Since winter 2019, SARS-CoV-2 has emerged, spread, and evolved all around the globe. We explore 4 y of evolutionary epidemiology of this virus, ranging from the applied public health challenges to the more conceptual evolutionary biology perspectives. Through this review, we first present the spread and lethality of the infections it causes, starting from its emergence in Wuhan (China) from the initial epidemics all around the world, compare the virus to other betacoronaviruses, focus on its airborne transmission, compare containment strategies ("zero-COVID" vs. "herd immunity"), explain its phylogeographical tracking, underline the importance of natural selection on the epidemics, mention its within-host population dynamics. Finally, we discuss how the pandemic has transformed (or should transform) the surveillance and prevention of viral respiratory infections and identify perspectives for the research on epidemiology of COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic caused substantial health losses but not much is known about how these are distributed across the population. We aimed to estimate the distribution of years of life lost (YLL) due to COVID-19 and investigate its variation across the Dutch population, taking into account preexisting differences in health.

We used linked administrative data covering the entire 50+ Dutch population over 2012-2018 (n = 6,102,334) to estimate counterfactual individual-level life expectancy for those who died from COVID-19 in 2020 and 2021. We estimated survival models and used Cox-LASSO and Cox-Elastic Net to perform variable selection among the large set of potential predictors in our data. Using individual-level life expectancy predictions, we generated the distribution of YLL due to COVID-19 for the entire 50+ population by age and income.

On average, we estimate that individuals who died of COVID-19 had a counterfactual life expectancy about 28% lower than that of the rest of the population. Within this average, there was substantial heterogeneity, with 20% of all individuals who died of COVID-19 having an estimated life expectancy exceeding that of the age-specific population average. Both the richest and poorest COVID-19 decedents lost the same average number of YLL, which were similarly dispersed.

Accounting for preexisting health problems is crucial when estimating YLL due to COVID-19. While average life expectancy among COVID-19 decedents was substantially lower than for the rest of the population, the popular notion that only the frail died from COVID-19 is not true.

Laboratory testing capabilities are critical for pandemic preparedness and response. However, deployable laboratory assets are not typically designed for the high-throughput demands of large-scale disease outbreaks. Validating such capabilities in field conditions requires deliberate planning and execution. Here, we outline the setup, execution, challenges, and lessons learned from the multinational Task Force Lab at Clean Care 2024 (CC24), a live NATO (North Atlantic Treaty Organization) training exercise in Hungary.

During CC24, an outbreak of a morbilliform virus, with pre-prepared nasopharyngeal swab samples, was simulated during the exercise. Task Force Lab received and processed samples to assess accuracy and turnaround times, while endemic disease surveillance and foodborne outbreak testing were also performed. Statistical analysis included daily performance updates and composite accuracy assessment, using a sample key maintained by a trusted agent within Task Force Lab.

Over the course of the exercise, 4 microbiology laboratories processed 891 samples. Two partner laboratories (Germany and Hungary) simultaneously handled 825 samples from the simulated outbreak with a 98% overall testing accuracy. Additional laboratories focused on endemic disease surveillance (Italy) and foodborne enteric disease outbreak testing (Romania). The 1st Area Medical Laboratory (United States) provided a command-and-control function, directed sample distribution, and results reporting. Key challenges included lack of standardized form usage and variability in laboratory capabilities.

Task Force Lab demonstrated the feasibility of conducting high throughput microbiological testing in a deployed setting, providing a framework for future exercises and real-world operations.

To explore the potential impact of the coronavirus disease 2019 (COVID-19) pandemic on the epidemiology of small-cell lung cancer (SCLC).

SCLC patients were collected from the Surveillance, Epidemiology, and End-Results (SEER) database (diagnosed between 2018 and 2021) and grouped according to the timing of the COVID-19 pandemic. Intergroup comparisons and survival analyses were performed on clinicopathologic characteristics and survival data to explore the differences in morbidity characteristics and survival in SCLC patients before and after the pandemic.

SCLC Patients diagnosed in the post-COVID-19 pandemic tended to have earlier tumor stage, receive chemotherapy (OR 1.14, 95% CI 1.02-1.27, P-value = 0.02) rather than radiotherapy (OR 0.89, 95% CI 0.84-0.96, P-value < 0.01), and have increased time to treatment delay. Balancing follow-up time and constructing improved survival curves, patients with SCLC diagnosed after the pandemic tended to have a worse prognosis.

Differences in some clinicopathologic factors and treatment choices, or the pandemic itself, may result in a tendency for patients with SCLC diagnosed after the pandemic to have a worse prognosis, alerting clinicians to the need to focus on the management and treatment of this population.

Effective pathogen surveillance is critical for public health decision-making, with both individual and environmental monitoring playing essential roles. While wastewater (WW) and individual whole genome sequencing (WGS) have been used to monitor SARS-CoV-2 dynamics, their complementary potential for enhancing national-level genomic surveillance remains underexplored. This study aimed to evaluate the unique and combined contributions of WW and individual WGS to genomic surveillance. We conducted SARS-CoV-2 WGS on over 4000 WW samples and 23,000 individual samples across Northern Ireland (NI) between 2021 and 2023. SARS-CoV-2 RNA was amplified using the ARTIC nCov-2019 and Mini-XT protocols and sequenced on Illumina MiSeq. Variant compositions in WW data were analysed using Freyja and compared to individual data using time series analysis, correlation assessments, and volatility measurements via numerical derivatives, with mean absolute error (MAE) calculations used to assess concordance. Wastewater treatment plants (WWTPs) were ranked by concordance to individual WGS data. WW and individual WGS complementarity was quantified by mutation classification and overlap analysis. Temporal curve shifting was used to identify lags or leads in variant detection and to infer differences in geospatial spread between WW and individual sequencing data. We confirmed strong concordance between WW and individual variant compositions (mean MAE = 6.2 %). MAE was inversely correlated with sequencing rate (Pearson r=-0.37, p < 0.001) and increased during periods with more circulating variants, highlighting the value of increased sequencing efforts during volatile periods. The population size served by a WWTP was not a reliable indicator of how well its variant composition matched that of the national individual sequencing programme. Both individual and WW-based sequencing (WBS) detected unique, as well as common mutations. Patterns of variant spread within NI were consistent between both programmes (Pearson r = 0.63, p = 0.036), providing complementary insights into variant trends and geospatial spread. We demonstrate that integration of individual and WW WGS data offers more comprehensive SARS-CoV-2 genomic surveillance and improves confidence in predictions of variant composition and spread.

