The Impact of Keeping Indoor Dining Closed on COVID-19 Rates Among Large US Cities: A Quasi-Experimental Design

Invited Commentary: Some Social Epidemiologic Lessons From the COVID-19 Pandemic

In their recent article, Dimitris et al. (Am J Epidemiol. 2022;191(6):980-986) presented a series of challenges modern epidemiology has faced during the coronavirus disease 2019 (COVID-19) pandemic, including challenges around the scientific progress, epidemiologic methods, interventions, equity, team science, and training needed to address these issues. Here, 2 social epidemiologists who have been working on COVID-19 inequities reflect on further lessons with an added year of perspective. We focus on 2 key challenges: 1) dominant biomedical individualistic narratives around the production of population health, and 2) the role of profit in policy-making. We articulate a need to consider social epidemiologic approaches, including acknowledging the importance of considering how societal systems lead to health inequities. To address these challenges, future (and current) epidemiologists should be trained in theories of population health distribution and political structures of governance. Last, we close with the need for better investment in public health infrastructure as a crucial step toward achieving population health equity.

Dining-Out Behavior as a Proxy for the Superspreading Potential of SARS-CoV-2 Infections: Modeling Analysis

BACKGROUND

While many studies evaluated the reliability of digital mobility metrics as a proxy of SARS-CoV-2 transmission potential, none examined the relationship between dining-out behavior and the superspreading potential of COVID-19.

OBJECTIVE

We employed the mobility proxy of dining out in eateries to examine this association in Hong Kong with COVID-19 outbreaks highly characterized by superspreading events.

METHODS

We retrieved the illness onset date and contact-tracing history of all laboratory-confirmed cases of COVID-19 from February 16, 2020, to April 30, 2021. We estimated the time-varying reproduction number (Rt) and dispersion parameter (k), a measure of superspreading potential, and related them to the mobility proxy of dining out in eateries. We compared the relative contribution to the superspreading potential with other common proxies derived by Google LLC and Apple Inc.

RESULTS

A total of 6391 clusters involving 8375 cases were used in the estimation. A high correlation between dining-out mobility and superspreading potential was observed. Compared to other mobility proxies derived by Google and Apple, the mobility of dining-out behavior explained the highest variability of k (ΔR-sq=9.7%, 95% credible interval: 5.7% to 13.2%) and Rt (ΔR-sq=15.7%, 95% credible interval: 13.6% to 17.7%).

CONCLUSIONS

We demonstrated that there was a strong link between dining-out behaviors and the superspreading potential of COVID-19. The methodological innovation suggests a further development using digital mobility proxies of dining-out patterns to generate early warnings of superspreading events.

Concentric regulatory zones failed to halt surging COVID-19: Brooklyn 2020

Methods

We relied on reports of confirmed case incidence and test positivity, along with data on the movements of devices with location-tracking software, to evaluate a novel scheme of three concentric regulatory zones introduced by then New York Governor Cuomo to address an outbreak of COVID-19 in South Brooklyn in the fall of 2020. The regulatory scheme imposed differential controls on access to eating places, schools, houses of worship, large gatherings and other businesses within the three zones, but without restrictions on mobility.

Results

Within the central red zone, COVID-19 incidence temporarily declined from 131.2 per 100,000 population during the week ending October 3 to 62.5 per 100,000 by the week ending October 31, but then rebounded to 153.6 per 100,000 by the week ending November 28. Within the intermediate orange and peripheral yellow zones combined, incidence steadily rose from 28.8 per 100,000 during the week ending October 3 to 109.9 per 100,000 by the week ending November 28. Data on device visits to pairs of eating establishments straddling the red-orange boundary confirmed compliance with access controls. More general analysis of device movements showed stable patterns of movement between and beyond zones unaffected by the Governor's orders. A geospatial regression model of COVID-19 incidence in relation to device movements across zip code tabulation areas identified a cluster of five high-movement ZCTAs with estimated reproduction number 1.91 (95% confidence interval, 1.27-2.55).

