This repository contains the datasets and R codes for reproducing the results in Global COVID-19 transmission rate is influenced by precipitation seasonality and the speed of climate temperature warming.
MIT licensed. Happy if you cite our study when using the data and codes:
Chiyomaru K & Takemoto K (2020) Global COVID-19 transmission rate is influenced by precipitation seasonality and the speed of climate temperature warming. medRxiv 2020.04.10.20060459. doi:10.1101/2020.04.10.20060459
Our datasets were generated based on 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository by Johns Hopkins CSSE (JHU CSSE COVID-19).
data_used_in_manuscirpt directory contains the datasets of the epidemic parameters, climate parameters, etc., used in our study.
The datasets were generated using the R codes (see "Codes" section).
We used the JHU CSSE COVID-19 data for the period between January 22, 2020 - April 6, 2020.
data_latest directory contains the datasets generated using the latest JHU CSSE COVID-19 data (updated when requested).
data_analysis.R analyses the data: ordinary least-squares regression and spatial analysis (spatial eigenvector mapping modeling).
Rscript data_analysis.R | tee output.txt
NOTE: need to clone JHU CSSE COVID-19.
git clone https://github.com/CSSEGISandData/COVID-19.git
compute_epidemic_parameters.R computes the following parameters using the time-series data in JHU CSSE COVID-19.
Rscript compute_epidemic_parameters.R [dataset_type]
dataset_type: Dataset type, global or US.
- number of confirmed cases per day
- total number of confirmed cases
- power law exponent
- growth rate (incidence package)
- doubling time
- growth rate (R0 package)
- R0 (R0 package)
- R0 estimated from exponential growth rate
- R0 estimated based on maximum likelihood
- R0 (earlyR package)
The parameters are computed from the data within a certain period (15 days since 30 cases have first recorded, in default). For estimating R0, the serial interval distributions in Nishiura et al. (2020), Wang et al. (2020), and Du et al. (2020) are used, respectively. See also the comments in the codes for details.
get_environmental_parameters.R obtains the following parameters from the databases based on the JHU CSSE COVID-19 data.
Rscript get_environmental_parameters.R [dataset_type]
dataset_type: Dataset type, global or US.
NOTE: need to manually download the raster data from the databases and to modify the code to specify the directories containing them. See also the comments in the codes for details.
- average temperature*
- maximum temperature*
- minimum temperature*
- diurnal temperature range*: maximum temperature - minimum temperature
- precipitation*
- solar radiation*
- wind speed*
- water vapor pressure*
- relative humidity* (computed based on water vapor pressure and average temperature)
- aridity index
- temperature seasonality
- precipitation seasonality
- elevation
- warming velocity: computed based on current annual mean temperature (AMT) and past AMT (CCSM).
- human footprint
- population density
- GDP per capita
- Human development index
*monthly parameters
- e-mail: takemoto@bio.kyutech.ac.jp
- twitter: @kztakemoto