Following its initial appearance in December 2019, coronavirus disease 2019 (COVID-19) quickly spread around the globe. Here, we evaluated the role of climate (temperature and precipitation), region-specific COVID-19 susceptibility (BCG vaccination factors, malaria incidence, and percentage of the population aged over 65 years), and human mobility (relative amounts of international visitors) in shaping the geographical patterns of COVID-19 case numbers across 1,020 countries/regions, and examined the sequential shift that occurred from December 2019 to June 30, 2020 in multiple drivers of the cumulative number of COVID-19 cases. Our regression model adequately explains the cumulative COVID-19 case numbers (per 1 million population). As the COVID-19 spread progressed, the explanatory power (R²) of the model increased, reaching > 70% in April 2020. Climate, host mobility, and host susceptibility to COVID-19 largely explained the variance among COVID-19 case numbers across locations; the relative importance of host mobility and that of host susceptibility to COVID-19 were both greater than that of climate. Notably, the relative importance of these factors changed over time; the number of days from outbreak onset drove COVID-19 spread in the early stage, then human mobility accelerated the pandemic, and lastly climate (temperature) propelled the phase following disease expansion. Our findings demonstrate that the COVID-19 pandemic is deterministically driven by climate suitability, cross-border human mobility, and region-specific COVID-19 susceptibility. The identification of these multiple drivers of the COVID-19 outbreak trajectory, based on mapping the spread of COVID-19, will contribute to a better understanding of the COVID-19 disease transmission risk and inform long-term preventative measures against this disease.

在2019年12月首次出现后，2019年冠状病毒病（COVID-19）迅速在全球蔓延。在这里，我们评估了气候（温度和降水），特定地区的COVID-19易感性（BCG疫苗接种因子，疟疾发病率和65岁以上人口的百分比）和人口流动性（相对国际访客数量）的作用塑造了1,020个国家/地区的COVID-19病例数的地理格局，并研究了从2019年12月到2020年6月30日发生的顺序转移，这些累积转移是由多个导致COVID-19病例数的驱动因素引起的。我们的回归模型充分说明了累计COVID-19病例数（每100万人口）。随着COVID-19传播的进展，解释力（R ²）模式的增加，到2020年4月达到> 70％。气候，寄主流动性和寄主对COVID-19的敏感性很大程度上解释了各地间COVID-19病例数之间的差异。宿主迁移的相对重要性和宿主对COVID-19的敏感性都比气候要高。值得注意的是，这些因素的相对重要性随时间而改变；疾病爆发的天数在早期推动了COVID-19的传播，然后人类的流动加速了大流行，最后，气候（温度）推动了疾病扩大之后的阶段。我们的发现表明，COVID-19大流行是由气候适宜性，跨境人员流动以及特定地区的COVID-19敏感性决定性地驱动的。识别出COVID-19爆发轨迹的这些多个驱动因素，