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Disaster Med Public Health Prep
. 2025 Apr 15:19:e75.
doi: 10.1017/dmp.2025.49. Geographical Variation in COVID-19 Transmission Potential and Case Burden, West Virginia, 2020-2023
Abigail A Buesseler 1 , Xinyi Hua 1 , Dorcas Ama Adom 2 , Shobhan Das 1 , Wendy S Kutten 1 , Olawumi Olatunde 1 , Olivia A Sheppard 1 , Jhy-Charm Soo 1 , Jing Kersey 1 , Kin On Kwok 3 4 5 , Gerardo Chowell 6 , Isaac Chun-Hai Fung 1
Affiliations
Objective: Substate-level analysis reveals geographical variation in COVID-19 epidemiology and facilitates improvement of prevention efforts with greater granularity.
Methods: We analyzed daily confirmed COVID-19 case count in West Virginia and its 9 regions (March 19, 2020-March 9, 2023). Nonparametric bootstrapping and a Poisson-distributed multiplier of 4 were applied to account for irregular and under-reporting. We used the R package EpiEstim to estimate the time-varying reproduction number Rt with 7-day-sliding-windows (2020-2023) and non-overlapping-time-windows between 5 policy changes (2020 only). Poisson regression was used to estimate the incidence rate ratio (IRR) between each region and West Virginia (2020, 2021, and 2022).
Results: Statewide Rt fluctuated over the study period, with the highest in March 2020 (close to 2) and the lowest Rt (<1) seen in June 2020. The Stay-at-home Order, Face Mask Mandate, and Virtual Learning Resumes saw 38.7% (95% credible interval [CrI]: 21.9%-57.5%), 10.6% (95% CrI, 3.2%-18.9%), and 9.4% (95% CrI, 3.2%-15.4%) corresponding decreases in Rt statewide. All regions experienced incidence rates different from the state. The IRRs ranged from 0.32 (95% CI, 0.32-0.33) (Northern region) to 1.90 (95% CI, 1.87-1.94) (Wood-Jackson region) in 2020.
Conclusions: Policies reducing human contacts, e.g., Stay-at-home Order and Virtual Learning Resumes, effectively reduced transmission statewide.
Keywords: COVID-19; SARS-CoV-2; United States; West Virginia; epidemiology; reproduction number.
. 2025 Apr 15:19:e75.
doi: 10.1017/dmp.2025.49. Geographical Variation in COVID-19 Transmission Potential and Case Burden, West Virginia, 2020-2023
Abigail A Buesseler 1 , Xinyi Hua 1 , Dorcas Ama Adom 2 , Shobhan Das 1 , Wendy S Kutten 1 , Olawumi Olatunde 1 , Olivia A Sheppard 1 , Jhy-Charm Soo 1 , Jing Kersey 1 , Kin On Kwok 3 4 5 , Gerardo Chowell 6 , Isaac Chun-Hai Fung 1
Affiliations
- PMID: 40230244
- DOI: 10.1017/dmp.2025.49
Objective: Substate-level analysis reveals geographical variation in COVID-19 epidemiology and facilitates improvement of prevention efforts with greater granularity.
Methods: We analyzed daily confirmed COVID-19 case count in West Virginia and its 9 regions (March 19, 2020-March 9, 2023). Nonparametric bootstrapping and a Poisson-distributed multiplier of 4 were applied to account for irregular and under-reporting. We used the R package EpiEstim to estimate the time-varying reproduction number Rt with 7-day-sliding-windows (2020-2023) and non-overlapping-time-windows between 5 policy changes (2020 only). Poisson regression was used to estimate the incidence rate ratio (IRR) between each region and West Virginia (2020, 2021, and 2022).
Results: Statewide Rt fluctuated over the study period, with the highest in March 2020 (close to 2) and the lowest Rt (<1) seen in June 2020. The Stay-at-home Order, Face Mask Mandate, and Virtual Learning Resumes saw 38.7% (95% credible interval [CrI]: 21.9%-57.5%), 10.6% (95% CrI, 3.2%-18.9%), and 9.4% (95% CrI, 3.2%-15.4%) corresponding decreases in Rt statewide. All regions experienced incidence rates different from the state. The IRRs ranged from 0.32 (95% CI, 0.32-0.33) (Northern region) to 1.90 (95% CI, 1.87-1.94) (Wood-Jackson region) in 2020.
Conclusions: Policies reducing human contacts, e.g., Stay-at-home Order and Virtual Learning Resumes, effectively reduced transmission statewide.
Keywords: COVID-19; SARS-CoV-2; United States; West Virginia; epidemiology; reproduction number.