csiro-risk-assessment/ClimateChangeMozziePredict

Mosquitoes abundance predictions in Africa until 2079 # Mosquitoes abundance predictions in Africa until 2079 ## Description This code calculates the predicted abundances of three species of mosquitoes following two scenarios of climate change. The code allows also to study the effect of wind advection on mosquito abundance in the context of climate change. Finally, the code allows to obtain the abundances of mosquitoes following different socio-economic pathways. This code depends on R packages, on Mozzie and AgslPredict. It also uses and modifies scripts and functions from Mozzie and AgslPredict. R packages imported, available on CRAN: - data.table, version 1.14.8 - fields, version 15.2 - terra, version 1.7.46 - tidyr, version 1.3.0, - ggplot2, version 2.3.5.2 - sf, version 1.0-16 - colorspace, version 2.1-0 - rnaturalearth, version 1.0.1 - ggpubr, version 0.6.0 - ncdf4, version 4.1.21 ## Licencing and disclaimer This code is released under a GPLv3 license. To discuss other licenses, please contact CSIRO via GitHub. Copyright (c) 2025 Commonwealth Scientific and Industrial Research Organisation (CSIRO) ABN 41 687 119 230. CSIRO does not make any guarantees of accuracy or relevance of the code. CSIRO does not guarantee the code has no security vulnerabilities. CSIRO does not guarantee to bug-fix or security-fix the code. CSIRO reserves the right to "retire" the code and make no further changes. ## How to process the data and obtain the results The code has been divided into small scripts, making it easier to modify and debug. The scripts are conceived so you can run the code in parallel on HPC. The code is written in both R and Python to support two projects that use these languages, Mozzie written in Python among others and AgslPredict written in R. A. Process climate data: Prepare the files of climate variables so they can be used as covariates in the statistical model. B. Run the statistical model: Use the model to predict the spatiotemporally varying parameter `q`. …