Modeling seasonal leptospirosis transmission and its association with rainfall and temperature in Thailand using time-series and ARIMAX analyses

被引:84
作者
Chadsuthi, Sudarat [1 ]
Modchang, Charin [1 ,2 ]
Lenbury, Yongwimon [3 ,4 ]
Iamsirithaworn, Sopon [5 ]
Triampo, Wannapong [1 ,2 ,6 ]
机构
[1] Mahidol Univ, Fac Sci, Dept Phys, Biophys Grp, Bangkok 10400, Thailand
[2] ThEP Ctr CHE, Bangkok, Thailand
[3] CHE, Ctr Excellence Math, Bangkok, Thailand
[4] Mahidol Univ, Fac Sci, Dept Math, Bangkok 10400, Thailand
[5] Minist Publ Hlth, Dept Dis Control, Bur Epidemiol, Nonthaburi, Thailand
[6] Mahidol Univ, Inst Innovat Learning, Salaya, Nakorn Pathom, Thailand
关键词
Time series analysis; Rainfall; Temperature; Leptospirosis; Thailand; PATHOGENIC LEPTOSPIRA; SEROVAR;
D O I
10.1016/S1995-7645(12)60095-9
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Objective: To study the number of leptospirosis cases in relations to the seasonal pattern, and its association with climate factors. Methods: Time series analysis was used to study the time variations in the number of leptospirosis cases. The Autoregressive Integrated Moving Average (ARIMA) model was used in data curve fitting and predicting the next leptospirosis cases. Results: We found that the amount of rainfall was correlated to leptospirosis cases in both regions of interest, namely the northern and northeastern region of Thailand, while, the temperature played a role in the northeastern region only. The use of multivariate ARIMA (ARIMAX) model showed that factoring in rainfall (with an 8 months lag) yields the best model for the northern region while the mould, which factors in rainfall (with a 10 months lag) and temperature (with an 8 months lag) was the best for the region. Conclusions: The models are able to show the trend in leptospirosis eases and closely lit the recorded data in both regions. The models can also be used to predict the next seasonal peak quite accurately.
引用
收藏
页码:539 / 546
页数:8
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