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      Absolute Humidity and the Seasonal Onset of Influenza in the Continental United States

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          Abstract

          Here, the authors demonstrate that variations of absolute humidity explain both the onset of wintertime influenza transmission and the overarching seasonality of this pathogen in temperate regions.

          Abstract

          Much of the observed wintertime increase of mortality in temperate regions is attributed to seasonal influenza. A recent reanalysis of laboratory experiments indicates that absolute humidity strongly modulates the airborne survival and transmission of the influenza virus. Here, we extend these findings to the human population level, showing that the onset of increased wintertime influenza-related mortality in the United States is associated with anomalously low absolute humidity levels during the prior weeks. We then use an epidemiological model, in which observed absolute humidity conditions temper influenza transmission rates, to successfully simulate the seasonal cycle of observed influenza-related mortality. The model results indicate that direct modulation of influenza transmissibility by absolute humidity alone is sufficient to produce this observed seasonality. These findings provide epidemiological support for the hypothesis that absolute humidity drives seasonal variations of influenza transmission in temperate regions.

          Author Summary

          The origin of seasonality in influenza transmission is both of palpable public health importance and basic scientific interest. Here, we present statistical analyses and a mathematical model of epidemic influenza transmission that provide strong epidemiological evidence for the hypothesis that absolute humidity (AH) drives seasonal variations of influenza transmission in temperate regions. We show that the onset of individual wintertime influenza epidemics is associated with anomalously low AH conditions throughout the United States. In addition, we use AH to modulate the basic reproductive number of influenza within a mathematical model of influenza transmission and compare these simulations with observed excess pneumonia and influenza mortality. These simulations capture key details of the observed seasonal cycle of influenza throughout the US. The results indicate that AH affects both the seasonality of influenza incidence and the timing of individual wintertime influenza outbreaks in temperate regions. The association of anomalously low AH conditions with the onset of wintertime influenza outbreaks suggests that skillful, short-term probabilistic forecasts of epidemic influenza could be developed.

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          Most cited references 30

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          The NCEP/NCAR 40-Year Reanalysis Project

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            Origins and evolutionary genomics of the 2009 swine-origin H1N1 influenza A epidemic.

            In March and early April 2009, a new swine-origin influenza A (H1N1) virus (S-OIV) emerged in Mexico and the United States. During the first few weeks of surveillance, the virus spread worldwide to 30 countries (as of May 11) by human-to-human transmission, causing the World Health Organization to raise its pandemic alert to level 5 of 6. This virus has the potential to develop into the first influenza pandemic of the twenty-first century. Here we use evolutionary analysis to estimate the timescale of the origins and the early development of the S-OIV epidemic. We show that it was derived from several viruses circulating in swine, and that the initial transmission to humans occurred several months before recognition of the outbreak. A phylogenetic estimate of the gaps in genetic surveillance indicates a long period of unsampled ancestry before the S-OIV outbreak, suggesting that the reassortment of swine lineages may have occurred years before emergence in humans, and that the multiple genetic ancestry of S-OIV is not indicative of an artificial origin. Furthermore, the unsampled history of the epidemic means that the nature and location of the genetically closest swine viruses reveal little about the immediate origin of the epidemic, despite the fact that we included a panel of closely related and previously unpublished swine influenza isolates. Our results highlight the need for systematic surveillance of influenza in swine, and provide evidence that the mixing of new genetic elements in swine can result in the emergence of viruses with pandemic potential in humans.
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              Strategies for mitigating an influenza pandemic.

              Development of strategies for mitigating the severity of a new influenza pandemic is now a top global public health priority. Influenza prevention and containment strategies can be considered under the broad categories of antiviral, vaccine and non-pharmaceutical (case isolation, household quarantine, school or workplace closure, restrictions on travel) measures. Mathematical models are powerful tools for exploring this complex landscape of intervention strategies and quantifying the potential costs and benefits of different options. Here we use a large-scale epidemic simulation to examine intervention options should initial containment of a novel influenza outbreak fail, using Great Britain and the United States as examples. We find that border restrictions and/or internal travel restrictions are unlikely to delay spread by more than 2-3 weeks unless more than 99% effective. School closure during the peak of a pandemic can reduce peak attack rates by up to 40%, but has little impact on overall attack rates, whereas case isolation or household quarantine could have a significant impact, if feasible. Treatment of clinical cases can reduce transmission, but only if antivirals are given within a day of symptoms starting. Given enough drugs for 50% of the population, household-based prophylaxis coupled with reactive school closure could reduce clinical attack rates by 40-50%. More widespread prophylaxis would be even more logistically challenging but might reduce attack rates by over 75%. Vaccine stockpiled in advance of a pandemic could significantly reduce attack rates even if of low efficacy. Estimates of policy effectiveness will change if the characteristics of a future pandemic strain differ substantially from those seen in past pandemics.
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                Author and article information

                Affiliations
                [1 ]College of Oceanic and Atmospheric Sciences, Oregon State University, Corvallis, Oregon, United States of America
                [2 ]Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
                [3 ]Center for Infectious Disease Dynamics, Pennsylvania State University, State College, Pennsylvania, United States of America
                [4 ]Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
                [5 ]Woodrow Wilson School, Princeton University, Princeton, New Jersey, United States of America
                [6 ]Center for Communicable Disease Dynamics, Harvard School of Public Health, Harvard University, Boston, Massachusetts, United States of America
                [7 ]Department of Epidemiology, Harvard School of Public Health, Harvard University, Boston, Massachusetts, United States of America
                [8 ]Department of Immunology and Infectious Diseases, Harvard School of Public Health, Harvard University, Boston, Massachusetts, United States of America
                Imperial College London, United Kingdom
                Author notes

                The author(s) have made the following declarations about their contributions: Conceived and designed the experiments: JS VEP CV BTG ML. Performed the experiments: JS. Analyzed the data: JS VEP CV BTG ML. Wrote the paper: JS VEP CV BTG ML.

                Contributors
                Role: Academic Editor
                Journal
                PLoS Biol
                plos
                plosbiol
                PLoS Biology
                Public Library of Science (San Francisco, USA )
                1544-9173
                1545-7885
                February 2010
                February 2010
                23 February 2010
                : 8
                : 2
                2826374
                20186267
                09-PLBI-RA-3961R2
                10.1371/journal.pbio.1000316
                (Academic Editor)
                This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
                Counts
                Pages: 13
                Categories
                Research Article
                Public Health and Epidemiology/Epidemiology
                Public Health and Epidemiology/Global Health
                Public Health and Epidemiology/Infectious Diseases

                Life sciences

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