Social Disadvantage, Politics, and Severe Acute Respiratory Syndrome Coronavirus 2 Trends: A County-level Analysis of United States Data

Association of socio-economic deprivation with COVID-19 incidence and fatality during the first wave of the pandemic in Italy: lessons learned from a local register-based study

BACKGROUND

COVID-19 has been characterised by its global and rapid spread, with high infection, hospitalisation, and mortality rates worldwide. However, the course of the pandemic showed differences in chronology and intensity in different geographical areas and countries, probably due to a multitude of factors. Among these, socio-economic deprivation has been supposed to play a substantial role, although available evidence is not fully in agreement. Our study aimed to assess incidence and fatality rates of COVID-19 across the levels of socio-economic deprivation during the first epidemic wave (March-May 2020) in the Italian Province of Foggia, Apulia Region.

METHODS

Based on the data of the regional active surveillance platform, we performed a retrospective epidemiological study among all COVID-19 confirmed cases that occurred in the Apulian District of Foggia, Italy, from March 1st to May 5th, 2020. Geocoded addresses were linked to the individual Census Tract (CT) of residence. Effects of socio-economic condition were calculated by means of the Socio-Economic and Health-related Deprivation Index (SEHDI) on COVID-19 incidence and fatality.

RESULTS

Of the 1054 confirmed COVID-19 cases, 537 (50.9%) were men, 682 (64.7%) were 0-64 years old, and 338 (32.1%) had pre-existing comorbidities. COVID-19 incidence was higher in the less deprived areas (p < 0.05), independently on age. The level of socio-economic deprivation did not show a significant impact on the vital status, while a higher fatality was observed in male cases (p < 0.001), cases > 65 years (p < 0.001), cases having a connection with a nursing home (p < 0.05) or having at least 1 comorbidity (p < 0.001). On the other hand, a significant protection for healthcare workers was apparent (p < 0.001).

CONCLUSIONS

Our findings show that deprivation alone does not affect COVID-19 incidence and fatality burden, suggesting that the burden of disease is driven by a complexity of factors not yet fully understood. Better knowledge is needed to identify subgroups at higher risk and implement effective preventive strategies.

SEIR Model to address the impact of face masks amid COVID-19 pandemic

Early in the pandemic of coronavirus disease 2019 (COVID-19), face masks were used extensively by the general public in several Asian countries. The lower transmission rate of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Asian countries compared with Western countries suggested that the wider community use of face masks has the potential to decrease transmission of SARS-CoV-2. A risk assessment model named Susceptible, Exposed, Infectious, Recovered (SEIR) model is used to quantitatively evaluate the potential impact of community face masks on SARS-CoV-2 reproduction number (R₀ ) and peak number of infectious persons. For a simulated population of one million, the model showed a reduction in R₀ of 49% and 50% when 60% and 80% of the population wore masks, respectively. Moreover, we present a modified model that considers the effect of mask-wearing after community vaccination. Interestingly mask-wearing still provided a considerable benefit in lowering the number of infectious individuals. The results of this research are expected to help public health officials in making prompt decisions involving resource allocation and crafting legislation.

[Social inequalities in the regional spread of SARS-CoV-2 infections]

Hintergrund und Ziel

Ob sozioökonomische Faktoren die Ausbreitung von SARS-CoV‑2 beeinflussen, ist nicht ausreichend beantwortet, da frühere Studien in der Regel kumulative Inzidenzen betrachtet und die zeitliche Entwicklung der Ausbreitung außer Acht gelassen haben. Dieser Beitrag konzentriert sich daher auf die Entwicklung von regionalen Neuinfektionen in Zusammenhang mit sozioökonomischen Faktoren. Ausgehend vom internationalen Forschungsstand präsentieren wir eigene Analysen von Meldedaten aus Deutschland.

Methoden

Diese Studie untersucht regionale Daten gemeldeter COVID-19-Fälle für die 401 Landkreise und kreisfreien Städte (Kreisebene) in Deutschland und vergleicht den zeitlichen Verlauf entlang sozioökonomischer Merkmale der Kreise. Betrachtet werden altersstandardisierte wöchentliche Inzidenzen für den Zeitraum 03.02.2020–28.03.2021. Sozial- und Wirtschaftsindikatoren auf Kreisebene stammen aus der INKAR(Indikatoren und Karten zur Raum- und Stadtentwicklung)-Datenbank (z. B. Einkommen, Beschäftigtenquote, Wohnfläche).

Ergebnisse

Während in der ersten und zu Beginn der zweiten Welle der Pandemie Kreise mit höherem mittleren Haushaltseinkommen höhere Inzidenzen hatten, stiegen sie in Kreisen mit niedrigem Einkommen ab Dezember 2020 deutlich an. Kreise mit einem hohen Anteil an Beschäftigten allgemein und speziell solchen im Produktionssektor hatten gerade in der zweiten und dritten Welle hohe Inzidenzen. Kreise mit einer geringen Wohnfläche je Einwohner hatten ab November 2020 ausgeprägt höhere Inzidenzen.

Schlussfolgerung

Der regionale Verlauf der Pandemie unterscheidet sich nach Sozial- und Wirtschaftsindikatoren. Eine differenzierte Betrachtung dieser Unterschiede könnte Hinweise auf zielgruppenspezifische Schutz- und Teststrategien geben und helfen, soziale Faktoren zu identifizieren, die Infektionen begünstigen.

