Evidence map›Paper›PMID 25843499›Full record

ArticleGlobal health action2015

Collecting syndromic surveillance data by mobile phone in rural India: implementation and feasibility.

Vishal Diwan, Deepak Agnihotri, Anette Hulth

Open access · goldAbstract read
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Article in Global health action, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.5field-weighted citation impact, top 11% of its field
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

11 citing papers in PubMed, 30 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Vishal DiwanDepartment of Public Health and Environment, R.D. Gardi Medical College, Ujjain, India.
Deepak AgnihotriDepartment of Public Health and Environment, R.D. Gardi Medical College, Ujjain, India.
Anette HulthDepartment of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden.
Ruxmaniben Deepchand Gardi Medical College · INKarolinska Institutet · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInfectious disease surveillance has long been a challenge for countries like India, where 75% of the health care services are private and consist of both formal and informal health care providers. Infectious disease surveillance data are regularly collected from governmental and qualified private facilities, but not from the informal sector. This study describes a mobile-based syndromic surveillance system and its application in a resource-limited setting, collecting data on patients' symptoms from formal and informal health care providers.

designThe study includes three formal and six informal health care providers from two districts of Madhya Pradesh, India. Data collectors were posted in the clinics during the providers' working hours and entered patient information and infectious disease symptoms on the mobile-based syndromic surveillance system.

resultsInformation on 20,424 patients was collected in the mobile-based surveillance system. The five most common (overlapping) symptoms were fever (48%), cough (38%), body ache (38%), headache (37%), and runny nose (22%). During the same time period, the government's disease surveillance program reported around 22,000 fever cases in one district as a whole. Our data - from a very small fraction of all health care providers - thus highlight an enormous underreporting in the official surveillance data, which we estimate here to capture less than 1% of the fever cases. Additionally, we found that patients from more than 600 villages visited the nine providers included in our study.

conclusionsThe study demonstrated that a mobile-based system can be used for disease surveillance from formal and informal providers in resource-limited settings. People who have not used smartphones or even computers previously can, in a short timeframe, be trained to fill out surveillance forms and submit them from the device. Technology, including network connections, works sufficiently for disease surveillance applications in rural parts of India. The data collected may be used to better understand the health-seeking behaviour of those visiting informal providers, as they do not report through any official channels. We also show that the underreporting to the government can be enormous.

Indexed as

Cell PhoneAdultCommunicable DiseasesCross-Sectional StudiesData CollectionFeasibility StudiesFemaleHumansIndiaMaleMiddle AgedPublic Health SurveillanceRural Health ServicesRural PopulationIndiainfectionsinformal providersmobile technologysyndromic surveillance

Identifiers

PMID25843499
PMCPMC4385906
OpenAlexW2017821914

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.