Data Challenge: Temperature and Precipitation as drivers of future Antibiotic resistance patterns in Enterobacteriaceae in Africa

Antimicrobial resistance (AMR) is a growing global threat, but Africa faces unique risks due to climatic fluctuations coupled with limited laboratory surveillance infrastructure. The emergence of multidrug-resistant bacterial pathogens is continuously increasing global health challenges. The crisis contributes to the mortality associated with bacterial AMR, with 1.27 million deaths in 2019 alone. Antibiotic misuse is widely known to be one of the key drivers that influence AMR. However, recent studies show that climate indices shape the resistance patterns. Temperature fluctuations influence resistance in bacterial pathogens, with warmer temperatures enhancing survival, transmission and facilitating horizontal gene transfer in Enterobacteriaceae, particularly Escherichia Coli and Klebsiella pneumoniae. Extreme climatic events (heavy rainfall and drought) facilitate survival, evolution and rapid spread of resistant Enterobacteriaceae. Therefore, this project aims to address these gaps by analyzing antibiotic resistance data in relation to temperature and precipitation climatic indices from 2019 to 2024. Antibiotic resistance data will be obtained from the Pfizer ATLAS database. It provides high-quality antimicrobial resistance data for the selected Enterobacteriaceae across diverse African countries. These make effective references for linking climate drivers with future resistance patterns. The study will use a linear mixed-effect model to quantify the association between temperature and precipitation against the antibiotic resistance rates. The spatial cluster analysis will identify high-risk hotspots where climate drivers accelerate resistance. Machine learning models (Random forest and Gradient boosting) will link climate drivers with antibiotic surveillance data. Afterwards, we will train the model and incorporate climate scenario projections to forecast future antibiotic resistance patterns under different climate conditions. The project will provide global evidence that climate change through extreme temperature and precipitation are highly pathogen-specific drivers of antibiotic resistance patterns in Africa and inform climate-dependent intervention policies in Africa.