{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T02:16:13Z","timestamp":1787019373676,"version":"build-2736575974"},"reference-count":33,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["SAGE Open Medicine"],"published-print":{"date-parts":[[2024,1]]},"abstract":"<jats:sec>\n                    <jats:title>Objectives:<\/jats:title>\n                    <jats:p>In Pakistan, the degradation of drinking water quality is exacerbated by the increasing population size and rapid industrialization. Contaminated water serves as the predominant source of numerous diseases, including diarrhea, gastroenteritis, and typhoid. This article explores the evolution of waterborne diseases across 21 districts of the Khyber Pakhtunkhwa province in Pakistan by monitoring changes in the clustering solutions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>The data employed in this study were sourced from 21 districts of KP by the Director-General Health Services. Cluster analysis was utilized to uncover patterns in waterborne disease incidence, while principal component analysis was employed to reveal underlying patterns and reduce dimensionality. Additionally, the MONItoring Clusters (MONIC) framework was applied for change detection, facilitating the identification of significant shifts in disease patterns over time and aiding in the understanding of temporal dynamics.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>\n                      Our analysis indicates that two clusters survived consistently over time, while other clusters exhibited inconsistency. Profiling of the surviving clusters (C\n                      <jats:sub>12<\/jats:sub>\n                      \u2192 C\n                      <jats:sub>24<\/jats:sub>\n                      \u2192 C\n                      <jats:sub>32<\/jats:sub>\n                      \u2192 C\n                      <jats:sub>43<\/jats:sub>\n                      ) suggests a gradual increase in cases of bloody diarrhea in the Swat Valley, Hangu, Karak, and Lakki Marwat regions. Similarly, profiling of the surviving clusters (\u2299\u2192 C\n                      <jats:sub>22<\/jats:sub>\n                      \u2192 C\n                      <jats:sub>34<\/jats:sub>\n                      \u2192 C\n                      <jats:sub>44<\/jats:sub>\n                      ) suggests an increase in the acute watery diarrhea (non-cholera) and typhoid fever in the regions of Peshawar, Nowshera, and Swabi.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>The findings of this study hold significant importance as they pinpoint the most vulnerable regions for various waterborne diseases. These insights offer valuable guidance to policymakers and health officials, empowering them to implement effective measures for controlling waterborne diseases in the respective regions of Khyber Pakhtunkhwa, Pakistan.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/20503121241263032","type":"journal-article","created":{"date-parts":[[2024,7,31]],"date-time":"2024-07-31T09:03:30Z","timestamp":1722416610000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":6,"title":["Evolution of waterborne diseases: A case study of Khyber Pakhtunkhwa, Pakistan"],"prefix":"10.1177","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4139-8292","authenticated-orcid":false,"given":"Muhammad","family":"Atif","sequence":"first","affiliation":[{"name":"Department of Statistics, University of Peshawar, Peshawar, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gohar","family":"Ayub","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, University of Swat, Swat, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fazal","family":"Shakoor","sequence":"additional","affiliation":[{"name":"Department of Statistics, University of Peshawar, Peshawar, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad","family":"Farooq","sequence":"additional","affiliation":[{"name":"Department of Statistics, University of Peshawar, Peshawar, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad","family":"Iqbal","sequence":"additional","affiliation":[{"name":"Department of Statistics, University of Peshawar, Peshawar, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qamruz","family":"Zaman","sequence":"additional","affiliation":[{"name":"Department of Statistics, University of Peshawar, Peshawar, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad","family":"Ilyas","sequence":"additional","affiliation":[{"name":"Department of Statistics, University of Malakand, Chakdara, Khyber Pakhtunkhwa, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2024,7,31]]},"reference":[{"issue":"12","key":"bibr1-20503121241263032","volume":"194","author":"Cisse G.","year":"2019","journal-title":"Acta Trop"},{"issue":"2","key":"bibr2-20503121241263032","first-page":"133","volume":"5","author":"Butt M","year":"2016","journal-title":"J Appl Emerg Sci"},{"key":"bibr3-20503121241263032","unstructured":"UNICEF. 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