MODCOVID - Using model-based evidence to optimise medical intervention profiles and disease management strategies for COVID-19 control

During the current COVID-19 pandemic governments have imposed varying social-distance measures, and since 2021 vaccines, to reduce infection incidence and associated disease burden of coronavirus infectious disease (COVID- 19). Guidance is needed to design optimal profiles of medical interventions and deployment schedules of control strategies to suppress transmission and avert mortality, especially in the face of new variants of concern which may evade immunity (from natural infections or vaccines). Mathematical models of SARS-CoV-2  transmission dynamics can efficiently estimate the quantitative impact of interventions from available evidence on disease progression, transmission, host immunity, and health system interactions.

In this project, we have developed and operationalized a model-based decision framework to inform the optimal properties of therapeutic and delivery strategies of new tools to achieve prevention and control of COVID-19 at the population and individual level. The Disease Modelling Unit has developed a new individual-based mathematical model of SARS-CoV-2 dynamics, OpenCOVID, to assess the impact of a range of prevention measures, vaccines, and medical interventions to improve the response and minimise cases, hospitalisations, and deaths in Switzerland and abroad. Our model OpenCOVID has been applied to support Swiss decision-making on vaccine rollouts and measures, as well as to predict the public health impact of new emerging SARS-Cov-2 variants of concern.

Our model is being used to inform future strategies for ongoing vaccination and response efforts as the world strives to recover from the pandemic's devastating health and economic effects.

Specifically, we will (i) Quantitatively investigate and optimize diagnostics and testing/response strategies as well as new treatments including small molecule therapeutics, biologics, vaccines, and immune-enhancement technologies; (ii) Estimate and compare individual and population health consequences of alternative diagnostics, and pharmaceutical strategies.

Public Health
Medical Interventions


Melissa Penny

Professor Melissa Penny, PhD, PD
Head of Unit


Project Facts