Spatial Clustering of Esophageal Cancer in Central Oromia, Ethiopia: A Spatial Autocorrelation and Scan Statistics Analysis

Kebele level: data_PLOS_One => study_area_new_new_final.shp 2.2. Woreda/distirict level: data_PLOS_One => study_area_district_56.shp 3. Spatial inequality’s data: 3.1.

Kebele level: data_PLOS_One => shape.file.k.xlsx 3.2. Woreda/ district level: data_PLOS_One => shape.file.w.xlsx 4. Spatial Autocorrelation’s data 4.1.

Woreda level Moran’s I (Global & LISA test), by GeoDa: data_PLOS_ONE => study_area_district_56.gel 4.2. Kebele level Moran’s I (Global & LISA test), By GeoDa: data_PLOS_ONE => study_area_new_new_final.gel 5. Scan statistic (SaTScan) data 5.1.

Kebele level: data_PLOS_One => SaTScan data and output => Kebele level => shape.file.k.xlsx 5.2. District/ woreda Level: data_PLOS_One => SaTScan data and output => Woreda level =>shape.file.w.56.xlsx 5.3. Outputs: 5.3.1.

Low rate kebele data_PLOS_One => SaTScan data and output => Kebele level => low rate kebele 5.3.2. High rate kebele data_PLOS_One => SaTScan data and output => Kebele level => High rate kebele 5.3.3. Low rate district/ woreda data_PLOS_One => SaTScan data and output => Woreda level => low rate woreda 5.3.4.

High rate district/ woreda data_PLOS_One => SaTScan data and output => Woreda level => High rate woreda 6. R Markdown showing the output of the analyzed data data_PLOS_One => PLOS ONE EC.Rmd