Lim Apiradee, Ammatawiyanon Lumpoo, Khurram Haris, Tongkumchum Phattrawan, McNeil Don
Department of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Pattani Campus, Pattani, Thailand.
Department of Sciences and Humanities, National University of Computer and Emerging Science, Chiniot-Faisalabad Campus, Chiniot, Pakistan.
PLoS Negl Trop Dis. 2025 Jul 23;19(7):e0013347. doi: 10.1371/journal.pntd.0013347. eCollection 2025 Jul.
Dengue is currently spreading and is considered a hyperendemic in Thailand. Outbreaks happen almost every year in various provinces of Thailand, especially the four southernmost provinces consistently reporting for more than a decade. This study aimed to explore the spatial distribution and high-risk areas using an occurrence-intensity model at a sub-district level in the four southernmost provinces of Thailand.
The record of the cases admitted to the hospital and diagnosed as dengue in the 377 sub-districts of four southernmost provinces, Songkhla, Pattani, Yala, and Narathiwat from 2008 to 2020, gender-age wise, were taken from the Office of Disease Prevention and Control, Ministry of Public Health, Thailand. We suggested a methodology based on the occurrence-intensity model to analyze the dengue cases in two steps. At first, the occurrence is determined by using the logistic regression model and considering the variable of interest as a case or not. While at second, the intensity is determined by fitting a log-linear regression model for disease intensity after excluding zeros.
The results from 78,416 observations revealed that a total number of 68,526 dengue cases were registered from 2008-2020 in all four southernmost provinces. The overall average occurrence rate was 28.3% while the average intensity was 419 per 100,000 population. The occurrence-intensity model gives a much better fit to the data and highlights that the gender-age patterns of occurrence and intensity are different. Occurrence is higher among young adult ages and then declines with age for each gender, whereas intensity is higher in children, young adults, and the elderly for each gender. The sub-districts are in the suburbs of the Songkhla province and sporadically, areas on the border of the Narathiwat province had high occurrence and intensity.
The spatial occurrence and intensity of dengue in sub-districts can provide valuable guidance to identify high-risk areas and monitor the intensity of dengue cases in these areas. This will be useful for healthcare departments in developing effective public health strategies for dengue control.
登革热目前正在传播，在泰国被视为高度地方性流行疾病。泰国各省份几乎每年都会爆发疫情，尤其是最南端的四个省份，十多年来一直持续报告疫情。本研究旨在利用发病强度模型，在泰国最南端四个省份的街道层面探索登革热的空间分布和高风险区域。
从泰国公共卫生部疾病预防控制办公室获取2008年至2020年期间，宋卡、北大年、也拉和那拉提瓦四个最南端省份的377个街道中，按性别和年龄划分的住院并被诊断为登革热的病例记录。我们提出了一种基于发病强度模型的方法，分两步分析登革热病例。首先，使用逻辑回归模型确定发病情况，并将感兴趣的变量视为是否为病例。其次，在排除零病例后，通过拟合疾病强度的对数线性回归模型来确定强度。
78416条观测结果显示，2008年至2020年期间，四个最南端省份共登记了68526例登革热病例。总体平均发病率为28.3%，而平均发病强度为每10万人419例。发病强度模型对数据的拟合效果更好，并突出显示出发病情况和强度的性别年龄模式不同。各性别中，年轻成年人的发病率较高，然后随年龄下降，而各性别中儿童、年轻成年人和老年人的发病强度较高。宋卡省郊区的街道以及北大年省边境地区偶尔出现高发病率和高强度。
街道层面登革热的空间发病情况和强度可为确定高风险区域以及监测这些区域登革热病例的强度提供有价值的指导。这将有助于卫生保健部门制定有效的登革热防控公共卫生策略。