This study seeks to assess the reporting quality of published health economic evaluations (HEEs) on vaccination and pharmaceuticals for Coronavirus Disease 2019 (COVID-19), and identify potential predictors associated with reporting quality.

A systematic literature search was performed in PubMed, Web of Science, Embase, the Cochrane Library, INAHTA, and Chinese databases (e.g., SinoMed, CNKI, and WANGFANG Database). HEEs published between January 1, 2020, and August 20, 2022, that considered both costs and outcomes of vaccination and pharmaceuticals for COVID-19 were included. The Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) statement scored the reporting quality for incorporated studies. A linear regression analysis was employed to characterize the impact of various features on reporting quality.

Fifty-two studies were included in the analysis. The average CHEERS score was 18.54±3.41, with the scoring rate of reporting quality was 67% (±12%). The most inadequately reported items included health economic analysis plan, time horizon, valuation of outcomes, heterogeneity, uncertainty, distributional effects, and stakeholder involvement. Higher reporting compliance was associated with articles applying a longer time horizon (no less than 1 year) and those using a societal perspective (p < 0.05). The investigations that did not specify a study perspective received the lowest scores among the subgroups.

Overall, the included HEEs on vaccination and pharmaceuticals for COVID-19 had moderate reporting quality. Future HEEs should be transparently and sufficiently reported in accordance with standard guidelines (e.g., the CHEERS 2022 statement), to increase the interpretability of results, improve the reporting quality, and better inform the decision-making.

Autoantibodies (AAbs) to interferon alpha, nuclear antigens, cardiolipin, and beta 2 glycoprotein 1, have been associated with COVID-19 severity. Despite relatively low COVID-19 morbidity and mortality in East and Central Africa, AAb prevalence in these populations remain understudied.

We evaluated AAb seroprevalence in 155 Ugandans, aged 40-50, using paired samples collected before and after the onset of the COVID-19 pandemic. Among these, 117 had serological evidence of SARS-CoV-2 infection, and 38 did not. To assess the effect of SARS-CoV-2 infection on AAb prevalence, we: 1) longitudinally compared AAb prevalence before and after evidence of infection, and 2) cross-sectionally compared AAb prevalence between those with and without infection evidence at both timepoints. Associations between AAbs and health characteristics were also explored.

There was no difference in AAb prevalence between individuals with and without evidence of infection, nor any longitudinal change after evidence of infection. However, we observed a higher-than-expected prevalence anti-beta 2 glycoprotein 1. Additionally, anti-cardiolipin was significantly associated with reported hypertension.

Our findings contribute to the limited literature on AAb prevalence in East Africa and suggest that SARS-CoV-2 does not induce these AAbs.

In 2022, the U.S. Centers for Disease Control and Prevention reported increases in antimicrobial resistance (AMR) across U.S. hospitals during the COVID-19 pandemic. The key drivers and lasting effects of this phenomenon remain unexplored.

To determine the incidence of AMR infections in U.S. hospitals during and beyond the pandemic and identify factors contributing to AMR.

Retrospective cohort study.

243 U.S. hospitals.

Adult hospitalizations, excluding inpatient transfers.

Prepandemic (January 2018 to December 2019), peak pandemic (March 2020 to February 2022), and waning pandemic (March to December 2022).

Incidence of methicillin-resistant Staphylococcus aureus; vancomycin-resistant Enterococci; extended-spectrum cephalosporin-resistant Enterobacterales; and carbapenem-resistant Enterobacterales, Acinetobacter baumannii, and Pseudomonas aeruginosa infections was evaluated among 120 continuously reporting hospitals. Infections detected more than 3 days after admission were classified as hospital-onset. Antibiotic exposure was estimated using a duration- and spectrum-weighted index. A competing risks analysis was done in 243 hospitals to identify risk factors for resistance.

During the peak of the COVID-19 pandemic, AMR infections increased from 182 to 193 per 10 000 hospitalizations (6.5% [95% CI, 5.1% to 8.0%]). Hospital-onset AMR infections increased from 28.9 to 38.0 per 10 000 hospitalizations (31.5% [CI, 27.3% to 35.8%]). Factors associated with hospital-onset AMR included illness severity (intensive care unit admission, mechanical ventilation, vasopressors, COVID-19 diagnosis), comorbidities (Elixhauser Comorbidity Index), and prior exposure to antibiotics, but not hospital factors. Prevalence of AMR returned to prepandemic levels as the pandemic waned (182 to 182 per 10 000 hospitalizations; 0.4% [CI, -1.4% to 2.2%]), however, hospital-onset AMR remained above baseline (28.9 to 32.3 per 10 000 hospitalizations; 11.6% [CI, 6.8% to 16.7%]).

Residual confounding; unknown appropriateness of antibiotics.

Sustained increases in hospital-onset AMR infections occurred in U.S. hospitals during the pandemic and were strongly associated with antibiotic exposure.

National Institutes of Health Clinical Center; National Heart, Lung, and Blood Institute; and National Institute of Allergy and Infectious Diseases Intramural Research Programs.

"Brain fog," a persistent cognitive impairment syndrome, stands out as a significant neurological aftermath of coronavirus disease 2019 (COVID-19). Yet, the underlying mechanisms by which COVID-19 induces cognitive deficits remain elusive. In our study, we observed an upregulation in the expression of genes linked to the inflammatory response and oxidative stress, whereas genes associated with cognitive function were downregulated in the brains of patients infected with COVID-19. Through single-nucleus RNA sequencing (snRNA-seq) analysis, we found that COVID-19 infection triggers the immune responses in microglia and astrocytes and exacerbates oxidative stress in oligodendrocytes, oligodendrocyte progenitors (OPCs), and neurons. Further investigations revealed that COVID-19 infection elevates LUC7L2 expression, which inhibits mitochondrial oxidative phosphorylation (OXPHOS) and suppresses the expression of mitochondrial complex genes such as MT-ND1, MT-ND2, MT-ND3, MT-ND4L, MT-CYB, MT-CO3, and MT-ATP6. A holistic approach to protect mitochondrial complex function, rather than targeting a single molecular, should be an effective therapeutic strategy to prevent and treat the long-term consequences of "long COVID."

