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Individual-Based Simulation Models of HIV Transmission: Reporting Quality and Recommendations

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  • Nadia N Abuelezam
  • Kathryn Rough
  • George R Seage III

Abstract

Background: Individual-based modeling is a growing technique in the HIV transmission and prevention literature, but insufficient attention has been paid to formally evaluate the quality of reporting in this field. We present reporting recommendations for individual-based models for HIV treatment and prevention, assess the quality of reporting in the existing literature, and comment on the contribution of this model type to HIV policy and prediction. Methods: We developed reporting recommendations for individual-based HIV transmission mathematical models, and through a systematic search, used them to evaluate the reporting in the existing literature. We identified papers that employed individual-based simulation models and were published in English prior to December 31, 2012. Articles were included if the models they employed simulated and tracked individuals, simulated HIV transmission between individuals in a particular population, and considered a particular treatment or prevention intervention. The papers were assessed with the reporting recommendations. Findings: Of 214 full text articles examined, 32 were included in the evaluation, representing 20 independent individual-based HIV treatment and prevention mathematical models. Manuscripts universally reported the objectives, context, and modeling conclusions in the context of the modeling assumptions and the model’s predictive capabilities, but the reporting of individual-based modeling methods, parameterization and calibration was variable. Six papers discussed the time step used and one discussed efforts to maintain internal validity in coding. Conclusion: Individual-based models represent detailed HIV transmission processes with the potential to contribute to inference and policy making for many different regions and populations. The rigor in reporting of assumptions, methods, and calibration of individual-based models focused on HIV transmission and prevention varies greatly. Higher standards for reporting of statistically rigorous calibration and model assumption testing need to be implemented to increase confidence in existing and future modeling results.

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  • Nadia N Abuelezam & Kathryn Rough & George R Seage III, 2013. "Individual-Based Simulation Models of HIV Transmission: Reporting Quality and Recommendations," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-1, September.
    • Handle: RePEc:plo:pone00:0075624
    DOI: 10.1371/journal.pone.0075624
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    Cited by:

    1. Eleanor J. Murray & James M. Robins & George R. Seage III & Kenneth A. Freedberg & Miguel A. Hernán, 2020. "The Challenges of Parameterizing Direct Effects in Individual-Level Simulation Models," Medical Decision Making, , vol. 40(1), pages 106-111, January.
    2. Matthew R Behrend & María-Gloria Basáñez & Jonathan I D Hamley & Travis C Porco & Wilma A Stolk & Martin Walker & Sake J de Vlas & for the NTD Modelling Consortium, 2020. "Modelling for policy: The five principles of the Neglected Tropical Diseases Modelling Consortium," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 14(4), pages 1-17, April.
    3. C Marijn Hazelbag & Jonathan Dushoff & Emanuel M Dominic & Zinhle E Mthombothi & Wim Delva, 2020. "Calibration of individual-based models to epidemiological data: A systematic review," PLOS Computational Biology, Public Library of Science, vol. 16(5), pages 1-17, May.
    4. Eleanor J. Murray, 2020. "Epidemiology's Time of Need: COVID-19 Calls for Epidemic-Related Economics," Journal of Economic Perspectives, American Economic Association, vol. 34(4), pages 105-120, Fall.

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