Detection of the Association Rules of the Occurrence of Brucellosis in Humans Using Spatial Data Mining

Abstract

Background and Objectives: Brucellosis is the most common disease in humans and animals, where its distribution is roughly global, so the control of this disease has an important impact on human health and livestock industry. The most important causes of this disease are environmental parameters (location). In this regard, identifying and discovering the relationship between environmental parameters and the outbreak and incidence of the disease can be effective in controlling and providing preventive measures and thus reducing the cost of treatment for humans and animals. Material and Methods: In this research, using spatial data and multidimensional association rules, the association between the occurrence of Brucellosis with environmental and human parameters such as temperature, humidity, altitude, land use, occupation and history of contact with the livestock and use of non-pasteurized dairy has been investigated with emphasis on location. The statistical population of this study is people with brucellosis in Hamedan province in 1394. Results: The results of this study indicate that factors of location and non location included temperature, altitude, humidity, history used of non-pasteurized dairy, history of contact with infected animals sick people, job and land use, can be effective in the spread of the disease. Conclusion: The results of the study show that the factors of temperature and elevation have had more effects in the discovered laws, so that areas with higher temperatures and lower altitudes than other areas include more patients. Also, people with agricultural and livestock jobs occupy the highest rates of patients in the laws that were discovered.