Geographical Variation in COVID-19 Transmission Potential and Case Burden, West Virginia, 2020-2023

Abigail A. Buesseler; Xinyi Hua; Dorcas Ama Adom; Shobhan Das; Wendy S. Kutten; Olawumi Olatunde; Olivia A. Sheppard; Jhy Charm Soo; Jing Kersey; Kin On Kwok; Gerardo Chowell; Isaac Chun Hai Fung

doi:10.1017/dmp.2025.49

Geographical Variation in COVID-19 Transmission Potential and Case Burden, West Virginia, 2020-2023

Abigail A. Buesseler, Xinyi Hua, Dorcas Ama Adom, Shobhan Das, Wendy S. Kutten, Olawumi Olatunde, Olivia A. Sheppard, Jhy Charm Soo, Jing Kersey, Kin On Kwok, Gerardo Chowell, Isaac Chun Hai Fung

Biostatistics, Epidemiology & Environmental Health Sciences

Research output: Contribution to journal › Article › peer-review

Abstract

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 (

Original language	English
Article number	e75
Journal	Disaster Medicine and Public Health Preparedness
Volume	19
DOIs	https://doi.org/10.1017/dmp.2025.49
State	Published - Apr 15 2025

Scopus Subject Areas

Public Health, Environmental and Occupational Health

Keywords

COVID-19
SARS-CoV-2
United States
West Virginia
epidemiology
reproduction number

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1017/dmp.2025.49

Cite this

Buesseler, A. A., Hua, X., Adom, D. A., Das, S., Kutten, W. S., Olatunde, O., Sheppard, O. A., Soo, J. C., Kersey, J., Kwok, K. O., Chowell, G., & Fung, I. C. H. (2025). Geographical Variation in COVID-19 Transmission Potential and Case Burden, West Virginia, 2020-2023. Disaster Medicine and Public Health Preparedness, 19, Article e75. https://doi.org/10.1017/dmp.2025.49

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title = "Geographical Variation in COVID-19 Transmission Potential and Case Burden, West Virginia, 2020-2023",

abstract = "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 (",

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author = "Buesseler, \{Abigail A.\} and Xinyi Hua and Adom, \{Dorcas Ama\} and Shobhan Das and Kutten, \{Wendy S.\} and Olawumi Olatunde and Sheppard, \{Olivia A.\} and Soo, \{Jhy Charm\} and Jing Kersey and Kwok, \{Kin On\} and Gerardo Chowell and Fung, \{Isaac Chun Hai\}",

note = "Publisher Copyright: {\textcopyright} The Author(s), 2025. Published by Cambridge University Press on behalf of Society for Disaster Medicine and Public Health, Inc.",

year = "2025",

month = apr,

day = "15",

doi = "10.1017/dmp.2025.49",

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T1 - Geographical Variation in COVID-19 Transmission Potential and Case Burden, West Virginia, 2020-2023

AU - Buesseler, Abigail A.

AU - Hua, Xinyi

AU - Adom, Dorcas Ama

AU - Das, Shobhan

AU - Kutten, Wendy S.

AU - Olatunde, Olawumi

AU - Sheppard, Olivia A.

AU - Soo, Jhy Charm

AU - Kersey, Jing

AU - Kwok, Kin On

AU - Chowell, Gerardo

AU - Fung, Isaac Chun Hai

PY - 2025/4/15

Y1 - 2025/4/15

N2 - 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 (

AB - 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 (

KW - COVID-19

KW - SARS-CoV-2

KW - United States

KW - West Virginia

KW - epidemiology

KW - reproduction number

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DO - 10.1017/dmp.2025.49

M3 - Article

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SN - 1935-7893

VL - 19

JO - Disaster Medicine and Public Health Preparedness

JF - Disaster Medicine and Public Health Preparedness

M1 - e75

ER -

Geographical Variation in COVID-19 Transmission Potential and Case Burden, West Virginia, 2020-2023

Abstract

Scopus Subject Areas

Keywords

UN SDGs

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