ArticlePloS one2020
Climate factors influence seasonal influenza activity in Bangkok, Thailand.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed, 53 citations in OpenAlex.
- Article
- LSTM-Based Recurrent Neural Network Predicts Influenza-Like-Illness in Variable Climate Zones.Immunity, inflammation and disease · 2026Article
- Leveraging universal and transfer learning models for influenza prediction in Thailand.Scientific reports · 2026Article
- Epidemiology, Distinct Seasonal Dynamics, and Age-Specific Characteristics of Eight Respiratory Viruses in Thailand, 2025.Journal of tropical medicine · 2026Article
- Projecting long-term excess risks of major infectious diseases associated with future extreme weather events in Thailand.PLoS neglected tropical diseases · 2026Article
- Incorporating meteorological factors into a SARIMA model for predicting pediatric influenza epidemics.Frontiers in public health · 2026Article
- Seasonal Pattern and Age-Specific Detection of Eight Respiratory Viruses Causing Acute Respiratory Infection in 2024, Bangkok, Thailand.Tropical medicine and infectious disease · 2025Article
- Seasonal trends and molecular evolution of SARS-CoV-2 in acute respiratory illness patients during the fifth year of COVID-19, Thailand.Scientific reports · 2025Article
- How virus migration and meteorological elements shape the seasonality of influenza a/H3N2: A case study in China.One health (Amsterdam, Netherlands) · 2025Article
- National spatiotemporal patterns of influenza-like illness in Iran: A pre-COVID-19 study (2015-2019).PloS one · 2025Article
- Article
- Viral Etiology Associated With Acute Respiratory Tract Infection Patients in Bangkok, Thailand.Cureus · 2024Article
- Heterogeneity of influenza infection at precise scale in Yinchuan, Northwest China, 2012-2022: evidence from Joinpoint regression and spatiotemporal analysis.Scientific reports · 2024Article
- Factors affecting the number of influenza patients before and during COVID-19 pandemic, Thailand.PloS one · 2024Article
- The role of vaccination and environmental factors on outbreaks of high pathogenicity avian influenza H5N1 in Bangladesh.One health (Amsterdam, Netherlands) · 2023Article
- A combination of annual and nonannual forces drive respiratory disease in the tropics.BMJ global health · 2023Article
- Lagging effects and prediction of pollutants and their interaction modifiers on influenza in northeastern China.BMC public health · 2023Article
- The impact of current and future climates on spatiotemporal dynamics of influenza in a tropical setting.PNAS nexus · 2023Article
- Repeatability and timing of tropical influenza epidemics.PLoS computational biology · 2023Article
- SARS-CoV-2 Antibody Dynamics after COVID-19 Vaccination and Infection: A Real-World Cross-Sectional Analysis.Vaccines · 2023Article
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Yearly increase in influenza activity is associated with cold and dry winter in the temperate regions, while influenza patterns in tropical countries vary significantly by regional climates and geographic locations. To examine the association between influenza activity in Thailand and local climate factors including temperature, relative humidity, and rainfall, we analyzed the influenza surveillance data from January 2010 to December 2018 obtained from a large private hospital in Bangkok. We found that approximately one in five influenza-like illness samples (21.6% or 6,678/30,852) tested positive for influenza virus. Influenza virus typing showed that 34.2% were influenza A(H1N1)pdm09, 46.0% were influenza A(H3N2), and 19.8% were influenza B virus. There were two seasonal waves of increased influenza activity. Peak influenza A(H1N1)pdm09 activity occurred in February and again in August, while influenza A(H3N2) and influenza B viruses were primarily detected in August and September. Time series analysis suggests that increased relative humidity was significantly associated with increased influenza activity in Bangkok. Months with peak influenza activity generally followed the most humid months of the year. We performed the seasonal autoregressive integrated moving average (SARIMA) multivariate analysis of all influenza activity on the 2011 to 2017 data to predict the influenza activity for 2018. The resulting model closely resembled the actual observed overall influenza detected that year. Consequently, the ability to predict seasonal pattern of influenza in a large tropical city such as Bangkok may enable better public health planning and underscores the importance of annual influenza vaccination prior to the rainy season.
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