Natural and socio-environmental factors contribute to the transmissibility of COVID-19: evidence from an improved SEIR model

IF 3 3区地球科学 Q2 BIOPHYSICS

International Journal of Biometeorology Pub Date : 2023-08-10 DOI:10.1007/s00484-023-02539-8

Jie Li, Kun Jia, Wenwu Zhao, Bo Yuan, Yanxu Liu

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Abstract

COVID-19 has ravaged Brazil, and its spread showed spatial heterogeneity. Changes in the environment have been implicated as potential factors involved in COVID-19 transmission. However, considerable research efforts have not elucidated the risk of environmental factors on COVID-19 transmission from the perspective of infectious disease dynamics. The aim of this study is to model the influence of the environment on COVID-19 transmission and to analyze how the socio-ecological factors affecting the probability of virus transmission in 10 states dramatically shifted during the early stages of the epidemic in Brazil. First, this study used a Pearson correlation to analyze the interconnection between COVID-19 morbidity and socio-ecological factors and identified factors with significant correlations as the dominant factors affecting COVID-19 transmission. Then, the time-lag effect of dominant factors on the morbidity of COVID-19 was investigated by constructing a distributed lag nonlinear model and standard two-stage meta-analytic model, and the results were considered in the improved SEIR model. Lastly, a machine learning method was introduced to explore the nonlinear relationship between the environmental propagation probability and socio-ecological factors. By analyzing the impact of environmental factors on virus transmission, it can be found that population mobility directly caused by human activities had a greater impact on virus transmission than temperature and humidity. The heterogeneity of meteorological factors can be accounted for by the diverse climate patterns in Brazil. The improved SEIR model was adopted to explore the interconnection of COVID-19 transmission and the environment, which revealed a new strategy to probe the causal links between them.

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自然和社会环境因素有助于新冠肺炎的传播性：来自改进的SEIR模型的证据。

新冠肺炎肆虐巴西，其传播表现出空间异质性。环境变化被认为是新冠肺炎传播的潜在因素。然而，大量的研究工作尚未从传染病动力学的角度阐明环境因素对新冠肺炎传播的风险。本研究的目的是模拟环境对新冠肺炎传播的影响，并分析在巴西疫情早期，影响10个州病毒传播概率的社会生态因素是如何急剧变化的。首先，本研究使用皮尔逊相关性分析了新冠肺炎发病率与社会生态因素之间的相互关系，并确定了具有显著相关性的因素是影响新冠肺炎传播的主导因素。然后，通过构建分布式滞后非线性模型和标准两阶段元分析模型，研究了主导因素对新冠肺炎发病率的时滞效应，并将其纳入改进的SEIR模型。最后，引入机器学习方法来探索环境传播概率与社会生态因素之间的非线性关系。通过分析环境因素对病毒传播的影响可以发现，人类活动直接引起的人口流动对病毒传播影响大于温度和湿度。巴西不同的气候模式可以解释气象因素的异质性。采用改进的SEIR模型来探索新冠肺炎传播与环境之间的相互联系，这揭示了一种新的策略来探索它们之间的因果关系。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Biometeorology 地学-环境科学

CiteScore

6.40

自引率

9.40%

发文量

183

审稿时长

1 months

期刊介绍： The Journal publishes original research papers, review articles and short communications on studies examining the interactions between living organisms and factors of the natural and artificial atmospheric environment. Living organisms extend from single cell organisms, to plants and animals, including humans. The atmospheric environment includes climate and weather, electromagnetic radiation, and chemical and biological pollutants. The journal embraces basic and applied research and practical aspects such as living conditions, agriculture, forestry, and health. The journal is published for the International Society of Biometeorology, and most membership categories include a subscription to the Journal.