We performed a global analysis with data from 149 countries to test whether temperature can explain the spatial variability of the spread rate and mortality of COVID-19 at the global scale. We performed partial correlation analysis and linear mixed effect modelling to evaluate the association of the spread rate and motility of COVID-19 with maximum, minimum, average temperatures and diurnal temperature variation (difference between daytime maximum and night-time minimum temperature) and other environmental and socio-economic parameters. After controlling the effect of the duration since the first positive case, partial correlation analysis revealed that temperature was not related with the spatial variability of the spread rate of COVID-19 at the global scale. Mortality was negatively related with temperature in the countries with high-income economies. In contrast, diurnal temperature variation was significantly and positively correlated with mortality in the low- and middle-income countries. Taking the country heterogeneity into account, mixed effect modelling revealed that inclusion of temperature as a fixed factor in the model significantly improved model skill predicting mortality in the low- and middle-income countries. Our analysis suggests that warm climate may reduce the mortality rate in high-income economies, but in low- and middle-income countries, high diurnal temperature variation may increase the mortality risk.

中文翻译：

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关于温度、社会经济和环境因素对 COVID-19 大流行的传播和死亡率影响的全球分析

我们对来自 149 个国家/地区的数据进行了全球分析，以测试温度是否可以解释全球范围内 COVID-19 传播率和死亡率的空间变异性。我们进行了偏相关分析和线性混合效应建模，以评估 COVID-19 的传播率和运动性与最高、最低、平均温度和昼夜温度变化（白天最高温度和夜间最低温度之间的差异）和其他环境的关联和社会经济参数。在控制了自第一个阳性病例以来的持续时间的影响后，偏相关分析表明，温度与全球范围内 COVID-19 传播率的空间变异性无关。在高收入经济体国家，死亡率与气温呈负相关。相比之下，昼夜温度变化与低收入和中等收入国家的死亡率显着正相关。考虑到国家的异质性，混合效应模型显示，将温度作为模型中的一个固定因素显着提高了模型预测低收入和中等收入国家死亡率的技能。我们的分析表明，温暖的气候可能会降低高收入经济体的死亡率，但在低收入和中等收入国家，昼夜温差大可能会增加死亡率风险。考虑到国家的异质性，混合效应模型显示，将温度作为模型中的一个固定因素显着提高了模型预测低收入和中等收入国家死亡率的技能。我们的分析表明，温暖的气候可能会降低高收入经济体的死亡率，但在低收入和中等收入国家，昼夜温差大可能会增加死亡率风险。考虑到国家的异质性，混合效应模型显示，将温度作为模型中的固定因素纳入模型显着提高了低收入和中等收入国家预测死亡率的模型技能。我们的分析表明，温暖的气候可能会降低高收入经济体的死亡率，但在低收入和中等收入国家，昼夜温差大可能会增加死亡率风险。