School of Public Health and Social Work, Queensland University of Technology, Brisbane 4059, Australia; Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane 4059, Australia.
Department of Disease Control, London School of Hygiene and Tropical Medicine, London WC1H 9SH, UK.
Sci Total Environ. 2020 Mar 15;708:134849. doi: 10.1016/j.scitotenv.2019.134849. Epub 2019 Nov 26.
Dengue in some regions has a bimodal seasonal pattern, with a first big seasonal peak followed by a second small seasonal peak. The factors associated with the second small seasonal peak remain unclear.
Monthly data on dengue cases in the Philippines and its 17 regions from 2008 to 2017 were collected and underwent a time series seasonal decomposition analysis. The associations of monthly average mean temperature, average relative humidity, and total rainfall with dengue in 19 provinces were assessed with a generalized additive model. Logistic regression and a classification and regression tree (CART) model were used to identify the factors associated with the second seasonal peak of dengue.
Dengue incidence rate in the Philippines increased substantially in the period 2013-2017, particularly for the regions in south Philippines. Dengue peaks in south Philippines predominantly occurred in August, with the peak in the national capital region (NCR) (i.e., Metropolitan Manila) occurring in September. The association between mean temperature and dengue appeared J-shaped or upside-down-V-shaped, and the association between relative humidity (or rainfall) and dengue was heterogeneous across different provinces (e.g., J shape, reverse J shape, or upside-down V shape, etc). Relative humidity was the only factor associated with the second seasonal peak of dengue (odds ratio: 1.144; 95% confidence interval: 1.023-1.279; threshold: 77%).
Dengue control and prevention resources are increasingly required in regions beyond the NCR, and relative humidity can be used as a predictor of the second seasonal peak of dengue in the Philippines.
某些地区的登革热呈双峰季节性模式,先有一个大的季节性高峰,然后是第二个小的季节性高峰。与第二个小季节性高峰相关的因素仍不清楚。
收集了 2008 年至 2017 年菲律宾及其 17 个地区的每月登革热病例数据,并进行了时间序列季节性分解分析。使用广义加性模型评估了 19 个省的月平均平均气温、平均相对湿度和总降雨量与登革热的关系。使用逻辑回归和分类回归树 (CART) 模型来确定与登革热第二个季节性高峰相关的因素。
菲律宾的登革热发病率在 2013-2017 年期间大幅上升,特别是在菲律宾南部地区。菲律宾南部地区的登革热高峰主要发生在 8 月,而首都地区(即马尼拉都会区)的高峰则发生在 9 月。平均温度与登革热之间的关系呈 J 形或倒 V 形,相对湿度(或降雨量)与登革热之间的关系在不同省份呈异质性(例如 J 形、倒 J 形或倒 V 形等)。相对湿度是与登革热第二个季节性高峰相关的唯一因素(优势比:1.144;95%置信区间:1.023-1.279;阈值:77%)。
除了 NCR 地区之外,越来越需要登革热控制和预防资源,相对湿度可用作菲律宾登革热第二个季节性高峰的预测指标。