Objectives. To examine the association of state Medicaid expansion status with mortality changes during the COVID-19 pandemic in the United States. Methods. Deaths among individuals 20 to 64 years of age in 3142 counties were identified from 2018 to 2022 mortality surveillance data. Age-adjusted mortality rates were calculated for each county and by cause of death. Changes in mortality rates before and after the onset of the COVID-19 pandemic (2018-2019 vs 2021-2022) in Medicaid expansion states relative to nonexpansion states were calculated after adjustment for county sociodemographic factors and state COVID-19 vaccination rates. Results. All-cause mortality rates increased in 2020-2021 nationwide and decreased slightly in 2022. Overall, the increase was slower in Medicaid expansion states, leading to a net decrease of 31.8 (95% confidence interval [CI] = 20.9, 42.8) deaths per 100 000 person-years associated with Medicaid expansion from 2018-2019 to 2021-2022. The decrease was largest for deaths from heart disease and liver disease and was observed across subpopulations stratified by sex, age, and race. Conclusions. Increases in mortality rates were slower in Medicaid expansion states than in nonexpansion states during the COVID-19 public health emergency, suggesting a protective effect of Medicaid expansion on population health during the pandemic. (Am J Public Health. 2025;115(6):890-899. https://doi.org/10.2105/AJPH.2025.308045).

Enhancing public health emergency (PHE) management capacities has become a critical challenge in global public health governance. During the Coronavirus Disease 2019 (COVID-19) pandemic, Shanghai and Shenzhen implemented region-specific measures tailored to local conditions, reflecting China's overarching control strategy. Systematically analysis of prevention and control policies is essential for optimizing PHE responses. While existing research has primarily focused on policy-outcome relationships through case studies or quantitative models, the application of policy tools across different pandemic stages remains underexplored.

To analyze the distribution and evolution of policy tools across pandemic stages, this study integrated the policy tool perspective with the "4Rs" crisis management theory to construct a two-dimensional analytical framework. Quantitative text analysis was employed within this framework to code and quantify pandemic prevention and control policies issued between January 2020 and December 2022. Policy texts were collected from the official websites of local governments and the Peking University Law website.

From the perspective of policy tools, both Shanghai and Shenzhen predominantly relied on authority tools, followed by incentive tools, with system-changing tools being the least utilized. From the crisis management dimension, the frequency of policy tool usage peaked during the crisis outbreak period, dropped significantly during the crisis receding period, and slightly rebounded during the crisis recovery period. The two-dimensional analysis revealed that, apart from Shanghai's emphasis on incentive tools during the crisis receding period, authority tools dominated across all crisis management stages in both cities. Additionally, as the pandemic progressed, the use of capacity-building tools and incentive tools increased significantly.

Chinese local governments primarily applied authority tools to drive institutional improvements, complemented by incentive tools and capacity-building tools to enhance policy effectiveness and public engagement. Optimizing PHE management requires dynamic adjustments to policy tools based on crisis stage characteristics, balancing rigidity with flexibility and immediate responses with long-term system development. The findings may provide valuable references for governments worldwide in formulating follow-up PHE policies and offer a replicable framework for future analyses in this field.

This study aimed to analyze the temporal and spatial distribution of home mortality in the municipality of Rio de Janeiro, Brazil, before and during the first year of the COVID-19 pandemic. It is an ecological study of residents aged 15 or older, developed in two stages: (i) Time-series analysis on mortality rates according to place of occurrence; home mortality rates (HMR) according to underlying cause, age, and sex; and the proportion of home deaths by race/color and educational level from 2010 to 2020, and; (ii) Spatial analysis to observe the spatiotemporal variation of home deaths from 2010 to 2020 by Administrative Region (AR). Data from the Brazilian Mortality Information System, population estimates and the Social Progress Index (SPI) were used, all of which are publicly available and anonymized. Between 2019 and 2020, home deaths increased by 25.5%, mainly due to infectious and parasitic diseases, mental disorders, and ill-defined causes. HMR increased in all age groups except 15-19 years, with a higher proportion of home deaths among black individuals and in those with up to three years of education. Two clusters were detected: the primary (2016-2020) showed the highest HMR in ARs with high SPI, while the secondary (2020) had the highest HMR in ARs with lower SPI. Excess mortality was observed in the first year of the COVID-19 pandemic in municipality of Rio de Janeiro. Changes in the profile and causes of home deaths, along with the rise of HRM in AR with lower SPI, suggest an increase in home mortality among socially vulnerable populations during the pandemic.

Life expectancy in high-income countries remained lower in 2022 compared to pre-pandemic levels in 2019. This study explores the deficit of life expectancy and excess of years of life lost (YLL) in Spain from 2020 to 2022, assessing both direct effects of infectious diseases and indirect effects of other causes of death.

Data on life expectancy and YLL from 2010 to 2022 were obtained from the Spanish Institute for Statistics (INE). Using linear regression, we estimated expected life expectancy and YLL for 2020-2022 under the assumption that pre-pandemic trends (2010-2019) had continued.

During the first year of the pandemic, Spanish women lost 1.10 years and men lost 1.40 years in life expectancy. By 2022, life expectancy remained lower than in 2019 for both sexes. The excess YLL was similar across 2020 (2.40 million YLL and 5.3 YLL/100 people), 2021 (2.35 million YLL, 5.1 YLL/100 people), and 2022 (2.35 million YLL, 5.0 YLL/100 people). Approximately 70% of this excess was attributable to infectious diseases (87% in 2020, 78% in 2021, and 43% in 2022). Other major contributors to excess YLL included external causes, circulatory diseases, digestive diseases, and endocrine, nutritional, and metabolic diseases, while cancer mortality did not show an excess during the pandemic period.

Mortality in Spain in 2022 remained elevated compared to pre-pandemic expectations. The contribution of non-infectious diseases to excess mortality increased over time.

