پديد آورندگان :
محمدي نيا،علي دانشگاه صنعتي خواجه نصيرالدين طوسي , عليمحمدي، عباس دانشگاه صنعتي خواجه نصيرالدين طوسي - دانشكده مهندسي نقشه-برداري , قائمي، زينب دانشگاه صنعتي خواجه نصيرالدين طوسي - دانشكده مهندسي نقشه برداري
كليدواژه :
بيماري واگير , رگرسيون وزندار جغرافيايي , تحليل مكاني , سيستم اطلاعات مكاني , لپتوسپيروز
چكيده فارسي :
بيش از 200 نوع بيماري مشترك بين دام و انسان در جهان وجود دارند كه لپتوسپيروز يكي از مهمترين آنها به شمار ميرود. هر ساله با شروع فصل شاليكاري در شمال كشور، اين بيماري شيوع پيدا كرده و در مواردي منجر به مرگ و مير ميشود. در مقايسه با ساير استانها در چند سال اخير، استان گيلان بيشترين ميزان گزارش بيماري لپتوسپيروز را به خود اختصاص داده است و از اين جهت مطالعه و مدلسازي اين بيماري در استان فوق از الويت زيادي برخوردار است. در اين تحقيق كارايي كرنلهاي ثابت و انطباقي در روش رگرسيون وزندار جغرافيايي (GWR) جهت مدلسازي بيماري لپتوسپيروز و تاثير 7 عامل محيطي بر آن در سالهاي 2009 تا 2011 در سطح دهستانهاي استان گيلان مورد بررسي قرار گرفته است. از دو معيار ضريب تبيين و خطاي ميانگين مربعات نيز براي ارزيابي نتايچ استفاده شده است. نتايج به دست آمده حاكي از آن است كه كرنل انطباقي نسبت به كرنل ثابت و نيز وزندهي زوج مربعي در مقايسه با وزندهي گوسين به ترتيب عملكرد بهتري دارند. از نظر معيارهاي انتخاب پهناي باند به ترتيب AIC، CV و BICنقش مفيدتري دارند. از نظر متغيرهاي محيطي نيز، پارامترهاي متوسط دما، رطوبت و تبخير بيشترين رابطه مثبت و ارتفاع و شيب رابطه عكس با بيماري لپتوسپيروز نشان ميدهند. نقشههاي تهيه شده از توزيع بيماري نشان ميدهند كه مناطق مركزي استان گيلان بيشتر از ساير مناطق در معرض ابتلا به اين بيماري بوده و مديريت و كنترل اين بيماري در اين مناطق از الويت بيشتري برخوردار است.
چكيده لاتين :
There are more than 200 types of zoonotic diseases in the world and leptospirosis is the most important. Leptospirosis occurs mostly in areas with a tropical climate and abundant rainfall. There are no specific statistics of this disease worldwide, and records are underestimated for several reasons. Hence, the World Health Organization (WHO) named leptospirosis as a neglected tropical disease in the world and more research is needed in this field. When paddy season in the north of Iran begins, the disease spread and in severe cases leads to death. Leptospirosis is recognized globally as a multi-faceted disease and failure to recognize or treat it onetime can lead to death of patients. The main cause of the spread of this disease is a bacterium present in the body of domestic and wild animals, especially mice and dogs (as reservoirs of disease) and transmitted through the urine or feces to the environment. As a result, the bacteria can be transmitted to the human body through injuries to the skin or contact with contaminated soil and water. The environment and occupation are very effective in the spread of the disease, which is recognized as a work-related illness and can be dangerous in both urban and rural areas. The emergence of this disease can be due to reasons such as agriculture, livestock, butchers, recreational activities and water sports, poverty, travel to tropical areas, and any activity that leads to contact with water, soil or contaminated environment. This disease is more prevalent in fishermen and farmers, especially sugar cane farmers and workers, and it is very important to cause problems such as inability to work properly in the time and season needed planting and harvesting, as well as medical costs and even mortality. Compared to other provinces, Guilan province has the highest rate of leptospirosis recently. Therefore, the study and modeling of this disease in the province is of great importance. In this paper, the disease statistics in the rural area during 2009-2011 were assessed as the dependant variable and five variables considered as independent variables for modeling spatial distribution. Considering the important effects of bandwidth and weighting function on modeling results, the efficiency of fixed and adaptive kernels, Bi-Square and Gaussian weighting functions investigated. Two criteria were utilized to evaluate the results include MSE and Definition Coefficient. The results showed that the adaptive kernel and Bi-Square performed better than the fixed kernel and Gaussian, respectively. In terms of bandwidth selection criteria, AIC, CV and BIC played more meaningful role consecutively. Among the environmental variables, Temperature, Humidity and Evaporation illustrated positive relationship with disease and, elevation and slope showed negative relationship. The maps of the distribution of the disease indicated that the central regions of Guilan province are more prone to this disease than the other areas, and management and control of the disease in these areas is very important. Finally, all results were assessed by validation criteria and decision makers can use this helpful information for prevention programs and allocation of budget to the risky areas.
