PhD Candidate Position Available at the Amsterdam Institute for Global Health & Development (AIGHD)
We are looking for a PhD Candidate with a strong computational background to help us with the SPRINGS Project.
This 4-year, fully funded PhD position is embedded in the EU project SPRINGS “Supporting Policy Regulations and Interventions to Negate aggravated Global diarrheal disease due to future climate Shocks”. SPRINGS aims to better understand the impact of climate change on the burden of water-borne infectious disease. It is an extensive international and multidisciplinary project, with involvement of climate scientists, microbiologists, medical professionals, and social scientists from all over the world. Diarrheal disease is a leading cause of morbidity and mortality in young children globally. Climate change threatens to reverse decades of global health progress in reducing diarrheal disease burden. The pathways by which climate hazards, including increased precipitation, flooding, and drought will alter diarrheal disease incidence in the coming years are insufficiently understood, hindering prioritization of future policies and interventions.
The objective of this PhD is to develop a model to simulate pathogen-specific diarrheal disease to assess and prioritize varied interventions to prevent climate-sensitive increases in diarrheal disease burden. The PhD project will specifically focus on mechanistic microsimulation techniques (such as spatial agent-based models) to forecast disease burden emerging from bottom-up human-pathogen, human-human, and human-environmental interactions under future climate scenarios. The model will be used to test and prioritize (based on value assessments) interventions designed to reduce diarrheal diseases across future climate shocks in varied geographic settings. The disease progression will depend on an individual’s level of exposure (based on climate, hydrological and microbial modelling by another PhD in the consortium), sensitivity and adaptive capacity based on preventive behavior from past experiences and social science surveys conducted within the consortium, alongside infrastructure, co-morbidities, care-seeking behavior, and other relevant factors. The model will capture epidemic statistics such as daily counts of new infections, symptomatic, mortality, morbidity, QALY overall and by context-specific demographic groups.
For more information, view the job announcement.
