Journal
FRONTIERS IN PUBLIC HEALTH
Volume 11, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fpubh.2023.1198973
Keywords
non-pharmaceutical interventions; COVID-19 pandemic; public health policymaking; multi-objective optimization; human mobility; multivariate time series analysis
Categories
Ask authors/readers for more resources
Non-pharmaceutical interventions have become the primary control strategies in the global fight against the COVID-19 pandemic due to the limited effectiveness of vaccines and therapies against emerging variants. However, implementing strict interventions for an extended period has negative impacts on the economy. This study uses vector autoregressive models and causality tests to investigate the temporal dynamics and associations between policies, mobility patterns, and virus transmission, aiming to find optimal strategies that balance public health and socio-economic recovery.
Given that the effectiveness of COVID-19 vaccines and other therapies is greatly limited by the continuously emerging variants, non-pharmaceutical interventions have been adopted as primary control strategies in the global fight against the COVID-19 pandemic. However, implementing strict interventions over extended periods of time is inevitably hurting the economy. Many countries are faced with the dilemma of how to take appropriate policy actions for socio-economic recovery while curbing the further spread of COVID-19. With an aim to solve this multi-objective decision-making problem, we investigate the underlying temporal dynamics and associations between policies, mobility patterns, and virus transmission through vector autoregressive models and the Toda-Yamamoto Granger causality test. Our findings reveal the presence of temporal lagged effects and Granger causality relationships among various transmission and human mobility variables. We further assess the effectiveness of existing COVID-19 control measures and explore potential optimal strategies that strike a balance between public health and socio-economic recovery for individual states in the U.S. by employing the Pareto optimality and genetic algorithms. The results highlight the joint power of the state of emergency declaration, wearing face masks, and the closure of bars, and emphasize the necessity of pursuing tailor-made strategies for different states and phases of epidemiological transmission. Our framework enables policymakers to create more refined designs of COVID-19 strategies and can be extended to other countries regarding best practices in pandemic response.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available