Not applicable.

Between March 2020-June 2021, over 30 million COVID-19 cases were reported in India. We described the COVID-19 response across the US Mission India (US Embassy New Delhi, US Consulates - Mumbai, Hyderabad, Chennai, and Kolkata) to use the learnings for a possible future pandemic. We reviewed COVID-19 mitigation activities at five US Mission India posts from March 2020-July 2021. We also analyzed case investigation and contact tracing data from Health Units (outpatient clinics), including demographics, clinical findings, test results, contact positivity rate, and compared attack rates across the posts during the same period. The US Mission in India, comprising multiple US Government agencies, initiated COVID-19 mitigation in March 2020 with educational sessions, infection prevention training, health assessments, and standard operating procedures. The Health Unit and US CDC India office initiated COVID-19 case investigations and conducted contact tracing. During the study period, 636 COVID-19 cases (72% males), including 48 clusters (size range 2-10 cases), were reported. Overall case fatality rate was 1.5% (10). Of case patients, 82% (523) were Indians, and 18% (113) were Americans. On presentation, 22% (138/625) of cases were asymptomatic. The median time from symptom onset to notification to the Health Unit was three days (Interquartile range 1-5). The Health Unit identified 2,484 contacts with a 25% positivity rate. The attack rates ranged between 10-19%, with the highest at 19% in Delhi, which was lower compared to the estimated attack rate for respective cities but closely resembled the pattern of COVID-19 waves in India. Collaboration between medical providers and public health specialists during the COVID-19 response in US Mission India led to new organizational capabilities in contact tracing, community education, and workflows. These strategies helped reduce morbidity and mortality within the US Mission during the pandemic.

Determining whether an allocation is equitable requires ethical and empirical analyses, specifically answers to 3 questions: (1) What is the ethical standard for fair allocation? (2) What is the quantitative equity metric for this standard? and (3) What do the empirical data demonstrate? Two ethical standards for assessing the fair allocation of scarce medical resources have been delineated: the COVID-19 Vaccines Global Access initiative's population-based standard and the COVID-19 health-burden standard. The equity metric for the population-based standard is vaccine per person in each country, and for the health-burden standard it is vaccine per excess deaths per country. When using excess deaths data from the World Health Organization and vaccine data from the United Nations Children's Fund, the health-burden standard showed that middle-income countries with high excess deaths (e.g., Indonesia, Peru, Mexico, Egypt, South Africa) were treated inequitably: not provided enough vaccines given their high excess deaths. The right standard to assess fair and equitable allocation is a health-burden assessment. According to this standard, contrary to assumptions and initial claims, low-income countries were not treated inequitably in COVID-19 vaccine allocation, and middle-income countries with high excess deaths were treated inequitably. (Am J Public Health. Published online ahead of print May 15, 2025:e1-e10. https://doi.org/10.2105/AJPH.2025.308077).

Respiratory viruses, such as SARS-CoV-2 and influenza, exploit host proteases like TMPRSS2 for entry, making TMPRSS2 a prime antiviral target. Here, the identification and characterization of Trypstatin, a 61-amino acid Kunitz-type protease inhibitor derived from human hemofiltrate are reported. Trypstatin inhibits TMPRSS2 and related proteases with high potency, exhibiting half-maximal inhibitory concentration values in the nanomolar range, comparable to the small molecule inhibitor camostat mesylate. In vitro assays demonstrate that Trypstatin effectively blocks spike-driven entry of SARS-CoV-2, SARS-CoV-1, MERS-CoV, and hCoV-NL63, as well as hemagglutinin-mediated entry of influenza A and B viruses. In primary human airway epithelial cultures, Trypstatin significantly reduces SARS-CoV-2 replication and retained activity in the presence of airway mucus. In vivo, intranasal administration of Trypstatin to SARS-CoV-2-infected Syrian hamsters reduces viral titers and alleviates clinical symptoms. These findings highlight Trypstatin's potential as a broad-spectrum antiviral agent against TMPRSS2-dependent respiratory viruses.

COVID-19 infection in pregnancy is associated with preterm birth and an increased risk of severe disease, needing intensive care admission for management of maternal multi-organ failure. The placenta, a fetal organ, functions as a barrier at the maternal interface and expresses the SARS-CoV-2 viral receptors. However, placental infection and transplacental transfer of virus are rare, suggesting placental resistance to viral infection. Here, we seek to determine the impact of severe COVID-19 infection on maternal, newborn, and placental outcomes.

A prospectively recruited cohort of pregnant COVID-19 patients (n = 204) at a quaternary perinatal academic center were retrospectively analyzed. During pregnancy umbilical artery (UA) Doppler assessment was performed to assess placental function. At delivery, maternal and fetal outcomes were assessed, with paired maternal peripheral blood and placenta samples collected (n = 26) for bulk RNA sequencing (RNA-seq). Post-sequencing analysis with single cell deconvolution and pathway analysis was performed.

Maternally-indicated preterm births were more frequent in severe, but not asymptomatic or mild/moderate COVID-19 infection. In severe COVID-19 infection, UA Doppler assessment was normal. Rates of fetal growth restriction and placenta:birth weight ratios were similar between groups. RNA-seq showed a distinct adaptive immune activation signature in peripheral blood while placental transcripts showed no significant changes in immune cell types.

Despite multi-organ failure, severe COVID-19 did not significantly impact placental function and transcriptomics with iatrogenic preterm birth indicated for maternal-indications.

Vulnerable subgroups of the population, such as care home residents, often face elevated mortality risks during crises like pandemics or wars. To correctly model and interpret the excess mortality of vulnerable groups during crises, a distinction must be made between the pre-existing heightened mortality of the vulnerable group, the general population's excess mortality during the crisis, and the crisis-specific excess mortality unique to the vulnerable group.

We introduce the concept of "excess excess" mortality, which captures the extra excess mortality experienced by vulnerable groups during crises, beyond what can be explained by their excess mortality due to being vulnerable and general population excess mortality. Using individual-level data from Statistics Netherlands, we model the excess excess mortality of Dutch care home residents aged 70 and older during the Covid-19 pandemic. We extend standard relative survival methods by incorporating multiple excess mortality components and use an additive hazards model to accommodate periods of negative excess hazard.

