Evidence map›Paper›PMID 38267460›Full record

ArticleScientific data2024

A consolidated and geolocated facility list in Senegal from triangulating secondary data.

Daouda M Gueye, Alioune Badara Ly, Babacar Gueye, Papa Ibrahima Ndour, Nancy Fullman, Patrick Y Liu, Khadim Mbaye, Aliou Diallo, Ibrahima Diatta, Saly Amos Diatta and 3 more

Abstract readDataset
In one paragraph

Article in Scientific data, 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

13 authors.

Daouda M GueyeInstitut de Recherche en Santé de Surveillance Epidémiologique et de Formations (IRESSEF), Dakar, Senegal.
Alioune Badara LyCentre des Opérations d'Urgence Sanitaire (COUS), Ministère de la Santé et de l'Action Sociale (MSAS), Dakar, Senegal.
Babacar GueyeDirection de la Planification, de la Recherche et des Statistiques (DPRS), MSAS, Dakar, Senegal.
Papa Ibrahima NdourDirection de la Planification, de la Recherche et des Statistiques (DPRS), MSAS, Dakar, Senegal.
Nancy FullmanExemplars in Global Health, Gates Ventures, Seattle, Washington, USA. nancy.fullman@gatesventures.com.
Patrick Y LiuExemplars in Global Health, Gates Ventures, Seattle, Washington, USA.
Khadim MbayeAgence Nationale de la Démographie et de la Statistique (ANSD), Dakar, Senegal.
Aliou DialloExpanded Programme on Immunisation Unit, WHO Country Office Senegal, Dakar, Senegal.
Ibrahima DiattaCentre des Opérations d'Urgence Sanitaire (COUS), Ministère de la Santé et de l'Action Sociale (MSAS), Dakar, Senegal.
Saly Amos DiattaInstitut de Recherche en Santé de Surveillance Epidémiologique et de Formations (IRESSEF), Dakar, Senegal.
Mouhamadou Moustapha ManeInstitut de Recherche en Santé de Surveillance Epidémiologique et de Formations (IRESSEF), Dakar, Senegal.
Gloria IkileziExemplars in Global Health, Gates Ventures, Seattle, Washington, USA.
Moussa SarrInstitut de Recherche en Santé de Surveillance Epidémiologique et de Formations (IRESSEF), Dakar, Senegal.

Funding

World Health Organization 001
6 · The paper itself

Abstract

Having a geolocated list of all facilities in a country - a "master facility list" (MFL) - can provide critical inputs for health program planning and implementation. To the best of our knowledge, Senegal has never had a centralized MFL, though many data sources currently exist within the broader Senegalese data landscape that could be leveraged and consolidated into a single database - a critical first step toward building a full MFL. We collated 12,965 facility observations from 16 separate datasets and lists in Senegal, and applied matching algorithms, manual checking and revisions as needed, and verification processes to identify unique facilities and triangulate corresponding GPS coordinates. Our resulting consolidated facility list has a total of 4,685 facilities, with 2,423 having at least one set of GPS coordinates. Developing approaches to leverage existing data toward future MFL establishment can help bridge data demands and inform more targeted approaches for completing a full facility census based on areas and facility types with the lowest coverage. Going forward, it is crucial to ensure routine updates of current facility lists, and to strengthen government-led mechanisms around such data collection demands and the need for timely data for health decision-making.

Identifiers

PMID38267460
PMCPMC10808422

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.