XI-ROR-01hxy9878-WEATHER Royal College of Surgeons in Ireland Aim: Develop a predictive warning system for extreme weather such as flooding in two vulnerable districts; eThekwini and Ugu districts of KZN province, South Africa. Firstly, the study will assess the relationship between extreme weather and health risk due to contamination of water, and associated disease outbreaks. Secondly, disease predictive modelling will be investigated. Lastly, a warning system to improve communication between affected communities and central healthcare providers will be developed from existing mobile phone platforms combined with predictive technology. Background: Weather patterns in KZN province are less predictable due to climate change causing significant disruption in communication, severe flood damage, limited access to safe, clean drinking water and infectious disease outbreaks causing deaths. A predictive warning system would assist communities/ health systems to prepare/ manage risk during weather-related flooding. Design: Past climate data from South African weather services, water quality reports from two district municipalities, and health data from the KZN Department of Health, will be combined to predict future flooding and associated health risks. WP1 will examine the evidence on EWEs and infectious disease outbreaks which will inform a comprehensive framework for monitoring health conditions and types of infections to build evaluation endpoint for the PWSi. Design and development of a pathogen and contamination management tool in WP1 which will share information with PWSi development in WP2. Examination of rainfall (time, intensity, duration, amount and floods) based on environmental parameters gathered in WP2 will aid in the development of PWSi comprising of a dashboard and free mobile app. WP3 will assess the disease burden, health needs and community experiences during flooding and resilience of health system to respond to flooding taking a mixed method approach. Finally, WP3 will pilot adapt and test a pathogen and continent management tool for the identification and management of resources during flooding. WP4 will apply an overarching Realist Evaluation and SROI approach (focus groups, interviews and questionnaires) to evaluate the efficiency, acceptability and cost effectiveness of PWSi impact on health outcomes during flooding in KZN province. Community Involvement: The SDCEA will establish a community engagement forum which will assist in identifying key local stakeholders, share information and coordinate communication between community hubs and local people. Impact: Capacity building is vital for research succession and the project integrates two PhD’s: one in health economics as no expertise in this discipline exists in the University of KwaZulu-Natal and one in AI technology. The predictive warning system will deliver value for money, enhancing communication, resource allocation, predict disease outbreaks, improving healthcare service delivery during flooding. Strong local partnerships with academics, clinicians and policymakers within SA will ensure that this research is disseminated widely and transferrable to other regions of the African sub-continent with similar weather events. Royal College of Surgeons in Ireland 155467.30 Income from funded organisation 73197