The findings confirm the severe impact of the Covid-19 pandemic on care home residents. In general, men and older age groups experienced higher excess excess mortality, both in absolute and relative terms.

Our approach offers a new perspective on how to model and interpret excess mortality in vulnerable groups during a crisis and provides a methodological foundation for investigating excess excess mortality in other contexts.

The number of studies on the health impacts of urban environmental stressors has been growing. However, research for South-Eastern Europe remains limited. We conducted a baseline Health Impact Assessment for Sofia, Bulgaria, focusing on air pollution, green space, road-traffic noise, and urban heat island (UHI) exposure aiming to promote discussions on sustainable, health-centric urban and transport planning policies.

The analysis was conducted at the neighbourhood level (n = 4969). The study population included 1,168,382 inhabitants, considering adults and children. Data were retrieved from Europe-wide and local exposure models, local censuses and surveys. We used comparative risk assessment methodology, comparing baseline with optimal scenarios for health, such as meeting World Health Organization (WHO) air quality and road-traffic noise guidelines, green space recommendations, and no UHI effect. We also examined exposure and health impact distributions by area-level socioeconomic status (SES). We approximated differences in baseline disease rates by SES using data from local surveys. The results were stratified by SES quartiles and analysed spatially using global and local bivariate Moran's I statistics, the latter to identify priority areas for intervention based on SES, environmental exposures, and health outcomes.

All Sofia residents lived in neighbourhoods where particulate matter with diameter ≤2.5 μm (PM2.5) and nitrogen dioxide (NO2) levels exceeded the WHO air quality guidelines, with mean noise levels of 62.2 dB(A) Lday, 77 % lacking sufficient availability of green space, and an average summer UHI of 2.5 °C. The largest mortality burden was from PM2.5 exposure (1939 annual deaths (95 % CI: 1349-2571)), followed by NO2 (1172 annual deaths (444-2027)), road-traffic noise (902 annual deaths (556-1311)), insufficient green space (217 annual deaths (169-262)), and UHI (95 summer deaths (58-130)). PM2.5 contributed to 17-21 % of cardiovascular disease cases, while noise accounted for 5 % of Ischaemic Heart Disease and stroke cases. NO2, noise, and UHI exposures tended to be higher in higher SES areas, while PM2.5 tended to be lower. Spatial analysis revealed that central areas, with high-SES populations, and northern, north-eastern, and north-western areas, with lower-SES populations, all experience high exposure and health impacts.

The analysis showed a significant health burden from urban environmental stressors in Sofia, with an uneven distribution across SES groups. Health-promoting policy interventions should consider both environmental and socioeconomic factors to prioritize areas for action.

The Coronavirus Disease 2019 (COVID-19) pandemic disrupted maternity care, highlighting the need for rapid, high-quality clinical practice guidelines (CPGs) to ensure safe care for pregnant women. We assessed the quality and recommendations of CPGs related to COVID-19 in pregnancy. Following prospective registration (PROSPERO number: CRD42022346031) we searched Medline, Web of Science, and UpToDate from inception until July 2024. The methodological quality was appraised using the Appraisal of Guidelines for Research and Evaluation II (AGREE II). A total of 27 CPGs were included. High scores were achieved in scope and purpose (21/27, 78%) and clarity (17/27, 63%). The most poorly addressed domains were rigour of development and applicability to clinical practice (18/27, 67% and 19/27, 70% scored low quality, respectively). Overall, only four (15%) guidelines were recommended. Most CPGs (25/27, 93%) addressed COVID-19 screening and transmission prevention, but few covered psychological care (3/27, 11%) or maternal delivery preferences (4/21, 19%). Consensus was found on timing and mode of delivery (16/17, 94%), but there was disagreement on delayed cord clamping and virus transmission interventions. Evidence-based practice requires health care providers, patients and stakeholders to be aware of variations in both the quality and recommendations of CPGs, especially during times of uncertainty.

10-20% of people infected with the coronavirus infection have long COVID symptoms, therefore, current research is the first regional assessment in Saudi Arabia to determine the relationship between long-term health complaints of COVID-19 survivors and health-related quality of life (HRQoL).

The study population comprised COVID-19 infection cases registered in the Ha'il region of Saudi Arabia from the beginning of the COVID-19 pandemic until September 2022. A retrospective research design was employed, and 295 participants completed a self-report questionnaire to assess long COVID symptoms and the Arabic version of the European 5-Dimensional Quality of Life (EQ-5D). Multiple linear regression was used to evaluate the predictive role of long COVID symptoms on the HRQoL of patients by choosing (p-value < 0.05).

The mean (SD) age of the participants was 38 years, (67.1%) were male and (58.6%) were married. On the long COVID-19 symptoms, the highest mean values were fatigue (M=2.3; 95% CI 2.1-2.4) followed by headache (M=2.1; 95% CI 2.0-2.3) and persistent cough (M=1.9; 95% CI 1.8-2.1). Findings show that HRQoL was problematic in domains of pain/discomfort as depicted by a highest mean score on this domain (M=4.24; 95% CI 4.14-4.33) followed by anxiety/depression (M=4.17: 95% CI 4.08-4.27). Multiple regression analysis showed that marital status (p=0.05), irregular exercise (p<0.01), duration of hospitalization (p<0.01), and oxygen therapy (p<0.05) were the independent background factors affecting HRQoL post-COVID-19. Among the long-COVID-19 symptoms, fatigue (p=0.05), persistent cough (p=0.001), dyspnea (p=0.02), and sexual dysfunction (p<0.001) were the independent factors that impacted the HRQoL after controlling for background variables.

The study has significant implications for Saudi Arabia's Health Sector Transformation Program that could achieve its goals of human centric care and patient satisfaction though addressing the negative impacts of specific long-COVID symptoms such as fatigue, persistent cough, dyspnea and sexual dysfunction and improving the HRQoL in domains of pain/discomfort and anxiety/depression.

