Respiratory syncytial virus infection trend is associated with meteorological factors

Ilada Thongpan,Yong Poovorawan,Sompong Vongpunsawad

doi:10.1038/s41598-020-67969-5

Ilada Thongpan, Yong Poovorawan + Show 1 more

Open Access

https://doi.org/10.1038/s41598-020-67969-5

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Journal: Scientific Reports	Publication Date: Jul 2, 2020
Citations: 26	License type: open-access

Affiliation: Chulalongkorn University

Abstract

Respiratory syncytial virus (RSV) infects young children and causes influenza-like illness. RSV circulation and prevalence differ among countries and climates. To better understand whether climate factors influence the seasonality of RSV in Thailand, we examined RSV data from children ≤ 5 years-old who presented with respiratory symptoms from January 2012–December 2018. From a total of 8,209 nasopharyngeal samples, 13.2% (1,082/8,209) was RSV-positive, of which 37.5% (406/1,082) were RSV-A and 36.4% (394/1,082) were RSV-B. The annual unimodal RSV activity from July–November overlaps with the rainy season. Association between meteorological data including monthly average temperature, relative humidity, rainfall, and wind speed for central Thailand and the incidence of RSV over 7-years was analyzed using Spearman’s rank and partial correlation. Multivariate time-series analysis with an autoregressive integrated moving average (ARIMA) model showed that RSV activity correlated positively with rainfall (r = 0.41) and relative humidity (r = 0.25), but negatively with mean temperature (r = − 0.27). The best-fitting ARIMA (1,0,0)(2,1,0)12 model suggests that peak RSV activity lags the hottest month of the year by 4 months. Our results enable possible prediction of RSV activity based on the climate and could help to anticipate the yearly upsurge of RSV in this region.

Highlights

Respiratory syncytial virus (RSV) infects young children and causes influenza-like illness
Most children who tested positive for RSV were one year of age or younger, and the average age of children with RSV infection did not appear to change from year to year (Fig. S1)
The highest proportion of monthly RSV-positive samples appeared between July and November, which coincided with the local rainy season (Fig. 1)

Summary

Introduction

Respiratory syncytial virus (RSV) infects young children and causes influenza-like illness. Association between meteorological data including monthly average temperature, relative humidity, rainfall, and wind speed for central Thailand and the incidence of RSV over 7-years was analyzed using Spearman’s rank and partial correlation. Multivariate time-series analysis with an autoregressive integrated moving average (ARIMA) model showed that RSV activity correlated positively with rainfall (r = 0.41) and relative humidity (r = 0.25), but negatively with mean temperature (r = − 0.27). We analyzed the pattern of laboratory-confirmed RSV prevalence from 2012 to 2018 and variations in the climate factors including the amount of average rainfall, relative humidity, temperature, and wind speed by using correlation analysis. Using the time series models approach, which assumes that prevalence data from the past several years can predict future trends and captures any lagged relationships among variables, we retrospectively forecasted RSV activity and compared the model with the actual incidence. Knowledge of the impact of climate variables on RSV seasons in Thailand may be useful in predicting the magnitude of the annual RSV infection in the region and assist in the planning of healthcare resources to handle this important respiratory infection

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Results

Conclusion