Excess mortality among essential workers in England and Wales during the COVID-19 pandemic

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.

Excess Mortality Calculations to Assess the Impact of the COVID-19 Pandemic: Concepts and Methodological Issues

We discuss some intriguing methodological aspects of excess mortality analyses, which have been widely used to describe the impact of the COVID-19 pandemic. We describe the main ways of presenting excess mortality: as a mortality rate (incidence rate) or as a percentage increase (relative risk or rate ratio). We discuss what should be regarded as the null value of excess mortality (i.e., when countries or regions can be judged as having fared equally well) and when age and sex standardization, adjustment for other determinants of the spread of a pandemic, or both is necessary. We discuss the level of detail by time and place and person that may be necessary. We note that an excess mortality comparison is essentially a difference-in-differences analysis. We conclude that, although one cannot rule out using excess mortality analyses for causal effect estimates, such analyses will remain most fruitful for generating hypotheses about both the efficiency of measures to curtail the pandemic and factors that cannot be influenced. Nevertheless, a judicious use of arguments and counterarguments can then lead to identifying best practices for various situations. (Am J Public Health. 2024;114(6):593-598. https://doi.org/10.2105/AJPH.2024.307572).

Risk factors for SARS-CoV-2 infection at a UK electricity-generating company: a test-negative design case-control study

OBJECTIVES

Identify workplace risk factors for SARS-CoV-2 infection, using data collected by a UK electricity-generating company.

METHODS

Using a test-negative design case-control study, we estimated the OR of infection by job category, site, test reason, sex, vaccination status, vulnerability, site outage and site COVID-19 weekly risk rating, adjusting for age, test date and test type.

RESULTS

From an original 80 077 COVID-19 tests, there were 70 646 included in the final analysis. Most exclusions were due to being visitor tests (5030) or tests after an individual first tested positive (2968).Women were less likely to test positive than men (OR=0.71; 95% CI 0.58 to 0.86). Test reason was strongly associated with positivity and although not a cause of infection itself, due to differing test regimes by area, it was a strong confounder for other variables. Compared with routine tests, tests due to symptoms were highest risk (94.99; 78.29 to 115.24), followed by close contact (16.73; 13.80 to 20.29) and broader-defined work contact 2.66 (1.99 to 3.56). After adjustment, we found little difference in risk by job category, but some differences by site with three sites showing substantially lower risks, and one site showing higher risks in the final model.

CONCLUSIONS

In general, infection risk was not associated with job category. Vulnerable individuals were at slightly lower risk, tests during outages were higher risk, vaccination showed no evidence of an effect on testing positive, and site COVID-19 risk rating did not show an ordered trend in positivity rates.

Risk perception of healthcare workers in the first wave of the COVID-19 pandemic in Brazil

Objectives

To validate the items of the Emotional Impact Questionnaire coronavirus disease-2019 (COVID-19) related to risk perception, estimating its degree, among healthcare workers in the first wave of COVID-19 pandemic, identifying possible associated factors.Methods: cross-sectional study in 1872 healthcare workers of Brazil. The population was characterized by sociodemographic and occupational information, knowledge about COVID-19, quality of information received, risk perception and preventive measures about the disease, and sense of coherence.

Results

Being divorced, having a chronic disease, spending more than 1 h per day getting informed about COVID-19, and always or almost always wearing a mask regardless of symptoms, as well as self-perception of health were associated with high-risk perception. An inverse association was found between risk perception, sense of coherence and not knowing if one has had occasional contact with confirmed COVID-19 cases.

Conclusion

Risk perception is influenced by emotions, experiences, and knowledge. Sense of coherence and resilience have a role in reducing risk perception. Understanding risk perception is crucial for developing effective strategies to mitigate the impact of the COVID-19 pandemic and other similar scenarios.

The impact of COVID-19 on life expectancy across socioeconomic groups in Denmark

BACKGROUND

Denmark was one of the few countries that experienced an increase in life expectancy in 2020, and one of the few to see a decrease in 2021. Because COVID-19 mortality is associated with socioeconomic status (SES), we hypothesize that certain subgroups of the Danish population experienced changes in life expectancy in 2020 and 2021 that differed from the country overall. We aim to quantify life expectancy in Denmark in 2020 and 2021 by SES and compare this to recent trends in life expectancy (2014-2019).

METHODS

We used Danish registry data from 2014 to 2021 for all individuals aged 30+. We classified the study population into SES groups using income quartiles and calculated life expectancy at age 30 by year, sex, and SES, and the differences in life expectancy from 2019 to 2020 and 2020 to 2021. We compared these changes to the average 1-year changes from 2014 to 2019 with 95% confidence intervals. Lastly, we decomposed these changes by age and cause of death distinguishing seven causes, including COVID-19, and a residual category.

