Modeling Seasonal Influenza Transmission and Its Association with Climate Factors in Thailand Using Time-Series and ARIMAX Analyses.

Charin Modchang,Wannapong Triampo,Sudarat Chadsuthi,Sopon Iamsirithaworn

doi:10.1155/2015/436495

Abstract

Influenza is a worldwide respiratory infectious disease that easily spreads from one person to another. Previous research has found that the influenza transmission process is often associated with climate variables. In this study, we used autocorrelation and partial autocorrelation plots to determine the appropriate autoregressive integrated moving average (ARIMA) model for influenza transmission in the central and southern regions of Thailand. The relationships between reported influenza cases and the climate data, such as the amount of rainfall, average temperature, average maximum relative humidity, average minimum relative humidity, and average relative humidity, were evaluated using cross-correlation function. Based on the available data of suspected influenza cases and climate variables, the most appropriate ARIMA(X) model for each region was obtained. We found that the average temperature correlated with influenza cases in both central and southern regions, but average minimum relative humidity played an important role only in the southern region. The ARIMAX model that includes the average temperature with a 4-month lag and the minimum relative humidity with a 2-month lag is the appropriate model for the central region, whereas including the minimum relative humidity with a 4-month lag results in the best model for the southern region.

Highlights

Influenza, commonly referred to as the flu, is a worldwide respiratory infectious disease that spreads from one person to another
We found that the southern region experienced small temperature variations and that its lowest temperature value is higher than in the central region
We found that the case time-series in the central region was significantly correlated with rainfall variables at lag of 0–4 months; average temperature at lags 3 and 4; maximum relative humidity at lags 0 and 1; minimum relative humidity at lags 0–2; and average relative humidity at lags 0–2

Summary

Introduction

Commonly referred to as the flu, is a worldwide respiratory infectious disease that spreads from one person to another. The disease is transmitted through the air by coughs or sneezes, creating aerosols containing the virus from infectious individuals. Individuals, who come into contact with or breathe in these aerosols, will likely become infected by the virus [1]. The first reported major global pandemic, known as the “Spanish” influenza, occurred in 1918; it was caused by a novel H1N1 virus subtype [2]. This pandemic was estimated to have cost the lives of 20–40 million people from 1918 to 1919 [3]

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Results

Conclusion