ArticleGlobal health action2015
Collecting syndromic surveillance data by mobile phone in rural India: implementation and feasibility.
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.
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Who cites it
11 citing papers in PubMed, 30 citations in OpenAlex.
- Experiences in running a complex electronic data capture system using mobile phones in a large-scale population trial in southern Nepal.Global health action · 2017Trial
- Filling the gap: artificial intelligence-driven one health integration to strengthen pandemic preparedness in resource-limited settings.Frontiers in public health · 2025Review
- From Fax to Secure File Transfer Protocol: The 25-Year Evolution of Real-Time Syndromic Surveillance in England.Journal of medical Internet research · 2024Article
- Integrated community based human and animal syndromic surveillance in Adadle district of the Somali region of Ethiopia.One health (Amsterdam, Netherlands) · 2021Article
- Electronic reporting of integrated disease surveillance and response: lessons learned from northeast, Nigeria, 2019.BMC public health · 2021Article
- Estimating COVID-19 cases and outbreaks on-stream through phone calls.Royal Society open science · 2021Article
- A Mobile App and Dashboard for Early Detection of Infectious Disease Outbreaks: Development Study.JMIR public health and surveillance · 2021Article
- Adaptation of a mobile phone health survey for risk factors for noncommunicable diseases in Colombia: a qualitative study.Global health action · 2020Article
- Implementing Nationwide Facility-based Electronic Disease Surveillance in Sierra Leone: Lessons Learned.Health security · 2020Article
- Current Status and Future Directions of mHealth Interventions for Health System Strengthening in India: Systematic Review.JMIR mHealth and uHealth · 2018Review
- Compliance of Specific Provisions of Tobacco Control Law around Educational Institutions in Delhi, India.International journal of preventive medicine · 2017Article
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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