Group | Mathematical Epidemiology

The research group Mathematical Epidemiology focuses on the intersection between mathematics, epidemiology and ecology. We combine field and laboratory data with theoretical and computational models to improve understanding of population, infection and disease dynamics, focusing on malaria and neglected tropical diseases.

Opisthorchis Modelling

By developing models of the transmission dynamics of food-borne trematodes, such as liver flukes, we elucidate the role of reservoirs hosts in maintaining transmission in rural areas of Lao PDR, and determine the impact of intervention strategies on reducing morbidity. Read more about the SNF project

NTD Modelling Consortium

As members of the Neglected Tropical Diseases Modelling Consortium, we advice global bodies and national control programs on the feasibility and ideal strategies towards elimination targets for human African trypanosomiasis. Further information and  link to a study on Assessing Strategies against Gambiense Sleeping Sickness through Mathematical Modeling.

Fairbanks E.L et al. Inference for entomological semi-field experiments: fitting a mathematical model assessing personal and community protection of vector-control interventions. Comput Biol Med. 2024;168:107716. DOI: 10.1016/j.compbiomed.2023.107716

Fairbanks E.L et al. Evaluating human landing catches as a measure of mosquito biting and the importance of considering additional modes of action. Sci Rep. 2024;14:11476. DOI: 10.1038/s41598-024-61116-0

Kamber L, Bürli C, Harbrecht H, Odermatt P, Sayasone S, Chitnis N. Modeling the persistence of Opisthorchis viverrini worm burden after mass-drug administration and education campaigns with systematic adherence. PLoS Negl Trop Dis. 2024;18(2):e0011362. DOI: 10.1371/journal.pntd.0011362

Newby G et al. Correction: Testing and treatment for malaria elimination: a systematic review. Malar J. 2024;23:63. DOI: 10.1186/s12936-024-04861-x

Vasconcelos A et al. Accelerating progress towards the 2030 neglected tropical diseases targets: How can quantitative modeling support programmatic decisions?. Clin Infect Dis. 2024;78(Suppl. 2):S83-S92. DOI: 10.1093/cid/ciae082