COVID-19 mortality and excess mortality among working-age residents in California, USA, by occupational sector: a longitudinal cohort analysis of mortality surveillance data

Evolving patterns of COVID-19 mortality in US counties: A longitudinal study of healthcare, socioeconomic, and vaccination associations

The COVID-19 pandemic emphasized the need for pandemic preparedness strategies to mitigate its impacts, particularly in the United States, which experienced multiple waves with varying policies, population response, and vaccination effects. This study explores the relationships between county-level factors and COVID-19 mortality outcomes in the U.S. from 2020 to 2023, focusing on disparities in healthcare access, vaccination coverage, and socioeconomic characteristics. We conduct multi-variable rolling regression analyses to reveal associations between various factors and COVID-19 mortality outcomes, defined as Case Fatality Rate (CFR) and Overall Mortality to Hospitalization Rate (OMHR), at the U.S. county level. Each analysis examines the association between mortality outcomes and one of the three hierarchical levels of the Social Vulnerability Index (SVI), along with other factors such as access to hospital beds, vaccination coverage, and demographic characteristics. Our results reveal persistent and dynamic correlations between various factors and COVID-19 mortality measures. Access to hospital beds and higher vaccination coverage showed persistent protective effects, while higher Social Vulnerability Index was associated with worse outcomes persistently. Socioeconomic status and vulnerable household characteristics within the SVI consistently associated with elevated mortality. Poverty, lower education, unemployment, housing cost burden, single-parent households, and disability population showed significant associations with Case Fatality Rates during different stages of the pandemic. Vulnerable age groups demonstrated varying associations with mortality measures, with worse outcomes predominantly during the Original strain. Rural-Urban Continuum Code exhibited predominantly positive associations with CFR and OMHR, while it starts with a positive OMHR association during the Original strain. This study reveals longitudinal persistent and dynamic factors associated with two mortality rate measures throughout the pandemic, disproportionately affecting marginalized communities. The findings emphasize the urgency of implementing targeted policies and interventions to address disparities in the fight against future pandemics and the pursuit of improved public health outcomes.

Mathematical assessment of the roles of age heterogeneity and vaccination on the dynamics and control of SARS-CoV-2

The COVID-19 pandemic, caused by SARS-CoV-2, disproportionately affected certain segments of society, particularly the elderly population (which suffered the brunt of the burden of the pandemic in terms of severity of the disease, hospitalization, and death). This study presents a generalized multigroup model, with m heterogeneous sub-populations, to assess the population-level impact of age heterogeneity and vaccination on the transmission dynamics and control of the SARS-CoV-2 pandemic in the United States. Rigorous analysis of the model for the homogeneous case (i.e., the model with m = 1) reveal that its disease-free equilibrium is globally-asymptotically stable for two special cases (with perfect vaccine efficacy or negligible disease-induced mortality) whenever the associated reproduction number is less than one. The model has a unique and globally-asymptotically stable endemic equilibrium, for special a case, when the associated reproduction threshold exceeds one. The homogeneous model was fitted using the observed cumulative mortality data for the United States during three distinct waves (Waves A (October 17, 2020 to April 5, 2021), B (July 9, 2021 to November 7, 2021) and C (January 1, 2022 to May 7, 2022)) chosen to align with time periods when the Alpha, Delta and Omicron were, respectively, the predominant variants in the United States. The calibrated model was used to derive a theoretical expression for achieving vaccine-derived herd immunity (needed to eliminate the disease in the United States). It was shown that, using the one-group homogeneous model, vaccine-derived herd immunity is not attainable during Wave C of the pandemic in the United States, regardless of the coverage level of the fully-vaccinated individuals. Global sensitivity analysis was carried out to determine the parameters of the model that have the most influence on the disease dynamics and burden. These analyses reveal that control and mitigation strategies that may be very effective during one wave may not be so very effective during the other wave or waves. However, strategies that target asymptomatic and pre-symptomatic infectious individuals are shown to be consistently effective across all waves. To study the impact of the disproportionate effect of COVID-19 on the elderly population, we considered the heterogeneous model for the case where the total population is subdivided into the sub-populations of individuals under 65 years of age and those that are 65 and older. The resulting two-group heterogeneous model, which was also fitted using the cumulative mortality data for wave C, was also rigorously analysed. Unlike for the case of the one-group model, it was shown, for the two-group model, that vaccine-derived herd immunity can indeed be achieved during Wave C of the pandemic if at least 61% of the populace is fully vaccinated. Thus, this study shows that adding age heterogeneity into a SARS-CoV-2 vaccination model with homogeneous mixing significantly reduces the level of vaccination coverage needed to achieve vaccine-derived herd immunity (specifically, for the heterogeneous model, herd-immunity can be attained during Wave C if a moderate proportion of susceptible individuals are fully vaccinated). The consequence of this result is that vaccination models for SARS-CoV-2 that do not explicitly account for age heterogeneity may be overestimating the level of vaccine-derived herd immunity threshold needed to eliminate the SARS-CoV-2 pandemic.

