Dynamics of Covid-19 mortality and social determinants of health: a spatiotemporal analysis of exceedance probabilities.
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ABSTRACT: Purpose
To determine the association of social factors with Covid-19 mortality and identify high-risk clusters.Methods
Data on Covid-19 deaths across 3,108 contiguous U.S. counties from the Johns Hopkins University and social determinants of health (SDoH) data from the County Health Ranking and the Bureau of Labor Statistics were fitted to Bayesian semi-parametric spatiotemporal Negative Binomial models, and 95% credible intervals (CrI) of incidence rate ratios (IRR) were used to assess the associations. Exceedance probabilities were used for detecting clusters.Results
As of October 31, 2020, the median mortality rate was 40.05 per 100, 000. The monthly urban mortality rates increased with unemployment (IRRadjusted:1.41, 95% CrI: 1.24, 1.60), percent Black population (IRRadjusted:1.05, 95% CrI: 1.04, 1.07), and residential segregation (IRRadjusted:1.03, 95% CrI: 1.02, 1.04). The rural monthly mortality rates increased with percent female population (IRRadjusted: 1.17, 95% CrI: 1.11, 1.24) and percent Black population (IRRadjusted:1.07 95% CrI:1.06, 1.08). Higher college education rates were associated with decreased mortality rates in rural and urban counties. The dynamics of exceedance probabilities detected the shifts of high-risk clusters from the Northeast to Southern and Midwestern counties.Conclusions
Spatiotemporal analyses enabled the inclusion of unobserved latent risk factors and aid in scientifically grounded decision-making at a granular level.
SUBMITTER: Paul R
PROVIDER: S-EPMC8451980 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundData regarding the geographical distribution of cases and risk factors for COVID-19 death in children and adolescents are scarce. We describe the spatial distribution of COVID-19 cases and deaths in paediatric population and their association with social determinants of health in Brazil.MethodsThis is a population-based ecological study with a spatial analysis of all cases and deaths due to COVID-19 in Brazil among children and adolescents aged 0-19 years from March 2020 to October 2021. The units of analysis were the 5570 municipalities. Data on COVID-19 cases and deaths, social vulnerability, health inequities, and health system capacity were obtained from publicly available databases. Municipalities were stratified from low to very high COVID-19 incidence and mortality using K-means clustering procedures, and spatial clusters and relative risks were estimated using spatial statistics with Poisson probability models. The relationship between COVID-19 estimates and social determinants of health was explored by using multivariate Beta regression techniques.FindingsA total of 33,991 COVID-19 cases and 2424 deaths among children and adolescents aged 0-19 years were recorded from March 2020 to October 2021. There was a spatial dependence for the crude mortality coefficient per 100,000 population in the paediatric population aged 0-19 years (I Moran 0·10; P < 0·001). Forty municipalities had higher mortality rates, of which 20 were in states from the Northeast region. Seven spatial clusters were identified for COVID-19 mortality, with four clusters in the Northeast region and three in the North region. Municipalities with higher social inequality and vulnerability had higher COVID-19 mortality in the paediatric population.InterpretationThe main clusters of risk for mortality among children and adolescents were identified in municipalities in the North and Northeast regions, which are the regions with the worst socioeconomic indicators and greatest health disparities in the country. Our findings confirmed the higher burden of COVID-19 for Brazilian paediatric population in municipalities with higher social inequality and vulnerability and worse socioeconomic indicators. To reduce the burden of COVID-19 on children, mass immunisation is necessary.FundingNone.
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