Evidence map›Paper›PMID 38915175›Full record

ArticleJMIR public health and surveillance2024

A Novel Web-Based Application for Influenza and COVID-19 Outbreak Detection and Response in Residential Aged Care Facilities.

Kai Hsun Hsiao, Emma Quinn, Travers Johnstone, Maria Gomez, Andrew Ingleton, Arun Parasuraman, Zeina Najjar, Leena Gupta

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Kai Hsun HsiaoPublic Health Unit, Sydney Local Health District, Sydney, Australia.ORCID 0000-0002-4880-7538
Emma QuinnPublic Health Unit, Sydney Local Health District, Sydney, Australia.ORCID 0000-0001-9567-6756
Travers JohnstonePublic Health Unit, Sydney Local Health District, Sydney, Australia.ORCID 0000-0002-5447-5509
Maria GomezPublic Health Unit, Sydney Local Health District, Sydney, Australia.ORCID 0000-0003-4336-6099
Andrew IngletonPublic Health Unit, Sydney Local Health District, Sydney, Australia.ORCID 0000-0001-7875-760X
Arun ParasuramanPublic Health Unit, Sydney Local Health District, Sydney, Australia.ORCID 0000-0002-6524-7288
Zeina NajjarPublic Health Unit, Sydney Local Health District, Sydney, Australia.ORCID 0000-0002-1972-9657
Leena GuptaPublic Health Unit, Sydney Local Health District, Sydney, Australia.ORCID 0000-0002-4283-2919

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unlabelled: The use of innovative digital health technologies in public health is expanding quickly, including the use of these tools in outbreak response. The translation of a digital health innovation into effective public health practice is a complex process requiring diverse enablers across the people, process, and technology domains. This paper describes a novel web-based application that was designed and implemented by a district-level public health authority to assist residential aged care facilities in influenza and COVID-19 outbreak detection and response. It discusses some of the challenges, enablers, and key lessons learned in designing and implementing such a novel application from the perspectives of the public health practitioners (the authors) that undertook this project.

Indexed as

COVID-19Disease OutbreaksHomes for the AgedInfluenza, HumanInternetAgedHumansaged careaged care homescommunicable disease controldigital healthinfluenzaoutbreaksurveillanceweb application

Identifiers

PMID38915175
PMCPMC11217159

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.