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  • 1.
    Ullah, Sami
    et al.
    Department of Fundamental & Applied Sciences, Universiti Teknologi PETRONAS, Seri Iskandar, Perak, Malaysia.
    Daud, Hanita
    Department of Fundamental & Applied Sciences, Universiti Teknologi PETRONAS, Seri Iskandar, Perak, Malaysia.
    Dass, Sarat C.
    School of Mathematical and Computer Sciences, Heriot-Watt University Malaysia, Putrajaya, Malaysia.
    Fanaee Tork, Hadi
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Kausarian, Husnul
    Department of Geological Engineering, Universitas Islam Riau, Pekanbaru, Indonesia.
    Khalil, Alamgir
    Department of Statistics, University of Peshawar, Peshawar, Pakistan.
    Space-Time Clustering Characteristics of Tuberculosis in Khyber Pakhtunkhwa Province, Pakistan, 2015–20192020In: International Journal of Environmental Research and Public Health, ISSN 1661-7827, E-ISSN 1660-4601, Vol. 17, no 4, article id 1413Article in journal (Refereed)
    Abstract [en]

    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 2015–2019 to design effective interventions. The spatial and space-time cluster analyses were conducted at the district-level based on the reported TB cases from January 2015 to April 2019 using space-time scan statistics (SaTScan). The most likely spatial and space-time clusters were detected in the northern rural part of the province. Additionally, two districts in the west were detected as the secondary space-time clusters. The most likely space-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-time clusters were detected at the start of the study period 2015–2016. The potential TB clusters in the remote rural part might be associated to the dry–cool climate and lack of access to the healthcare centers in the remote areas. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.

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