PREPRINT: Climate effect on COVID-19 spread rate: an online surveillance tool
COVID-19 outbreak poses an unprecedented challenge for societies, healthcare organizations and economies. In the present analysis we coupled climate data with COVID-19 spread rates worldwide, and in a single country (USA).
Methods: Data of confirmed COVID-19 cases was derived from the COVID-19 Global Cases by the CSSE at Johns Hopkins University up to March 19, 2020. We assessed disease spread by two measures: replication rate (RR), the slope of the logarithmic curve of confirmed cases, and the rate of spread (RoS), the slope of the linear regression of the logarithmic curve. Results: Based on predefined criteria, the mean COVID-19 RR was significantly lower in warm climate countries (0.12± 0.02) compared with cold countries (0.24± 0.01), (P<0.0001). Similarly, RoS was significantly lower in warm climate countries 0.12± 0.02 vs. 0.25± 0.01 than in cold climate countries (P<0.001). In all countries (independent of climate classification) both RR and RoS displayed a moderate negative correlation with temperature R= -0.69, 95% confidence interval [CI], -0.87 to -0.36; P<0.001 and R= -0.72, 95% confidence interval [CI], -0.87 to -0.36; P<0.001, respectively. We identified a similar moderate negative correlation with the dew point temperature. Additional climate variables did not display a significant correlation with neither RR nor RoS. Finally, in an ancillary analysis, COVID-19 intra-country model using an inter-state analysis of the USA did not identify yet correlation between climate parameters and RR or RoS as of March, 19, 2020. Conclusions: Our analysis suggests a plausible negative correlation between warmer climate and COVID-19 spread rate as defined by RR and RoS worldwide. This initial correlation should be interpreted cautiously and be further validated over time, the pandemic is at different stages in various countries as well as in regions within these countries. As such, some associations may be more affected by local transmission patterns rather than by climate. Importantly, we provide an online surveillance dashboard (https://covid19.net.technion.ac.il/) to further assess the association between climate parameters and outbreak dynamics worldwide as time goes by