Design of non-pharmaceutical intervention strategies for pandemic influenza outbreaks

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Abstract

Background

As seen during past pandemic influenza outbreaks, pharmaceutical interventions (PHIs) with vaccines and antivirals are the most effective methods of mitigation. However, availability of PHIs is unlikely to be adequate during the early stages of a pandemic. Hence, for early mitigation and possible containment, non-pharmaceutical interventions (NPIs) offer a viable alternative. Also, NPIs may be the only available interventions for most underdeveloped countries. In this paper we present a comprehensive methodology for design of effective NPI strategies.

Methods

We develop a statistical ANOVA-based design approach that uses a detailed agent-based simulation as an underlying model. The design approach obtains the marginal effect of the characteristic parameters of NPIs, social behavior, and their interactions on various pandemic outcome measures including total number of contacts, infections, and deaths. We use the marginal effects to establish regression equations for the outcome measures, which are optimized to obtain NPI strategies. Efficacy of the NPI strategies designed using our methodology is demonstrated using simulated pandemic influenza outbreaks with different levels of virus transmissibility.

Results

Our methodology was able to design effective NPI strategies, which were able to contain outbreaks by reducing infection attack rates (IAR) to below 10 % in low and medium virus transmissibility scenarios with 33 % and 50 % IAR, respectively. The level of reduction in the high transmissibility scenario (with 65 % IAR) was also significant. As noted in the published literature, we also found school closure to be the single most effective intervention among all NPIs.

Conclusions

If harnessed effectively, NPIs offer a significant potential for mitigation of pandemic influenza outbreaks. The methodology presented here fills a gap in the literature, which, though replete with models on NPI strategy evaluation, lacks a treatise on optimal strategy design.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2458-14-1328) contains supplementary material, which is available to authorized users.

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Most cited references 30

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Mitigation strategies for pandemic influenza in the United States.

Timothy Germann, Kai Kadau, Ira Longini … (2006)

Recent human deaths due to infection by highly pathogenic (H5N1) avian influenza A virus have raised the specter of a devastating pandemic like that of 1917-1918, should this avian virus evolve to become readily transmissible among humans. We introduce and use a large-scale stochastic simulation model to investigate the spread of a pandemic strain of influenza virus through the U.S. population of 281 million individuals for R(0) (the basic reproductive number) from 1.6 to 2.4. We model the impact that a variety of levels and combinations of influenza antiviral agents, vaccines, and modified social mobility (including school closure and travel restrictions) have on the timing and magnitude of this spread. Our simulations demonstrate that, in a highly mobile population, restricting travel after an outbreak is detected is likely to delay slightly the time course of the outbreak without impacting the eventual number ill. For R(0) < 1.9, our model suggests that the rapid production and distribution of vaccines, even if poorly matched to circulating strains, could significantly slow disease spread and limit the number ill to <10% of the population, particularly if children are preferentially vaccinated. Alternatively, the aggressive deployment of several million courses of influenza antiviral agents in a targeted prophylaxis strategy may contain a nascent outbreak with low R(0), provided adequate contact tracing and distribution capacities exist. For higher R(0), we predict that multiple strategies in combination (involving both social and medical interventions) will be required to achieve similar limits on illness rates.

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Estimating the impact of school closure on influenza transmission from Sentinel data.

Simon Cauchemez, Alain-Jacques Valleron, Pierre-Yves Boëlle … (2008)

The threat posed by the highly pathogenic H5N1 influenza virus requires public health authorities to prepare for a human pandemic. Although pre-pandemic vaccines and antiviral drugs might significantly reduce illness rates, their stockpiling is too expensive to be practical for many countries. Consequently, alternative control strategies, based on non-pharmaceutical interventions, are a potentially attractive policy option. School closure is the measure most often considered. The high social and economic costs of closing schools for months make it an expensive and therefore controversial policy, and the current absence of quantitative data on the role of schools during influenza epidemics means there is little consensus on the probable effectiveness of school closure in reducing the impact of a pandemic. Here, from the joint analysis of surveillance data and holiday timing in France, we quantify the role of schools in influenza epidemics and predict the effect of school closure during a pandemic. We show that holidays lead to a 20-29% reduction in the rate at which influenza is transmitted to children, but that they have no detectable effect on the contact patterns of adults. Holidays prevent 16-18% of seasonal influenza cases (18-21% in children). By extrapolation, we find that prolonged school closure during a pandemic might reduce the cumulative number of cases by 13-17% (18-23% in children) and peak attack rates by up to 39-45% (47-52% in children). The impact of school closure would be reduced if it proved difficult to maintain low contact rates among children for a prolonged period.

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Modeling targeted layered containment of an influenza pandemic in the United States.

M. Elizabeth Halloran, Neil M Ferguson, Stephen Eubank … (2008)

Planning a response to an outbreak of a pandemic strain of influenza is a high public health priority. Three research groups using different individual-based, stochastic simulation models have examined the consequences of intervention strategies chosen in consultation with U.S. public health workers. The first goal is to simulate the effectiveness of a set of potentially feasible intervention strategies. Combinations called targeted layered containment (TLC) of influenza antiviral treatment and prophylaxis and nonpharmaceutical interventions of quarantine, isolation, school closure, community social distancing, and workplace social distancing are considered. The second goal is to examine the robustness of the results to model assumptions. The comparisons focus on a pandemic outbreak in a population similar to that of Chicago, with approximately 8.6 million people. The simulations suggest that at the expected transmissibility of a pandemic strain, timely implementation of a combination of targeted household antiviral prophylaxis, and social distancing measures could substantially lower the illness attack rate before a highly efficacious vaccine could become available. Timely initiation of measures and school closure play important roles. Because of the current lack of data on which to base such models, further field research is recommended to learn more about the sources of transmission and the effectiveness of social distancing measures in reducing influenza transmission.

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Author and article information

Contributors

Dayna L Martinez: d.martinez@neu.edu

Tapas K Das: das@usf.edu

Journal

Journal ID (nlm-ta): BMC Public Health

Journal ID (iso-abbrev): BMC Public Health

Title: BMC Public Health

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2458

Publication date (Electronic): 29 December 2014

Publication date PMC-release: 29 December 2014

Publication date Collection: 2014

Volume: 14

Electronic Location Identifier: 1328

Affiliations

[ ]Department of Mechanical and Industrial Engineering, Northeastern University, 360 Huntington Avenue, Boston, MA USA 02115

[ ]Industrial and Management Systems Engineering, University of South Florida, 4202 East Fowler Avenue, ENB 118, Tampa, FL USA 33620

Article

Publisher ID: 7561

DOI: 10.1186/1471-2458-14-1328

PMC ID: 4532250

PubMed ID: 25547377

SO-VID: 8f394599-50ba-421b-b5da-51e56b4ea217

License:

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 29 April 2014

Date accepted : 11 December 2014

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ScienceOpen disciplines: Public health

Keywords: pandemic influenza,mitigation strategies,non-pharmaceutical interventions

Data availability:

ScienceOpen disciplines: Public health

Keywords: pandemic influenza, mitigation strategies, non-pharmaceutical interventions

Design of non-pharmaceutical intervention strategies for pandemic influenza outbreaks

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Abstract

Background

Methods

Results

Conclusions

Electronic supplementary material

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PLOS: COVID-19 pandemic

Most cited references 30

Mitigation strategies for pandemic influenza in the United States.

Estimating the impact of school closure on influenza transmission from Sentinel data.

Modeling targeted layered containment of an influenza pandemic in the United States.

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