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Assessing the public health impact of tolerance-based therapies with mathematical models.
- Source :
- PLoS Computational Biology; 5/4/2018, Vol. 14 Issue 5, p1-14, 14p, 1 Diagram, 2 Graphs
- Publication Year :
- 2018
-
Abstract
- Disease tolerance is a defense strategy against infections that aims at maintaining host health even at high pathogen replication or load. Tolerance mechanisms are currently intensively studied with the long-term goal of exploiting them therapeutically. Because tolerance-based treatment imposes less selective pressure on the pathogen it has been hypothesised to be “evolution-proof”. However, the primary public health goal is to reduce the incidence and mortality associated with a disease. From this perspective, tolerance-based treatment bears the risk of increasing the prevalence of the disease, which may lead to increased mortality. We assessed the promise of tolerance-based treatment strategies using mathematical models. Conventional treatment was implemented as an increased recovery rate, while tolerance-based treatment was assumed to reduce the disease-related mortality of infected hosts without affecting recovery. We investigated the endemic phase of two types of infections: acute and chronic. Additionally, we considered the effect of pathogen resistance against conventional treatment. We show that, for low coverage of tolerance-based treatment, chronic infections can cause even more deaths than without treatment. Overall, we found that conventional treatment always outperforms tolerance-based treatment, even when we allow the emergence of pathogen resistance. Our results cast doubt on the potential benefit of tolerance-based over conventional treatment. Any clinical application of tolerance-based treatment of infectious diseases has to consider the associated detrimental epidemiological feedback. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1553734X
- Volume :
- 14
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- PLoS Computational Biology
- Publication Type :
- Academic Journal
- Accession number :
- 129454359
- Full Text :
- https://doi.org/10.1371/journal.pcbi.1006119