Evidence map›Paper›PMID 40117245›Full record

ArticlePloS one2025

Fine scale mapping of water sources in low-income settings: A comparative study in Misungwi, Tanzania.

Claudia Duguay, Charles Thickstun, Jacklin F Mosha, Tatu Aziz, Alphaxard Manjurano, Alison Krentel, Natacha Protopopoff, Manisha A Kulkarni

Abstract readComparative Study
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Claudia DuguaySchool of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada.ORCID https://orcid.org/0000-0002-9577-5719
Charles ThickstunSchool of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada.
Jacklin F MoshaNational Institute for Medical Research Tanzania, Mwanza Research Centre, Mwanza, Tanzania.
Tatu AzizNational Institute for Medical Research Tanzania, Mwanza Research Centre, Mwanza, Tanzania.
Alphaxard ManjuranoNational Institute for Medical Research Tanzania, Mwanza Research Centre, Mwanza, Tanzania.
Alison KrentelSchool of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada.
Natacha ProtopopoffFaculty of Infectious and Tropical Diseases, Disease Control Department, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Manisha A KulkarniSchool of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada.ORCID https://orcid.org/0000-0002-5084-4960

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Access to safe water, sanitation, and hygiene is a basic human need for health and well-being. Yet, 2.2 billion people globally in 2022 did not have access to safely managed drinking water. Presently there are no publicly available methods for monitoring and measuring access to water sources in low-income settings at a fine spatial scale. The objective of this study was to map and identify areas with improved and unimproved water points in Misungwi, Tanzania using two different methods: 1) community mapping with direct field observations, and 2) drone imagery. We quantified and summarized the number of improved and unimproved water sources, as defined by the WHO/UNICEF Joint Monitoring Programme core questions and noted their specific uses where applicable. We also compared the results of both data collection methods outlining their respective advantages and limitations. The community maps and direct field observations not only served as a method to identify water sources, but also provided insights into how community members used and interacted with each water source. In contrast, the drone imagery only served as a method to systematically identify water sources in the study area. A notable advantage of the drone imagery, however, was its ability to identify more unimproved water sources (225 vs 90) compared to the direct field observations. Both methods were effective in identifying water sources at a fine scale, but the drone imagery involved a more time-intensive process, demanded advanced skills, and incurred a higher cost compared to the community mapping with direct field observations. This study highlights the need for accurate and readily accessible data on water sources which is imperative for planning, developing, and managing improved water sources, especially in underserved areas such as Misungwi, Tanzania.

Indexed as

Drinking WaterEnvironmental MonitoringPovertyWater SupplyHumansSanitationTanzaniaDrinking Water

Identifiers

PMID40117245
PMCPMC11927903

What OpenQuestion holds

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Registered trials

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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.