Salehi Masoud, Mohammad Kazem, Farahani Mahmud M, Zeraati Hojjat, Nourijelyani Keramat, Zayeri Farid
Department of Biostatistics and Epidemiology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Saudi Med J. 2008 Dec;29(12):1791-6.
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.
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.
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).
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.
确定环境因素对疟疾风险的影响，并绘制伊朗伊斯兰共和国锡斯坦-俾路支斯坦省疟疾标准发病率的空间地图。
在这项横断面研究中，对2001年3月21日（伊朗新年）至2006年3月21日期间登记的42162例新疟疾病例的数据进行了研究。为了描述环境因素与疟疾风险之间的统计关联，采用了广义线性混合模型方法。此外，我们使用二阶平稳克里金法和变差函数来确定疟疾标准发病率之间合适的空间相关结构，并在所研究区域提供合适的疟疾风险地图。
空间建模得到的结果显示，湿度（p = 0.0004）、温度（p < 0.0001）和海拔（p < 0.0001）与疟疾风险呈正相关，而降水量（p = 0.0029）与疟疾风险呈负相关。此外，基于预测值的疟疾风险地图显示，该省南部（俾路支斯坦）的疟疾风险高于北部地区（锡斯坦）。
由于影响疟疾风险的有效环境因素超出人类控制范围，该省的卫生政策制定者应更加关注高温、高海拔、高湿度以及低降雨地区。
