TY - JOUR
T1 - Quantifying compliance with COVID-19 mitigation policies in the US
T2 - A mathematical modeling study
AU - Yamamoto, Nao
AU - Jiang, Bohan
AU - Wang, Haiyan
N1 - Publisher Copyright:
© 2021 The Authors
PY - 2021/1
Y1 - 2021/1
N2 - The outbreak of COVID-19 disrupts the life of many people in the world. In response to this global pandemic, various institutions across the globe had soon issued their prevention guidelines. Governments in the US had also implemented social distancing policies. However, those policies, which were designed to slow the spread of COVID-19, and its compliance, have varied across the states, which led to spatial and temporal heterogeneity in COVID-19 spread. This paper aims to propose a spatio-temporal model for quantifying compliance with the US COVID-19 mitigation policies at a regional level. To achieve this goal, a specific partial differential equation (PDE) is developed and validated with short-term predictions. The proposed model describes the combined effects of transboundary spread among state clusters in the US and human mobilities on the transmission of COVID-19. The model can help inform policymakers as they decide how to react to future outbreaks.
AB - The outbreak of COVID-19 disrupts the life of many people in the world. In response to this global pandemic, various institutions across the globe had soon issued their prevention guidelines. Governments in the US had also implemented social distancing policies. However, those policies, which were designed to slow the spread of COVID-19, and its compliance, have varied across the states, which led to spatial and temporal heterogeneity in COVID-19 spread. This paper aims to propose a spatio-temporal model for quantifying compliance with the US COVID-19 mitigation policies at a regional level. To achieve this goal, a specific partial differential equation (PDE) is developed and validated with short-term predictions. The proposed model describes the combined effects of transboundary spread among state clusters in the US and human mobilities on the transmission of COVID-19. The model can help inform policymakers as they decide how to react to future outbreaks.
KW - COVID-19
KW - Google Community Mobility Reports
KW - Partial differential equation
KW - Social distancing
KW - Validation
UR - http://www.scopus.com/inward/record.url?scp=85102248282&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85102248282&partnerID=8YFLogxK
U2 - 10.1016/j.idm.2021.02.004
DO - 10.1016/j.idm.2021.02.004
M3 - Article
AN - SCOPUS:85102248282
SN - 2468-0427
VL - 6
SP - 503
EP - 513
JO - Infectious Disease Modelling
JF - Infectious Disease Modelling
ER -