Estimation of transmission distance between cases of (re-)emerging respiratory infectious diseases and its potential application in outbreak response

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Authors: Wenlong Zhu, Xueyao Liang, Xinyu Wang, Wenyong Zhou, Qianyi Ge, Minyi Yang, Bo Zheng, Zexuan Wen, Zhixi Liu, Ye Yao, Yang Liu, Weibing Wang
Cited by: 0
References: 33

Abstract

Quantifying transmission distance helps to understand infectious disease spread patterns, but few studies have assessed this for (re-)emerging respiratory infectious diseases. The COVID-19 pandemic's extensive surveillance and high-quality data in China offer a strong model for studying the spread pattern of respiratory infections. We collected COVID-19 outbreak data from June 2020 to December 2022 in mainland China to estimate transmission distances, examine the association between urban characteristics and transmission distance, and explore its implications in outbreak response. The mean transmission distance of all outbreaks was 18.94 km. This distance varied by SARS-CoV-2 variants, with wild-type outbreaks showing shortest transmission distance (3.08 km) and Omicron outbreaks showing longest transmission distance (20.17 km). Transmission distance was positively associated with city size and total length of roads. Potential transmission areas identified as areas within transmission distance of the first 100 cases contained 63.84-99.61% of cases. Providing testing services to residents in these areas helped to control the outbreak. Our results suggest that transmission distances can help predict where emerging respiratory infectious diseases may spread next spatially and guide the implementation of targeted interventions.

Fields of Study & Subjects

COVID-19 epidemiological studies Data-Driven Disease Surveillance SARS-CoV-2 and COVID-19 Research

Publication details

Journal / source
Infectious Disease Modelling
Volume
11
Issue
3
Pages
920–929
Publication date
24 February 2026
Language
EN