Figure 1.
Patterns of RSV activity across the United States for hospitalization and laboratory testing data.
(A) Time series of weekly RSV hospitalizations in select states. Raw hospitalization data is shown in blue, while the rescaled data accounting for the addition of an RSV-specific ICD-9 code in September 1996 is shown in green. (B) Age distribution of RSV hospitalizations across ten states. (C) Center of gravity of RSV activity in states with at least ten consecutive years of laboratory reports. (D) Strength of biennial cycle in RSV activity, as indicated by the ratio of the biennial to annual Fourier amplitude for laboratory report data.
Table 1.
Univariate regression of timing of RSV activity in 50 US states and District of Columbia, 1989–2010, against monthly climatic, population and geographic indicators.
Figure 2.
Transmission dynamic model for RSV and fit to age-specific hospitalization data.
(A) Compartmental diagram illustrating the structure of the model. White boxes represent infection states in the model, while grey boxes represent diseased/observed states (severe lower respiratory disease, D, and observed cases, H). (B) Model fit to weekly RSV hospitalization data for California and Florida. The ICD9-CM coded hospitalization data is shown in blue, the rescaled data is shown in green, and the fitted models are shown in red. (C) Age distribution of RSV hospitalizations in California and Florida for hospitalization data and fitted models.
Table 2.
Transmission dynamic model parameters.
Table 3.
Correlation coefficients between climatic variables and estimated seasonality parameters in RSV transmission model.
Figure 3.
Relationship between estimated seasonality parameters for model fit to laboratory report data and select climatic factors.
The estimated amplitude of seasonal forcing in RSV transmission (top) and the estimated seasonal offset parameter (bottom: φ = 0 represents January 1 and φ = −0.2 represents October 19) is plotted against (A) annual mean vapor pressure (hecta-Pascals), (B) annual mean minimum temperature (°C), (C) annual mean precipitation (mm/month), and (D) amplitude (relative to the annual mean) and timing of trough in potential evapotranspiration (PET; 0 = January 1, 0.1 = February 6). The colorbar on the right indicates the ratio of the biennial to annual Fourier amplitude for the observed data (outer circle) and fitted model (inner diamond). Select states are labeled: Arizona (AZ), Florida (FL), Georgia (GA), Hawaii (HI), Louisiana (LA), Montana (MT), New York (NY), South Dakota (SD), Texas (TX), Wyoming (WY).
Figure 4.
Monthly patterns of RSV activity and potential evapotranspiration.
(A) The mean number of RSV hospitalizations per 100,000 total population per month for select states, beginning in July. (B) The monthly mean potential evapotranspiration (mm/day) is plotted for each state.