increase disparities in access to surgical care.
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Affiliation(s)
- Laurent G. Glance
- Department of Anesthesiology and Perioperative Medicine, University of Rochester School of Medicine, Rochester, New York
- Department of Public Health Sciences, University of Rochester School of Medicine, Rochester, New York
- RAND Health, RAND, Boston, Massachusetts
| | - Eeshwar K. Chandrasekar
- Department of Anesthesiology and Perioperative Medicine, University of Rochester School of Medicine, Rochester, New York
| | - Ernie Shippey
- Vizient Center for Advanced Analytics, Chicago, Illinois
| | - Patricia W. Stone
- Columbia School of Nursing, Center for Health Policy, New York, New York
| | | | | | - Jingjing Shang
- Columbia School of Nursing, Center for Health Policy, New York, New York
| | - Stewart J. Lustik
- Department of Anesthesiology and Perioperative Medicine, University of Rochester School of Medicine, Rochester, New York
| | - Isaac Y. Wu
- Department of Anesthesiology and Perioperative Medicine, University of Rochester School of Medicine, Rochester, New York
| | - Michael P. Eaton
- Department of Anesthesiology and Perioperative Medicine, University of Rochester School of Medicine, Rochester, New York
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29
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García-García D, Morales E, de la Fuente-Nunez C, Vigo I, Fonfría ES, Bordehore C. Identification of the first COVID-19 infections in the US using a retrospective analysis (REMEDID). Spat Spatiotemporal Epidemiol 2022; 42:100517. [PMID: 35934325 PMCID: PMC9087146 DOI: 10.1016/j.sste.2022.100517] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 04/15/2022] [Accepted: 05/09/2022] [Indexed: 11/13/2022]
Abstract
Accurate detection of early COVID-19 cases is crucial to reduce infections and deaths, however, it remains a challenge. Here, we used the results from a seroprevalence study in 50 US states to apply our Retrospective Methodology to Estimate Daily Infections from Deaths (REMEDID) with the aim of analyzing the initial spread of SARS-CoV-2 infections across the US. Our analysis revealed that the virus likely entered the country through California on December 28, 2019, which corresponds to 16 days prior to the officially recognized entry date established by the Centers of Disease Control and Prevention. Furthermore, the REMEDID algorithm provides evidence that SARS-CoV-2 entered, on average, a month earlier than previously reflected in official data for each US state. Collectively, our mathematical modeling provides more accurate estimates of the initial COVID-19 cases in the US, and has the ability to be extrapolated to other countries and used to retrospectively track the progress of the pandemic. The use of approaches such as REMEDID are highly recommended to better understand the early stages of an outbreak, which will enable health authorities to improve mitigation and preventive measures in the future.
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30
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Lutz CB, Giabbanelli PJ. When Do We Need Massive Computations to Perform Detailed COVID-19 Simulations? ADVANCED THEORY AND SIMULATIONS 2022; 5:2100343. [PMID: 35441122 PMCID: PMC9011599 DOI: 10.1002/adts.202100343] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 11/01/2021] [Indexed: 12/25/2022]
Abstract
The COVID-19 pandemic has infected over 250 million people worldwide and killed more than 5 million as of November 2021. Many intervention strategies are utilized (e.g., masks, social distancing, vaccinations), but officials making decisions have a limited time to act. Computer simulations can aid them by predicting future disease outcomes, but they also require significant processing power or time. It is examined whether a machine learning model can be trained on a small subset of simulation runs to inexpensively predict future disease trajectories resembling the original simulation results. Using four previously published agent-based models (ABMs) for COVID-19, a decision tree regression for each ABM is built and its predictions are compared to the corresponding ABM. Accurate machine learning meta-models are generated from ABMs without strong interventions (e.g., vaccines, lockdowns) using small amounts of simulation data: the root-mean-square error (RMSE) with 25% of the data is close to the RMSE for the full dataset (0.15 vs 0.14 in one model; 0.07 vs 0.06 in another). However, meta-models for ABMs employing strong interventions require much more training data (at least 60%) to achieve a similar accuracy. In conclusion, machine learning meta-models can be used in some scenarios to assist in faster decision-making.
