Thazhathedath Hariharan Hariprasad, Surendran Anish Thekkumkara, Haridasan Retheesh Kollerazhikathu, Venkitaraman Sriram, Robert Dennis, Narayanan Sorna P, Mammen Pratheesh C, Siddharth Selva Raja, Kuriakose Sekhar L
Department of Community Medicine Government Medical College Thiruvananthapuram India.
Department of Health & Family Welfare Government of Kerala Thiruvananthapuram India.
Geohealth. 2021 Oct 1;5(10):e2020GH000378. doi: 10.1029/2020GH000378. eCollection 2021 Oct.
Many of the respiratory pathogens show seasonal patterns and association with environmental factors. In this article, we conducted a cross-sectional analysis of the influence of environmental factors, including climate variability, along with development indicators on the differential global spread and fatality of COVID-19 during its early phase. Global climate data we used are monthly averaged gridded data sets of temperature, humidity and temperature anomaly. We used Human Development Index (HDI) to account for all nation wise socioeconomic factors that can affect the reporting of cases and deaths and build a stepwise negative binomial regression model. In the absence of a development indicator, all environmental variables excluding the specific humidity have a significant association with the spread and mortality of COVID-19. Temperature has a weak negative association with COVID-19 mortality. However, HDI is shown to confound the effect of temperature on the reporting of the disease. Temperature anomaly, which is being regarded as a global warming indicator, is positively associated with the pandemic's spread and mortality. Viewing newer infectious diseases like SARS-CoV-2 from the perspective of climate variability has a lot of public health implications, and it necessitates further research.
许多呼吸道病原体呈现季节性模式并与环境因素相关联。在本文中,我们对环境因素(包括气候变异性)以及发展指标对COVID-19早期阶段在全球范围内的不同传播和致死情况的影响进行了横断面分析。我们使用的全球气候数据是温度、湿度和温度异常的月平均网格化数据集。我们使用人类发展指数(HDI)来考量所有可能影响病例和死亡报告的国家层面社会经济因素,并建立了逐步负二项回归模型。在没有发展指标时,除比湿外的所有环境变量均与COVID-19的传播和死亡率存在显著关联。温度与COVID-19死亡率呈弱负相关。然而,HDI显示出会混淆温度对疾病报告的影响。被视为全球变暖指标的温度异常与大流行的传播和死亡率呈正相关。从气候变异性角度看待像SARS-CoV-2这样的新型传染病具有诸多公共卫生意义,这需要进一步研究。