Spatial-temporal patterns and risk factors for human leptospirosis in Thailand, 2012-2018

被引:8
|
作者
Chadsuthi, Sudarat [1 ]
Chalvet-Monfray, Karine [2 ,3 ]
Geawduanglek, Suchada [4 ]
Wongnak, Phrutsamon [2 ,3 ]
Cappelle, Julien [2 ,5 ,6 ]
机构
[1] Naresuan Univ, Fac Sci, Dept Phys, Phitsanulok 65000, Thailand
[2] Univ Lyon, INRAE, VetAgro Sup, UMR EPIA, F-69280 Marcy Letoile, France
[3] Univ Clermont Auvergne, INRAE, VetAgro Sup, UMR EPIA, F-63122 St Genes Champanelle, France
[4] Mahidol Univ, Fac Sci, Med & Grad Educ Div, Bangkok 10400, Thailand
[5] INRAE, CIRAD, UMR ASTRE, F-34398 Montpellier, France
[6] CIRAD, UMR ASTRE, F-34398 Montpellier, France
关键词
LOCAL INDICATORS; TEMPERATURE; ASSOCIATION; RAINFALL; FEATURES; WATER;
D O I
10.1038/s41598-022-09079-y
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Leptospirosis is a globally important zoonotic disease. The disease is particularly important in tropical and subtropical countries. Infections in humans can be caused by exposure to infected animals or contaminated soil or water, which are suitable for Leptospira. To explore the cluster area, the Global Moran's I index was calculated for incidences per 100,000 population at the province level during 2012-2018, using the monthly and annual data. The high-risk and low-risk provinces were identified using the local indicators of spatial association (LISA). The risk factors for leptospirosis were evaluated using a generalized linear mixed model (GLMM) with zero-inflation. We also added spatial and temporal correlation terms to take into account the spatial and temporal structures. The Global Moran's I index showed significant positive values. It did not demonstrate a random distribution throughout the period of study. The high-risk provinces were almost all in the lower north-east and south parts of Thailand. For yearly reported cases, the significant risk factors from the final best-fitted model were population density, elevation, and primary rice crop arable areas. Interestingly, our study showed that leptospirosis cases were associated with large areas of rice production but were less prevalent in areas of high rice productivity. For monthly reported cases, the model using temperature range was found to be a better fit than using percentage of flooded area. The significant risk factors from the model using temperature range were temporal correlation, average soil moisture, normalized difference vegetation index, and temperature range. Temperature range, which has strongly negative correlation to percentage of flooded area was a significant risk factor for monthly data. Flood exposure controls should be used to reduce the risk of leptospirosis infection. These results could be used to develop a leptospirosis warning system to support public health organizations in Thailand.
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页数:11
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