A mobility-adjusted framework for regional Rt estimation: enhancing spatial interpretation of transmission dynamics

This study presents a mobility-adjusted framework for estimating [Formula: see text] that incorporates inter-regional movement to better capture spatial transmission dynamics. The method mitigates inflated estimates in low-incidence areas and identifies mobility-driven risks in highly connected regions, offering context-aware insights beyond conventional approaches. While not universally superior, it complements existing methods and provides a practical tool for geographically targeted interventions, adaptable to diverse epidemiological settings where spatial connectivity shapes outbreaks.

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Publication Details

Journal
BMC Infectious Diseases
Published
2025-11-03
DOI
https://doi.org/10.1186/s12879-025-11889-0
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
0.00

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article

A mobility-adjusted framework for regional Rt estimation: enhancing spatial interpretation of transmission dynamics

Arsen Abdulali, Byul Nim Kim, Jeongwon Jo, Young Kim et al.
BMC Infectious Diseases
COVID-19 epidemiological studies
article

A mobility-adjusted framework for regional Rt estimation: enhancing spatial interpretation of transmission dynamics

Arsen Abdulali, Byul Nim Kim, Jeongwon Jo, Young Kim, Sunmi ‍Lee, Gerardo Chowell
article en

Abstract

This study presents a mobility-adjusted framework for estimating [Formula: see text] that incorporates inter-regional movement to better capture spatial transmission dynamics. The method mitigates inflated estimates in low-incidence areas and identifies mobility-driven risks in highly connected regions, offering context-aware insights beyond conventional approaches. While not universally superior, it complements existing methods and provides a practical tool for geographically targeted interventions, adaptable to diverse epidemiological settings where spatial connectivity shapes outbreaks.

BMC Infectious DiseasesVol. 25(1)
Queen Mary University of London (GB), Georgia State University (US), University of Cambridge (GB), Kyung Hee University (KR)
National Research Foundation, National Research Foundation of Korea, Ministry of Science and ICT, South Korea
Openalex Percentile: Top 64%
COVID-19 epidemiological studies
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