Demographic changes in COVID-19 mortality during the pandemic: analysis of trends in disparities among workers using California's mortality surveillance system

BACKGROUND

There is limited information on the extent and patterns of disparities in COVID-19 mortality throughout the pandemic. We aimed to examine trends in disparities by demographics over variants in the pre- and post-vaccine availability period among Californian workers using a social determinants of health lens.

METHODS

Using death certificates, we identified all COVID-19 deaths that occurred between January 2020 and May 2022 among workers aged 18-64 years in California (CA). We derived estimates for at-risk worker populations using the Current Population Survey. The waves of COVID-19 mortality in the pre-vaccine availability period were March 2020-June 2020 (wave 1), and July 2020-November 2020 (wave 2), and in the post-vaccine availability period: December 2020-May 2021 (wave 3), June 2021-January 2022 (wave 4), and February 2022-May 2022 (wave 5). Poisson regression models with robust standard errors were used to determine wave-specific mortality rate ratios (MRRs). We examined the change in MRR across waves by including an interaction term between each demographic characteristic and wave period in different models. The role of potential misclassification of Race/ethnicity on death certificates was examined using probabilistic quantitative bias analysis as sensitivity analysis.

RESULTS

Among the 24.1 million working age CA population included in the study, there were 26,068 COVID-19 deaths in the period between January 2020 and May 2022. Compared with their respective reference groups, workers who were 50-64 years old, male, Native Hawaiian, Latino, or African American, foreign-born; individuals who had lower education; and unmarried were disproportionately affected by COVID-19 mortality. While disparities by sex, race/ethnicity and foreign-born status narrowed in later waves (post-vaccine availability), disparities by age, education level and marital status did not change substantially across waves.

CONCLUSION

Demographic disparities in COVID-19 mortality narrowed in the post-vaccine availability waves. However, the existence of disparities across all waves of the pandemic, even in an era of widespread vaccine coverage, could indicate remaining gaps in prevention and differential vulnerability. Addressing the underlying social, structural, and occupational factors that contribute to these disparities is critical for achieving health equity.

Changes in all-cause and cause-specific mortality by occupational skill during COVID-19 epidemic in Spain

BACKGROUND

There is little information on the differential impact of the COVID-19 pandemic on mortality by occupation. The objective was to examine changes in mortality during the COVID-19 period compared with the prepandemic period in different occupational groups in Spain.

METHODS

Average mortality in the entire period 2020-2021, and each of its semesters, was compared, respectively, with the average mortality in the entire period 2017-2019, and the corresponding semester (first or second) of this last period, across occupational skill levels. For this, age-standardised death rates and age-adjusted mortality rate ratios (MRRs) obtained through Poisson regression were used. Data were obtained from the National Institute of Statistics and the Labour Force Survey.

RESULTS

The excess all-cause mortality during the 2020-2021 pandemic period by the MRR was higher in low-skilled (1.18, 95% CI 1.16 to 1.20) and medium-skilled workers (1.14; 95% CI 1.13 to 1.15) than high-skilled workers (1.04; 95% CI 1.02 to 1.05). However, the greatest excess mortality was observed in low-skilled workers in 2020 and in medium-skilled workers in 2021. Focusing on causes of death other than COVID-19, low-skilled workers showed the highest MRR from cardiovascular diseases (1.31; 95% CI 1.26 to 1.36) and high-skilled workers the lowest (1.02; 95% CI 0.98 to 1.02). However, this pattern was reversed for mortality from external causes, with low-skilled workers showing the lowest MRR (1.04; 95% CI 0.97 to 1.09) and high-skilled workers the highest (1.08; 95% CI 1.03 to 1.13).