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Affiliation(s)
- Christopher B. Lutz
- Department of Computer Science & Software EngineeringMiami University205 Benton HallOxfordOH45056USA
| | - Philippe J. Giabbanelli
- Department of Computer Science & Software EngineeringMiami University205 Benton HallOxfordOH45056USA
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31
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Rothenberg R. How much Covid? GLOBAL EPIDEMIOLOGY 2022; 4:100070. [PMID: 35005606 PMCID: PMC8720681 DOI: 10.1016/j.gloepi.2021.100070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Accepted: 12/24/2021] [Indexed: 11/21/2022] Open
Affiliation(s)
- Richard Rothenberg
- School of Public Health, Georgia State University, 140 Decatur St., Atlanta, GA 30303, United States of America
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32
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Ayoub HH, Mumtaz GR, Seedat S, Makhoul M, Chemaitelly H, Abu-Raddad LJ. Estimates of global SARS-CoV-2 infection exposure, infection morbidity, and infection mortality rates in 2020. GLOBAL EPIDEMIOLOGY 2021; 3:100068. [PMID: 34841244 PMCID: PMC8609676 DOI: 10.1016/j.gloepi.2021.100068] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 10/31/2021] [Accepted: 11/19/2021] [Indexed: 12/16/2022] Open
Abstract
We aimed to estimate, albeit crudely and provisionally, national, regional, and global proportions of respective populations that have been infected with SARS-CoV-2 in the first year after the introduction of this virus into human circulation, and to assess infection morbidity and mortality rates, factoring both documented and undocumented infections. The estimates were generated by applying mathematical models to 159 countries and territories. The percentage of the world's population that has been infected as of 31 December 2020 was estimated at 12.56% (95% CI: 11.17-14.05%). It was lowest in the Western Pacific Region at 0.66% (95% CI: 0.59-0.75%) and highest in the Americas at 41.92% (95% CI: 37.95-46.09%). The global infection fatality rate was 10.73 (95% CI: 10.21-11.29) per 10,000 infections. Globally per 1000 infections, the infection acute-care bed hospitalization rate was 19.22 (95% CI: 18.73-19.51), the infection ICU bed hospitalization rate was 4.14 (95% CI: 4.10-4.18). If left unchecked with no vaccination and no other public health interventions, and assuming circulation of only wild-type variants and no variants of concern, the pandemic would eventually cause 8.18 million deaths (95% CI: 7.30-9.18), 163.67 million acute-care hospitalizations (95% CI: 148.12-179.51), and 33.01 million ICU hospitalizations (95% CI: 30.52-35.70), by the time the herd immunity threshold is reached at 60-70% infection exposure. The global population remained far below the herd immunity threshold by end of 2020. Global epidemiology reveals immense regional variation in infection exposure and morbidity and mortality rates.
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Affiliation(s)
- Houssein H. Ayoub
- Mathematics Program, Department of Mathematics, Statistics, and Physics, College of Arts and Sciences, Qatar University, Doha, Qatar
| | - Ghina R. Mumtaz
- Department of Epidemiology and Population Health, American University of Beirut, Beirut, Lebanon
| | - Shaheen Seedat
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation – Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, NY, New York, USA
| | - Monia Makhoul
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation – Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, NY, New York, USA
| | - Hiam Chemaitelly
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation – Education City, Doha, Qatar
| | - Laith J. Abu-Raddad
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation – Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, NY, New York, USA
- Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
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Moghadas SM, Sah P, Shoukat A, Meyers LA, Galvani AP. Population Immunity Against COVID-19 in the United States. Ann Intern Med 2021; 174:1586-1591. [PMID: 34516275 PMCID: PMC8442744 DOI: 10.7326/m21-2721] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND As of 28 July 2021, 60% of adults in the United States had been fully vaccinated against COVID-19, and more than 34 million cases had been reported. Given the uncertainty regarding undocumented infections, the population level of immunity against COVID-19 in the United States remains undetermined. OBJECTIVE To estimate the population immunity, defined as the proportion of the population that is protected against SARS-CoV-2 infection due to prior infection or vaccination. DESIGN Statistical and simulation modeling to estimate overall and age-specific population immunity. SETTING United States. PARTICIPANTS Simulated age-stratified population representing U.S. demographic characteristics. MEASUREMENTS The true number of SARS-CoV-2 infections in the United States was inferred from data on reported deaths using age-specific infection-fatality rates (IFRs). Taking into account the estimates for vaccine effectiveness and protection against reinfection, the overall population immunity was determined as the sum of protection levels in vaccinated persons and those who were previously infected but not vaccinated. RESULTS Using age-specific IFR estimates from the Centers for Disease Control and Prevention, it was estimated that as of 15 July 2021, 114.9 (95% credible interval [CrI], 103.2 to 127.4) million persons had been infected with SARS-CoV-2 in the United States. The mean overall population immunity was 62.0% (CrI, 58.4% to 66.4%). Adults aged 65 years or older were estimated to have the highest immunity level (77.2% [CrI, 76.2% to 78.6%]), and children younger than 12 years had the lowest immunity level (17.9% [CrI, 14.4% to 21.9%]). LIMITATION Publicly reported deaths may underrepresent actual deaths. CONCLUSION As of 15 July 2021, the U.S. population immunity against COVID-19 may still have been insufficient to contain the outbreaks and safely revert to prepandemic social behavior. PRIMARY FUNDING SOURCE National Science Foundation, National Institutes of Health, Notsew Orm Sands Foundation, Canadian Institutes of Health Research, and Natural Sciences and Engineering Research Council of Canada.
