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, 8 (2), e1000316

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

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

Jeffrey Shaman et al. PLoS Biol.

Erratum in

  • PLoS Biol. 2010;8(3). doi: 10.1371/annotation/35686514-b7a9-4f65-9663-7baefc0d63c0

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.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Analyses of laboratory data, environmental data, and SIRS model simulations.
(A) Log-linear regression of guinea pig airborne influenza virus transmission data , on specific humidity (a measure of AH); (B) log-linear regression of 1-h influenza virus survival data on specific humidity; (C) functional relationship between R 0(t) and q(t) per Equation 4; (D) 1972–2002 daily climatology of 2-m above-ground NCEP-NCAR reanalysis specific humidity for Arizona, Florida, Illinois, New York state, and Washington state; (E) 1972–2002 average daily values of R 0(t) derived from the specific humidity climatology using the best-fit parameter combination from SIRS simulations (R 0max = 3.52; R 0min = 1.12) and the functional form (Figure 1C and Equation 4); (F) average R E(t) for all wintertime outbreaks in the ten best-fit simulations at each state shown for 100 d prior to through 150 d post outbreak onset (minimum 400 infections/day during 2 wk prior; minimum 5,000 infections/day at least 1 d during subsequent 30 d). Figure 1A and 1B are redrawn from Shaman and Kohn using specific humidity as the measure of AH.
Figure 2
Figure 2. AH′ associated with the observed onset of epidemic influenza.
Top, plots of AH′ averaged for the site-winters with an influenza outbreak showing the 6 wk prior to and 4 wk following outbreak onset. The conditions at each of the site-winters are defined based on the onset date for that site-winter. The onset dates are defined as the date at which wintertime observed excess P&I mortality had been at or above a prescribed threshold level for two continuous weeks (e.g., 0.01 deaths/100,000 people/day). Not every site-winter produced an outbreak as defined by a particular onset threshold. Depending on the threshold level used, 1,181–1,420 epidemics were identified among 1,470 possible (30 winters each for the 48 contiguous states plus the District of Columbia). Each solid line is the averaged AH′ associated with influenza onset as defined by a different threshold mortality rate. The dashed line shows AH′ = 0. Bottom, plot of R 0(t) anomalies using the above AH′ values. The R 0(t) anomalies are calculated using the best combined-fit estimates of R 0max and R 0min (Table 1). The dashed line shows R 0(t) = 0.
Figure 3
Figure 3. Mean annual cycles for the best-fit SIRS model simulations at the five state sites.
Here, best-fit simulations were selected individually for each state based on RMS error after scaling the 31-y mean daily infection number to the 31-y mean observed daily excess P&I mortality rate. Thick blue line shows the best-fit simulation; thinner green lines show the next nine best simulations.
Figure 4
Figure 4. AH′ associated with SIRS simulated influenza onset.
Top, plots of average AH′ associated with wintertime influenza onset for the ten best-fit SIRS model simulations at the five state sites (Arizona, Florida, Illinois, New York, and Washington). The onset dates are defined as the date on which wintertime infection rates have been at or above a prescribed level for two continuous weeks (e.g., 50 infections/100,000 people/day). Each solid line is the averaged AH′ associated with influenza onset as defined by a different threshold infection rate. The dashed line shows AH′ = 0. Bottom, plots of R 0(t) anomalies using the AH′ values. The R 0(t) anomalies are calculated using the parameters R 0max and R 0min from each best-fit simulation (Table S3). The dashed line shows R 0(t) = 0.

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