CONCLUSION

Globally, in Spain, during the 2020-2021 COVID-19 epidemic period, low-skilled workers experienced a greater excess all-cause mortality than other occupational groups, but this was not the case during the entire epidemic period or for all causes of death.

Occupation and SARS-CoV-2 in Europe: a review

INTRODUCTION

Workplace features such as ventilation, temperature and the extent of contact are all likely to relate to personal risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Occupations relating to healthcare, social care, education, transport and food production and retail are thought to have increased risks, but the extent to which these risks are elevated and how they have varied over time is unclear.

METHODS

We searched for population cohort studies conducted in Europe that compared coronavirus disease 2019 (COVID-19) outcomes between two or more different occupational groups. Data were extracted on relative differences between occupational groups, split into four time-periods corresponding to pandemic waves.

RESULTS

We included data from 17 studies. 11 studies used SARS-CoV-2 as their outcome measure and six used COVID-19 hospitalisation and mortality. During waves one and two, the majority of studies saw elevated risks in the five groups that we looked at. Only seven studies used data from wave three onwards. Elevated risks were observed in waves three and four for social care and education workers in some studies.

CONCLUSIONS

Evidence relating to occupational differences in COVID-19 outcomes in Europe largely focuses on the early part of the pandemic. There is consistent evidence that the direction and magnitude of differences varied with time. Workers in the healthcare, transport and food production sectors saw highly elevated risks in the early part of the pandemic in the majority of studies but this did not appear to continue. There was evidence that elevated risks of infection in the education and social care sectors may have persisted.

Excess deaths associated with COVID-19 by rurality and demographic factors in the United States

PURPOSE

To estimate percent excess deaths during the COVID-19 pandemic by rural-urban residence in the United States and to describe rural-urban disparities by age, sex, and race/ethnicity.

METHODS

Using US mortality data, we used overdispersed Poisson regression models to estimate monthly expected death counts by rurality of residence, age group, sex, and race/ethnicity, and compared expected death counts with observed deaths. We then summarized excess deaths over 6 6-month time periods.

FINDINGS

There were 16.9% (95% confidence interval [CI]: 16.8, 17.0) more deaths than expected between March 2020 and February 2023. The percent excess varied by rurality (large central metro: 18.2% [18.1, 18.4], large fringe metro: 15.6% [15.5, 15.8], medium metro: 18.1% [18.0, 18.3], small metro: 15.5% [15.3, 15.7], micropolitan rural: 16.3% [16.1, 16.5], and noncore rural: 15.8% [15.6, 16.1]). The percent excess deaths were 20.2% (20.1, 20.3) for males and 13.6% (13.5, 13.7) for females, and highest for Hispanic persons (49% [49.0, 49.6]), followed by non-Hispanic Black persons (28% [27.5, 27.9]) and non-Hispanic White persons (12% [11.6, 11.8]). The 6-month time periods with the highest percent excess deaths for large central metro areas were March 2020-August 2020 and September 2020-February 2021; for all other areas, these time periods were September 2020-February 2021 and September 2021-February 2022.

CONCLUSION

Percent excess deaths varied by rurality, age group, sex, race/ethnicity, and time period. Monitoring excess deaths by rurality may be useful in assessing the impact of the pandemic over time, as rural-urban patterns appear to differ.

Changes in mental distress among employees during the three years of the COVID-19 pandemic in Germany

OBJECTIVES

The COVID-19 pandemic changed the future of work sustainably and led to a general increase in mental stress. A study conducted during the second and third pandemic wave with a retrospective survey of the first wave among 1,545 non-healthcare workers confirmed an increase in anxiety and depression symptoms and showed a correlation with the occupational SARS-CoV-2 infection risk. This online follow-up survey aims to examine changes in mental distress as the pandemic progressed in Germany and to identify factors influencing potential changes.

