Associations between Meteorological Parameters and Influenza Activity in Berlin (Germany), Ljubljana (Slovenia), Castile and León (Spain) and Israeli Districts

Abstract

Background: Studies in the literature have indicated that the timing of seasonal influenza epidemic varies across latitude, suggesting the involvement of meteorological and environmental conditions in the transmission of influenza. In this study, we investigated the link between meteorological parameters and influenza activity in 9 sub-national areas with temperate and subtropical climates: Berlin (Germany), Ljubljana (Slovenia), Castile and León (Spain) and all 6 districts in Israel.

Methods: We estimated weekly influenza-associated influenza-like-illness (ILI) or Acute Respiratory Infection (ARI) incidence to represent influenza activity using data from each country's sentinel surveillance during 2000-2011 (Spain) and 2006-2011 (all others). Meteorological data was obtained from ground stations, satellite and assimilated data. Two generalized additive models (GAM) were developed, with one using specific humidity as a covariate and another using minimum temperature. Precipitation and solar radiation were included as additional covariates in both models. The models were adjusted for previous weeks' influenza activity, and were trained separately for each study location.

Results: Influenza activity was inversely associated (p<0.05) with specific humidity in all locations. Minimum temperature was inversely associated with influenza in all 3 temperate locations, but not in all subtropical locations. Inverse associations between influenza and solar radiation were found in most locations. Associations with precipitation were location-dependent and inconclusive. We used the models to estimate influenza activity a week ahead for the 2010/2011 period which was not used in training the models. With exception of Ljubljana and Israel's Haifa District, the models could closely follow the observed data especially during the start and the end of epidemic period. In these locations, correlation coefficients between the observed and estimated ranged between 0.55 to 0.91and the model-estimated influenza peaks were within 3 weeks from the observations.

Conclusion: Our study demonstrated the significant link between specific humidity and influenza activity across temperate and subtropical climates, and that inclusion of meteorological parameters in the surveillance system may further our understanding of influenza transmission patterns.

Fig 1. Study Locations.

Fig 2. Plots of the meteorological smooth terms for Model 1 (with specific humidity).

Only terms that are significant are plotted. The y-axis is in the predictor scale (log(y)) and normalized, while the x-axis is the value of the meteorological variable. The dashed lines are the 95% confidence interval. Downward slope indicates inverse relationship, while upward slope indicates proportional relationship.

Fig 3. Percentage change in model deviance when the specified meteorological parameter was excluded from Model 2.

SH is specific humidity, PRCP is precipitation and SR is solar radiation.

Fig 4. Estimated influenza activity in 2010/2011 season using Model 1 (with specific humidity).

Black line is the observations, red line is the predicted influenza and the shaded areas are the 95% CI.

Fig 5. Plots of the meteorological smooth terms for Model 2 (with minimum temperature).

Only terms that are significant are plotted. The y-axis is in the predictor scale (log(y)) and normalized, while the x-axis is the value of the meteorological variable. The dashed lines are the 95% confidence interval. Downward slope indicates inverse relationship, while upward slope indicates proportional relationship.

Fig 6. Percentage change in model deviance when the specified meteorological parameter was excluded from Model 2.

TMIN is minimum temperature, PRCP is precipitation and SR is solar radiation.

Fig 7. Estimated influenza activity in 2010/2011 season using Model 2 (with minimum temperature).

Black line is the observations, red line is the predicted influenza and the shaded areas are the 95% CI.