Evidence map›Paper›PMID 28574303›Full record

ArticleGlobal health action2017

Technological solutions for an effective health surveillance system for road traffic crashes in Burkina Faso.

Emmanuel Bonnet, Aude Nikiéma, Zoumana Traoré, Salifou Sidbega, Valéry Ridde

Abstract read
In one paragraph

Article in Global health action, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
–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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  11. Artificial Intelligence in Public Health and Epidemiology.Yearbook of medical informatics · 2018
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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

5 authors.

Emmanuel Bonneta UMI Résiliences 236 , French National Research Institute for Sustainable Development (IRD) , Bondy , France.
Aude Nikiémab CNRST , Institut des Sciences des Sociétés (INSS) , Ouagadougou , Burkina Faso.
Zoumana Traoréc Africasys , Paris , France.
Salifou Sidbegad Département de Géographie , Université de Ouagadougou , Ouagadougou , Burkina Faso.
Valéry Riddee University of Montreal School of Public Health (ESPUM) , Montreal , Canada.ORCID 0000-0001-9299-8266

Funding

CIHR CPP-137901CIHR ROH-115213
6 · The paper itself

Abstract

backgroundIn the early 2000s, electronic surveillance systems began to be developed to collect and transmit data on infectious diseases in low-income countries (LICs) in real-time using mobile technologies. Such surveillance systems, however, are still very rare in Africa. Among the non-infectious epidemics to be surveilled are road traffic injuries, which constitute major health events and are the fifth leading cause of mortality in Africa. This situation also prevails in Burkina Faso, whose capital city, Ouagadougou, is much afflicted by this burden. There is no surveillance system, but there have been occasional surveys, and media reports of fatal crashes are numerous and increasing in frequency.

objectiveThe objective of this article is to present the methodology and implementation of, and quality of results produced by, a prototype of a road traffic crash and trauma surveillance system in the city of Ouagadougou.

methodsA surveillance system was deployed in partnership with the National Police over a six-month period, from February to July 2015, across the entire city of Ouagadougou. Data were collected by all seven units of the city's National Police road crash intervention service. They were equipped with geotracers that geolocalized the crash sites and sent their positions by SMS (short message service) to a surveillance platform developed using the open-source tool Ushahidi. Descriptive statistical analyses and spatial analyses (kernel density) were subsequently performed on the data collected.

resultsThe process of data collection by police officers functioned well. Researchers were able to validate the data collection on road crashes by comparing the number of entries in the platform against the number of reports completed by the crash intervention teams. In total, 873 crash scenes were recorded over 3 months. The system was accessible on the Internet for open consultation of the map of crash sites. Crash-concentration analyses were produced that identified 'hot spots' in the city. Nearly 80% of crashes involved two-wheeled vehicles. Crashes were more numerous at night and during rush hours. They occurred primarily at intersections with traffic lights. With regard to health impacts, half of the injured were under the age of 29 years, and 6 persons were killed.

conclusionsThis pilot study demonstrated the feasibility of developing simple surveillance systems, based on mHealth, in LICs.

Indexed as

Biomedical TechnologyAccidents, TrafficAdultAgedAged, 80 and overBurkina FasoFemaleGovernment ProgramsHealth SurveysHumansMaleMiddle AgedPilot ProjectsPopulation Surveillanceinjurypublic healthRoad safetysystemtrauma

Identifiers

PMID28574303
PMCPMC5496062

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.