METHODS

Longitudinal data from 260 subjects were available for this analysis. Mental distress related to anxiety and depression symptoms, assessed by the Patient Health Questionnaire-4 (PHQ-4), and occupational risk factors were solicited at the end of 2022 and retrospectively at the fifth wave. Categorized PHQ-4 scores were modelled with mixed ordinal regression models and presented with odds ratios (OR) and 95% confidence intervals (95% CI).

RESULTS

A previous diagnosis of a depressive or anxiety disorder was a strong risk factor for severe symptoms (OR 3.49, 95% CI 1.71-7.11). The impact of occupational SARS-CoV-2 infection risk on mental distress was increased, albeit failing to reach the formal level of statistical significance (high risk OR 1.83, 95% CI 0.59-5.63; probable risk OR 1.72, 95% CI 0.93-3.15). Mental distress was more pronounced in those with a previous diagnosis of anxiety and depression. Confirmed occupational risk factors were protective measures against occupational SARS-CoV-2 infection perceived as inadequate, chronic work-related stress, overcommitment, reduced interactions with fellow-workers, and work-privacy conflicts.

CONCLUSIONS

The pandemic had a negative impact on anxiety and depression symptoms among the studied non-healthcare workers, particularly early in the pandemic, although this effect does not appear to be permanent. There are modifiable risk factors that can protect workers' mental health, including strengthening social interactions among employees and reducing work-privacy conflicts.

Systematic review of empiric studies on lockdowns, workplace closures, and other non-pharmaceutical interventions in non-healthcare workplaces during the initial year of the COVID-19 pandemic: benefits and selected unintended consequences

BACKGROUND

We conducted a systematic review aimed to evaluate the effects of non-pharmaceutical interventions within non-healthcare workplaces and community-level workplace closures and lockdowns on COVID-19 morbidity and mortality, selected mental disorders, and employment outcomes in workers or the general population.

METHODS

The inclusion criteria included randomized controlled trials and non-randomized studies of interventions. The exclusion criteria included modeling studies. Electronic searches were conducted using MEDLINE, Embase, and other databases from January 1, 2020, through May 11, 2021. Risk of bias was assessed using the Risk of Bias in Non-Randomized Studies of Interventions (ROBINS-I) tool. Meta-analysis and sign tests were performed.

RESULTS

A total of 60 observational studies met the inclusion criteria. There were 40 studies on COVID-19 outcomes, 15 on anxiety and depression symptoms, and five on unemployment and labor force participation. There was a paucity of studies on physical distancing, physical barriers, and symptom and temperature screening within workplaces. The sign test indicated that lockdown reduced COVID-19 incidence or case growth rate (23 studies, p < 0.001), reproduction number (11 studies, p < 0.001), and COVID-19 mortality or death growth rate (seven studies, p < 0.05) in the general population. Lockdown did not have any effect on anxiety symptoms (pooled standardized mean difference = -0.02, 95% CI: -0.06, 0.02). Lockdown had a small effect on increasing depression symptoms (pooled standardized mean difference = 0.16, 95% CI: 0.10, 0.21), but publication bias could account for the observed effect. Lockdown increased unemployment (pooled mean difference = 4.48 percentage points, 95% CI: 1.79, 7.17) and decreased labor force participation (pooled mean difference = -2.46 percentage points, 95% CI: -3.16, -1.77). The risk of bias for most of the studies on COVID-19 or employment outcomes was moderate or serious. The risk of bias for the studies on anxiety or depression symptoms was serious or critical.

CONCLUSIONS

Empiric studies indicated that lockdown reduced the impact of COVID-19, but that it had notable unwanted effects. There is a pronounced paucity of studies on the effect of interventions within still-open workplaces. It is important for countries that implement lockdown in future pandemics to consider strategies to mitigate these unintended consequences.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration # CRD42020182660.

Sex Differences in COVID-19 Deaths, by Industry and Occupation, 2021

INTRODUCTION

The COVID-19 pandemic has disproportionately impacted workers in certain industries and occupations. The infection risk for SARS-CoV-2 and future respiratory viruses in the workplace is a significant concern for workers, employers, and policymakers. This study describes the differences in COVID-19 mortality by sex and industry/occupation among working-age U.S. residents in 49 states and New York City.