Lipid nanoparticles (LNPs) have emerged as a transformative platform for the targeted delivery of therapeutic agents, revolutionizing treatment paradigms across a spectrum of diseases. Since the inception of liposomes in the 1960s, lipid-based nanotechnology has evolved to address limitations such as poor bioavailability, off-target effects, and instability, thereby enhancing the efficacy and safety of drug administration. This review highlights the latest advancements in LNPs technology, focusing on their application in cancer therapy, gene therapy, infectious disease management, glaucoma, and other clinical areas. Recent studies underscore the potential of LNPs to deliver messenger RNA (mRNA) and small interfering RNA (siRNA) for precise genetic intervention, exemplified by breakthroughs in RNA interference and CRISPR-Cas9 genome editing. Additionally, LNPs have been successfully employed to ameliorate conditions, demonstrating their versatility in addressing both acute and chronic disorders. However, challenges persist concerning large-scale manufacturing, long-term stability, and comprehensive safety evaluations. Future research must focus on optimizing formulations, exploring synergistic combinations with existing therapies, and expanding the scope of treatable diseases. The integration of LNPs into personalized medicine and the exploration of applications in other diseases represent promising avenues for further investigation. LNPs are poised to play an increasingly central role in the development of next-generation therapeutics.

The aim was to determine the effect of the COVID-19 pandemic on diabetic retinopathy and referral rates in the English National Health Service (NHS) Diabetic Eye Screening Programme (DESP).

Non-patient identifiable data are submitted centrally from the 57 regional centres in the NHS DESP on a quarterly basis and analysed using STATA, comparing 01/04/2019-31/03/2020 and 01/04/2021-31/03/2022. Patient characteristics were analysed from National Diabetes Audit (NDA) data.

There were 2,274,635 grades from the 57 centres in 2019-2020 and 2,199,623 grades in 2021-2022. The proportion of eyes with referable DR increased from 3.1% in 2019-2020 to 3.2% in the 2021-2022 NHS year (p < 0.01) with a small increase in the level of non-referable DR from 24.6% to 24.8% (p < 0.01). The median proportion of ungradable eyes in 2019-2020 was 2.6% (IQR: 2.3% to 3.3%) increasing to 3.1% (IQR: 2.5% to 3.7%) in 2021-2022. NDA data demonstrated that the proportions with type 1 diabetes receiving eye screening were higher in the latter year (8.3% vs. 7.3%).

The COVID-19 pandemic was associated with small increases in referable retinopathy rates from 3.1% to 3.2%, non-referable DR from 24·6% to 24.8% and an increase in the ungradable image rate from 2.6% to 3.1%, the latter increase possibly being caused by untreated cataract during the pandemic. Risk stratification of invitations in the recovery period was believed to have contributed to keeping the referable rates low and supports a similar approach in extension of the screening interval for low-risk groups.

Excess mortality has been one of the commonly used measures of the population health effects of the COVID-19 pandemic. Denmark, Finland, Norway and Sweden share several health and socioeconomic characteristics but adopted different control measures and experienced varying degrees of case and hospitalization burden during the pandemic. Using mortality trends between 2001 and 2019 and a combination of models, we estimated and compared annual and monthly excess mortality in these countries nationally as well as stratified by age, sex and subnational regions between 2020 and 2023.

Multi-model study.

Three methods were used to estimate mortality: i) a Bayesian spatial model with a random effect component for spatial dependence among subregions and trend and seasonality terms; ii) a Bayesian GAMM model with terms for annual trend (a thin-plate spline) and within-year seasonality (a cyclic cubic spline); and, iii) a combination of autoregressive and exponential trend smoothing methods. Estimates from these approaches were combined using model averaging.

Based on age-standardized mortality rates (per 100,000 population) of the averaged estimates: Finland had the highest cumulative excess mortality of the four countries; older age groups (70+ year) accounted for nearly all excess mortality; men had higher excess rates than women; and capital regions had some of the lowest rates relative to other regions in each country. With a few exceptions, mortality in 2023 returned to pre-pandemic levels. Model verification indicated good calibration and superior skill of the combination model relative to its component models.

We believe our approach better quantifies uncertainty than individual models, and our estimates are comprehensive, spatially, temporally and demographically well-resolved, and can support further association studies.

Viral respiratory infections remain a major and recurrent public health threat. Among them, influenza viruses are responsible for ⁓500,000 deaths worldwide and a high economic burden. The recurrent threat of emerging zoonotic or pandemic viruses worsens this scenario, being SARS-CoV-2 and the millions of COVID-19 deaths the most recent example. The rapid evolution of circulating influenza and SARS-CoV-2 viruses allows the emergence and dissemination of variant strains carrying mutations resulting in suboptimal vaccine protection and/or reduced efficacy of current limited therapeutic arsenal. In this context, host-targeted approaches constitute a promising antiviral strategy aiming to achieve broad-spectrum activity and mitigate the emergence of viral resistance against classic direct acting antivirals. Here, we demonstrated that diltiazem, a calcium channel blocker currently used to treat angor, induces an ISG expression profile characteristic of an antiviral cellular state mainly driven by IFN-λ. We then evaluated the potential of the diltiazem-baloxavir combination against Influenza A wild-type and the PA I38T resistant strain in cell culture and human airway epithelia (HAE). We analogously evaluated the diltiazem-molnupiravir combination against SARS-CoV-2, including variants of concern. Our results demonstrate the broad-spectrum antiviral activity of diltiazem against Influenza A viruses, including resistant strains, as well as the capacity to potentiate the antiviral effect of baloxavir. The diltiazem-molnupiravir combination further reduced viral production and protected the integrity of HAE infected with SARS-CoV-2. This study highlights the major interest of combining direct acting and host-targeted agents as a promising strategy against circulating and emerging viruses.

