@article{scholars13475,
         journal = {International Journal of Environmental Research and Public Health},
       publisher = {MDPI},
            year = {2020},
           title = {Space-time clustering characteristics of tuberculosis in Khyber Pakhtunkhwa Province, Pakistan, 2015{\^a}??2019},
             doi = {10.3390/ijerph17041413},
          volume = {17},
            note = {cited By 5},
          number = {4},
          author = {Ullah, S. and Daud, H. and Dass, S. C. and Fanaee-t, H. and Kausarian, H. and Khalil, A.},
            issn = {16617827},
        abstract = {The number of tuberculosis (TB) cases in Pakistan ranks fifth in the world. The National TB Control Program (NTP) has recently reported more than 462,920 TB patients in Khyber Pakhtunkhwa province, Pakistan from 2002 to 2017. This study aims to identify spatial and space-time clusters of TB cases in Khyber Pakhtunkhwa province Pakistan during 2015{\^a}??2019 to design effective interventions. The spatial and space{\^a}??time cluster analyses were conducted at the district-level based on the reported TB cases from January 2015 to April 2019 using space{\^a}??time scan statistics (SaTScan). The most likely spatial and space{\^a}??time clusters were detected in the northern rural part of the province. Additionally, two districts in the west were detected as the secondary space{\^a}??time clusters. The most likely space{\^a}??time cluster shows a tendency of spread toward the neighboring districts in the central part, and the most likely spatial cluster shows a tendency of spread toward the neighboring districts in the south. Most of the space{\^a}??time clusters were detected at the start of the study period 2015{\^a}??2016. The potential TB clusters in the remote rural part might be associated to the dry{\^a}??cool climate and lack of access to the healthcare centers in the remote areas. {\^A}{\copyright} 2020 by the authors. Licensee MDPI, Basel, Switzerland.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079833294&doi=10.3390\%2fijerph17041413&partnerID=40&md5=8f08cf6a8eaca1cadeced1e211d46d1c},
        keywords = {cluster analysis; detection method; health impact; health risk; public health; spatial analysis; tuberculosis, adult; article; climate; cluster analysis; controlled study; female; human; major clinical study; male; Pakistan; spatiotemporal analysis; tuberculosis control; Pakistan; rural population; spatiotemporal analysis; tuberculosis, Khyber-Pakhtunkhwa; Pakistan, Climate; Humans; Pakistan; Rural Population; Space-Time Clustering; Tuberculosis}
}