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Comparison of two individual-based model simulators for HIV epidemiology in a population with HSV-2 using as case study Yaoundé-Cameroon, 1980-2005

View ORCID ProfileDiana M Hendrickx, View ORCID ProfileJoão Dinis Sousa, View ORCID ProfilePieter J.K. Libin, View ORCID ProfileWim Delva, View ORCID ProfileJori Liesenborgs, View ORCID ProfileNiel Hens, View ORCID ProfileViktor Müller, View ORCID ProfileAnne-Mieke Vandamme
doi: https://doi.org/10.1101/637389
Diana M Hendrickx
1I-BioStat, Data Science Institute, Hasselt University, Hasselt, Belgium
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  • For correspondence: diana.hendrickx@uhasselt.be
João Dinis Sousa
2KU Leuven – University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, B-3000, Leuven, Belgium
3Global Health and Tropical Medicine (GHTM), Unidade de Microbiologia Médica, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisbon, Portugal
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Pieter J.K. Libin
2KU Leuven – University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, B-3000, Leuven, Belgium
4Artificial Intelligence Lab, Department of Computer Science, Vrije Universiteit Brussel, 1050 Brussels, Belgium
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Wim Delva
1I-BioStat, Data Science Institute, Hasselt University, Hasselt, Belgium
2KU Leuven – University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, B-3000, Leuven, Belgium
5The South African Department of Science and Technology-National Research Foundation (DST-NRF) Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
6Department of Global Health, Faculty of Medicine and Health, Stellenbosch University, Stellenbosch, South Africa
7International Centre for Reproductive Health, Ghent University, Ghent, Belgium
8School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
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Jori Liesenborgs
9Expertise Centre for Digital Media, Hasselt University – tUL, Diepenbeek, Belgium
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Niel Hens
1I-BioStat, Data Science Institute, Hasselt University, Hasselt, Belgium
10Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
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Viktor Müller
11Institute of Biology, Eötvös Loránd University, Budapest, Hungary
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Anne-Mieke Vandamme
2KU Leuven – University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, B-3000, Leuven, Belgium
3Global Health and Tropical Medicine (GHTM), Unidade de Microbiologia Médica, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisbon, Portugal
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ABSTRACT

Model comparisons have been widely used to guide intervention strategies to control infectious diseases. Agreement between different models is crucial for providing robust evidence for policy-makers because differences in model properties can influence their predictions. In this study, we compared models implemented by two individual-based model simulators for HIV epidemiology in a population with Herpes simplex virus type 2 (HSV-2). For each model simulator, we constructed four models, starting from a simplified basic model and stepwise including more model complexity. For the resulting eight models, the predictions of the impact of behavioural interventions on the HIV epidemic in Yaoundé (Cameroon) were compared. The results show that differences in model assumptions and model complexity can influence the size of the predicted impact of the intervention, as well as the predicted qualitative behaviour of the HIV epidemic after the intervention. Moreover, two models that agree in their predictions of the HIV epidemic in the absence of intervention can have different outputs when predicting the impact of interventions. Without additional data, it is impossible to determine which of these two models is the most reliable. These findings highlight the importance of making more data available for the calibration and validation of epidemiological models.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted December 06, 2020.
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Comparison of two individual-based model simulators for HIV epidemiology in a population with HSV-2 using as case study Yaoundé-Cameroon, 1980-2005
Diana M Hendrickx, João Dinis Sousa, Pieter J.K. Libin, Wim Delva, Jori Liesenborgs, Niel Hens, Viktor Müller, Anne-Mieke Vandamme
bioRxiv 637389; doi: https://doi.org/10.1101/637389
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Comparison of two individual-based model simulators for HIV epidemiology in a population with HSV-2 using as case study Yaoundé-Cameroon, 1980-2005
Diana M Hendrickx, João Dinis Sousa, Pieter J.K. Libin, Wim Delva, Jori Liesenborgs, Niel Hens, Viktor Müller, Anne-Mieke Vandamme
bioRxiv 637389; doi: https://doi.org/10.1101/637389

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