Evidence map›Paper›PMID 33881406›Full record

SynthesisJMIR public health and surveillance2021

Web-Based Apps for Responding to Acute Infectious Disease Outbreaks in the Community: Systematic Review.

Emma Quinn, Kai Hsun Hsiao, Isis Maitland-Scott, Maria Gomez, Melissa T Baysari, Zeina Najjar, Leena Gupta

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis 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 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.4field-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

7 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
  2. Use of Digital Tools in Arbovirus Surveillance: Scoping Review.Journal of medical Internet research · 2024
    Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. 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

7 authors at 2 institutions in 1 country.

Emma Quinn *Sydney Local Health District, Camperdown Public Health Unit, Royal Prince Alfred Hospital Campus, Camperdown, Sydney, NSW, Australia.ORCID 0000-0001-9567-6756
Kai Hsun Hsiao *Sydney Local Health District, Camperdown Public Health Unit, Royal Prince Alfred Hospital Campus, Camperdown, Sydney, NSW, Australia.ORCID 0000-0002-4880-7538
Isis Maitland-ScottSydney Local Health District, Camperdown Public Health Unit, Royal Prince Alfred Hospital Campus, Camperdown, Sydney, NSW, Australia.ORCID 0000-0003-4941-440X
Maria GomezSydney Local Health District, Camperdown Public Health Unit, Royal Prince Alfred Hospital Campus, Camperdown, Sydney, NSW, Australia.ORCID 0000-0003-4336-6099
Melissa T BaysariCharles Perkins Centre, Faculty of Medicine and Health, University of Sydney, Camperdown, Sydney, NSW, Australia.ORCID 0000-0003-1645-9126
Zeina NajjarSydney Local Health District, Camperdown Public Health Unit, Royal Prince Alfred Hospital Campus, Camperdown, Sydney, NSW, Australia.ORCID 0000-0002-1972-9657
Leena GuptaSydney Local Health District, Camperdown Public Health Unit, Royal Prince Alfred Hospital Campus, Camperdown, Sydney, NSW, Australia.ORCID 0000-0002-4283-2919
Royal Prince Alfred Hospital · AUThe University of Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWeb-based technology has dramatically improved our ability to detect communicable disease outbreaks, with the potential to reduce morbidity and mortality because of swift public health action. Apps accessible through the internet and on mobile devices create an opportunity to enhance our traditional indicator-based surveillance systems, which have high specificity but issues with timeliness.

objectiveThe aim of this study is to describe the literature on web-based apps for indicator-based surveillance and response to acute communicable disease outbreaks in the community with regard to their design, implementation, and evaluation.

methodsWe conducted a systematic search of the published literature across four databases (MEDLINE via OVID, Web of Science Core Collection, ProQuest Science, and Google Scholar) for peer-reviewed journal papers from January 1998 to October 2019 using a keyword search. Papers with the full text available were extracted for review, and exclusion criteria were applied to identify eligible papers.

resultsOf the 6649 retrieved papers, 23 remained, describing 15 web-based apps. Apps were primarily designed to improve the early detection of disease outbreaks, targeted government settings, and comprised either complex algorithmic or statistical outbreak detection mechanisms or both. We identified a need for these apps to have more features to support secure information exchange and outbreak response actions, with a focus on outbreak verification processes and staff and resources to support app operations. Evaluation studies (6 out of 15 apps) were mostly cross-sectional, with some evidence of reduction in time to notification of outbreak; however, studies lacked user-based needs assessments and evaluation of implementation.

conclusionsPublic health officials designing new or improving existing disease outbreak web-based apps should ensure that outbreak detection is automatic and signals are verified by users, the app is easy to use, and staff and resources are available to support the operations of the app and conduct rigorous and holistic evaluations.

Indexed as

InternetMobile ApplicationsCommunity-Acquired InfectionsDisease OutbreaksHumanseHealthinfectious diseasesmHealthmobile appsmobile phoneoutbreakssoftware

Identifiers

PMID33881406
PMCPMC8100883
OpenAlexW3113806128

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.