Evidence map›Paper›PMID 35764949›Full record

ArticleInternational journal of emergency medicine2022

Using social media in Kenya to quantify road safety: an analysis of novel data.

J Austin Lee, Lyndsey Armes, Benjamin W Wachira

Abstract read
In one paragraph

Article in International journal of emergency medicine, 2022. 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

3 authors.

J Austin LeeDepartment of Emergency Medicine, Brown University Warren Alpert Medical School, Providence, RI, USA. jaustinlee@brown.edu.
Lyndsey ArmesSchool of Public Health, Brown University, Providence, RI, USA.
Benjamin W WachiraThe Aga Khan University, Nairobi, Kenya.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRoad traffic injuries are a large and growing cause of morbidity and mortality in low- and middle-income countries, especially in Africa. Systematic data collection for traffic incidents in Kenya is lacking and in many low- and middle-income countries available data sources are disparate or missing altogether. Many Kenyans use social media platforms, including Twitter; many road traffic incidents are publicly reported on the microblog platform. This study is a prospective cohort analysis of all tweets related to road traffic incidents in Kenya over a 24-month period (February 2019 to January 2021).

resultsA substantial number of unique road incidents (3882) from across Kenya were recorded during the 24-month study period. The details available for each incident are widely variable, as reported and posted on Twitter. Particular times of day and days of the week had a higher incidence of reported road traffic incidents. A total of 2043 injuries and 1503 fatalities were recorded.

conclusionsTwitter and other digital social media platforms can provide a novel source for road traffic incident and injury data in a low- and middle-income country. The data collected allows for the potential identification of local and national trends and provides opportunities to advocate for improved roadways and health systems for the emergent care from road traffic incidents and associated traumatic injuries.

Indexed as

KenyaRoad safetyRoad trafficSocial mediaTraumaTwitter

Identifiers

PMID35764949
PMCPMC9238258

What OpenQuestion holds

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LicenceCC BY
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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.