Concurrent assessment of epidemiological and operational uncertainties for optimal outbreak control: Ebola as a case study

Shou-Li Li, Matthew J. Ferrari, Ottar N. Bjornstad, Michael C. Runge, Christopher J. Fonnesbeck, Michael J. Tildesley, David Pannell, Katriona Shea

Research output: Contribution to journalArticle

Abstract

Determining how best to manage an infectious disease outbreak may be hindered by both epidemiological uncertainty (i.e. about epidemiological processes) and operational uncertainty (i.e. about the effectiveness of candidate interventions). However, these two uncertainties are rarely addressed concurrently in epidemic studies. We present an approach to simultaneously address both sources of uncertainty, to elucidate which source most impedes decision-making. In the case of the 2014 West African Ebola outbreak, epidemiological uncertainty is represented by a large ensemble of published models. Operational uncertainty about three classes of interventions is assessed for a wide range of potential intervention effectiveness. We ranked each intervention by caseload reduction in each model, initially assuming an unlimited budget as a counterfactual. We then assessed the influence of three candidate cost functions relating intervention effectiveness and cost for different budget levels. The improvement in management outcomes to be gained by resolving uncertainty is generally high in this study; appropriate information gain could reduce expected caseload by more than 50%. The ranking of interventions is jointly determined by the underlying epidemiological process, the effectiveness of the interventions and the size of the budget. An epidemiologically effective intervention might not be optimal if its costs outweigh its epidemiological benefit. Under higher-budget conditions, resolution of epidemiological uncertainty is most valuable. When budgets are tight, however, operational and epidemiological uncertainty are equally important. Overall, our study demonstrates that significant reductions in caseload could result from a careful examination of both epidemiological and operational uncertainties within the same modelling structure. This approach can be applied to decision-making for the management of other diseases for which multiple models and multiple interventions are available.

Original languageEnglish
Article number20190774
Number of pages10
JournalPhilosophical Transactions of the Royal Society B - Biological Sciences
Volume286
Issue number1905
DOIs
Publication statusPublished - 19 Jun 2019

Cite this

Li, Shou-Li ; Ferrari, Matthew J. ; Bjornstad, Ottar N. ; Runge, Michael C. ; Fonnesbeck, Christopher J. ; Tildesley, Michael J. ; Pannell, David ; Shea, Katriona. / Concurrent assessment of epidemiological and operational uncertainties for optimal outbreak control : Ebola as a case study. In: Philosophical Transactions of the Royal Society B - Biological Sciences. 2019 ; Vol. 286, No. 1905.
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Concurrent assessment of epidemiological and operational uncertainties for optimal outbreak control : Ebola as a case study. / Li, Shou-Li; Ferrari, Matthew J.; Bjornstad, Ottar N.; Runge, Michael C.; Fonnesbeck, Christopher J.; Tildesley, Michael J.; Pannell, David; Shea, Katriona.

In: Philosophical Transactions of the Royal Society B - Biological Sciences, Vol. 286, No. 1905, 20190774, 19.06.2019.

Research output: Contribution to journalArticle

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T2 - Ebola as a case study

AU - Li, Shou-Li

AU - Ferrari, Matthew J.

AU - Bjornstad, Ottar N.

AU - Runge, Michael C.

AU - Fonnesbeck, Christopher J.

AU - Tildesley, Michael J.

AU - Pannell, David

AU - Shea, Katriona

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AB - Determining how best to manage an infectious disease outbreak may be hindered by both epidemiological uncertainty (i.e. about epidemiological processes) and operational uncertainty (i.e. about the effectiveness of candidate interventions). However, these two uncertainties are rarely addressed concurrently in epidemic studies. We present an approach to simultaneously address both sources of uncertainty, to elucidate which source most impedes decision-making. In the case of the 2014 West African Ebola outbreak, epidemiological uncertainty is represented by a large ensemble of published models. Operational uncertainty about three classes of interventions is assessed for a wide range of potential intervention effectiveness. We ranked each intervention by caseload reduction in each model, initially assuming an unlimited budget as a counterfactual. We then assessed the influence of three candidate cost functions relating intervention effectiveness and cost for different budget levels. The improvement in management outcomes to be gained by resolving uncertainty is generally high in this study; appropriate information gain could reduce expected caseload by more than 50%. The ranking of interventions is jointly determined by the underlying epidemiological process, the effectiveness of the interventions and the size of the budget. An epidemiologically effective intervention might not be optimal if its costs outweigh its epidemiological benefit. Under higher-budget conditions, resolution of epidemiological uncertainty is most valuable. When budgets are tight, however, operational and epidemiological uncertainty are equally important. Overall, our study demonstrates that significant reductions in caseload could result from a careful examination of both epidemiological and operational uncertainties within the same modelling structure. This approach can be applied to decision-making for the management of other diseases for which multiple models and multiple interventions are available.

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KW - epidemiological uncertainty

KW - operational uncertainty

KW - optimal control

KW - DISEASE EPIDEMIC

KW - DECISION-MAKING

KW - GREAT-BRITAIN

KW - STRATEGIES

KW - SPREAD

KW - IMPACT

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DO - 10.1098/rspb.2019.0774

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JO - Philosophical Transactions of the Royal Society B - Biological Sciences

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