Evidence map›Paper›PMID 37034306›Full record

ArticleDigital health

Digital dashboards with paradata can improve data quality where disease surveillance relies on real-time data collection.

Sanjeev K Gupta, Himmat Singh, Mahesh C Joshi, Amit Sharma

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

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

10 citing papers in PubMed.

  1. Spatiotemporal Dynamics of Urban Population Based on Mobile Signaling Data and Its Correlation With Wastewater Quantity and Quality.Water environment research : a research publication of the Water Environment Federation · 2026
    Article
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  9. Prevalence and Correlates of Malnutrition in Nuh District, Haryana State, India.The American journal of tropical medicine and hygiene · 2024
    Article
  10. Review
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

4 authors.

Sanjeev K GuptaICMR-National Institute of Malaria Research, New Delhi, India.
Himmat SinghICMR-National Institute of Malaria Research, New Delhi, India.
Mahesh C JoshiKumaun University, Nainital, Uttarakhand, India.
Amit SharmaICMR-National Institute of Malaria Research, New Delhi, India.ORCID https://orcid.org/0000-0002-3305-0034

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dealing with the threats of vector-borne diseases necessitates robust disease surveillance systems. The gathered information from surveillance studies is used to evaluate the effectiveness of control measures. It also guides the allocation of resources within the healthcare system. The disease surveillance data also identify high-risk populations or geographic areas to target interventions. Because of the importance of surveillance in decision-making and its timely requirement, real-time data collection is vital. A few advantages of real-time data collection apps are building powerful digital forms, exporting data for quick analysis in various formats, and being open-source. These apps automate data collection and transfer to an online server even without an internet connection. While collecting disease surveillance data digitally one crucial aspect lacking is data quality. This paper aims to present the importance of dashboards that includes paradata in improving data quality using real-time data collection tools in disease surveillance. Various types of paradata such as timestamps, geo-referencing, audio recording and so on help enhance the quality of data and can help monitor and evaluate surveillance staff. The outcomes of the paradata analysis may lead to the retraining of the surveillance team and even re-planning of surveillance. Undoubtedly, real-time data collection is the way of the future in any field-based study, and studies should be planned in conjunction with paradata to ensure that high-quality data are recorded.

Indexed as

dashboardData qualitymobile appreal-time data collectionvector-borne diseases

Identifiers

PMID37034306
PMCPMC10074606

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.