Development of a community-based COVID-19 intervention in rural Ghana: a document analysis.

BACKGROUND: The COVID-19 pandemic has caused the loss of millions of lives and economic breakdowns in many countries across the globe. Despite the limited availability of vaccines and the challenges of poor health infrastructure, few interventions have been developed and implemented for those who live in rural areas, particularly in sub-Saharan Africa. In response, Cocoa360, a global health nonprofit in rural Ghana designed an intervention called Cocoa360's COVID-19 Preparedness and Outbreak Prevention Plan (CoCoPOPP). This paper aimed to examine the extent to which CoCoPOPP's design aligned with the Promoting Action on Research Implementation in Health Services (PARIHS) framework. METHODS: We reviewed documents influencing CoCoPOPP's design between March and June 2021. A total of 11 documents were identified for analysis. Using the Promoting Action on Research Implementation in Health Services (PARIHS) framework as a guide, thematic analysis was done to analyze the extracted data. RESULTS: Overall, CoCoPOPP's design aligned with the evidence, context, and facilitation domains of the PARIHS framework. It positioned CoCoPOPP as an intervention that considered the unique context of a rural Ghanaian setting. It was guided by robust and high-quality published and non-published evidence and engaged external and internal stakeholders during its implementation. CoCoPOPP's context-dependent nature positions it for potential replication in sub-Saharan Africa's rural communities with similar farming contexts. Specific areas that were less well and/or not addressed were the unintended negative consequences of community engagement, the absence of primary data in the guiding evidence, and the lack of a facilitation continuum coupled with the role of power during the facilitation process. CONCLUSION: CoCoPOPP, Cocoa360's response to the COVID-19 pandemic in rural Ghana, is an evidence-driven, context-dependent public health intervention that has been designed to reduce COVID-19 infections and prevent potential deaths. This study underscores the importance of considering the unique community and cultural contexts, employing evidence, and engaging local and external actors as facilitators when designing interventions to respond to global health pandemics.

Associations of online religious participation during COVID-19 lockdown with subsequent health and well-being among UK adults.

BACKGROUND: In-person religious service attendance has been linked to favorable health and well-being outcomes. However, little research has examined whether online religious participation improves these outcomes, especially when in-person attendance is suspended. METHODS: Using longitudinal data of 8951 UK adults, this study prospectively examined the association between frequency of online religious participation during the stringent lockdown in the UK (23 March -13 May 2020) and 21 indicators of psychological well-being, social well-being, pro-social/altruistic behaviors, psychological distress, and health behaviors. All analyses adjusted for baseline socio-demographic characteristics, pre-pandemic in-person religious service attendance, and prior values of the outcome variables whenever data were available. Bonferroni correction was used to correct for multiple testing. RESULTS: Individuals with online religious participation of ≥1/week (v. those with no participation at all) during the lockdown had a lower prevalence of thoughts of self-harm in week 20 (odds ratio 0.24; 95% CI 0.09-0.62). Online religious participation of <1/week (v. no participation) was associated with higher life satisfaction (standardized ß = 0.25; 0.11-0.39) and happiness (standardized ß = 0.25; 0.08-0.42). However, there was little evidence for the associations between online religious participation and all other outcomes (e.g. depressive symptoms and anxiety). CONCLUSIONS: There was evidence that online religious participation during the lockdown was associated with some subsequent health and well-being outcomes. Future studies should examine mechanisms underlying the inconsistent results for online v. in-person religious service attendance and also use data from non-pandemic situations.

HIV Infection Prevalence Significantly Intersects With COVID-19 Infection At the Area Level: A US County-Level Analysis.

