This upload contains all replication material for "Ultraviolet radiation decreases COVID-19 growth rates: Global causal estimates and seasonal implications" (preprint). Please note that this manuscript is under review and the data and code are likely to change (updated versions will be uploaded to Zenodo as soon as they are available). Authors: Tamma Carleton, Jules Cornetet, Peter Huybers, Kyle C. Meng, Jonathan Proctor. Code is located within CCHMP_covid_climate_code_release.zip, and is written in R, Stata, and Matlab. The working directory should be set to the repository folder at the top of each script. Please find the code needed to replicate the main findings of the paper described below: Plots of data: R and Stata scripts to make figures 1B, S1, S2, S3, S4 and S13 can be found within “code/analysis/data_plots/”. Regression analysis: Stata scripts to run the distributed lag regressions and plot the results in figures 2, S6, S7, S8 and S9 can be found within “code/analysis/regressions/” Seasonal simulations: R and Stata scripts to replicate the seasonal simulation shown in figures 3, S5 and S10 can be found within “code/analysis/seasonal_sim/”. SEIR simulations: Matlab scripts to replicate the SEIR simulations shown in figures S11 and S12 can be found within “code/analysis/SEIR/”. Data are located within CCHMP_covid_climate_data_release.zip.

{"references": ["Carleton et al., (preprint, 2020). Ultraviolet radiation decreases COVID-19 growth rates: Global causal estimates and seasonal implications. http://ssrn.com/abstract=3588601"]}