Unit | Infectious Disease Modelling

The Infectious Disease Modelling unit makes use of techniques of computational sciences, statistics and mathematical modelling to better understand and to address contemporary issues in infectious disease and global health. Our main projects are on malaria, and other vector-borne diseases. We focus on understanding transmission dynamics, pathogenesis, and the impacts of health interventions in the contexts of real-world health systems.

Impact on Infectious Diseases

Our research helps to identify the potential of new innovations, such as new drugs or ways of killing mosquitoes. We investigate different strategies, and ways of allocating resources in order to achieve effective and equitable impact on infectious diseases.  We work closely with other major research institutions in low- and middle-income countries and in Switzerland. Our audience includes researchers, global health donors and public health policy makers.

Malaria Modelling Ressource Centre

The Malaria Modelling Resource Centre of this unit provides an outreach and response capacity enabling us to advise partners including malaria control programmes on the likely effects of different malaria interventions and integrated control strategies. This contributes to the Swiss TPH role as a WHO Collaborating Centre for Modelling, Monitoring and Training for Malaria Control and Elimination.

Briët O et al. Attrition, physical integrity and insecticidal activity of long-lasting insecticidal nets in sub-Saharan Africa and modelling of their impact on vectorial capacity. Malar J. 2020;19:310. DOI: 10.1186/s12936-020-03383-6

Burgert L et al. Ensemble modeling highlights importance of understanding parasite-host behavior in preclinical antimalarial drug development. Sci Rep. 2020;10:4410. DOI: 10.1038/s41598-020-61304-8

Camponovo F et al. Proteome-wide analysis of a malaria vaccine study reveals personalized humoral immune profiles in Tanzanian adults. Elife. 2020;9:e53080. DOI: 10.7554/eLife.53080

Castaño M.S, Aliee M, Mwamba Miaka E, Keeling M.J, Chitnis N, Rock K.S. Screening strategies for a sustainable endpoint for gambiense sleeping sickness. J Infect Dis. 2020;221(Suppl. 5):S539-S545. DOI: 10.1093/infdis/jiz588

Castaño M.S et al. Assessing the impact of aggregating disease stage data in model predictions of human African trypanosomiasis transmission and control activities in Bandundu province (DRC). PLoS Negl Trop Dis. 2020;14:e0007976. DOI: 10.1371/journal.pntd.0007976