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Prediction and prevention of non-Markovian epidemic spreading in coupled system
Chaos, Solitons & Fractals ( IF 5.3 ) Pub Date : 2024-12-12 , DOI: 10.1016/j.chaos.2024.115869 Lun Ge, Yongshang Long, Ying Liu, Ming Tang, Shuguang Guan
Chaos, Solitons & Fractals ( IF 5.3 ) Pub Date : 2024-12-12 , DOI: 10.1016/j.chaos.2024.115869 Lun Ge, Yongshang Long, Ying Liu, Ming Tang, Shuguang Guan
Considering the transportation of goods and movement of people between social zones and lockdown zones through channels such as medical activities and express deliveries, we propose a non-Markovian disease transmission model in a coupled system. Simulation and prediction results for COVID-19 spreading during the lockdowns of cities such as Shanghai, Beijing and Jilin in 2022 demonstrate that the coupled-system model exhibits a superior short-term and long-term predictive capacity of epidemic situations, compared with the conventional single-system model. In evaluation of the suppression effect of interventions in social zones, it is found that reducing the inter-subsystem coupling strength can contain epidemic outbreaks more effectively than the population size in social zones. Additionally, enhancing the frequency of nucleic acid testing in social zones can observably mitigate the outbreaks. A twice a day PCR frequency for social zone personnels is expected to result in a theoretical outbreak size that is approximately half of the actual outbreak size. Our work provides new insights into the transmission mechanism of the disease under urban lockdowns and offers a scientific basis for the development of effective prevention and control strategies.
更新日期：2024-12-12
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