An investigation into the cyclical incidence of dengue fever
An investigation into the cyclical incidence of dengue fever
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DOI：
10.1016/s0277-9536(00)00443-3
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发表时间：
2001-12-01
影响因子：
5.4
通讯作者：
Keating, J
中科院分区：
文献类型：
--
作者：
Keating, J
本研究的目的是回顾登革热传播的主题，并探讨季节性温度波动与登革热周期性发病率之间的关系。从波多黎各（1988-1992年）的数据被用来测试提出的模型。登革热是一种病毒性疾病，由四种抗原性不同的血清型中的任何一种引起。它由伊蚊传播，每年感染8000万人。目前，登革热在全球特定的热带和亚热带地区流行，在美洲、亚洲和一些太平洋岛屿已报告流行性登革热。波多黎各的数据来自NCDC/NOAA和Perez等人（1994年）进行的一项研究。采用多元线性回归分析确定波多黎各月平均滞后温度与登革热月发病率之间是否存在关系。达到了统计学显著性，二阶模型产生的R-2为0.71。残差分析显示正自相关，从而削弱了模型预测登革热月发病率的能力。这表明，与群体免疫史、新血清型的引入或人口结构转变相关的其他力量或因素也在影响登革热的周期性传播。还必须获得病例聚类信息、区域登革热分布和人口密度转换，以评估该模型的预测能力。需要进行更多的研究，以避免将问题过于简单化。如果不尝试建立重要的相关性，登革热的预防和控制将仍然是许多发展中国家和发达国家的一项艰巨任务。(C)2001爱思唯尔科技有限公司版权所有。
The purpose of this research was to review the topic of dengue fever transmission and investigate the relationship between seasonal temperature fluctuations and cyclical dengue fever incidence. Data from Puerto Rico (1988-1992) were used to test the model proposed. Dengue fever is a viral disease caused by any one of four antigenically distinct serotypes. It is transmitted by Aedes mosquitoes and infects 80 million people per year. Currently, dengue is endemic in specific tropical and subtropical regions worldwide and epidemic dengue has been reported in the Americas, Asia and some Pacific Islands. Data for Puerto Rico were collected from the NCDC/NOAA and a study conducted by Perez et al. (1994). Multivariate linear regression analysis was used to determine if a relationship exists between the monthly mean temperature lagged and the monthly incidence of dengue fever in Puerto Rico. Statistical significance was achieved and a second-order model produced an R-2 of 0.71. A residual analysis reveals positive autocorrelation, thus weakening the model's power to predict monthly dengue incidence. This suggests that other forces or factors related to the history of the herd immunity, the introduction of a new serotype, or demographic transitions are also influencing the cyclical transmission of dengue fever. Case clustering information, regional dengue distributions, and population density transformations must also be obtained in order to assess the forecasting ability of this model. Additional research is needed to avoid oversimplifying the problem. Without such attempts at establishing significant correlations, dengue prevention and control will remain a formidable task for many developing and developed countries. (C) 2001 Elsevier Science Ltd. All rights reserved.