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dc.contributor.authorMummert, Anna
dc.contributor.authorWeiss, Howard
dc.contributor.authorLong, Li-Ping
dc.contributor.authorAmigó, José M
dc.contributor.authorWan, Xiu-Feng
dc.date.accessioned2015-10-09T19:50:45Z
dc.date.available2015-10-09T19:50:45Z
dc.date.issued4/23/2013
dc.identifier.issn1932-6203
dc.identifier.urihttp://hdl.handle.net/11668/2488
dc.identifier.urihttp://dx.doi.org/10.1371/journal.pone.0060343
dc.description.abstractBACKGROUND: A striking characteristic of the past four influenza pandemic outbreaks in the United States has been the multiple waves of infections. However, the mechanisms responsible for the multiple waves of influenza or other acute infectious diseases are uncertain. Understanding these mechanisms could provide knowledge for health authorities to develop and implement prevention and control strategies. MATERIALS AND METHODS: We exhibit five distinct mechanisms, each of which can generate two waves of infections for an acute infectious disease. The first two mechanisms capture changes in virus transmissibility and behavioral changes. The third mechanism involves population heterogeneity (e.g., demography, geography), where each wave spreads through one sub-population. The fourth mechanism is virus mutation which causes delayed susceptibility of individuals. The fifth mechanism is waning immunity. Each mechanism is incorporated into separate mathematical models, and outbreaks are then simulated. We use the models to examine the effects of the initial number of infected individuals (e.g., border control at the beginning of the outbreak) and the timing of and amount of available vaccinations. RESULTS: Four models, individually or in any combination, reproduce the two waves of the 2009 H1N1 pandemic in the United States, both qualitatively and quantitatively. One model reproduces the two waves only qualitatively. All models indicate that significantly reducing or delaying the initial numbers of infected individuals would have little impact on the attack rate. Instead, this reduction or delay results in a single wave as opposed to two waves. Furthermore, four of these models also indicate that a vaccination program started earlier than October 2009 (when the H1N1 vaccine was initially distributed) could have eliminated the second wave of infection, while more vaccine available starting in October would not have eliminated the second wave.
dc.publisherPublic Library of Science
dc.relation.ispartofseriesPLoS ONE (Volume 8, Issue 4)
dc.subject.otherBiological
dc.subject.otherDisease Susceptibility
dc.subject.otherDisease Susceptibility: virology
dc.subject.otherH1N1 Subtype
dc.subject.otherH1N1 Subtype: genetics
dc.subject.otherH1N1 Subtype: physiology
dc.subject.otherHuman
dc.subject.otherHuman: epidemiology
dc.subject.otherHuman: immunology
dc.subject.otherHuman: prevention & control
dc.subject.otherHuman: transmission
dc.subject.otherHumans
dc.subject.otherInfluenza
dc.subject.otherInfluenza A Virus
dc.subject.otherInfluenza Vaccines
dc.subject.otherInfluenza Vaccines: administration & dosage
dc.subject.otherModels
dc.subject.otherMutation
dc.subject.otherPandemics
dc.subject.otherPandemics: statistics & numerical data
dc.subject.otherStatistical
dc.subject.otherTime Factors
dc.subject.otherUnited States
dc.subject.otherUnited States: epidemiology
dc.subject.otherVaccination
dc.titleA perspective on multiple waves of influenza pandemics.
dc.typeArticle
dc.publisher.departmentDepartment of Basic Sciences
dc.publisher.collegeCollege of Veterinary Medicine
dc.identifier.doi10.1371/journal.pone.0060343


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