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Spatially refined time-varying reproduction numbers of SARS-CoV-2 in Arkansas and Kentucky and their relationship to population size and public health policy, March – November 2020()
PURPOSE: To examine the time-varying reproduction number, R(t), for COVID-19 in Arkansas and Kentucky and investigate the impact of policies and preventative measures on the variability in R(t). METHODS: Arkansas and Kentucky county-level COVID-19 cumulative case count data (March 6-November 7, 2020...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8750695/ https://www.ncbi.nlm.nih.gov/pubmed/35031444 http://dx.doi.org/10.1016/j.annepidem.2021.12.012 |
Sumario: | PURPOSE: To examine the time-varying reproduction number, R(t), for COVID-19 in Arkansas and Kentucky and investigate the impact of policies and preventative measures on the variability in R(t). METHODS: Arkansas and Kentucky county-level COVID-19 cumulative case count data (March 6-November 7, 2020) were obtained. R(t) was estimated using the R package ‘EpiEstim’, by county, region (Delta, non-Delta, Appalachian, non-Appalachian), and policy measures. RESULTS: The R(t) was initially high, falling below 1 in May or June depending on the region, before stabilizing around 1 in the later months. The median R(t) for Arkansas and Kentucky at the end of the study were 1.15 (95% credible interval [CrI], 1.13, 1.18) and 1.10 (95% CrI, 1.08, 1.12), respectively, and remained above 1 for the non-Appalachian region. R(t) decreased when facial coverings were mandated, changing by -10.64% (95% CrI, -10.60%, -10.70%) in Arkansas and -5.93% (95% CrI, -4.31%, -7.65%) in Kentucky. The trends in R(t) estimates were mostly associated with the implementation and relaxation of social distancing measures. CONCLUSIONS: Arkansas and Kentucky maintained a median R(t) above 1 during the entire study period. Changes in R(t) estimates allow quantitative estimates of potential impact of policies such as facemask mandate. |
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