Zusatzmaterial online

Zusätzliche Informationen sind in der Online-Version dieses Artikels (10.1007/s00103-021-03387-w) enthalten.

Social Determinants of Adherence to COVID-19 Risk Mitigation Measures Among Adults With Cardiovascular Disease

Supplemental Digital Content is available in the text.

Social determinants of health (SDOH) may limit the practice of coronavirus disease 2019 (COVID-19) risk mitigation guidelines with health implications for individuals with underlying cardiovascular disease (CVD). Population-based evidence of the association between SDOH and practicing such mitigation strategies in adults with CVD is lacking. We used the National Opinion Research Center’s COVID-19 Household Impact Survey conducted between April and June 2020 to evaluate sociodemographic disparities in adherence to COVID-19 risk mitigation measures in a sample of respondents with underlying CVD representing 18 geographic areas of the United States.

Prevalence of RT-qPCR-detected SARS-CoV-2 infection at schools: First results from the Austrian School-SARS-CoV-2 prospective cohort study

BACKGROUND

The role of schools in the SARS-CoV-2 pandemic is much debated. We aimed to quantify reliably the prevalence of SARS-CoV-2 infections at schools detected with reverse-transcription quantitative polymerase-chain-reaction (RT-qPCR).

METHODS

This nationwide prospective cohort study monitors a representative sample of pupils (grade 1-8) and teachers at Austrian schools throughout the school year 2020/2021. We repeatedly test participants for SARS-CoV-2 infection using a gargling solution and RT-qPCR. We herein report on the first two rounds of examinations. We used mixed-effects logistic regression to estimate odds ratios and robust 95% confidence intervals (95% CI).

FINDINGS

We analysed data on 10,734 participants from 245 schools (9465 pupils, 1269 teachers). Prevalence of SARS-CoV-2 infection increased from 0·39% at round 1 (95% CI 028-0·55%, 28 September-22 October 2020) to 1·39% at round 2 (95% CI 1·04-1·85%, 10-16 November). Odds ratios for SARS-CoV-2 infection were 2·26 (95% CI 1·25-4·12, P = 0·007) in regions with >500 vs. ≤500 inhabitants/km², 1·67 (95% CI 1·42-1·97, P<0·001) per two-fold higher regional 7-day community incidence, and 2·78 (95% CI 1·73-4·48, P<0·001) in pupils at schools with high/very high vs. low/moderate social deprivation. Associations of regional community incidence and social deprivation persisted in a multivariable adjusted model. Prevalence did not differ by average number of pupils per class nor between age groups, sexes, pupils vs. teachers, or primary (grade 1-4) vs. secondary schools (grade 5-8).

INTERPRETATION

This monitoring study in Austrian schools revealed SARS-CoV-2 infection in 0·39%-1·39% of participants and identified associations of regional community incidence and social deprivation with higher prevalence.

FUNDING

BMBWF Austria.

High-throughput wastewater analysis for substance use assessment in central New York during the COVID-19 pandemic

Wastewater entering sewer networks represents a unique source of pooled epidemiological information. In this study, we coupled online solid-phase extraction with liquid chromatography-high resolution mass spectrometry to achieve high-throughput analysis of health and lifestyle-related substances in untreated municipal wastewater during the coronavirus disease 2019 (COVID-19) pandemic. Twenty-six substances were identified and quantified in influent samples collected from six wastewater treatment plants during the COVID-19 pandemic in central New York. Over a 12 week sampling period, the mean summed consumption rate of six major substance groups (i.e., antidepressants, antiepileptics, antihistamines, antihypertensives, synthetic opioids, and central nervous system stimulants) correlated with disparities in household income, marital status, and age of the contributing populations as well as the detection frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater and the COVID-19 test positivity in the studied sewersheds. Nontarget screening revealed the covariation of piperine, a nontarget substance, with SARS-CoV-2 RNA in wastewater collected from one of the sewersheds. Overall, this proof-of-the-concept study demonstrated the utility of high-throughput wastewater analysis for assessing the population-level substance use patterns during a public health crisis such as COVID-19.

The Use of Penalized Regression Analysis to Identify County-Level Demographic and Socioeconomic Variables Predictive of Increased COVID-19 Cumulative Case Rates in the State of Georgia

Systemic inequity concerning the social determinants of health has been known to affect morbidity and mortality for decades. Significant attention has focused on the individual-level demographic and co-morbid factors associated with rates and mortality of COVID-19. However, less attention has been given to the county-level social determinants of health that are the main drivers of health inequities. To identify the degree to which social determinants of health predict COVID-19 cumulative case rates at the county-level in Georgia, we performed a sequential, cross-sectional ecologic analysis using a diverse set of socioeconomic and demographic variables. Lasso regression was used to identify variables from collinear groups. Twelve variables correlated to cumulative case rates (for cases reported by 1 August 2020) with an adjusted r squared of 0.4525. As time progressed in the pandemic, correlation of demographic and socioeconomic factors to cumulative case rates increased, as did number of variables selected. Findings indicate the social determinants of health and demographic factors continue to predict case rates of COVID-19 at the county-level as the pandemic evolves. This research contributes to the growing body of evidence that health disparities continue to widen, disproportionality affecting vulnerable populations.