Evidence map›Paper›PMID 26792526›Full record

ArticleBMC public health2016

High road utilizers surveys compared to police data for road traffic crash hotspot localization in Rwanda and Sri Lanka.

Catherine A Staton, Vijitha De Silva, Elizabeth Krebs, Luciano Andrade, Stephen Rulisa, Badra Chandanie Mallawaarachchi, Kezhi Jin, Joao RicardoVissoci, Truls Østbye

Abstract read
In one paragraph

Article in BMC public health, 2016. 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. Road traffic crash experience among commercial motorcyclists in Kigali, Rwanda.International journal of injury control and safety promotion · 2020
    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

9 authors.

Catherine A StatonDivision of Emergency Medicine, Duke University Medicine Center, Durham, USA. catherine.staton@duke.edu.
Vijitha De SilvaDuke Global Health Institute, Durham, NC, USA. pvdesilva@gmail.com.
Elizabeth KrebsDivision of Emergency Medicine, Duke University Medicine Center, Durham, USA. krebse@gmail.com.
Luciano AndradeState University of West of Parana / Unioeste, Foz do Iguaçu, Brazil. luc.and1973@gmail.com.
Stephen RulisaCollege of Medicine and Health Sciences, University of Rwanda, Butare, Rwanda. s.rulisa@gmail.com.
Badra Chandanie MallawaarachchiSouthern Provincial Director of Health Services Office, Galle, Sri Lanka. chandipushpa@yahoo.com.
Kezhi JinDepartment of Occupational Health; School of Public Health, Fudan University, Shanghai, China. zhkjin@fudan.edu.cn.
Joao RicardoVissociDuke Global Health Institute, Durham, NC, USA. joaovissoci@gmail.com.
Truls ØstbyeDepartment of Community Medicine; Faculty of Medicine, University of Ruhuna, Matara, Sri Lanka. Truls.ostbye@dm.duke.edu.

Funding

Vanderbilt-Emory-Cornell-Duke Consortium for Global Health Fellows (VECDor)R25TW009337 · FIC · VANDERBILT UNIVERSITY MEDICAL CENTER · PI HEIMBURGER, DOUGLAS CORBETT, VERMUND, STEN H. · 2012 to 2016
$6.3M
FIC NIH HHS R25 TW009337
6 · The paper itself

Abstract

backgroundRoad traffic crashes (RTCs) are a leading cause of death. In low and middle income countries (LMIC) data to conduct hotspot analyses and safety audits are usually incomplete, poor quality, and not computerized. Police data are often limited, but there are no alternative gold standards. This project evaluates high road utilizer surveys as an alternative to police data to identify RTC hotspots.

methodsRetrospective police RTC data was compared to prospective data from high road utilizer surveys regarding dangerous road locations. Spatial analysis using geographic information systems was used to map dangerous locations and identify RTC hotspots. We assessed agreement (Cohen's Kappa), sensitivity/specificity, and cost differences.

resultsIn Rwanda police data identified 1866 RTC locations from 2589 records while surveys identified 1264 locations from 602 surveys. In Sri Lanka, police data identified 721 RTC locations from 752 records while survey data found 3000 locations from 300 surveys. There was high agreement (97 %, 83 %) and kappa (0.60, 0.60) for Rwanda and Sri Lanka respectively. Sensitivity and specificity are 92 % and 95 % for Rwanda and 74 % and 93 % for Sri Lanka. The cost per crash location identified was $2.88 for police and $2.75 for survey data in Rwanda and $2.75 for police and $1.21 for survey data in Sri Lanka.

conclusionSurveys to locate RTC hotspots have high sensitivity and specificity compared to police data. Therefore, surveys can be a viable, inexpensive, and rapid alternative to the use of police data in LMIC.

Indexed as

Accidents, TrafficData CollectionGeographic Information SystemsHumansPoliceReproducibility of ResultsRwandaSafetySpatial AnalysisSri Lanka

Identifiers

PMID26792526
PMCPMC4719689

What OpenQuestion holds

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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.