A predictive model for Dengue Hemorrhagic Fever epidemics
A predictive model for Dengue Hemorrhagic Fever epidemics
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DOI：
10.1080/09603120801966043
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发表时间：
2008-01-01
影响因子：
3.2
通讯作者：
Ridd, Peter
中科院分区：
文献类型：
--
作者：
Halide, Halmar;Ridd, Peter
建立并检验了预测马卡萨尔市每月登革出血热（DHF）病例的统计模型。该模型使用过去和现在的DHF案例，气候和气象观测作为输入。使用逐步回归方法选择这些输入，以预测未来DHF病例。该模型进行独立测试，其技能评估使用两个技能措施。使用选定的变量作为输入，该模型能够预测在长达六个月的筹备时间内的中度严重流行病。预测中最重要的输入变量是DHF病例的当前数量，其次是三到四个月前的相对湿度。提前1-6个月的预测足以启动各种活动来对抗DHF流行。该模型适用于预警，由于其简单的数据要求和计算工作量，很容易成为一个操作工具。
A statistical model for predicting monthly Dengue Hemorrhagic Fever (DHF) cases from the city of Makassar is developed and tested. The model uses past and present DHF cases, climate and meteorological observations as inputs. These inputs are selected using a stepwise regression method to predict future DHF cases. The model is tested independently and its skill assessed using two skill measures. Using the selected variables as inputs, the model is capable of predicting a moderately-severe epidemic at lead times of up to six months. The most important input variable in the prediction is the present number of DHF cases followed by the relative humidity three to four months previously. A prediction 1-6 months in advance is sufficient to initiate various activities to combat DHF epidemic. The model is suitable for warning and easily becomes an operational tool due to its simplicity in data requirement and computational effort.