[Spatial regression analysis of relationship between schistosome infection rate of Oncomelania hupensis snails and climate factors].
OBJECTIVE
To explore the relationship between the schistosome infection rate of O. hupensis snails and the climate factors in endemic areas of schistosomiasis, so as to provide the evidence for improving the snail control.


METHODS
The snail and climate data of 18 counties in Hubei Province in 2009 were collected to obtain the infection rate of O. hupensis snails and to fit the spatial regression models.


RESULTS
The multiple linear regression model showed that the residuals were autocorrelated (Moran's I = 0.182 8, P < 0.01) and the spatial regression was necessary. The spatial lag model (SLM) was selected according to the results obtained by Lagrange multiplier statistics. The spatial parameter ρ of SLM was significant (p= - 0.151 5, P < 0.05) and the infection rate of O. hupensis snails was positively correlated with the annual average temperature (P < 0.05). The correlations between the infection rate of O. hupensis and the annual average relative humidity, precipitation and sunshine duration were not significant respectively (all P > 0.05).


CONCLUSIONS
The spatial regression models could be well applied in the analysis of the relationship between the O. hupensis snails and climate factors. The annual average temperature is the primary climate factor influencing the infection of O. hupensis snails.
Yan-yan
YY
Chen
Jian-bing
JB
Iu
Ying
Y
Xiao
Xiao-rong
XR
Zhou
Yong
Y
Jiang
Ling-feng
LF
Dai
Shun-xiang
SX
Cai
D000818:Animals; D002681:China; D002980:Climate; D012044:Regression Analysis; D012547:Schistosoma / Q000302:isolation & purification*; D012908:Snails / Q000469:parasitology*