Evidence map›Paper›PMID 28628629›Full record

ArticlePloS one2017

Understanding mSOS: A qualitative study examining the implementation of a text-messaging outbreak alert system in rural Kenya.

Mitsuru Toda, Ian Njeru, Dejan Zurovac, David Kareko, Shikanga O-Tipo, Matilu Mwau, Kouichi Morita

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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

  1. Pooled it
  2. Pooled it
  3. Advance Warning and Response Systems in Kenya: A Scoping Review.medRxiv : the preprint server for health sciences · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Climate change and One Health.FEMS microbiology letters · 2018
    Review
  10. 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

7 authors.

Mitsuru TodaNagasaki University Institute of Tropical Medicine, Nagasaki, Japan.
Ian NjeruKenya Ministry of Health Disease Surveillance and Response Unit, Nairobi, Kenya.
Dejan ZurovacOxford University, Oxford, United Kingdom.
David KarekoKenya Ministry of Health Disease Surveillance and Response Unit, Nairobi, Kenya.
Shikanga O-TipoKenya Ministry of Health Disease Surveillance and Response Unit, Nairobi, Kenya.
Matilu MwauKenya Medical Research Institute, Nairobi, Kenya.
Kouichi MoritaNagasaki University Institute of Tropical Medicine, Nagasaki, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Outbreaks of epidemic diseases pose serious public health risks. To overcome the hurdles of sub-optimal disease surveillance reporting from the health facilities to relevant authorities, the Ministry of Health in Kenya piloted mSOS (mobile SMS-based disease outbreak alert system) in 2013-2014. In this paper, we report the results of the qualitative study, which examined factors that influence the performances of mSOS implementation. In-depth interviews were conducted with 11 disease surveillance coordinators and 32 in-charges of rural health facilities that took part in the mSOS intervention. Drawing from the framework analysis, dominant themes that emerged from the interviews are presented. All participants voiced their excitement in using mSOS. The results showed that the technology was well accepted, easy to use, and both health workers and managers unanimously recommended the scale-up of the system despite challenges encountered in the implementation processes. The most challenging components were the context in which mSOS was implemented, including the lack of strong existing structure for continuous support supervision, feedback and response action related to disease surveillance. The study revealed broader health systems issues that should be addressed prior to and during the intervention scale-up.

Indexed as

Disease OutbreaksText MessagingHealth FacilitiesHumansKenyaPublic HealthQualitative ResearchRural Population

Identifiers

PMID28628629
PMCPMC5476271

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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.