Case study submitted as part of Lancet Commission call for case studies.
Team members / location: Professor Mary Lynch/UK/Republic of Ireland/University of KwaZulu-Natal
Issue: The KwaZulu-Natal (KZN) province in South Africa (SA) is bordered by the Indian ocean to the east and the Drakensberg Mountain escarpment to the west. KZN province is home to 19% of the SA population and characterised by large informal housing settlements located near rivers. eThekwini (urban) and Ugu (rural) are two health districts both experiencing extreme weather events (EWE) in the past two years and in April 2022, floods devastated parts of KwaZulu-Natal province causing displacement, homelessness, illness and death. 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.
Intervention: A predictive Early Warning System (EWS) would assist communities/ health systems to prepare/manage risk during weather-related flooding. The EWS will develop two interfaces for stakeholders. These are:
- Dashboard which will be used by authorities (South African Weather Services, Disaster Management organisations and Department of Health) to assist in disaster planning and management and resource allocation;
- Mobile app that will be free to download by community members and the public, which will provide real-time information on extreme weather and disease outbreak.
These interfaces and the underpinning technologies are aids to assist authorities and individuals in developing disaster management plans, prepare for EWE’s and/or to evacuate the affected areas thereby mitigating or averting disasters. This will be supported by strengthening the health system’s resilience and ability to respond to disasters.
Outcomes:
- environmental - The EWS will monitor, classify and predict high resolution spatial-temporal rainfall (time, intensity, duration, amount and floods) based on environmental parameters such as temperature, pressure, humidify, wind speed for vulnerable communities in KZN province using low-cost sensors mobile and fixed sensors and AI. The EWS will assist in understanding the impact of flooding on vulnerable communities and identify the risks of disease outbreak.
- social - The WEATHER project will apply a Social Return On Investment (SROI) evaluation which takes account of the economic, environmental and social value of interventions combining qualitative narratives as well as quantitative/ financial measurements of real-world research. SROI analysis will be used to value the change that the EWS makes to the outcomes that matter to people and the associated social value generated when people’s lives are improved owing to the successful combination of resources, input and processes. The dashboard and free mobile app, will provide location-specific information for vulnerable communities, community leaders, disaster management and healthcare organisations improving the preparedness and response.
- financial - The creation of the predictive EWS is crucial for disaster management which can save lives and protect communities from the adverse effects of EWE’s.
- clinical
- Patient outcomes – to be determined
- Population outcomes - The immediate outcome of the WEATHER project is to develop EWS for adverse weather in the chosen research sites for the benefit of communities and government, which has the potential to be expanded to the entire province and beyond. In addition, the study will assess the climate resilience of the health system and train and mentor healthcare workers to ensure their health system is resilient and responsive in the presence of climate changes. The successful development of an early warning system and improved climate resilience of the health system will positively impact communities and the country.
Key learning point:
- To be determined over the life cycle of the WEATHER project.
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