Evidence map›Paper›PMID 34254937›Full record

ArticleJMIR medical informatics2021

Contact Tracing Apps: Lessons Learned on Privacy, Autonomy, and the Need for Detailed and Thoughtful Implementation.

Katie Hogan, Briana Macedo, Venkata Macha, Arko Barman, Xiaoqian Jiang

Abstract read
In one paragraph

Article in JMIR medical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  11. Making data for good better.PLOS digital health · 2022
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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

5 authors.

Katie Hogan *Department of Bioengineering, Rice University, Houston, TX, United States.ORCID https://orcid.org/0000-0003-1244-4541
Briana Macedo *School of Engineering, Princeton University, Princeton, NJ, United States.ORCID https://orcid.org/0000-0002-8873-699X
Venkata MachaSchool of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States.ORCID https://orcid.org/0000-0002-6880-1352
Arko BarmanDepartment of Electrical & Computer Engineering, Rice University, Houston, TX, United States.ORCID https://orcid.org/0000-0002-5357-5786
Xiaoqian JiangSchool of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, United States.ORCID https://orcid.org/0000-0001-9933-2205

Funding

Open Health Natural Language Processing CollaboratoryU01TR002062 · NCATS · MAYO CLINIC ROCHESTER · PI JIANG, XIAOQIAN, LIU, HONGFANG · 2017 to 2021
$7.6M
Finding Combinatorial Drug Repositioning Therapy For Alzheimer'S Disease And Related DementiasR01AG066749 · NIA · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI JIANG, XIAOQIAN, ZHENG, WENJIN JIM · 2020 to 2024
$4.4M
Secure outsourced computation of genomic dataR41HG010978 · NHGRI · ELIMU INFORMATICS, INC. · PI BOXWALA, AZIZ A, KIM, MIRAN · 2019 to 2020
$566k
3D-Printed Demineralized Bone Matrix Hydrogels for Craniofacial Bone Tissue Regeneration.F31DE030333 · NIDCR · RICE UNIVERSITY · PI HOGAN, KATIE · 2020 to 2022
$141k
NCATS NIH HHS U01 TR002062NHGRI NIH HHS R41 HG010978NIA NIH HHS R01 AG066749NIDCR NIH HHS F31 DE030333
6 · The paper itself

Abstract

The global and national response to the COVID-19 pandemic has been inadequate due to a collective lack of preparation and a shortage of available tools for responding to a large-scale pandemic. By applying lessons learned to create better preventative methods and speedier interventions, the harm of a future pandemic may be dramatically reduced. One potential measure is the widespread use of contact tracing apps. While such apps were designed to combat the COVID-19 pandemic, the time scale in which these apps were deployed proved a significant barrier to efficacy. Many companies and governments sprinted to deploy contact tracing apps that were not properly vetted for performance, privacy, or security issues. The hasty development of incomplete contact tracing apps undermined public trust and negatively influenced perceptions of app efficacy. As a result, many of these apps had poor voluntary public uptake, which greatly decreased the apps' efficacy. Now, with lessons learned from this pandemic, groups can better design and test apps in preparation for the future. In this viewpoint, we outline common strategies employed for contact tracing apps, detail the successes and shortcomings of several prominent apps, and describe lessons learned that may be used to shape effective contact tracing apps for the present and future. Future app designers can keep these lessons in mind to create a version that is suitable for their local culture, especially with regard to local attitudes toward privacy-utility tradeoffs during public health crises.

Indexed as

appcontact tracingCOVID-19eHealthelectronic healthhealth informationmHealthmobile healthmobile phone appspandemicprivacysmartphone apps

Identifiers

PMID34254937
PMCPMC8291141

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.