Evidence map›Paper›PMID 33139766›Full record

ArticleScientific reports2020

A Bayesian Belief Network model to link sanitary inspection data to drinking water quality in a medium resource setting in rural Indonesia.

D Daniel, Widya Prihesti Iswarani, Saket Pande, Luuk Rietveld

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. 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
1.2field-weighted citation impact, top 22% of its field
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, 10 citations in OpenAlex.

  1. Difficulties in the Modeling ofMolecules (Basel, Switzerland) · 2022
    Article
  2. Contextual Determinants of General Household Hygiene Conditions in Rural Indonesia.International journal of environmental research and public health · 2021
    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

4 authors at 1 institution in 1 country.

D DanielDepartment of Water Management, Delft University of Technology, Delft, The Netherlands. d.daniel@tudelft.nl.
Widya Prihesti IswaraniDepartment of Water Management, Delft University of Technology, Delft, The Netherlands.
Saket PandeDepartment of Water Management, Delft University of Technology, Delft, The Netherlands.
Luuk RietveldDepartment of Water Management, Delft University of Technology, Delft, The Netherlands.
Delft University of Technology · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Assessing water quality and identifying the potential source of contamination, by Sanitary inspections (SI), are essential to improve household drinking water quality. However, no study link the water quality at a point of use (POU), household level or point of collection (POC), and associated SI data in a medium resource setting using a Bayesian Belief Network (BBN) model. We collected water samples and applied an adapted SI at 328 POU and 265 related POC from a rural area in East Sumba, Indonesia. Fecal contamination was detected in 24.4 and 17.7% of 1 ml POC and POU samples, respectively. The BBN model showed that the effect of holistic-combined interventions to improve the water quality were larger compared to individual intervention. The water quality at the POU was strongly related to the water quality at the POC and the effect of household water treatment to improve the water quality was more prominent in the context of better sanitation and hygiene conditions. In addition, it was concluded that the inclusion of extra "external" variable (fullness level of water at storage), besides the standard SI variables, could improve the model's performance in predicting the water quality at POU. Finally, the BBN approach proved to be able to illustrate the interdependencies between variables and to simulate the effect of the individual and combination of variables on the water quality.

Identifiers

PMID33139766
PMCPMC7606607
OpenAlexW3095406630

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.