RESULTS

We observed a mortality gradient in life expectancy changes across SES groups in both pandemic years. Among women, those of higher SES experienced a larger increase in life expectancy in 2020 and a smaller decrease in 2021 compared to those of lower SES. Among men, those of higher SES experienced an increase in life expectancy in both 2020 and 2021, while those of lower SES experienced a decrease in 2021. The impact of COVID-19 mortality on changes in life expectancy in 2020 was counterbalanced by improvements in non-COVID-19 mortality, especially driven by cancer and cardiovascular mortality. However, in 2021, non-COVID-19 mortality contributed negatively even for causes as cardiovascular mortality that has generally a positive impact on life expectancy changes, resulting in declines for most SES groups.

CONCLUSIONS

COVID-19 mortality disproportionally affected those of lower SES and exacerbated existing social inequalities in Denmark. We conclude that in health emergencies, particular attention should be paid to those who are least socially advantaged to avoid widening the already existing mortality gap with those of higher SES. This research contributes to the discussion on social inequalities in mortality in high-income countries.

Evaluating COVID-19 Risk to Essential Workers by Occupational Group: A Case Study in Massachusetts

Occupational exposure to SARS-CoV-2 varies by profession, but "essential workers" are often considered in aggregate in COVID-19 models. This aggregation complicates efforts to understand risks to specific types of workers or industries and target interventions, specifically towards non-healthcare workers. We used census tract-resolution American Community Survey data to develop novel essential worker categories among the occupations designated as COVID-19 Essential Services in Massachusetts. Census tract-resolution COVID-19 cases and deaths were provided by the Massachusetts Department of Public Health. We evaluated the association between essential worker categories and cases and deaths over two phases of the pandemic from March 2020 to February 2021 using adjusted mixed-effects negative binomial regression, controlling for other sociodemographic risk factors. We observed elevated COVID-19 case incidence in census tracts in the highest tertile of workers in construction/transportation/buildings maintenance (Phase 1: IRR 1.32 [95% CI 1.22, 1.42]; Phase 2: IRR: 1.19 [1.13, 1.25]), production (Phase 1: IRR: 1.23 [1.15, 1.33]; Phase 2: 1.18 [1.12, 1.24]), and public-facing sales and services occupations (Phase 1: IRR: 1.14 [1.07, 1.21]; Phase 2: IRR: 1.10 [1.06, 1.15]). We found reduced case incidence associated with greater percentage of essential workers able to work from home (Phase 1: IRR: 0.85 [0.78, 0.94]; Phase 2: IRR: 0.83 [0.77, 0.88]). Similar trends exist in the associations between essential worker categories and deaths, though attenuated. Estimating industry-specific risk for essential workers is important in targeting interventions for COVID-19 and other diseases and our categories provide a reproducible and straightforward way to support such efforts.

Parasitic Resilience: The Next Phase of Public Health Preparedness Must Address Power Imbalances Between Communities

Community resilience, a system's ability to maintain its essential functions despite disturbance, is a cornerstone of public health preparedness. However, as currently practiced, community resilience generally focuses on defined neighborhood characteristics to describe factors such as vulnerability or social capital. This ignores the way that residents of some neighborhoods (as "essential workers") were required during the COVID-19 pandemic to sacrifice their wellbeing for the sake of others staying at home in more affluent neighborhoods. Using the global care chain theory, we analyze the way that the resilience of affluent neighborhoods depends on siphoning off the labor of other, less affluent neighborhoods, creating what we call the parasitic nature of resilience. We argue that understanding this neighborhood interdependence-and accounting for its parasitic nature-should be prioritized by public health authorities to prevent unintentional harm in future pandemics. Otherwise, any public health emergency response that relies on this labor (as did the COVID-19 pandemic response) depends on exploitative practices that produce the very disparities the response is trying to address. We explore the theoretical grounding and practical effects of this idea to provide the preparedness enterprise with an initial set of theoretical tools to move from a model of community resilience to one of community renewal. The community renewal model is based on an underlying ethics of care, in which systems are redesigned to become more prosocial during a public health response. We believe this model can more successfully address the tragic inequities in labor and health outcomes that we see during public health emergencies.

Occupational differences in the prevalence and severity of long-COVID: analysis of the Coronavirus (COVID-19) Infection Survey

OBJECTIVES

To establish whether prevalence and severity of long-COVID symptoms vary by industry and occupation.

