Simulating antiviral-based interventions for mitigating epidemic outbreaks

An emerging infectious disease is a potential threat to humanity, health systems, and the economies of countries around the world.

Control measures based on city lockdowns, isolation of infected individuals, and contact tracing are commonly used to reduce the number of cases and delay the epidemic peak. However, the recent COVID-19 pandemic demonstrated that such interventions might be inadequate to control local outbreaks effectively, especially when vaccines are unavailable or immune-evasive variants arise. In addition, strict non-pharmaceutical measures are associated with profound social and economic disruptions, resulting in a lack of long-term sustainability. Therefore, additional interventions must be considered to achieve an optimal trade-off between outbreak control and intervention stringency. Antiviral drugs have been shown to reduce the viral shedding period and the viral peak, suggesting that their administration may decrease the likelihood of disease transmission. However, it is unclear how an antiviral-based strategy impacts population-level transmission and how it should be combined with non-pharmaceutical interventions. To gain insights into this, we developed a simulation model in which antivirals are administered in combination with contact tracing and isolation of infectious individuals, showing that the use of antivirals can further decrease both the attack rate and the number of cases at peak.
The developed simulation model has mainly three novel aspects compared to similar tools reported in the scientific literature. First, infection progression and viral load dynamics are simulated for each infected individual. Second, the efficacy of the antiviral drug is set to depend on the time of drug administration, which can vary with respect to the individual progression of the infection. In addition, the administration of antivirals is combined with contact tracing and testing.
Governments and public health officials can use the simulation model to efficiently define the type and level of severity of interventions needed to mitigate emerging outbreaks. In addition, pharmaceutical manufacturers can use the simulation tool in the development phase of the antiviral compound. By varying drug characteristics such as route of administration and drug efficacy, the impact of a specific compound in reducing infections at the population level can be simulated.


Andrea Torneri(1), Pieter Libin(1,2,3), Joris Vanderlocht(1,4), Niel Hens(1,5)


Interuniversity Institute of Biostatistics and statistical Bioinformatics, Data Science Institute, Hasselt University (1), Artificial Intelligence Lab, Department of Computer Science, Vrije Universiteit Brussel (2), KU Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, University of Leuven (3), Bioqube Ventures (4), Centre for Health Economic Research and Modelling Infectious Diseases, University of Antwerp (5)

Presenting author

Emiliano Mancini, Doctor-Navorser, Hasselt University
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