Discussion

In the highly populous area of South Brooklyn, controls on access alone, without restrictions on movement, were inadequate to halt an advancing COVID-19 outbreak.

Considering multiple governance levels in epidemiologic analysis of public policies

Epidemiology is increasingly asking questions about the use of policies to address structural inequities and intervene on health disparities and public health challenges. However, there has been limited explicit consideration of governance structures in the design of epidemiologic policy analysis. To advance empirical and theoretical inquiry in this space, we propose a model of governance analysis in which public health researchers consider at what level 1) decision-making authority for policy sits, 2) policy is implemented, 3) and accountability for policy effects appear. We follow with examples of how these considerations might improve the evaluation of the policy drivers of population health. Consideration and integration of multiple levels of governance, as well as interactions between levels, can help epidemiologists design studies including new opportunities for quasi-experimental designs and stronger counterfactuals, better quantify the policy drivers of inequities, and aid research evidence and policy development work in targeting multiple levels of governance, ultimately supporting evidence-based policy making.

General practitioner visits after SARS-CoV-2 omicron compared with the delta variant in children in Norway: a prospective nationwide registry study

BACKGROUND

SARS-CoV-2 infection in children is followed by an immediate increase in primary care utilisation. The difference in utilisation following infection with the delta and omicron virus variants is unknown.

OBJECTIVES

To study whether general practitioner (GP) contacts were different in children infected with the omicron versus delta variant for up to 4 weeks after the week testing positive.

SETTING

Primary care.

PARTICIPANTS

All residents in Norway aged 0-10. After excluding 47 683 children with a positive test where the virus variant was not identified as delta or omicron and 474 children who were vaccinated, the primary study population consisted of 613 448 children.

MAIN OUTCOME MEASURES

GP visits.

METHODS

We estimated the difference in the weekly share visiting the GP after being infected with the delta or omicron variant to those in the study population who were either not tested or who tested negative using an event study design, controlling for calendar week of consultation, municipality fixed effects and sociodemographic factors in multivariate logistic regressions.

RESULTS

Compared with preinfection, increased GP utilisation was found for children 1 and 2 weeks after testing positive for the omicron variant, with an OR of 6.7 (SE: 0.69) in the first week and 5.5 (0.72) in the second week. This increase was more pronounced for children with the delta variant, with an OR of 8.2 (0.52) in the first week and 7.1 (0.93) in the second week. After 2 weeks, the GP utilisation returned to preinfection levels.

CONCLUSION

The omicron variant appears to have resulted in less primary healthcare interactions per infected child compared with the delta variant.

Racial and ethnic inequities in occupational exposure across and between US cities

Research suggests that racial/ethnic disparities in COVID-19 in the US are largely driven by higher rates of exposure to SARS-CoV-2 among Hispanic/Latino and Black populations. Occupational exposures play a large role in structuring risk of exposure, and essential workers are at elevated risk of COVID-19 infection. At a national-level, workers categorized as "essential" and "high-risk" are disproportionately Hispanic/Latino, but we lack analysis examining local-level racial/ethnic disparities in potential occupational exposures. Using the 2015-2019 5-year American Community Survey, we estimated disparities between the proportion of US Born Hispanic/Latino, foreign-born Hispanic/Latino, and non-Hispanic white (NHW) essential or high-risk workers in 27 of the largest metropolitan areas in the country. We found that, on average, 66.3%, 69.9%, and 62.6% of US-born Hispanics, foreign-born Hispanics, and NHW, respectively, are essential workers, while 50.7%, 49.9%, 49.5% are high exposure risk workers, respectively. The median absolute difference in proportions of US born Hispanic/Latino and NHW essential workers was 4.2%, and between foreign-born Hispanic/Latino and NHW essential workers was 7.5%, but these disparities varied widely by city. High likelihood of occupational transmission may help explain disparities in COVID-19 infection and mortality for Hispanic/Latino populations, especially foreign-born, and may also help explain heterogeneity in the magnitude of these disparities, with relevance for other acute infectious respiratory illnesses spread in the workplace.