METHODS

We used Office for National Statistics COVID-19 Infection Survey (CIS) data (February 2021-April 2022) of working-age participants (16-65 years). Exposures were industry, occupation and major Standard Occupational Classification (SOC) group. Outcomes were self-reported: (1) long-COVID symptoms and (2) reduced function due to long-COVID. Binary (outcome 1) and ordered (outcome 2) logistic regression were used to estimate odds ratios (OR)and prevalence (marginal means).

RESULTS

Public facing industries, including teaching and education, social care, healthcare, civil service, retail and transport industries and occupations, had the highest likelihood of long-COVID. By major SOC group, those in caring, leisure and other services (OR 1.44, 95% CIs 1.38 to 1.52) had substantially elevated odds than average. For almost all exposures, the pattern of ORs for long-COVID symptoms followed SARS-CoV-2 infections, except for professional occupations (eg, some healthcare, education, scientific occupations) (infection: OR<1 ; long-COVID: OR>1). The probability of reporting long-COVID for industry ranged from 7.7% (financial services) to 11.6% (teaching and education); whereas the prevalence of reduced function by 'a lot' ranged from 17.1% (arts, entertainment and recreation) to 22%-23% (teaching and education and armed forces) and to 27% (not working).

CONCLUSIONS

The risk and prevalence of long-COVID differs across industries and occupations. Generally, it appears that likelihood of developing long-COVID symptoms follows likelihood of SARS-CoV-2 infection, except for professional occupations. These findings highlight sectors and occupations where further research is needed to understand the occupational factors resulting in long-COVID.

Excess mortality among essential workers in England and Wales during the COVID-19 pandemic: an updated analysis

BACKGROUND

Excess mortality from all causes combined during the COVID-19 pandemic in England and Wales in 2020 was predominantly higher for essential workers. In 2021, the vaccination programme had begun, new SARS-CoV-2 variants were identified and different policy approaches were used. We have updated our previous analyses of excess mortality in England and Wales to include trends in excess mortality by occupation for 2021.

METHODS

We estimated excess mortality for working age adults living in England and Wales by occupational group for each month in 2021 and for the year as a whole.

RESULTS

During 2021, excess mortality remained higher for most groups of essential workers than for non-essential workers. It peaked in January 2021 when all-cause mortality was 44.6% higher than expected for all occupational groups combined. Excess mortality was highest for adults working in social care (86.9% higher than expected).

CONCLUSION

Previously, we reported excess mortality in 2020, with this paper providing an update to include 2021 data. Excess mortality was predominantly higher for essential workers during 2021. However, unlike the first year of the pandemic, when healthcare workers experienced the highest mortality, the highest excess mortality during 2021 was experienced by social care workers.

Changes in COVID-19-related mortality across key demographic and clinical subgroups in England from 2020 to 2022: a retrospective cohort study using the OpenSAFELY platform

BACKGROUND

COVID-19 has been shown to differently affect various demographic and clinical population subgroups. We aimed to describe trends in absolute and relative COVID-19-related mortality risks across clinical and demographic population subgroups during successive SARS-CoV-2 pandemic waves.

METHODS

We did a retrospective cohort study in England using the OpenSAFELY platform with the approval of National Health Service England, covering the first five SARS-CoV-2 pandemic waves (wave one [wild-type] from March 23 to May 30, 2020; wave two [alpha (B.1.1.7)] from Sept 7, 2020, to April 24, 2021; wave three [delta (B.1.617.2)] from May 28 to Dec 14, 2021; wave four [omicron (B.1.1.529)] from Dec 15, 2021, to April 29, 2022; and wave five [omicron] from June 24 to Aug 3, 2022). In each wave, we included people aged 18-110 years who were registered with a general practice on the first day of the wave and who had at least 3 months of continuous general practice registration up to this date. We estimated crude and sex-standardised and age-standardised wave-specific COVID-19-related death rates and relative risks of COVID-19-related death in population subgroups.

