Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
PLoS One. 2020 Sep 29;15(9):e0239729. doi: 10.1371/journal.pone.0239729. eCollection 2020.
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.
泰国流感活动与当地气候因素的关联分析
在温带地区,流感活动的年度增加与寒冷干燥的冬季有关,而热带国家的流感模式因地区气候和地理位置的不同而有很大差异。为了研究泰国流感活动与当地气候因素(包括温度、相对湿度和降雨量)之间的关联,我们分析了曼谷一家大型私立医院 2010 年 1 月至 2018 年 12 月的流感监测数据。结果显示,约五分之一的流感样疾病样本(21.6%或 6,678/30,852)检测出流感病毒阳性。流感病毒分型显示,34.2%为甲型 H1N1pdm09,46.0%为甲型 H3N2,19.8%为乙型流感病毒。有两个季节性流感活动高峰。甲型 H1N1pdm09 的高峰期出现在 2 月和 8 月,而甲型 H3N2 和乙型流感病毒主要在 8 月和 9 月检测到。时间序列分析表明,相对湿度增加与曼谷流感活动增加显著相关。流感活动高峰期的月份通常紧随一年中最潮湿的月份。我们对 2011 年至 2017 年的数据进行了所有流感活动的季节性自回归综合移动平均(SARIMA)多元分析,以预测 2018 年的流感活动。由此产生的模型与当年实际检测到的整体流感非常相似。因此,在曼谷等大型热带城市预测流感的季节性模式的能力可能会使更好的公共卫生计划成为可能,并强调了在雨季前进行年度流感疫苗接种的重要性。