METHODS

The 2021 National Vital Statistics System public use multiple-cause-of-death data for U.S. decedents aged 15-64 years (working age) with information on usual industry and occupation were analyzed in 2022. Age-standardized COVID-19 death rates for selected demographic characteristics and adjusted proportional mortality ratios were estimated by sex and usual industry and occupation.

RESULTS

In 2021, 133,596 (14.3%) U.S. decedents aged 15-64 years had COVID-19 listed as the underlying cause of death; the highest COVID-19 death rate was among persons aged 55-64 years (172.4 of 100,000 population) and males (65.5 of 100,000 population). Among males and females, American Indian or Alaskan Native and Black or African American, respectively, had the highest death rates. Hispanic males had higher age-adjusted death rates than Hispanic females. Working-age male decedents in the public administration (proportional mortality ratio=1.39) and management of companies and enterprises industries (proportional mortality ratio=1.39) and community and social services occupations (proportional mortality ratio=1.68) and female decedents in the utilities industry (proportional mortality ratio=1.20) and protective services occupation (proportional mortality ratio=1.18) had the highest proportional mortality ratios.

CONCLUSIONS

COVID-19 death rates and proportional mortality ratios varied by sex, industry, and occupation groups. These findings underscore the importance of workplace public health interventions, which could protect workers and their communities.

Evidence on COVID-19 Mortality and Disparities Using a Novel Measure, COVID excess mortality percentage: Evidence from Indiana, Wisconsin, and Illinois

COVID-19 mortality rates increase rapidly with age, are higher among men than women, and vary across racial/ethnic groups, but this is also true for other natural causes of death. Prior research on COVID-19 mortality rates and racial/ethnic disparities in those rates has not considered to what extent disparities reflect COVID-19-specific factors, versus preexisting health differences. This study examines both questions. We study the COVID-19-related increase in mortality risk and racial/ethnic disparities in COVID-19 mortality, and how both vary with age, gender, and time period. We use a novel measure validated in prior work, the COVID Excess Mortality Percentage (CEMP), defined as the COVID-19 mortality rate (Covid-MR), divided by the non-COVID natural mortality rate during the same time period (non-Covid NMR), converted to a percentage. The CEMP denominator uses Non-COVID NMR to adjust COVID-19 mortality risk for underlying population health. The CEMP measure generates insights which differ from those using two common measures-the COVID-MR and the all-cause excess mortality rate. By studying both CEMP and COVID-MRMR, we can separate the effects of background health from Covid-specific factors affecting COVID-19 mortality. We study how CEMP and COVID-MR vary by age, gender, race/ethnicity, and time period, using data on all adult decedents from natural causes in Indiana and Wisconsin over April 2020-June 2022 and Illinois over April 2020-December 2021. CEMP levels for racial and ethnic minority groups can be very high relative to White levels, especially for Hispanics in 2020 and the first-half of 2021. For example, during 2020, CEMP for Hispanics aged 18-59 was 68.9% versus 7.2% for non-Hispanic Whites; a ratio of 9.57:1. CEMP disparities are substantial but less extreme for other demographic groups. Disparities were generally lower after age 60 and declined over our sample period. Differences in socio-economic status and education explain only a small part of these disparities.

Causes and costs of global COVID-19 vaccine inequity

Despite the rapid development of safe and effective COVID-19 vaccines and the widely recognized health and economic benefits of vaccination, there exist stark differences in vaccination rates across country income groups. While more than 70% of the population is fully vaccinated in high-income countries, vaccination rates in low-income countries are only around 30%. The paper reviews the factors behind global COVID-19 vaccine inequity and the health, social, and economic costs triggered by this inequity. The main contributors to vaccine inequity include vaccine nationalism, intellectual property rights, constraints in manufacturing capacity, poor resilience of healthcare systems, and vaccine hesitancy. Vaccine inequity has high costs, including preventable deaths and cases of illnesses in low-income countries, slow economic recovery, and large learning losses among children. Increasing vaccination rates in low-income countries is in the self-interest of higher-income countries as it may prevent the emergence of new variants and continuous disruptions to global supply chains.

Genomic surveillance reveals dynamic shifts in the connectivity of COVID-19 epidemics

The maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of "local" when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.

