Year: 2023
Type: article
Abstract: Targeted public health interventions for an emerging epidemic are essential for preventing pandemics and reducing their impact on health and society. During 2020–2022, China invested significant efforts in strict zero-COVID policies to contain outbreaks of varying scales caused by different SARS-CoV-2 variants. This presented a unique opportunity to utilise a real-world dataset to investigate the effects and challenges of public health interventions aimed at eliminating local transmission of emerging or introduced respiratory infections in diverse settings. Based on a multi-year empirical dataset containing 131 outbreaks observed in China from April 2020 to May 2022 and simulated scenarios, we ranked the relative effectiveness of the public health interventions by their reduction in instantaneous reproduction number. We found that, overall, reducing physical contact between individuals was most effective (median 23%, interquartile range [IQR] 20–26%), followed by the use of face masks (19%, IQR 16–23%) and close contact tracing (15%, IQR 14–16%). However, contact tracing played a more critical role in containing outbreaks during the initial phases, but as the spread persisted, social distancing measures became increasingly prominent and mass screening likely had little effect. In addition, these measures struggled to zero out infections that had high transmissibility and a short latent period, regardless of population size. Our findings provide quantitative insights on the impacts of different rapid public-health responses against emerging contagions with varying epidemiological and socio-economic contexts.
Source: Nature Communications
Institutions: Chinese Academy of Sciences, Institute of Geographic Sciences and Natural Resources Research, University of Chinese Academy of Sciences, State Key Laboratory of Resources and Environmental Information System, Jiangxi Normal University, University of Southampton, Beijing Center for Disease Prevention and Control, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Virginia Tech, Zhengzhou Normal University, Johns Hopkins University, University of Florida, Chinese Academy of Medical Sciences & Peking Union Medical College, Fudan University
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $6,411
Awards: G1339864048, G1526324536, G2100296040, The University of Southampton - to characterize the seasonality of the SARS-CoV2 virus is different setting around the world to best support mitigation efforts, G546399402, G6021568041, G6683154401, Human mobility models to forecast disease dynamics and the effectiveness of public health interventions
OpenAlex ID: W4386255238