Background: In patients with COVID-19 pneumonia, the estimation of PaO2 represents the method of choice for monitoring a patient's oxygenation status and assessing disease severity. The aim of this study is, therefore, to investigate the correlation between SpO2/FiO2 and PaO2/FiO2, as well as radiological and laboratory biomarkers of severity. Methods: In this monocentric observational, analytical, retrospective large cohort study, consecutive patients with a confirmed diagnosis of pneumonia from SARS-CoV-2, hospitalized at the Cotugno Hospital-AORN dei Colli-of Naples, between 1 September 2020 and 28 February 2022 were considered for study inclusion. Patients with missing data were excluded. Results: We included 585 patients (median age 63 [22-95]). Mean PaO2/FiO2 was 203 [66-433], whilst mean SpO2/FiO2 was 240 [81-471]. We found that P/F ratio could be predicted from S/F ratio, as described by the linear regression equation (P/F = 13.273 + 0.790 × S/F). In addition, we found that SpO2/FiO2 ratio significantly correlated with HRCT score and laboratory markers of severity, including IL-6, D-Dimer, and NLR. Conclusions: SpO2/FiO2 ratio represents a highly useful resource as a valid surrogate of P/F ratio in patients with COVID pneumonia, also correlating with other biomarkers of severity, such as HRCT score and key laboratory markers.

The Independent Panel for Pandemic Preparedness and Response issued a series of recommendations for future pandemic preparedness and response. Latin America's COVID-19-related deaths represented 25 % of the global demises, despite harboring less than 8 % of the world's population. As little data exists to support whether the Panel's recommendations reflect public health professionals' priorities in the region the study aimed to define these priorities utilizing a Delphi study.

A consensus-building modified Delphi technique.

For the first two rounds, participants were asked to rank a list of topics across seven domains on a 4-point Likert scale. Topics voted by at least 75 % of participants in either round as very important were included in the final round. Participants ranked the topics from each of the seven domains in numeric order to define top priorities.

A total of 115 responses were obtained across three rounds. Most respondents were involved in direct efforts against COVID-19 (75·0-86·%) and a considerable proportion had more than 16 years of public health experience (37·3-50·0 %). The top priority issues were zoonotic disease-pathogen surveillance systems (27·4 points), robust infection and prevention control programs (22·8 points), and indicator and event-based monitoring and reporting systems (22·1 points).

Establishing priorities for future pandemics is critical to ensure better health outcomes. The region should strengthen collaboration and enhance its capacities while conducting country-level analysis and defining priorities for future arrangements.

Infectious diseases, caused by pathogenic microorganisms and capable of spreading, pose a significant threat to global public health. Developing efficient and cost-effective techniques for treating infectious diseases is crucial in curbing their progression and reducing patients' morbidity and mortality. Nanobodies (Nbs), a novel class of affinity reagents derived from unique heavy chain-only antibodies in camelids, represent the smallest intact and fully functional antigen-binding fragments. Compared with conventional antibodies and their antigen binding fragments, Nbs offer numerous advantages, including high affinity, exceptional target specificity, cost-effective production, easy accessibility, and robust stability, demonstrating immense potential in infectious disease treatment. This review introduces Nbs and focuses on discussing their mechanisms and intervention strategies in the treatment of viral and bacterial infections.

Many explanations have been advanced for why the frequency of deaths associated with Covid-19 varied so much across countries. Previous work has provided evidence that numerous social, economic, and environmental factors correlate with Covid-19 outcomes. One problem researchers face in identifying which of these explanations are best able to explain cross-country variation is that the number of these explanations is too large to be usefully included in a single regression model. This paper uses Bayesian Model Averaging (BMA) to address this problem, focusing on excess mortality to ensure meaningful comparisons across countries. The results suggest that a key determinant of countries' success in containing Covid-19 has been the strength of the Rule of Law. We also find evidence that rainfall and seaborders are key potential explanations for differences in excess mortality.

Concerns have been raised about discrepancies in COVID-19 mortality data, particularly between preliminary and final datasets of vital statistics in Serbia. In the original preliminary dataset, released daily during the ongoing pandemic, there was an underestimation of deaths in contrast to those reported in the subsequently released yearly dataset of vital statistics.

This study aimed to assess the accuracy of the final mortality dataset and justify its use in further analyses. In addition, we quantified the relative impact of COVID-19 on the death rate in the Serbian capital's population. In the process, we aimed to explore whether any evidence of cause-of-death misattribution existed in the final published datasets.

Data were sourced from the electronic databases of the Statistical Office of the Republic of Serbia. The dataset included yearly recorded deaths and the causes of death of all citizens currently living in the territory of Belgrade, the capital of the Republic of Serbia, from 2015 to 2021. Standardization and modeling techniques were utilized to quantify the direct impact of COVID-19 and to estimate excess deaths. To account for year-to-year trends, we used a mixed-effects hierarchical Poisson generalized linear regression model to predict mortality for 2020 and 2021. The model was fitted to the mortality data observed from 2015 to 2019 and used to generate mortality predictions for 2020 and 2021. Actual death rates were then compared to the obtained predictions and used to generate excess mortality estimates.

The total number of excess deaths, calculated from model estimates, was 3175 deaths (99% CI 1715-4094) for 2020 and 8321 deaths (99% CI 6975-9197) for 2021. The ratio of estimated excess deaths to reported COVID-19 deaths was 1.07. The estimated increase in mortality during 2020 and 2021 was 12.93% (99% CI 15.74%-17.33%) and 39.32% (99% CI 35.91%-39.32%) from the expected values, respectively. Those aged 0-19 years experienced an average decrease in mortality of 22.43% and 23.71% during 2020 and 2021, respectively. For those aged up to 39 years, there was a slight increase in mortality (4.72%) during 2020. However, in 2021, even those aged 20-39 years had an estimated increase in mortality of 32.95%. For people aged 60-79 years, there was an estimated increase in mortality of 16.95% and 38.50% in 2020 and 2021, respectively. For those aged >80 years, the increase was estimated at 11.50% and 34.14% in 2020 and 2021, respectively. The model-predicted deaths matched the non-COVID-19 deaths recorded in the territory of Belgrade. This concordance between the predicted and recorded non-COVID-19 deaths provides evidence that the cause-of-death misattribution did not occur in the territory of Belgrade.

The finalized mortality dataset for Belgrade can be safely used in COVID-19 impact analysis. Belgrade experienced a significant increase in mortality during 2020 and 2021, with most of the excess mortality attributable to SARS-CoV-2. Concerns about increased mortality from causes other than COVID-19 in Belgrade seem misplaced as their impact appears negligible.

