A multiplicity of environmental, economic and social factor analyses to understand COVID-19 diffusion

Juan Qiu; Rendong Li; Dongfeng Han; Qihui Shao; Yifei Han; Xiyue Luo; Yanlin Wu

doi:10.1016/j.onehlt.2021.100335

A multiplicity of environmental, economic and social factor analyses to understand COVID-19 diffusion

One Health. 2021 Dec:13:100335. doi: 10.1016/j.onehlt.2021.100335. Epub 2021 Oct 5.

Authors

Juan Qiu¹, Rendong Li¹, Dongfeng Han^{1

2}, Qihui Shao^{1

2}, Yifei Han^{1

2}, Xiyue Luo³, Yanlin Wu³

Affiliations

¹ Key Laboratory of Monitoring and Estimate for Environment and Disaster of Hubei Province, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China.
² University of Chinese Academy of Sciences, Beijing, China.
³ Faculty of Resources and Environmental Science, Hubei University, Wuhan, China.

Abstract

Research on the impact of the environment on COVID-19 diffusion lacks a full-comprehensive perspective, and neglecting the multiplicity of the human-environment system can lead to misleading conclusions. We attempted to reveal all pre-existing environmental-to-human and human-to-human determinants that influence the transmission of COVID-19. As such, We estimated the daily case incidence ratios (CIR) of COVID-19 for prefectures across mainland China, and used a mixed-effects mixed-distribution model to study the association between the CIR and 114 factors related to climate, atmospheric environmental quality, terrain, population, economic, human mobility as well as non-pharmaceutical interventions (NPIs). Not only the changes in determinants over time as the pandemic progresses but also their lag and interaction effects were examined. CO, O₃, PM₁₀ and PM_2.5 were found positively linked with CIR, but the effect of NO₂ was negative. The temperature had no significant association with CIR, and the daily minimum humidity was a significant negatively predictor. NPIs' level was negatively associated with CIR until with a lag of 15 days. Higher accumulated destination migration scale flow from the epicenter and lower distance to the epicenter (DisWH) were associated with a higher CIR, however, the interaction between DisWH and the time was positive. The more economically developed and more densely populated cities have a higher probability of CIR occurrence, but they may not have a higher CIR intensity.The COVID-19 diffusion are caused by a multiplicity of environmental, economic, social factors as well as NPIs. First, multiple pollutants carried simultaneously on particulate matter affect COVID-19 transmission. Second, the temperature has a limited impact on the spread of the epidemic. Third, NPIs must last for at least 15 days or longer before the effect has been apparent. Fourth, the impact of population movement from the epicenter on COVID-19 gradually diminished over time and intraregional migration deserves more attention.

Keywords: Atmospheric environmental quality; COVID-19; Human mobility; Meteorology; Mixed-effects mixed-distribution model; Non-pharmaceutical interventions.