Evidence map›Paper›PMID 33687334›Full record

ArticleJMIR public health and surveillance2021

A Mobile App and Dashboard for Early Detection of Infectious Disease Outbreaks: Development Study.

Euijoon Ahn, Na Liu, Tej Parekh, Ronak Patel, Tanya Baldacchino, Tracy Mullavey, Amanda Robinson, Jinman Kim

Open access · goldAbstract read
In one paragraph

Article in JMIR public health and surveillance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
2.9field-weighted citation impact, top 9% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Euijoon AhnSchool of Computer Science, The University of Sydney, Darlington, Australia.ORCID 0000-0001-7027-067X
Na LiuThe University Sydney Business School, Darlington, Australia.ORCID 0000-0003-1046-0775
Tej ParekhSchool of Computer Science, The University of Sydney, Darlington, Australia.ORCID 0000-0003-4519-5887
Ronak PatelSchool of Computer Science, The University of Sydney, Darlington, Australia.ORCID 0000-0002-8871-6390
Tanya BaldacchinoTelehealth Technology Centre, Nepean Hospital, Nepean Blue Mountains Local Health District, Kingswood, Australia.ORCID 0000-0002-8247-7704
Tracy MullaveyTelehealth Technology Centre, Nepean Hospital, Nepean Blue Mountains Local Health District, Kingswood, Australia.ORCID 0000-0002-1865-1106
Amanda RobinsonPublic Health Unit, Nepean Hospital, Nepean Blue Mountains Local Health District, Kingswood, Australia.ORCID 0000-0001-8258-4983
Jinman KimSchool of Computer Science, The University of Sydney, Darlington, Australia.ORCID 0000-0001-5960-1060
The University of Sydney · AUNepean Hospital · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOutbreaks of infectious diseases pose great risks, including hospitalization and death, to public health. Therefore, improving the management of outbreaks is important for preventing widespread infection and mitigating associated risks. Mobile health technology provides new capabilities that can help better capture, monitor, and manage infectious diseases, including the ability to quickly identify potential outbreaks.

objectiveThis study aims to develop a new infectious disease surveillance (IDS) system comprising a mobile app for accurate data capturing and dashboard for better health care planning and decision making.

methodsWe developed the IDS system using a 2-pronged approach: a literature review on available and similar disease surveillance systems to understand the fundamental requirements and face-to-face interviews to collect specific user requirements from the local public health unit team at the Nepean Hospital, Nepean Blue Mountains Local Health District, New South Wales, Australia.

resultsWe identified 3 fundamental requirements when designing an electronic IDS system, which are the ability to capture and report outbreak data accurately, completely, and in a timely fashion. We then developed our IDS system based on the workflow, scope, and specific requirements of the public health unit team. We also produced detailed design and requirement guidelines. In our system, the outbreak data are captured and sent from anywhere using a mobile device or a desktop PC (web interface). The data are processed using a client-server architecture and, therefore, can be analyzed in real time. Our dashboard is designed to provide a daily, weekly, monthly, and historical summary of outbreak information, which can be potentially used to develop a future intervention plan. Specific information about certain outbreaks can also be visualized interactively to understand the unique characteristics of emerging infectious diseases.

conclusionsWe demonstrated the design and development of our IDS system. We suggest that the use of a mobile app and dashboard will simplify the overall data collection, reporting, and analysis processes, thereby improving the public health responses and providing accurate registration of outbreak information. Accurate data reporting and collection are a major step forward in creating a better intervention plan for future outbreaks of infectious diseases.

Indexed as

Mobile ApplicationsAustraliaCommunicable DiseasesDisease OutbreaksEarly DiagnosisHumansPublic Health Surveillancedisease notificationinfectious disease reportingmobile appmobile phonepublic health

Identifiers

PMID33687334
PMCPMC7988388
OpenAlexW3121864895

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.