title: Modelling the transmission dynamics and control of the novel 2009 swine influenza (H1N1) pandemic.
abstract: The paper presents a deterministic compartmental model for the transmission dynamics of swine influenza (H1N1) pandemic in a population in the presence of an imperfect vaccine and use of drug therapy for confirmed cases. Rigorous analysis of the model, which stratifies the infected population in terms of their risk of developing severe illness, reveals that it exhibits a vaccine-induced backward bifurcation when the associated reproduction number is less than unity. The epidemiological consequence of this result is that the effective control of H1N1, when the reproduction number is less than unity, in the population would then be dependent on the initial sizes of the subpopulations of the model. For the case where the vaccine is perfect, it is shown that having the reproduction number less than unity is necessary and sufficient for effective control of H1N1 in the population (in such a case, the associated disease-free equilibrium is globally asymptotically stable). The model has a unique endemic equilibrium when the reproduction number exceeds unity. Numerical simulations of the model, using data relevant to the province of Manitoba, Canada, show that it reasonably mimics the observed H1N1 pandemic data for Manitoba during the first (Spring) wave of the pandemic. Further, it is shown that the timely implementation of a mass vaccination program together with the size of the Manitoban population that have preexisting infection-acquired immunity (from the first wave) are crucial to the magnitude of the expected burden of disease associated with the second wave of the H1N1 pandemic. With an estimated vaccine efficacy of approximately 80%, it is projected that at least 60% of Manitobans need to be vaccinated in order for the effective control or elimination of the H1N1 pandemic in the province to be feasible. Finally, it is shown that the burden of the second wave of H1N1 is expected to be at least three times that of the first wave, and that the second wave would last until the end of January or early February, 2010.
authors.affiliation: Department of Mathematics, University of Manitoba, Winnipeg, Manitoba, R3T 2N2, Canada.
authors.forename: O
authors.initials: O
authors.lastname: Sharomi
authors.forename: C N
authors.initials: CN
authors.lastname: Podder
authors.forename: A B
authors.initials: AB
authors.lastname: Gumel
authors.forename: S M
authors.initials: SM
authors.lastname: Mahmud
authors.forename: E
authors.initials: E
authors.lastname: Rubinstein
mesh_terms: D000998:Antiviral Agents / Q000627:therapeutic use; D003198:Computer Simulation; D006801:Humans; D053118:Influenza A Virus, H1N1 Subtype; D007252:Influenza Vaccines / Q000627:therapeutic use; D007251:Influenza, Human / Q000453:epidemiology / Q000517:prevention & control / Q000635:transmission* / Q000821:virology; D008350:Manitoba / Q000453:epidemiology; D008954:Models, Biological; D058873:Pandemics
chemical_list: D000998:Antiviral Agents; D007252:Influenza Vaccines