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Affiliation(s)
| | - Pratha Sah
- Yale School of Public Health, New Haven, Connecticut (P.S., A.S., A.P.G.)
| | - Affan Shoukat
- Yale School of Public Health, New Haven, Connecticut (P.S., A.S., A.P.G.)
| | - Lauren Ancel Meyers
- The University of Texas at Austin, Austin, Texas, and Santa Fe Institute, Santa Fe, New Mexico (L.A.M.)
| | - Alison P Galvani
- Yale School of Public Health, New Haven, Connecticut (P.S., A.S., A.P.G.)
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Feldman JM, Bassett MT. Variation in COVID-19 Mortality in the US by Race and Ethnicity and Educational Attainment. JAMA Netw Open 2021; 4:e2135967. [PMID: 34812846 PMCID: PMC8611482 DOI: 10.1001/jamanetworkopen.2021.35967] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2021] [Accepted: 09/29/2021] [Indexed: 11/14/2022] Open
Abstract
Importance Racial and ethnic inequities in COVID-19 mortality have been well documented, but little prior research has assessed the combined roles of race and ethnicity and educational attainment. Objective To measure inequality in COVID-19 mortality jointly by race and ethnicity and educational attainment. Design, Setting, and Participants This cross-sectional study analyzed data on COVID-19 mortality from the 50 US states and the District of Columbia for the full calendar year 2020. It included all persons in the United States aged 25 years or older and analyzed them in subgroups jointly stratified by age, sex, race and ethnicity, and educational attainment. Main Outcomes and Measures Population-based cumulative mortality rates attributed to COVID-19.F. Results Among 219.1 million adults aged 25 years or older (113.3 million women [51.7%]; mean [SD] age, 51.3 [16.8] years), 376 125 COVID-19 deaths were reported. Age-adjusted cumulative mortality rates per 100 000 ranged from 54.4 (95% CI, 49.8-59.0 per 100 000 population) among Asian women with some college to 699.0 (95% CI, 612.9-785.0 per 100 000 population) among Native Hawaiian and Other Pacific Islander men with a high school degree or less. Racial and ethnic inequalities in COVID-19 mortality rates remained when comparing within educational attainment categories (median rate ratio reduction, 17% [IQR, 0%-25%] for education-stratified estimates vs unstratified, with non-Hispanic White individuals as the reference). If all groups had experienced the same mortality rates as college-educated non-Hispanic White individuals, there would have been 48% fewer COVID-19 deaths among adults aged 25 years or older overall, including 71% fewer deaths among racial and ethnic minority populations and 89% fewer deaths among racial and ethnic minority populations aged 25 to 64 years. Conclusions and Relevance Public health research and practice should attend to the ways in which populations that share socioeconomic characteristics may still experience racial and ethnic inequity in the distribution of risk factors for SARS-CoV-2 exposure and infection fatality rates (eg, housing, occupation, and prior health status). This study suggests that a majority of deaths among racial and ethnic minority populations could have been averted had all groups experienced the same mortality rate as college-educated non-Hispanic White individuals, thus highlighting the importance of eliminating joint racial-socioeconomic health inequities.
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Affiliation(s)
- Justin M. Feldman
- FXB Center for Health and Human Rights, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Mary T. Bassett
- FXB Center for Health and Human Rights, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
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Moghadas SM, Galvani AP. The Unrecognized Death Toll of COVID-19 in the United States. ACTA ACUST UNITED AC 2021; 1:100033. [PMID: 34396362 PMCID: PMC8354557 DOI: 10.1016/j.lana.2021.100033] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 07/21/2021] [Indexed: 11/17/2022]
Affiliation(s)
- Seyed M Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, Canada M3J 1P3
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut 06520, USA
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