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      Evaluating the Combined Effectiveness of Influenza Control Strategies and Human Preventive Behavior

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      PLoS ONE
      Public Library of Science

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          Abstract

          Control strategies enforced by health agencies are a major type of practice to contain influenza outbreaks. Another type of practice is the voluntary preventive behavior of individuals, such as receiving vaccination, taking antiviral drugs, and wearing face masks. These two types of practices take effects concurrently in influenza containment, but little attention has been paid to their combined effectiveness. This article estimates this combined effectiveness using established simulation models in the urbanized area of Buffalo, NY, USA. Three control strategies are investigated, including: Targeted Antiviral Prophylaxis (TAP), workplace/school closure, community travel restriction, as well as the combination of the three. All control strategies are simulated with and without regard to individual preventive behavior, and the resulting effectiveness are compared. The simulation outcomes suggest that weaker control strategies could suffice to contain influenza epidemics, because individuals voluntarily adopt preventive behavior, rendering these weaker strategies more effective than would otherwise have been expected. The preventive behavior of individuals could save medical resources for control strategies and avoid unnecessary socio-economic interruptions. This research adds a human behavioral dimension into the simulation of control strategies and offers new insights into disease containment. Health policy makers are recommended to review current control strategies and comprehend preventive behavior patterns of local populations before making decisions on influenza containment.

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          Most cited references45

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          Threshold Models of Collective Behavior

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            Emergence and pandemic potential of swine-origin H1N1 influenza virus.

            Influenza viruses cause annual epidemics and occasional pandemics that have claimed the lives of millions. The emergence of new strains will continue to pose challenges to public health and the scientific communities. A prime example is the recent emergence of swine-origin H1N1 viruses that have transmitted to and spread among humans, resulting in outbreaks internationally. Efforts to control these outbreaks and real-time monitoring of the evolution of this virus should provide us with invaluable information to direct infectious disease control programmes and to improve understanding of the factors that determine viral pathogenicity and/or transmissibility.
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              Modelling the influence of human behaviour on the spread of infectious diseases: a review.

              Human behaviour plays an important role in the spread of infectious diseases, and understanding the influence of behaviour on the spread of diseases can be key to improving control efforts. While behavioural responses to the spread of a disease have often been reported anecdotally, there has been relatively little systematic investigation into how behavioural changes can affect disease dynamics. Mathematical models for the spread of infectious diseases are an important tool for investigating and quantifying such effects, not least because the spread of a disease among humans is not amenable to direct experimental study. Here, we review recent efforts to incorporate human behaviour into disease models, and propose that such models can be broadly classified according to the type and source of information which individuals are assumed to base their behaviour on, and according to the assumed effects of such behaviour. We highlight recent advances as well as gaps in our understanding of the interplay between infectious disease dynamics and human behaviour, and suggest what kind of data taking efforts would be helpful in filling these gaps.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2011
                17 October 2011
                : 6
                : 10
                : e24706
                Affiliations
                [1]Department of Geography, University of Florida, Gainesville, Florida, United States of America
                Umeå University, Sweden
                Author notes

                Conceived and designed the experiments: LM. Performed the experiments: LM. Analyzed the data: LM. Wrote the paper: LM.

                Article
                PONE-D-11-06779
                10.1371/journal.pone.0024706
                3197180
                22043275
                dee81aae-451f-4798-b5f7-5c1415492ccd
                Liang Mao. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 13 April 2011
                : 16 August 2011
                Page count
                Pages: 8
                Categories
                Research Article
                Computer Science
                Computerized Simulations
                Medicine
                Infectious Diseases
                Infectious Disease Control
                Infectious Disease Modeling
                Public Health
                Behavioral and Social Aspects of Health
                Social and Behavioral Sciences
                Geography
                Geoinformatics
                Geocomputation

                Uncategorized
                Uncategorized

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