Prior MIDAS initiatives have developed agent-based models of infectious disease that contain sufficient biologic, behavioral and geographically detailed data to assess the impact of mitigation strategies on epidemic outcomes. Local, state and national policy makers have used tools based on these models to evaluate mitigation strategies in epidemic influenza and other infectious diseases. However, these tools have not yet provided policy makers with fully integrated evaluations across all dimensions of interest, nor have they provided comprehensive measures of the confidence surrounding model results. When making decisions regarding potential or real infectious disease threats, policy makers must balance a wide array of agendas and priorities which extend beyond the epidemic outcomes of number of cases and the subsequent mortality and morbidity of the disease. Through multiple interactions with policy makers, we characterized and aggregated these into three measurable dimensions represented in the """"""""LEO"""""""" acronym: Legal and policy specifications. Economic resources and assets, and Operational performance. Although we have conducted investigations that used components of this framework to evaluate different strategies, these evaluations were conducted outside of the simulation model of disease. Therefore, there are two overarching goals of the Policy Methods project in this application: 1) provide integrated model-based mechanisms to evaluate the implementation of disease mitigation strategies, including the laws and policies that support them, the economic costs and savings they produce, and the operational capabilities they require;and 2) provide estimates of the variability of model results and the value of reducing model uncertainty to increase surety that appropriate mitigation decisions are made. This work will develop, in collaboration with the external policy makers involved in the Policy Studies component of this application, the methods and tools to inform infectious disease decision making across a broad array of clinical, economic, legal and social concerns.

Public Health Relevance

Successful completion of this work will provide a platform that allows policy makers to evaluate potential mitigation strategies across a much wider range of policy-relevant outcomes, including geographically specific detail regarding the impact of mitigation strategies on epidemic outcomes, economic consequences, and the legal and operational ability of health care and public health organizations to respond to threats.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Specialized Center--Cooperative Agreements (U54)
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Special Emphasis Panel (ZGM1-BBCB-5 (MI))
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University of Pittsburgh
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Brooks, Logan C; Farrow, David C; Hyun, Sangwon et al. (2018) Nonmechanistic forecasts of seasonal influenza with iterative one-week-ahead distributions. PLoS Comput Biol 14:e1006134
Biggerstaff, Matthew; Johansson, Michael; Alper, David et al. (2018) Results from the second year of a collaborative effort to forecast influenza seasons in the United States. Epidemics 24:26-33
EspaƱa, Guido; Grefenstette, John; Perkins, Alex et al. (2018) Exploring scenarios of chikungunya mitigation with a data-driven agent-based model of the 2014-2016 outbreak in Colombia. Sci Rep 8:12201
Paternina-Caicedo, Angel; Driessen, Julia; Roberts, Mark et al. (2018) Heterogeneity Between States in the Health and Economic Impact of Measles Immunization in the United States. Open Forum Infect Dis 5:ofy137
Althouse, Benjamin M; Guerbois, Mathilde; Cummings, Derek A T et al. (2018) Role of monkeys in the sylvatic cycle of chikungunya virus in Senegal. Nat Commun 9:1046
Buchanich, Jeanine M; Doerfler, Shannon M; Lann, Michael F et al. (2018) Improvement in racial disparities in years of life lost in the USA since 1990. PLoS One 13:e0194308
Lauer, Stephen A; Sakrejda, Krzysztof; Ray, Evan L et al. (2018) Prospective forecasts of annual dengue hemorrhagic fever incidence in Thailand, 2010-2014. Proc Natl Acad Sci U S A 115:E2175-E2182
Brownwright, Tenley K; Dodson, Zan M; van Panhuis, Willem G (2017) Spatial clustering of measles vaccination coverage among children in sub-Saharan Africa. BMC Public Health 17:957
Kirsch, Thomas D; Moseson, Heidi; Massaquoi, Moses et al. (2017) Impact of interventions and the incidence of ebola virus disease in Liberia-implications for future epidemics. Health Policy Plan 32:205-214
Grubaugh, Nathan D; Ladner, Jason T; Kraemer, Moritz U G et al. (2017) Genomic epidemiology reveals multiple introductions of Zika virus into the United States. Nature 546:401-405

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