Vaccination against COVID-19 has been the primary public health measure implemented to limit the spread of the disease. However, there is still considerable scope for improvement in vaccine coverage, particularly in sub-Saharan African countries. The factors influencing the acceptance or reluctance of the COVID-19 vaccine have been widely studied, but there is a gap in the literature with regard to dynamic populations, particularly travelers, who are one of the priority target groups for vaccination. This study assessed the perceptions, attitudes and practices regarding the COVID-19 vaccine, and explored factors associated with vaccination status among travelers.

A cross-sectional survey was conducted at several points of entry (PoEs) selected for six survey sites (N'djili airport, Ngobila beach, Lufu, Boma, Moanda, and Kananga), located in three provinces of the Democratic Republic of the Congo (Kinshasa, Kongo Central and Kasaï Central), from February 20 to March 05, 2023. The data were summarized and logistic regression models were performed to assess factors associated with vaccination status.

A total of 2742 travelers were included in this survey. Of these, 54% had received at least one dose of COVID-19 vaccine. Multivariable logistic regression analyses revealed that that several factors were significantly associated with vaccination status. These included age (under 60 years), marital status (single), occupation (other than healthcare worker), mode of travel (other than airplane), and poor perceptions of the vaccine. The most frequently cited reasons for vaccination among respondents who had received the vaccine were the prevention of COVID-19 infection and the ease of travel. In contrast, unvaccinated participants expressed greater concern about the safety and effectiveness of the vaccine, as well as vaccine-related side effects. Furthermore, travel disruption and inappropriate vaccination sites have been identified as significant obstacles to the acceptance of vaccination at the PoEs.

It is essential that awareness initiatives address concerns and misconceptions about vaccine safety and effectiveness. The influence of social media platforms may be harnessed for the dissemination of accurate information from the most trusted information sources, including healthcare professionals, to the target population. In addition, accompanying measures should be considered to facilitate vaccination compliance at different PoEs.

Despite widespread vaccination efforts, significant excess mortality continued in various countries following the COVID-19 pandemic. This study aims to estimate excess mortality during 2022 in 21 countries and regions, and to examine the relationship of governmental control measures and vaccination rates with excess mortality during 2021-2 at an ecological level.

Excess mortality for 2022 was estimated by analysing weekly mortality data from January 2020 to December 2022 across 21 countries and regions participating in the C-MOR consortium. This was achieved by comparing the observed age-standardized mortality rates per 100 000 population to a baseline derived from historical data (2015-19). Governmental control measures and vaccination efforts were investigated for their association with weekly excess mortality during 2021-2 in multilevel models with country as a random effect.

All 21 countries experienced excess mortality in 2022, ranging from 8.6 (Peru) to 116.2 (Georgia) per 100 000 population, noting that rates were not directly comparable across countries. Many countries had higher excess mortality in 2022 compared with previous years. Mauritius showed a significant excess mortality for the first time in 2022. The proportion of COVID-19 deaths relative to total deaths decreased in 2022 for most countries, except Australia. Governmental control measures and vaccinations were associated with reduced excess mortality in 2021 and 2022, respectively.

The study reveals sustained excess mortality throughout 2022. Excess deaths were mainly non-COVID-19-related, likely due to displaced mortality or to broader long-term impacts of the pandemic response. Governmental control policies and vaccination efforts were associated with lower excess mortality. These findings provide critical insights into pandemic mortality dynamics and emphasize the need for continued vigilance and adaptive public health strategies.

Using an elimination strategy, Hong Kong was able to minimise COVID-19 mortality in 2020 and 2021, but a large epidemic caused by the Omicron variant occurred in 2022. We aimed to estimate the overall, age-, sex-, epidemic period- and cause-specific excess mortality in 2022 in Hong Kong and compare excess mortality to laboratory-confirmed COVID-19 mortality.

We used negative binomial regression analysis to model time series of weekly all-cause and cause-specific deaths from 2010 to 2021 to predict the weekly number of deaths in 2022 against counterfactual baselines projected from the trends in the absence of a pandemic. The estimated excess deaths were compared with laboratory-confirmed COVID-19 deaths overall and by age and epidemic period.

We estimated that there were 13 500 (95% confidence interval (CI) = 13 400, 13 600) excess deaths in 2022, which was slightly higher than the 12 228 deaths recorded with laboratory-confirmed COVID-19, with the majority of the excess deaths and laboratory-confirmed deaths occurring among older adults. The increased number of excess deaths over laboratory-confirmed COVID-19 deaths was most substantial from February to April 2022 (a difference of 847 deaths), when the most prominent Omicron wave peaked. Most of the excess deaths (78%) were from respiratory causes, while 10% were from cardiovascular causes. A slight reduction in malignant neoplasm mortality was identified among older adults in 2022.

A substantial increase in population mortality was identified in 2022 in Hong Kong, slightly larger than the laboratory-confirmed COVID-19 deaths. Deaths from COVID-19 may have displaced some deaths that would otherwise have occurred due to other causes.

Viral codon fitness (VCF) of the host and the VCF shifting has seldom been studied under quantitative measurements, although they could be concepts vital to understand pathogen epidemiology. This study demonstrates that the relative synonymous codon usage (RSCU) of virus genomes together with other genomic properties are predictive of virus host codon fitness through tree-based machine learning. Statistical analysis on the RSCU data matrix also revealed that the wobble position of the virus codons is critically important for the host codon fitness distinction. As the trained models can well characterise the host codon fitness of the viruses, the frequency and other details stored at the leaf nodes of these models can be reliably translated into human virus codon fitness score (HVCF score) as a readout of codon fitness of any virus infecting human. Specifically, we evaluated and compared HVCF of virus genome sequences from human sources and others and evaluated HVCF of SARS-CoV-2 genome sequences from NCBI virus database, where we found no obvious shifting trend in host codon fitness towards human-non-infectious. We also developed a bioinformatics tool to simulate codon-based virus fitness shifting using codon compositions of the viruses, and we found that Tylonycteris bat coronavirus HKU4 related viruses may have close relationship with SARS-CoV-2 in terms of human codon fitness. The finding of abundant synonymous mutations in the predicted codon fitness shifting path also provides new insights for evolution research and virus monitoring in environmental surveillance.