Health system resilience under climate shocks: Modelling patient access disruptions and health outcomes during flood events

Supervisors: Dr Patrick Fahr, Dr Luke Allen, Dr Jesus Lizana, Dr Nevan Fučkar 

Flooding is among the most frequent and destructive climate hazards, increasingly disrupting access to health services, particularly in low-lying, underserved, or infrastructurally fragile regions. This DPhil project will develop a systems-based modelling framework to assess how flood events impede physical access to health facilities through damage to road networks and infrastructure, and how this, in turn, affects patient flow, clinic functionality, and ultimately, health outcomes. The student will design a simulation model, potentially combining geospatial network analysis, discrete-event simulation, and health impact estimation, to evaluate: (1) changes in travel time and service catchment areas under different flood scenarios; (2) impacts on patient attendance, service capacity, and turnover; and (3) the resulting burden of avoidable morbidity and mortality due to foregone or delayed care. Methodological components may include GIS-based accessibility modelling (e.g. travel time surfaces, catchment delineation), network disruption analysis using flood and road layers, and discrete-event simulation to examine clinic-level operational dynamics. To estimate health consequences, the project may apply burden of disease methods, including DALYs, to quantify losses associated with reduced access.

A further component of the project will assess potential damage to the built environment, including roads, bridges, and health facilities, using flood hazard maps, land use data, and infrastructure vulnerability models. This component will be developed in collaboration with colleagues from the Department of Engineering and the Environmental Change Institute at the University of Oxford, who bring expertise in climate risk modelling and infrastructure resilience. Incorporating this perspective will enable a more integrated assessment of system-wide resilience and support the prioritisation of infrastructure investments or protective measures in flood-prone settings.

The analysis may focus on one or more health conditions where delays in access significantly affect outcomes. A particular emphasis is encouraged on maternal and neonatal emergencies, where timely access to skilled care is critical for survival. Other relevant areas might include febrile illnesses in children or chronic condition management (e.g. dialysis or insulin access). The project will leverage open data sources such as OpenStreetMap, remote sensing flood maps, and population distribution datasets, to simulate access barriers and patient flows. Ideally, the analysis will be grounded in a real-world case study, with a focus on settings where maternal and newborn health outcomes are a core concern.

Preferred applicant background/skills: The ideal candidate will have a strong background in quantitative, systems-based research, with demonstrated skills in areas such as geospatial analysis, simulation modelling, or environmental data science. A Master’s degree in a relevant discipline such as health geography, environmental engineering, public health, data science, or health systems research is expected. Familiarity with tools such as GIS, R or Python, and modelling techniques (e.g., discrete-event simulation, network analysis, or accessibility modelling) is highly desirable. Experience working with spatial datasets, remote sensing, or infrastructure risk assessments would be advantageous. The candidate should be analytically strong, interdisciplinary in mindset, and motivated to work at the intersection of climate adaptation, health systems resilience, and infrastructure planning. A willingness to engage with real-world case studies and collaborate across disciplines is essential.