STDSIM: A Microsimulation Model for Decision Support in the Control of HIV and Other STDs

Bakker, Roel; Korenromp, Eline L.; Meester, Elisabeth I.; Ploeg, C. van der; Voeten, Hélène; Vliet, C. van; Vlas, Sake De; Habbema, J. Dik F.

doi:10.1097/00007435-200011000-00029

Cited by 6 publications

(7 citation statements)

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“…Several simulation tools (i.e. CEPAC [34], EMOD [35] HIV-CDM [36], MicroCOSM [37], PATH [38], STDSIM [39] and TITAN [40]) were used in the articles modelling HIV. Similarly, two platforms (i.e.…”

Section: Computational Aspects and The Use Of Platformsmentioning

confidence: 99%

Calibration of individual-based models to epidemiological data: A systematic review

et al. 2020

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Individual-based models (IBMs) informing public health policy should be calibrated to data and provide estimates of uncertainty. Two main components of model-calibration methods are the parameter-search strategy and the goodness-of-fit (GOF) measure; many options exist for each of these. This review provides an overview of calibration methods used in IBMs modelling infectious disease spread. We identified articles on PubMed employing simulation-based methods to calibrate IBMs informing public health policy in HIV, tuberculosis, and malaria epidemiology published between 1 January 2013 and 31 December 2018. Articles were included if models stored individual-specific information, and calibration involved comparing model output to population-level targets. We extracted information on parameter-search strategies, GOF measures, and model validation. The PubMed search identified 653 candidate articles, of which 84 met the review criteria. Of the included articles, 40 (48%) combined a quantitative GOF measure with an algorithmic parameter-search strategyeither an optimisation algorithm (14/40) or a sampling algorithm (26/40). These 40 articles varied widely in their choices of parameter-search strategies and GOF measures. For the remaining 44 (52%) articles, the parameter-search strategy could either not be identified (32/44) or was described as an informal, non-reproducible method (12/44). Of these 44 articles, the majority (25/44) were unclear about the GOF measure used; of the rest, only five quantitatively evaluated GOF. Only a minority of the included articles, 14 (17%) provided a rationale for their choice of model-calibration method. Model validation was reported in 31 (37%) articles. Reporting on calibration methods is far from optimal in epidemiological modelling studies of HIV, malaria and TB transmission dynamics. The adoption of better documented, algorithmic calibration methods could improve both reproducibility and the quality of inference in model-based epidemiology. There is a need for research comparing the performance of calibration methods to inform decisions about the parameter-search strategies and GOF measures.

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Section: Computational Aspects and The Use Of Platformsmentioning

confidence: 99%

Calibration of individual-based models to epidemiological data: A systematic review

et al. 2020

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“…For example, in EMOD, males and females are placed in a separate queue, where they stay for a predefined period, after which they form a relationship 7 . In STDsim, the order of going out to search for a partner and for being available for a relationship are both determined by stochastic processes 8 .…”

Section: Introductionmentioning

confidence: 99%

SimpactCyan 1.0: An Open-source Simulator for Individual-Based Models in HIV Epidemiology with R and Python Interfaces

Liesenborgs

Hendrickx

Kuylen

et al. 2019

Sci Rep

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SimpactCyan is an open-source simulator for individual-based models in HIV epidemiology. Its core algorithm is written in C++ for computational efficiency, while the R and Python interfaces aim to make the tool accessible to the fast-growing community of R and Python users. Transmission, treatment and prevention of HIV infections in dynamic sexual networks are simulated by discrete events. A generic “intervention” event allows model parameters to be changed over time, and can be used to model medical and behavioural HIV prevention programmes. First, we describe a more efficient variant of the modified Next Reaction Method that drives our continuous-time simulator. Next, we outline key built-in features and assumptions of individual-based models formulated in SimpactCyan, and provide code snippets for how to formulate, execute and analyse models in SimpactCyan through its R and Python interfaces. Lastly, we give two examples of applications in HIV epidemiology: the first demonstrates how the software can be used to estimate the impact of progressive changes to the eligibility criteria for HIV treatment on HIV incidence. The second example illustrates the use of SimpactCyan as a data-generating tool for assessing the performance of a phylodynamic inference framework.

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“…While some modelling tools (e.g. STDSIM for simulating transmission of HIV and other Sexually Transmitted Diseases 11 ) are not open source, other IBMs (e.g. EMOD 14 ) are relatively difficult to modify.…”

Section: Introductionmentioning

confidence: 99%

“…A large amount of general frameworks for individual-based simulations have been developed in the last decades. These platforms vary widely in terms of platform properties, usability, operating ability, pragmatics and security management, making [5][6][7] GEMFsim continuous, Gillespie algorithm static 8 FAVITES continuous, Gillespie algorithm static 9 EpiModel discrete dynamic 10 STDsim discrete dynamic 11 NetLogo discrete dynamic 12,13 EMOD discrete dynamic 14 HIV-CDM discrete dynamic 15 MicroCOSM discrete dynamic 16 Path 2.0 discrete dynamic (through RNetLogo) 17 TITAN discrete dynamic 18 Table 1. Functional and structural differences between SimpactCyan and existing tools for IBM studies in HIV epidemiology.…”

Section: Introductionmentioning

confidence: 99%

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SimpactCyan 1.0: An Open-source Simulator for Individual-Based Models in HIV Epidemiology with R and Python Interfaces

Liesenborgs

Hendrickx

Kuylen

et al. 2018

Preprint

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SimpactCyan is an open-source simulator for individual-based models in HIV epidemiology. Its core algorithm is written in C++ for computational efficiency, while the R and Python interfaces aim to make the tool accessible to the fast-growing community of R and Python users. Transmission, treatment and prevention of HIV infections in dynamic sexual networks are simulated by discrete events. A generic "intervention" event allows model parameters to be changed over time, and can be used to model medical and behavioural HIV prevention programmes. First, we describe a more efficient variant of the modified Next Reaction Method that drives our continuous-time simulator. Next, we outline key built-in features and assumptions of individual-based models formulated in SimpactCyan, and provide code snippets for how to formulate, execute and analyse models in SimpactCyan through its R and Python interfaces. Lastly, we give two examples of applications in HIV epidemiology: the first demonstrates how the software can be used to estimate the impact of progressive changes to the eligibility criteria for HIV treatment on HIV incidence. The second example illustrates the use of SimpactCyan as a data-generating tool for assessing the performance of a phylodynamic inference framework. 2/1610/16

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STDSIM: A Microsimulation Model for Decision Support in the Control of HIV and Other STDs

Cited by 6 publications

References 0 publications

Calibration of individual-based models to epidemiological data: A systematic review

Calibration of individual-based models to epidemiological data: A systematic review

SimpactCyan 1.0: An Open-source Simulator for Individual-Based Models in HIV Epidemiology with R and Python Interfaces

SimpactCyan 1.0: An Open-source Simulator for Individual-Based Models in HIV Epidemiology with R and Python Interfaces

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