Model-informed risk assessment and decision making for an emerging infectious disease in the Asia-Pacific region
Moss, Robert, Hickson, Roslyn I., McVernon, Jodie, McCaw, James M., Hort, Krishna, Black, Jim, Madden, John R., Tran, Nhi H., McBryde, Emma S., and Geard, Nicholas (2016) Model-informed risk assessment and decision making for an emerging infectious disease in the Asia-Pacific region. PLoS Neglected Tropical Diseases, 10 (9). e0005018. pp. 1-25.
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Abstract
Background: Effective response to emerging infectious disease (EID) threats relies on health care systems that can detect and contain localised outbreaks before they reach a national or international scale. The Asia-Pacific region contains low and middle income countries in which the risk of EID outbreaks is elevated and whose health care systems may require international support to effectively detect and respond to such events. The absence of comprehensive data on populations, health care systems and disease characteristics in this region makes risk assessment and decisions about the provision of such support challenging.
Methodology/principal findings: We describe a mathematical modelling framework that can inform this process by integrating available data sources, systematically explore the effects of uncertainty, and provide estimates of outbreak risk under a range of intervention scenarios. We illustrate the use of this framework in the context of a potential importation of Ebola Virus Disease into the Asia-Pacific region. Results suggest that, across a wide range of plausible scenarios, preemptive interventions supporting the timely detection of early cases provide substantially greater reductions in the probability of large outbreaks than interventions that support health care system capacity after an outbreak has commenced.
Conclusions/significance: Our study demonstrates how, in the presence of substantial uncertainty about health care system infrastructure and other relevant aspects of disease control, mathematical models can be used to assess the constraints that limited resources place upon the ability of local health care systems to detect and respond to EID outbreaks in a timely and effective fashion. Our framework can help evaluate the relative impact of these constraints to identify resourcing priorities for health care system support, in order to inform principled and quantifiable decision making.
| Item ID: | 46516 |
|---|---|
| Item Type: | Article (Research - C1) |
| ISSN: | 1935-2735 |
| Additional Information: | This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
| Funders: | Department of Foreign Affairs and Trade of the Australian Government (DFAT), National Health and Medical Research Council of Australia (NHMRC), Australian Research Council (ARC) |
| Projects and Grants: | NHMRC Career Development Award CDF 1061321, ARC Future Fellowship DE130100660, NHMRC Career Development Award CRE PRISM2, ARC Discovery Early Career Research Award DE 130100660, NHMRC Excellence in Policy Relevant Infectious Diseases Simulation and Mathematical Modelling CRE PRISM2, NHMRC Career Development Award CDF 1034464 |
| Date Deposited: | 23 Nov 2016 07:38 |
| FoR Codes: | 32 BIOMEDICAL AND CLINICAL SCIENCES > 3202 Clinical sciences > 320211 Infectious diseases @ 50% 44 HUMAN SOCIETY > 4407 Policy and administration > 440706 Health policy @ 50% |
| SEO Codes: | 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920109 Infectious Diseases @ 50% 92 HEALTH > 9202 Health and Support Services > 920207 Health Policy Evaluation @ 50% |
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