Abstract：
.In this study, we assessed the impact of satellite-based Land Surface Temperature (LST) and Air Temperature (AT) on covid-19. First, we spatio-temporally kriged the LST and applied bias correction. The epidemic shape, timing, and size were compared after and before adjusting for the predictors. Given the non-linear behavior of a pandemic, a semi-parametric regression model was used. In addition, the interaction effect between the predictors and season was assessed. Before adjusting for the predictors, the peak happened at the end of hot season. After adjusting, it was attenuated and slightly moved forward. Moreover, the Attributable Fraction (AF) and Peak to Trough Relative (PTR) were % 23 (95% CI; 15, 32) and 1.62 (95%CI; 1.34, 1.97), respectively. We found that temperature might have changed the seasonal variation of covid-19. However, given the large uncertainty after adjusting for the variables, it was hard to provide conclusive evidence in the region we studied.
摘要：
.在这项研究中,我们评估了基于卫星的地表温度(LST)和气温(AT)对covid-19的影响。首先,我们在时空上对LST进行了克里，并应用了偏差校正。流行病的形状，定时,和大小在调整预测因子之后和之前进行了比较。鉴于大流行的非线性行为，使用半参数回归模型。此外,评估了预测因子与季节之间的交互效应.在调整预测因子之前，高峰发生在炎热的季节结束时。调整后,它被衰减并稍微向前移动。此外，归因分数(AF)和峰值相对于沟槽(PTR)分别为%23(95%CI;15，32)和1.62(95CI;1.34，1.97)，分别。我们发现温度可能改变了covid-19的季节性变化。然而,考虑到变量调整后的较大不确定性，在我们研究的地区很难提供确凿的证据。