FINDINGS

18 895 870 adults were included in wave one, 19 014 720 in wave two, 18 932 050 in wave three, 19 097 970 in wave four, and 19 226 475 in wave five. Crude COVID-19-related death rates per 1000 person-years decreased from 4·48 deaths (95% CI 4·41-4·55) in wave one to 2·69 (2·66-2·72) in wave two, 0·64 (0·63-0·66) in wave three, 1·01 (0·99-1·03) in wave four, and 0·67 (0·64-0·71) in wave five. In wave one, the standardised COVID-19-related death rates were highest in people aged 80 years or older, people with chronic kidney disease stage 5 or 4, people receiving dialysis, people with dementia or learning disability, and people who had received a kidney transplant (ranging from 19·85 deaths per 1000 person-years to 44·41 deaths per 1000 person-years, compared with from 0·05 deaths per 1000 person-years to 15·93 deaths per 1000 person-years in other subgroups). In wave two compared with wave one, in a largely unvaccinated population, the decrease in COVID-19-related mortality was evenly distributed across population subgroups. In wave three compared with wave one, larger decreases in COVID-19-related death rates were seen in groups prioritised for primary SARS-CoV-2 vaccination, including people aged 80 years or older and people with neurological disease, learning disability, or severe mental illness (90-91% decrease). Conversely, smaller decreases in COVID-19-related death rates were observed in younger age groups, people who had received organ transplants, and people with chronic kidney disease, haematological malignancies, or immunosuppressive conditions (0-25% decrease). In wave four compared with wave one, the decrease in COVID-19-related death rates was smaller in groups with lower vaccination coverage (including younger age groups) and conditions associated with impaired vaccine response, including people who had received organ transplants and people with immunosuppressive conditions (26-61% decrease).

INTERPRETATION

There was a substantial decrease in absolute COVID-19-related death rates over time in the overall population, but demographic and clinical relative risk profiles persisted and worsened for people with lower vaccination coverage or impaired immune response. Our findings provide an evidence base to inform UK public health policy for protecting these vulnerable population subgroups.

FUNDING

UK Research and Innovation, Wellcome Trust, UK Medical Research Council, National Institute for Health and Care Research, and Health Data Research UK.

International recommendations for plasma Epstein-Barr virus DNA measurement in nasopharyngeal carcinoma in resource-constrained settings: lessons from the COVID-19 pandemic

The effects of the COVID-19 pandemic continue to constrain health-care staff and resources worldwide, despite the availability of effective vaccines. Aerosol-generating procedures such as endoscopy, a common investigation tool for nasopharyngeal carcinoma, are recognised as a likely cause of SARS-CoV-2 spread in hospitals. Plasma Epstein-Barr virus (EBV) DNA is considered the most accurate biomarker for the routine management of nasopharyngeal carcinoma. A consensus statement on whether plasma EBV DNA can minimise the need for or replace aerosol-generating procedures, imaging methods, and face-to-face consultations in managing nasopharyngeal carcinoma is urgently needed amid the current pandemic and potentially for future highly contagious airborne diseases or natural disasters. We completed a modified Delphi consensus process of three rounds with 33 international experts in otorhinolaryngology or head and neck surgery, radiation oncology, medical oncology, and clinical oncology with vast experience in managing nasopharyngeal carcinoma, representing 51 international professional societies and national clinical trial groups. These consensus recommendations aim to enhance consistency in clinical practice, reduce ambiguity in delivering care, and offer advice for clinicians worldwide who work in endemic and non-endemic regions of nasopharyngeal carcinoma, in the context of COVID-19 and other airborne pandemics, and in future unexpected settings of severe resource constraints and insufficiency of personal protective equipment.

Occupational differences in SARS-CoV-2 infection: analysis of the UK ONS COVID-19 infection survey

BACKGROUND

Concern remains about how occupational SARS-CoV-2 risk has evolved during the COVID-19 pandemic. We aimed to ascertain occupations with the greatest risk of SARS-CoV-2 infection and explore how relative differences varied over the pandemic.

METHODS

Analysis of cohort data from the UK Office of National Statistics COVID-19 Infection Survey from April 2020 to November 2021. This survey is designed to be representative of the UK population and uses regular PCR testing. Cox and multilevel logistic regression were used to compare SARS-CoV-2 infection between occupational/sector groups, overall and by four time periods with interactions, adjusted for age, sex, ethnicity, deprivation, region, household size, urban/rural neighbourhood and current health conditions.

RESULTS

Based on 3 910 311 observations (visits) from 312 304 working age adults, elevated risks of infection can be seen overall for social care (HR 1.14; 95% CI 1.04 to 1.24), education (HR 1.31; 95% CI 1.23 to 1.39), bus and coach drivers (1.43; 95% CI 1.03 to 1.97) and police and protective services (HR 1.45; 95% CI 1.29 to 1.62) when compared with non-essential workers. By time period, relative differences were more pronounced early in the pandemic. For healthcare elevated odds in the early waves switched to a reduction in the later stages. Education saw raises after the initial lockdown and this has persisted. Adjustment for covariates made very little difference to effect estimates.

CONCLUSIONS

Elevated risks among healthcare workers have diminished over time but education workers have had persistently higher risks. Long-term mitigation measures in certain workplaces may be warranted.