| Malaria is one of major tropical diseases in Hainan province, which has been transmitting and prevailing for all the year, is a serious threaten to public health. The stable climate conditions and diversity geographical feature in Hainan province offers fine environmental condition for the transmission and prevalence, meanwhile also brings some difficulty for malaria surveillance measure, control strategy and prevention plan. So, study on the physical environmental condition effecting the distribution and prevalence of malaria is very active significance.Based on study on the relationship between the climate factors and prevalence of malaria in WanNing city and NanQiao countryside, WanNing city, we had got the results as follow: In WanNing city, the monthly incidence rate correlated positively with monthly mean temperature, monthly maximum temperature, monthly minimum temperature and monthly rainfall(P < 0.01), negatively with the difference of month extremity temperature(P < 0.01). By the stepwise multivariable regression, we established the equation as follow. I1/2=-0.972 + 0.06919Tmean(I is monthly incidence rate, Tmeanis monthly mean temperature, R2=0.465, P = 0.000). In NanQiao countryside, the monthlyincidence rate and the mosquito density correlated positively with monthly mean temperature, monthly maximum temperature and monthly minimum temperature(P < 0.01), negatively with the difference of month extremity temperature(P < 0.01). Also, we established the equation as follow: log D=0.03188Tmean(D is the monthly anopheles density, R2=0.936, P=0.000); I1/2=-0.984 + 0.08869Tmean- 0.0102Trainfall(Trainfall is monthly rainfall R2=0.375, P=0.000); in addtion, the monthly incidence rate correlated positively with the monthly mosquito density(P=0.015). The result illustrates that the climate factors play the part of prevalence of malaria.We try to found out the relationship between the remotely sensed surrogates-NDVI, the climate factors and prevalence of malaria in Hainan province in 1995 using Common Factor Analysis. First we extracted principal component from 12 data(10 data for NDVI each) of each variable as follow: monthly mean NDVI, monthly maximum NDVI monthly minimum NDVI, monthly mean temperature, monthly maximum temperature, monthly minimum temperature, monthly rainfall and monthly relative humidity in Hainan province in 1995. Then using each common factors score, we established the equation as follow:I=-0.0219+0.463F2 -NDVImean+0.519F2 -Rainfall(R2 = 0.799, P=0.000), I is incidence rate transformed by standardization variable, F2 -NDVImean is the second common factort of monthly mean NDVI, F2 -Rainfall is the second common factor of monthly rainfall.To explore the spatial distribution of malaria in Hainan Province, we analyse the spatial tendency and distribution characteristic of malaria in hainan Province from 1995 to 1999 using the spatial local interpolation technique in the ArcGIS 8.1 software. We adopt spherical model to draft Semivariogramsfunction through Semivariogram Cloud result, and then produce the spatial distribution maps of Malaria incidence in hainan Province from 1995 to 1999. By distribution map in transmission season, we found that the incidence of malaria in the south of Hainan Province were higher than that in the north. In the north, the incidence of malaria present fluctuated situation in space and time, and that in the south, present high level standing situation in time and relative invariable distribution in space. In the south the incidence of malaria in east coastal were higher than that of other parts. The characteristic of distribution maps in non-transmission season is very dissimilar with those of in transmission season. The distribution maps take on anomalous prevalence section partition whose transition is relative smooth, Compared with transmission season, the incidence of malaria in the north show relative strong fluctuate in intension and range, but the incidence of malaria in the north is very complex. The prediction error of the cross-v... |
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