Parallel evolution and control method for predicting the effectiveness of non-pharmaceutical interventions in pandemics

• Published in: Journal of public health Vol. 32; no. 4; pp. 713 - 724
• Main Authors: Huang, Hai-nan, Xie, Tian, Chen, Wei-fan, Wei, Yao-yao
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2024; Springer Nature B.V
• Subjects: Control methods; COVID-19; Decision making; Disease control; Disinfection; Emergency management; Emergency medical services; Emergency preparedness; Epidemic models; Epidemiology; Evolution; Health behavior; Health Promotion and Disease Prevention; Management methods; Mathematical models; Medicine; Medicine & Public Health; Original; Original Article; Pandemics; Predictive control; Public Health; COVID-19; Parallel control and management; Non-pharmaceutical interventions; Epidemiological model
• ISSN: 2198-1833; 1613-2238
• DOI: 10.1007/s10389-023-01843-2

Aim Nonpharmaceutical interventions (NPIs) are important strategies to utilize in reducing the negative systemic impact pandemic disasters have on human health. However, early on in the pandemic, the lack of prior knowledge and the rapidly changing nature of pandemics make it challenging to construct effective epidemiological models that can be used for anti-contagion decision-making. Subject and methods Based on the parallel control and management theory (PCM) and epidemiological models, we developed a Parallel Evolution and Control Framework for Epidemics (PECFE), which can optimize epidemiological models according to the dynamic information during the evolution of pandemics. Results The cross-application between PCM and epidemiological models enabled us to successfully construct an anti-contagion decision-making model for the early stages of COVID-19 in Wuhan, China. Using the model, we estimated the effects of gathering bans, intra-city traffic blockades, emergency hospitals, and disinfection, forecasted pandemic trends under different NPIs strategies, and analyzed specific strategies to prevent pandemic rebounds. Conclusion The successful simulation and forecasting of the pandemic showed that the PECFE could be effective in constructing decision models during pandemic outbreaks, which is crucial for emergency management where every second counts.