Estimating disease burden of a potential A(H7N9) pandemic influenza outbreak in the United States

Abstract Background Since spring 2013, periodic emergence of avian influenza A(H7N9) virus in China has heightened the concern for a possible pandemic outbreak among humans, though it is believed that the virus is not yet human-to-human transmittable. Till June 2017, A(H7N9) has resulted in 1533 lab...

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Main Authors: Walter Silva, Tapas K. Das, Ricardo Izurieta
Format: Article
Language:English
Published: BMC 2017-11-01
Series:BMC Public Health
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12889-017-4884-5
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spelling doaj-ef8fea71255c40c996220a99b8c530f52020-11-24T23:55:58ZengBMCBMC Public Health1471-24582017-11-0117111310.1186/s12889-017-4884-5Estimating disease burden of a potential A(H7N9) pandemic influenza outbreak in the United StatesWalter Silva0Tapas K. Das1Ricardo Izurieta2Department of Industrial and Management System Engineering, University of South FloridaDepartment of Industrial and Management System Engineering, University of South FloridaCollege of Public Health, University of South FloridaAbstract Background Since spring 2013, periodic emergence of avian influenza A(H7N9) virus in China has heightened the concern for a possible pandemic outbreak among humans, though it is believed that the virus is not yet human-to-human transmittable. Till June 2017, A(H7N9) has resulted in 1533 laboratory-confirmed cases of human infections causing 592 deaths. The aim of this paper is to present disease burden estimates (measured by infection attack rates (IAR) and number of deaths) in the event of a possible pandemic outbreak caused by human-to-human transmission capability acquired by A(H7N9) virus. Even though such a pandemic will likely spread worldwide, our focus in this paper is to estimate the impact on the United States alone. Method The method first uses a data clustering technique to divide 50 states in the U.S. into a small number of clusters. Thereafter, for a few selected states in each cluster, the method employs an agent-based (AB) model to simulate human A(H7N9) influenza pandemic outbreaks. The model uses demographic and epidemiological data. A few selected non-pharmaceutical intervention (NPI) measures are applied to mitigate the outbreaks. Disease burden for the U.S. is estimated by combining results from the clusters applying a method used in stratified sampling. Results Two possible pandemic scenarios with R 0 = 1.5 and 1.8 are examined. Infection attack rates with 95% C.I. (Confidence Interval) for R 0 = 1.5 and 1.8 are estimated to be 18.78% (17.3–20.27) and 25.05% (23.11–26.99), respectively. The corresponding number of deaths (95% C.I.), per 100,000, are 7252.3 (6598.45–7907.33) and 9670.99 (8953.66–10,389.95). Conclusions The results reflect a possible worst-case scenario where the outbreak extends over all states of the U.S. and antivirals and vaccines are not administered. Our disease burden estimations are also likely to be somewhat high due to the fact that only dense urban regions covering approximately 3% of the geographic area and 81% of the population are used for simulating sample outbreaks. Outcomes from these simulations are extrapolated over the remaining 19% of the population spread sparsely over 97% of the area. Furthermore, the full extent of possible NPIs, if deployed, could also have lowered the disease burden estimates.http://link.springer.com/article/10.1186/s12889-017-4884-5InfluenzaInfluenza a virus -H7N9 subtypeAgent-based simulation modelCluster analysisSampling studies
collection DOAJ
language English
format Article
sources DOAJ
author Walter Silva
Tapas K. Das
Ricardo Izurieta
spellingShingle Walter Silva
Tapas K. Das
Ricardo Izurieta
Estimating disease burden of a potential A(H7N9) pandemic influenza outbreak in the United States
BMC Public Health
Influenza
Influenza a virus -H7N9 subtype
Agent-based simulation model
Cluster analysis
Sampling studies
author_facet Walter Silva
Tapas K. Das
Ricardo Izurieta
author_sort Walter Silva
title Estimating disease burden of a potential A(H7N9) pandemic influenza outbreak in the United States
title_short Estimating disease burden of a potential A(H7N9) pandemic influenza outbreak in the United States
title_full Estimating disease burden of a potential A(H7N9) pandemic influenza outbreak in the United States
title_fullStr Estimating disease burden of a potential A(H7N9) pandemic influenza outbreak in the United States
title_full_unstemmed Estimating disease burden of a potential A(H7N9) pandemic influenza outbreak in the United States
title_sort estimating disease burden of a potential a(h7n9) pandemic influenza outbreak in the united states
publisher BMC
series BMC Public Health
issn 1471-2458
publishDate 2017-11-01
description Abstract Background Since spring 2013, periodic emergence of avian influenza A(H7N9) virus in China has heightened the concern for a possible pandemic outbreak among humans, though it is believed that the virus is not yet human-to-human transmittable. Till June 2017, A(H7N9) has resulted in 1533 laboratory-confirmed cases of human infections causing 592 deaths. The aim of this paper is to present disease burden estimates (measured by infection attack rates (IAR) and number of deaths) in the event of a possible pandemic outbreak caused by human-to-human transmission capability acquired by A(H7N9) virus. Even though such a pandemic will likely spread worldwide, our focus in this paper is to estimate the impact on the United States alone. Method The method first uses a data clustering technique to divide 50 states in the U.S. into a small number of clusters. Thereafter, for a few selected states in each cluster, the method employs an agent-based (AB) model to simulate human A(H7N9) influenza pandemic outbreaks. The model uses demographic and epidemiological data. A few selected non-pharmaceutical intervention (NPI) measures are applied to mitigate the outbreaks. Disease burden for the U.S. is estimated by combining results from the clusters applying a method used in stratified sampling. Results Two possible pandemic scenarios with R 0 = 1.5 and 1.8 are examined. Infection attack rates with 95% C.I. (Confidence Interval) for R 0 = 1.5 and 1.8 are estimated to be 18.78% (17.3–20.27) and 25.05% (23.11–26.99), respectively. The corresponding number of deaths (95% C.I.), per 100,000, are 7252.3 (6598.45–7907.33) and 9670.99 (8953.66–10,389.95). Conclusions The results reflect a possible worst-case scenario where the outbreak extends over all states of the U.S. and antivirals and vaccines are not administered. Our disease burden estimations are also likely to be somewhat high due to the fact that only dense urban regions covering approximately 3% of the geographic area and 81% of the population are used for simulating sample outbreaks. Outcomes from these simulations are extrapolated over the remaining 19% of the population spread sparsely over 97% of the area. Furthermore, the full extent of possible NPIs, if deployed, could also have lowered the disease burden estimates.
topic Influenza
Influenza a virus -H7N9 subtype
Agent-based simulation model
Cluster analysis
Sampling studies
url http://link.springer.com/article/10.1186/s12889-017-4884-5
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