Unit | Disease Modelling

The Disease Modelling unit develops and uses approaches in computational sciences, statistics and mathematical modelling to understand and address contemporary issues in infectious diseases and global health. We work in the areas of malaria and neglected tropical diseases.

We are an interdisciplinary group of researchers that apply mathematical models to understand disease and to inform public health decision-making. We design data-, biology- and epidemiologically-informed mathematical models covering aspects of disease dynamics, population transmission, vector life-cycles, health systems access and intervention effects.

Understanding Disease Dynamics and Informing Decision Making

We use these models to understand disease dynamics and transmission, and to estimate impacts of health interventions at individual or population level in the context of real-world health systems. We contribute epidemiological insights and evidence to inform public health decision making. We aim to increase the impact of interventions, to eliminate, prevent and treat infectious diseases. We work closely with other research institutions in Switzerland and abroad, as well as global health donors and public health policy stakeholders

Nakul Chitnis

Nakul Chitnis

PhD, PD Dr.

Head of Unit ad. int.

Core Malaria Software for Modellers Worldwide

Core to our modelling work is the development and use of an individual-based model of malaria transmission dynamics known as OpenMalaria. This model is an open-source tool for simulating the dynamics of malaria transmission and epidemiology, and the impact of interventions on health and economic outcomes. The model can simulate malaria in village or district size human populations, and has been used to address questions on disease dynamics and the use of interventions. Developed and maintained by the Disease Modelling Unit of Swiss TPH, our OpenMalaria model is used by a wide range of modellers worldwide. A new collaboration with the Bill & Melinda Gates Foundation supports the improvement and maintenance of OpenMalaria as well as the development of new mathematical malaria models. This project will provide model-based evidence for the Foundation and key partners towards improved investment and decision-making for better malaria control and elimination. Read more

Evaluating New Vector Control Tools

There has been substantial progress in reducing malaria transmission in the Greater Mekong Subregion. However, progress has stalled with reports of increase in the number of cases, multidrug-resistant malaria, and pyrethroid-resistant mosquitoes. The risk of infection is greatest among mobile and migrant populations. Many of the dominant malaria vectors in this subregion feed and rest outdoors, yet there is limited available protection against mosquito biting outdoors for at-risk populations. To address these pressing challenges, the University of California, San Francisco, Malaria Elimination Initiative in partnership with the University of Notre Dame, IVCC, Swiss TPH, and a consortium of project partners propose to evaluate new vector control tools that aim to reduce human exposure to mosquito bites outdoors. Read more

Braunack-Mayer L et al. Design and selection of drug properties to increase the public health impact of next-generation seasonal malaria chemoprevention: a modelling study. Lancet Glob Health. 2024;12(3):e478-e490. DOI: 10.1016/s2214-109x(23)00550-8

De Salazar P.M et al. Severe outcomes of malaria in children under time-varying exposure. Nat Commun. 2024;15:4069. DOI: 10.1038/s41467-024-48191-7

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, B├╝rli 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