| Abstrakt: |
Seasonal influenza causes 5 million severe illnesses and 500,000 deaths annually worldwide. Among the factors that have been linked to influenza transmission are meteorological parameters, especially temperature and humidity. Low temperature and humidity have been associated with influenza seasonality in the temperate regions, whereas the tropics typically observe higher influenza transmission during rainy season. In this study, we assessed the role of meteorological factors on influenza transmission using both satellite-derived and ground station data for temperate and sub-tropical regions. Auto Regressive Integrated Moving Average and Neural Network were employed to assess the meteorological indicators and for forecasting. Our findings show that measures of temperature, humidity, rainfall and solar radiation can be used as indicators to forecast influenza. We also found that rainfall can be used as a predictor for sub-tropical region, but not in all temperate regions. Overall, our models can predict the timing of influenza peak. [ABSTRACT FROM PUBLISHER] |