Prevalence of SARS-CoV-2 infection and impact of the COVID-19 pandemic in avocado farmworkers from Mexico

Introduction

The COVID-19 pandemic disproportionately affected farmworkers in the United States and Europe, leading to increased morbidity and mortality. However, little is known about the specific impact of the pandemic on agriculture and food production workers in low- and middle-income countries. This study aimed to investigate the prevalence of SARS-CoV-2 infection and assess the mental health and economic consequences of the COVID-19 pandemic among avocado farmworkers in Michoacan, Mexico.

Methods

We conducted a cross-sectional study of adult farmworkers (n = 395) in May 2021. We collected survey data, nasal swabs and saliva samples for SARS-CoV-2 RNA detection, and blood samples for immunoglobulin G (IgG) reactivity measurements.

Results

None of the farmworkers tested positive for SARS-CoV-2 RNA. However, among unvaccinated farmworkers (n = 336, 85%), approximately one-third (33%) showed evidence of past infection (positive for IgG against SARS-CoV-2). Unvaccinated farmworkers who lived with other farmworkers (aRR = 1.55; 95% CI: 1.05, 2.05), had ever lived with someone with COVID-19 (aRR = 1.82; 95% CI: 1.22, 2.43), and who had diabetes (aRR = 2.19; 95% CI: 1.53, 2.85) had a higher risk of testing IgG-positive for SARS-CoV-2 infection. In contrast, unvaccinated farmworkers living in more rural areas (outside of Tingambato or Uruapan) (aRR = 0.71; 95% CI: 0.46, 0.96) or cooking with wood-burning stove (aRR = 0.75; 95% CI: 0.55, 0.96) had a lower risk of IgG-positivity. Moreover, 66% of farmworkers reported a negative impact of the pandemic on their lives, 29% reported experiencing food insecurity and difficulty paying bills, and 10% reported depression or anxiety symptoms.

Conclusion

The COVID-19 pandemic has significantly affected the mental health and financial well-being of avocado farmworkers. Consequently, the implementation of interventions and prevention efforts, such as providing mental health support and food assistance services, is imperative.

Temporal assessment of disparities in California COVID-19 mortality by industry: a population-based retrospective cohort study

PURPOSE

To assess changes in the COVID-19 mortality rate and disparities over variants or waves by industry.

METHODS

We identified COVID-19 deaths that occurred between January 2020 and May 2022 among California workers aged 18-64 years using death certificates, and estimated Californians at risk using the Current Population Survey. The waves in deaths were wave 1: March-June 2020, wave 2: July-November 2020, wave 3/Epsilon and Alpha variants: December 2020-May 2021, wave 4/Delta variant: June 2021-January 2022, and wave 5/Omicron variant: February-May 2022. We used Poisson regression to generate wave-specific mortality rate ratios (MRR) and included an interaction term between industry and wave in different models to assess significance of the change in MRR.

RESULTS

In all waves of the pandemic, healthcare, other services, manufacturing, transportation, and retail trade industries had higher mortality rates than the professional, scientific, and technical industry. The healthcare industry had the highest relative rate earlier in the pandemic, while other services, utilities, and accommodation and food services industries had substantial increases in MRR in later waves.

CONCLUSIONS

Industries that consistently had disproportionate COVID-19 mortality may have benefitted from protections that consider workers' increased exposure and vulnerability to severe outcomes.

Risk factors for clinical stages of COVID-19 amongst employees of the International Committee of the Red Cross (ICRC) worldwide over a period of 12 months

BACKGROUND

Essential workers carry a higher risk of SARS-CoV-2 infection and COVID-19 mortality than individuals working in non-essential activities. Scientific studies on COVID-19 risk factors and clinical courses for humanitarian aid workers (HAW) specifically are lacking. The nature of their work brings HAW in proximity to various populations, therefore potentially exposing them to the virus. The objective of this study is to assess severity degrees of COVID-19 in relation to multiple risk factors in a cohort of HAW.

METHODS

Retrospective cohort study of data collected by the Staff Health Unit of the International Committee of the Red Cross, over 12 months (February 2021 - January 2022). Prevalence of demographic and health risk factors and outcome events were calculated. Factors associated with disease severity were explored in univariable and multivariable logistic regression models. Resulting OR were reported with 95%CI and p-values from Wald Test. P-values < 0.05 were considered significant.

