Predicting diarrhoea outbreaks with climate change

specific types of climate variables. Current research is applying further predictive machine learning methods in an ongoing effort to develop automated early-warning systems for broad- spectrum disease outbreak prediction across various developing nations with deficient public health systems. Supporting information S1 Appendix. (PDF) S1 Fig. Violin plots showing the distribution of the upward augmented data for lopera- mide (diarrhoea) and climate variables across theprovinces. EC = Eastern Cape, FS = Free State, GA = Gauteng, KZ = KwaZulu Natal, LP = Limpopo, MP = Mpumalanga, NC = Northern Cape, NW = North West, WC = Western Cape. (TIF) S2 Fig. Violin plots showing the distribution of the downward augmented data for lopera- mide (diarrhoea) and climate variables across theprovinces. EC = Eastern Cape, FS = Free State, GA = Gauteng, KZ = KwaZulu Natal, LP = Limpopo, MP = Mpumalanga, NC = Northern Cape, NW = North West, WC = Western Cape. (TIF) Acknowledgments The authors would like to extend their gratitude to the Applied Center for Climate and Earth Systems Research (ACCESS) under the Council for Scientific Research (CSIR), South Africa and Clicks Pharmaceuticals, South Africa for providing data that was relevant to this study. Author Contributions Conceptualization: Tassallah Abdullahi, Geoff Nitschke, Neville Sweijd. Data curation: Tassallah Abdullahi, Neville Sweijd. Methodology: Tassallah Abdullahi, Geoff Nitschke. Resources: Neville Sweijd. Supervision: Geoff Nitschke. Writing – original draft: Tassallah Abdullahi.

Writing – review & editing: Tassallah Abdullahi, Geoff Nitschke, Neville Sweijd. References 1. Troeger C, et al. Estimates of the Global, Regional, and National Morbidity, Mortality, and Aetiologies of Diarrhoea in 195 Countries: A Systematic Analysis for the Global Burden of Disease Study 2016. The Lancet Infectious Diseases. 2018; 18(11):1211–1228. https://doi.org/10.1016/S1473-3099(18)30362-1 2. WHO, et al. The World Health Report: 1996: Fighting Disease, Fostering Development. WHO, Geneva, Switzerland: WHO; 1996. 3. Kosek M, Bern C, Guerrant R. The Global Burden of Diarrhoeal Disease, as Estimated from Studies Published between 1992 and 2000. Bulletin of the World Health Organization. 2003; 81:197–204. PMID: 12764516 4. Bradshaw D, Groenewald P, Laubscher R, Nannan N, Nojilana B, Norman R, et al. Initial Burden of Dis- ease Estimates for South Africa, 2000. South African Medical Journal. 2003; 93(9):682–688. PMID: 14635557 PLOS ONE Predicting diarrhoea outbreaks with climate change PLOS ONE | https://doi.org/10.1371/journal.pone.0262008 April 19, 2022 16 / 18