Abstract
BackgroundIndividual-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.MethodsWe 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.FindingsOf 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.ConclusionIndividual-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.
Highlights
HIV transmission is influenced by numerous interactions between the biology of the virus and the behavior of individuals
The dynamics of transmission, treatment, and prevention are increasingly being represented by infectious disease mathematical models, which are accepted in the HIV literature as powerful predictive tools that motivate policy and inform clinical trial design [1]
The guidelines highlight the necessary components of general mathematical model reporting and the specific issues related to individual-based model reporting
Summary
HIV transmission is influenced by numerous interactions between the biology of the virus and the behavior of individuals. Individual-based simulations increase flexibility by allowing for heterogeneous individuals, interactions between individuals, correspondence to real life data, and a representation of the environment with which individuals interact [2,3] This model type allows individuals to have rationality in their actions (as opposed to completely random behavior) and simulates learning at individual and population levels [2]. We apply these guidelines to existing HIV transmission and prevention individual-based models (found through a systematic search strategy) to assess the quality of reporting for this model type We hope these guidelines will be a starting point for discussion with modelers to form standardized reporting guidelines for the united goal of improving the quality of the individual-based HIV modeling literature, and increasing their use among policy making consumers
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