RESULTS

We included 2377 patients. The mean age was 39.5y.o. Two thirds of the patients were males, and 3/4 were national staff. Most cases (3/4) were reported by three regions (Africa, Asia and Middle East). Over 95% of patients were either asymptomatic or presented mild symptoms, 9 died (CFR 0.38%). Fifty-two patients were hospitalised and 7 needed a medical evacuation outside the country of assignment. A minority (14.76%) of patients had at least one risk factor for severe disease; the most recorded one was high blood pressure (4.6%). Over 55% of cases occurred during the predominance of Delta Variant of Concern. All pre-existing risk factors were significantly associated with a moderate or higher severity of the disease (except pregnancy and immunosuppression).

CONCLUSIONS

We found strong epidemiological evidence of associations between comorbidities, old age, and the severity of COVID-19. Increased occupational risks of moderate to severe forms of COVID-19 do not only depend on workplace safety but also on social contacts and context.

COVID-19 and All-Cause Mortality by Race, Ethnicity, and Age Across Five Periods of the Pandemic in the United States

Racial/ethnic and age disparities in COVID-19 and all-cause mortality during 2020 are well documented, but less is known about their evolution over time. We examine changes in age-specific mortality across five pandemic periods in the United States from March 2020 to December 2022 among four racial/ethnic groups (non-Hispanic White, non-Hispanic Black, Hispanic, and non-Hispanic Asian) for ages 35+. We fit Gompertz models to all-cause and COVID-19 death rates by 5-year age groups and construct age-specific racial/ethnic mortality ratios across an Initial peak (Mar-Aug 2020), Winter peak (Nov 2020-Feb 2021), Delta peak (Aug-Oct 2021), Omicron peak (Nov 2021-Feb 2022), and Endemic period (Mar-Dec 2022). We then compare to all-cause patterns observed in 2019. The steep age gradients in COVID-19 mortality in the Initial and Winter peak shifted during the Delta peak, with substantial increases in mortality at working ages, before gradually returning to an older age pattern in the subsequent periods. We find a disproportionate COVID-19 mortality burden on racial and ethnic minority populations early in the pandemic, which led to an increase in all-cause mortality disparities and a temporary elimination of the Hispanic mortality advantage at certain age groups. Mortality disparities narrowed over time, with racial/ethnic all-cause inequalities during the Endemic period generally returning to pre-pandemic levels. Black and Hispanic populations, however, faced a younger age gradient in all-cause mortality in the Endemic period relative to 2019, with younger Hispanic and Black adults in a slightly disadvantageous position and older Black adults in a slightly advantageous position, relative to before the pandemic.

Occupational COVID-19 Exposures and Illnesses among Workers in California-Analysis of a New Occupational COVID-19 Surveillance System

Little is known about occupational SARS-CoV-2 exposures and COVID-19 outcomes. We established a Doctor's First Reports of Occupational Injury or Illness (DFR)-based surveillance system to study cases of work-related COVID-19 exposures and disease. The surveillance data included demographics, occupation, industry, exposure, and illness, details including hospitalization and lost work. We classified workers into 'healthcare', non-healthcare 'public-facing', or 'other' worker groups, and rural-urban commuting areas (RUCAs). We describe worker exposures and outcomes overall by worker group and RUCA. We analyzed 2848 COVID-19 DFRs representing workers in 22 detailed occupation groups and 19 industry groups. Most DFRs were for workers in metropolitan RUCAs (89%) and those in healthcare (42%) and public-facing (24%) worker groups. While DFRs were from 382 unique worksites, 52% were from four hospitals and one prison. Among 1063 DFRs with a suspected exposure, 73% suspected exposure to a patient or client. Few DFRs indicated hospitalization (3.9%); however, the proportion hospitalized was higher among nonmetropolitan (7.4%) and public-facing (6.7%) workers. While 56% of DFRs indicated some lost work time, the proportion was highest among public-facing (80%) workers. Healthcare and prison workers were the majority of reported occupational COVID-19 exposures and illnesses. The risk of COVID-19 hospitalization and lost work may be highest among nonmetropolitan and public-facing workers.

