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Updated: Dec 16, 2025

An In vitro Model to Study Immune Responses of Human Peripheral Blood Mononuclear Cells to Human Respiratory Syncytial Virus Infection
Published on: December 10, 2013
Respiratory syncytial virus infection trend is associated with meteorological factors
Ilada Thongpan1, Sompong Vongpunsawad1, Yong Poovorawan2
1Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand.
Insights
Climate factors significantly influence respiratory syncytial virus (RSV) seasonality in Thailand. Higher rainfall and humidity, and lower temperatures, correlate with increased RSV activity, peaking four months after the hottest period.
Area of Science:
- Environmental Science
- Epidemiology
- Virology
Background:
- Respiratory syncytial virus (RSV) is a major cause of respiratory illness in young children globally.
- RSV seasonality varies geographically, suggesting a role for climatic factors.
- Understanding local drivers of RSV is crucial for public health interventions.
Purpose of the Study:
- To investigate the relationship between meteorological factors and RSV seasonality in Thailand.
- To analyze RSV incidence data in children under five years old from 2012-2018.
- To develop a predictive model for RSV outbreaks based on climate data.
Main Methods:
- Collected and analyzed 8,209 nasopharyngeal samples from children with respiratory symptoms.
- Utilized Spearman's rank and partial correlation to assess associations between meteorological data and RSV incidence.
- Employed a multivariate time-series analysis using an ARIMA model to identify climate-RSV correlations and lags.
Main Results:
- RSV was detected in 13.2% of samples, with RSV-A and RSV-B strains identified.
- RSV activity showed a unimodal pattern from July to November, coinciding with the rainy season.
- Positive correlations were found between RSV incidence and rainfall (r=0.41) and relative humidity (r=0.25).
- A negative correlation was observed between RSV incidence and mean temperature (r=-0.27).
- The ARIMA model indicated peak RSV activity lagged the hottest month by four months.
Conclusions:
- Climate, specifically rainfall and humidity, significantly influences RSV seasonality in Thailand.
- Temperature plays an inverse role, with cooler periods associated with higher RSV activity.
- The findings support the potential for climate-based prediction of RSV outbreaks in the region.
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.
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