BACKGROUND: Limited empirical evidence exists about the extent to which the current HIV epidemic intersects with COVID-19 infections at the area/geographic level. Moreover, little is known about how demographic, social, economic, behavioral, and clinical determinants are jointly associated with these infectious diseases. SETTING: Contiguous US counties (N = 3108). METHODS: We conducted a cross-sectional analysis and investigated the joint association between new HIV infection prevalence in 2018 and COVID-19 infections (January 22, 2020 and October 7, 2020) and explore the contribution of factors such as income inequality, binge drinking, and socioeconomic deprivation. We used Bayesian multivariate spatial models to estimate the cross-disease correlations between these diseases and identified hotspots, which we defined as a county with a posterior probability greater than 80% of being in the top decile of that disease. RESULTS: New HIV infection prevalence and COVID-19 infection moderately and significantly intersect [spatial correlation = 0.37, 95% credible interval (CrI) = 0.36-0.37]. Seventy-five counties, mostly in the south, were at elevated burden for HIV and COVID-19 infections. Higher income inequality was positively associated with both COVID-19 (relative risk 1.05, 95% CrI = 1.03-1.07) and HIV infection (relative risk = 1.12, 95% CrI = 1.09-1.15). CONCLUSIONS: We found that there is a considerable intersection between the current distribution of HIV burden with COVID-19 infections at the area level. We identified areas that federal funding and vaccination campaigns should prioritize for prevention and care efforts.

Association of Poor Mental-Health Days With COVID-19 Infection Rates in the U.S.

INTRODUCTION: Limited evidence exists about the association between prior prevalence of poor mental health at the area level and subsequent rates of COVID-19 infections. This association was tested using area-level nationwide population data in the U.S. METHODS: A nationwide study including 2,839 U.S. counties was conducted. Poor mental health was the age-adjusted average number of days within the past 30 days that adults reported poor mental health, including depression, stress, and problems with emotions, from the Behavioral Risk Factor Surveillance System. COVID-19 infection rates were cumulative confirmed cases between January 22 and October 7, 2020 per 100,000 people in the general population. Bayesian spatial mixed-effects regression estimated the relationship between COVID-19 infection and poor mental-health days at the county level in 2019 and change in poor mental health between 2010 and 2019, adjusted for several covariates. RESULTS: Poor mental-health days in 2019 were positively associated with higher COVID-19 infection rates (RRR=1.059, 95% credible interval=1.003, 1.117). Change in mental health was not significantly associated with COVID-19. CONCLUSIONS: Prior rates of poor mental health in a county were associated with a higher burden of COVID-19 infection. Interventions that improve well-being and strengthen mental-health systems at the community and other geographic levels are needed to address post-COVID-19 mental health problems.

Neighborhood Social Cohesion and Inequalities in COVID-19 Diagnosis Rates by Area-Level Black/African American Racial Composition.

Geographic inequalities in COVID-19 diagnosis are now well documented. However, we do not sufficiently know whether inequalities are related to social characteristics of communities, such as collective engagement. We tested whether neighborhood social cohesion is associated with inequalities in COVID-19 diagnosis rate and the extent the association varies across neighborhood racial composition. We calculated COVID-19 diagnosis rates in Philadelphia, PA, per 10,000 general population across 46 ZIP codes, as of April 2020. Social cohesion measures were from the Southeastern Pennsylvania Household Health Survey, 2018. We estimated Poisson regressions to quantify associations between social cohesion and COVID-19 diagnosis rate, testing a multiplicative interaction with Black racial composition in the neighborhood, which we operationalize via a binary indicator of ZIP codes above vs. below the city-wide average (41%) Black population. Two social cohesion indicators were significantly associated with COVID-19 diagnosis. Associations varied across Black neighborhood racial composition (p <0.05 for the interaction test). In ZIP codes with ≥41% of Black people, higher collective engagement was associated with an 18% higher COVID-19 diagnosis rate (IRR=1.18, 95%CI=1.11, 1.26). In contrast, areas with <41% of Black people, higher engagement was associated with a 26% lower diagnosis rate (IRR=0.74, 95%CI=0.67, 0.82). Neighborhood social cohesion is associated with both higher and lower COVID-19 diagnosis rates, and the extent of associations varies across Black neighborhood racial composition. We recommend some strategies for reducing inequalities based on the segmentation model within the social cohesion and public health intervention framework.