Evaluation of a prototype local ventilation system to mitigate retail store worker exposure to airborne particles

The objective of this study is to evaluate a prototype local ventilation system (LVS) intended to reduce retail store workers' exposure to aerosols. The evaluation was carried out in a large aerosol test chamber where relatively uniform concentrations of polydisperse sodium chloride and glass-sphere particles were generated to test the system with nano- and micro-size particles. In addition, a cough simulator was constructed to mimic aerosols released by mouth breathing and coughing. Particle reduction efficiencies of the LVS were determined in four different experimental conditions using direct reading instruments and inhalable samplers. The particle reduction efficiency (%) depended on the position beneath the LVS, but the percentage was consistently high at the LVS center as follows: (1) > 98% particle reduction relative to background aerosols; (2) > 97% in the manikin's breathing zone relative to background aerosols; (3) > 97% during mouth breathing and coughing simulation; and (4) > 97% with a plexiglass barrier installation. Lower particle reduction (<70%) was observed when the LVS airflow was disturbed by background ventilation airflow. The lowest particle reduction (<20%) was observed when the manikin was closest to the simulator during coughing.

COVID-19 Risk by Workers' Occupation and Industry in the United States, 2020‒2021

Objectives. To assess the risk of COVID-19 by occupation and industry in the United States. Methods. Using the 2020-2021 National Health Interview Survey, we estimated the risk of having had a diagnosis of COVID-19 by workers' industry and occupation, with and without adjustment for confounders. We also examined COVID-19 period prevalence by the number of workers in a household. Results. Relative to workers in other industries and occupations, those in the industry "health care and social assistance" (adjusted prevalence ratio = 1.23; 95% confidence interval = 1.11, 1.37), or in the occupations "health practitioners and technical," "health care support," or "protective services" had elevated risks of COVID-19. However, compared with nonworkers, workers in 12 of 21 industries and 11 of 23 occupations (e.g., manufacturing, food preparation, and sales) were at elevated risk. COVID-19 prevalence rose with each additional worker in a household. Conclusions. Workers in several industries and occupations with public-facing roles and adults in households with multiple workers had elevated risk of COVID-19. Public Health Implications. Stronger workplace protections, paid sick leave, and better health care access might mitigate working families' risks from this and future pandemics. (Am J Public Health. Published online ahead of print April 13, 2023:e1-e10. https://doi.org/10.2105/AJPH.2023.307249).

Characterization of perceived biohazard exposures, personal protective equipment, and training resources among a sample of formal U.S. solid waste workers: A pilot study

In the United States, the majority of waste workers work with solid waste. In solid waste operations, collection, sorting, and disposal can lead to elevated biohazard exposures (e.g., bioaerosols, bloodborne and other pathogens, human and animal excreta). This cross-sectional pilot study aimed to characterize solid waste worker perception of biohazard exposures, as well as worker preparedness and available resources (e.g., access to personal protective equipment, level of training) to address potential biohazard exposures. Three sites were surveyed: (1) a family-owned, small-scale waste disposal facility, (2) a county-level, recycling-only facility, and (3) an industrial-sized, large-scale facility that contains a hauling and landfill division. Survey items characterized occupational biohazards, resources to mitigate and manage those biohazards, and worker perceptions of biohazard exposures. Descriptive statistics were generated. The majority of workers did not report regularly coming into contact with blood, feces, and bodily fluids (79%). As such, less than one-fifth were extremely concerned about potential illness from biological exposures (19%). Yet, most workers surveyed (71%) reported an accidental laceration/cut that would potentially expose workers to biohazards. This study highlights the need for additional research on knowledge of exposure pathways and perceptions of the severity of exposure among this occupational group.

Which Curve Are We Flattening? The Disproportionate Impact of COVID-19 Among Economically Marginalized Communities in Ontario, Canada, Was Unchanged From Wild-Type to Omicron

Person-level surveillance (N = 14 million) and neighborhood-level income data were used to explore magnitude of inequalities in COVID-19 hospitalizations and deaths over 5 waves in Ontario, Canada. Despite attempts at equity-informed policies alongside fluctuating levels of public health measures, the magnitude of inequalities in hospitalizations and deaths remained unchanged across waves.