Please use this identifier to cite or link to this item: https://covid-19.conacyt.mx/jspui/handle/1000/286
Calibration of individual-based models to epidemiological data: a systematic review
Jonathan Dushoff
Emanuel M Dominic
Zinhle E Mthombothi
Wim Delva
C. Marijn Hazelbag
Novel Coronavirus
Acceso Abierto
Atribución-NoComercial-SinDerivadas
10.1101/19006056
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 strategy - either 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. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement WD was supported by grant 12L5816N from the Research Foundation – Flanders (FWO). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ### Author Declarations All relevant ethical guidelines have been followed and any necessary IRB and/or ethics committee approvals have been obtained. Yes All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes Any clinical trials involved have been registered with an ICMJE-approved registry such as ClinicalTrials.gov and the trial ID is included in the manuscript. Not Applicable I have followed all appropriate research reporting guidelines and uploaded the relevant Equator, ICMJE or other checklist(s) as supplementary files, if applicable. Not Applicable All relevant data are within the manuscript and its Supporting Information files.
Cold Spring Harbor Laboratory Press
2020
Preimpreso
https://www.medrxiv.org/content/10.1101/19006056v2
Inglés
VIRUS RESPIRATORIOS
Appears in Collections:Artículos científicos

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