Evidence map›Paper›PMID 37938887›Full record

ArticleJournal of medical Internet research2023

Community-Based Digital Contact Tracing of Emerging Infectious Diseases: Design and Implementation Study With Empirical COVID-19 Cases.

Hsiao-Chi Wang, Ting-Yu Lin, Yu-Chin Yao, Chen-Yang Hsu, Chang-Jung Yang, Tony Hsiu-Hsi Chen, Yen-Po Yeh

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.8field-weighted citation impact, top 11% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Chatbots and COVID-19: Taking Stock of the Lessons Learned.Journal of medical Internet research · 2024
    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

7 authors at 2 institutions in 1 country.

Hsiao-Chi WangChanghua County Public Health Bureau, Changhua County, Taiwan.ORCID 0009-0009-8343-9353
Ting-Yu LinInstitute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan.ORCID 0000-0003-3595-1570
Yu-Chin YaoChanghua County Public Health Bureau, Changhua County, Taiwan.ORCID 0009-0001-3425-0409
Chen-Yang HsuMaster of Public Health Program, College of Public Health, National Taiwan University, Taipei, Taiwan.ORCID 0000-0001-8586-0277
Chang-Jung YangInstitute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan.ORCID 0009-0007-5517-8155
Tony Hsiu-Hsi ChenInstitute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan.ORCID 0000-0002-5799-6705
Yen-Po YehChanghua County Public Health Bureau, Changhua County, Taiwan.ORCID 0000-0002-1091-387X
National Taiwan University · TWChanghua County Public Health Bureau · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundContact tracing for containing emerging infectious diseases such as COVID-19 is resource intensive and requires digital transformation to enable timely decision-making.

objectiveThis study demonstrates the design and implementation of digital contact tracing using multimodal health informatics to efficiently collect personal information and contain community outbreaks. The implementation of digital contact tracing was further illustrated by 3 empirical SARS-CoV-2 infection clusters.

methodsThe implementation in Changhua, Taiwan, served as a demonstration of the multisectoral informatics and connectivity between electronic health systems needed for digital contact tracing. The framework incorporates traditional travel, occupation, contact, and cluster approaches and a dynamic contact process enabled by digital technology. A centralized registry system, accessible only to authorized health personnel, ensures privacy and data security. The efficiency of the digital contact tracing system was evaluated through a field study in Changhua.

resultsThe digital contact tracing system integrates the immigration registry, communicable disease report system, and national health records to provide real-time information about travel, occupation, contact, and clusters for potential contacts and to facilitate a timely assessment of the risk of COVID-19 transmission. The digitalized system allows for informed decision-making regarding quarantine, isolation, and treatment, with a focus on personal privacy. In the first cluster infection, the system monitored 665 contacts and isolated 4 (0.6%) cases; none of the contacts (0/665, 0%) were infected during quarantine. The estimated reproduction number of 0.92 suggests an effective containment strategy for preventing community-acquired outbreak. The system was also used in a cluster investigation involving foreign workers, where none of the 462 contacts (0/462, 0%) tested positive for SARS-CoV-2.

conclusionsBy integrating the multisectoral database, the contact tracing process can be digitalized to provide the information required for risk assessment and decision-making in a timely manner to contain a community-acquired outbreak when facing the outbreak of emerging infectious disease.

Indexed as

Communicable Diseases, EmergingCOVID-19Contact TracingHumansQuarantineSARS-CoV-2COVID-19digital contact tracingpublic healthsurveillance

Identifiers

PMID37938887
PMCPMC10666017
OpenAlexW4388539643

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.