Evidence map›Paper›PMID 39092162›Full record

ArticleSAGE open medicine2024

Evolution of waterborne diseases: A case study of Khyber Pakhtunkhwa, Pakistan.

Muhammad Atif, Gohar Ayub, Fazal Shakoor, Muhammad Farooq, Muhammad Iqbal, Qamruz Zaman, Muhammad Ilyas

Abstract read
In one paragraph

Article in SAGE open medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Muhammad AtifDepartment of Statistics, University of Peshawar, Peshawar, Pakistan.ORCID https://orcid.org/0000-0002-4139-8292
Gohar AyubDepartment of Mathematics and Statistics, University of Swat, Swat, Pakistan.
Fazal ShakoorDepartment of Statistics, University of Peshawar, Peshawar, Pakistan.
Muhammad FarooqDepartment of Statistics, University of Peshawar, Peshawar, Pakistan.
Muhammad IqbalDepartment of Statistics, University of Peshawar, Peshawar, Pakistan.
Qamruz ZamanDepartment of Statistics, University of Peshawar, Peshawar, Pakistan.
Muhammad IlyasDepartment of Statistics, University of Malakand, Chakdara, Khyber Pakhtunkhwa, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: 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. Methods: 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. Results: Our analysis indicates that two clusters survived consistently over time, while other clusters exhibited inconsistency. Profiling of the surviving clusters (C Conclusion: 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.

Indexed as

Change detectionclusteringwaterborne diseaseswindowing approach

Identifiers

PMID39092162
PMCPMC11292715

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.