Cryptosporidium parvum

Project

Global waterborne pathogen modelling

Waterborne pathogens pose a health risk all over the world. In many regions quantitative information on these pathogens is essential, but unavailable. The main objective of this project is to increase our knowledge on the sources, fate and transport of waterborne pathogens by spatially explicit modelling of past, contemporary and future trends worldwide. This project focuses on the development of the global model GloWPa-Crypto.

PhD research: A Spatially Explicit Modelling Approach to Estimate Waterborne Pathogen Concentrations in the Surface Waters of the World

Waterborne pathogens pose a health risk all over the world. In many regions quantitative information on these pathogens is essential, but unavailable. The main objective of this project is to increase our knowledge on the sources, fate and transport of waterborne pathogens by spatially explicit modelling of past, contemporary and future trends worldwide. This project focuses on the development of the global model GloWPa-Crypto. The PhD project encompasses the following activities:

1.       Lessons from other large-scale models: a review of the literature on models of pathogens and nutrients in surface waters.

2.       Modelling human emissions of Cryptosporidium to surface waters. Using Bangladesh and India as case study, the human emissions part of the model is elaborated to different sanitation systems and tested in a sensitivity analysis.

3.       Modelling livestock emissions of Cryptosporidium to surface water. The livestock emissions part of the model is updated and elaborated.

4.       From emissions to concentrations in surface water. A hydrological module is developed, based on data from the VIC hydrological model. The emission models are coupled to the hydrological module to calculated Cryptosporidium concentrations in surface water.

5.         Scenario analysis. The model is applied in a scenario analysis with the de Shared Socioeconomic Pathway (SSP)scenarios.

This project will provide information on pathogen levels in data-sparse regions, identify pathogen-hotspots, identify the relative contribution of different sources, and allow projecting future concentrations. Its results may be used for monitoring programs aimed at a better quantification of the risks of waterborne pathogens based on empirical data, and as a basis for policies aimed at reducing these risks.