OBJECTIVE: To identify the effect of environmental factors on malaria risk, and to visualize spatial map of malaria standard incidence rates in Sistan and Baluchistan province, Islamic Republic of Iran. METHODS: In this cross-sectional study, the data from 42,162 registered new malaria cases from 21 March 2001 (Iranian new year) to 21 of March 2006 were studied. To describe the statistical association between environmental factors and malaria risk, a generalized linear mixed model approach was utilized. In addition, we used the second ordered stationary Kriging, and a variogram to determine the appropriate spatial correlation structure among the malaria standard incidence rates, and provide a proper malaria risk map in the area under study. RESULTS: The obtained results from the spatial modeling revealed that humidity (p=0.0004), temperature (p<0.0001), and elevation (p<0.0001) were positively, and precipitation (p=0.0029) was inversely correlated with the malaria risk. Moreover, the malaria risk map based on the predicted values showed that the south part of this province (Baluchistan), has a higher risk of malaria, compared to the northern area (Sistan). CONCLUSION: Since the effective environmental factors on malaria risk are out of human's control, the health policy makers in this province should pay more attention to the areas with high temperature, elevation, and humidity, as well as, low rainfall districts.
OBJECTIVE: To identify the effect of environmental factors on malaria risk, and to visualize spatial map of malaria standard incidence rates in Sistan and Baluchistan province, Islamic Republic of Iran. METHODS: In this cross-sectional study, the data from 42,162 registered new malaria cases from 21 March 2001 (Iranian new year) to 21 of March 2006 were studied. To describe the statistical association between environmental factors and malaria risk, a generalized linear mixed model approach was utilized. In addition, we used the second ordered stationary Kriging, and a variogram to determine the appropriate spatial correlation structure among the malaria standard incidence rates, and provide a proper malaria risk map in the area under study. RESULTS: The obtained results from the spatial modeling revealed that humidity (p=0.0004), temperature (p<0.0001), and elevation (p<0.0001) were positively, and precipitation (p=0.0029) was inversely correlated with the malaria risk. Moreover, the malaria risk map based on the predicted values showed that the south part of this province (Baluchistan), has a higher risk of malaria, compared to the northern area (Sistan). CONCLUSION: Since the effective environmental factors on malaria risk are out of human's control, the health policy makers in this province should pay more attention to the areas with high temperature, elevation, and humidity, as well as, low rainfall districts.
Authors: Sophie A Lee; Christopher I Jarvis; W John Edmunds; Theodoros Economou; Rachel Lowe Journal: J R Soc Interface Date: 2021-05-26 Impact factor: 4.118