ISDS Annual Conference Proceedings 2012. This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License (http://creativecommons.org/licenses/by-nc/3.0/), permitting all non-commercial use, distribution, andreproduction in any medium, provided the original work is properly cited.ISDS 2012 Conference AbstractsParametric Uncertainty in Intra-Herd Foot-and-MouthDisease Epidemiological ModelsEric Nicholas Generous*Defense Systems Analysis Division, Los Alamos National Laboratory, Los Alamos, NM, USAObjectiveThe objective of this project is to understand how parametric un-certainty within intra-herd Foot-and-Mouth disease epidemiologicalmodels affects the outbreak simulations and what implications thishas on surveillance and control strategy and policy.IntroductionThe rapid transmission and poor control policy response duringrecent Foot-and-Mouth disease (FMD) outbreaks have underscoredthe need for better decision support tools. At the foundation of thesedecision support tools are the epidemiological models that are para-meterized with the data generated from pathogenesis studies of theFMD virus that contain contact transmission data. These values beingused to parameterize the model, contrary to assumption, contain asignificant amount of uncertainty, which propagates throughout themodel affecting output. To understand how parametric uncertaintymight affect output, a variety of disease transmission parameters weregenerated from contact transmission data and parameterized to anintra-herd model.MethodsData was initially collected and analyzed for papers that couldmeet several criteria: they must be contact transmission studies, theymust measure viremia (the level of virus in the blood), and they mustobserve clinical signs.For the studies that met the criteria, tables were constructed and thefollowing information from each paper was collected: serotype,strain, animal species, unique animal identifier, unit of measurementutilized by virus quantification, duration and quantity of viremia, andthe time to first report of clinical signs.Three different durations of disease states for the latent, sub-clin-ically infectious, and clinically infectious periods were generatedfrom the viremia data for each individual animal and grouped in threeways: by strain of virus, by similar experimental design, and all to-gether. Gamma, weibull, and normal distributions were fitted to thedata in each group.The distributions for each group were then used to parameterize astochastic, state transition intra-herd model. Output from the modelwas analyzed by examining the uncertainty and variance in time to50% herd infected, time to 2% herd clinically infected, and percent-age of herd infected at 2% herd clinically infected for each distribu-tion and group.ResultsThere is a lack of a standardized definition for disease state dura-tions of the Foot-and-Mouth Disease virus in the literature. As a re-sult, many different models utilize slightly differing values generatedfrom the same data. This project discovered that depending on thedefinitions used to determine the disease state durations, the modeloutput varied significantly. Additionally, durations of the disease stateperiods do not follow a normal distribution as may be assumed bymany modelers, and are more accurately described by distributionsthat allow for non-zero skewness.ConclusionsThe data being used to parameterize intra-herd Foot-and-Mouthdisease models contains a significant amount of uncertainty that cancause the model output to vary significantly. This uncertainty needsto be clearly communicated to decision makers who use results gen-erated from FMD intra-herd models and illustrates the need for moreresources to be put into addressing the issue of basic parameters suchas contact rate and disease state duration. Currently no studies havebeen conducted on the contact rate of animals on farms and the cur-rent values used for disease state durations vary drastically depend-ing on the data and methods used. Without a better understanding ofthe basic parameters, even the most advanced models will not be ac-curate.KeywordsControl; Foot and Mouth Disease; Epidemiological Model; Uncer-tainty; Parameters*Eric Nicholas GenerousE-mail: generous@lanl.govOnline Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 5(1):e147, 2013
