Evidence map›Paper›PMID 38395830›Full record

ArticleBMC public health2024

Looking under the lamp-post: quantifying the performance of contact tracing in the United States during the SARS-CoV-2 pandemic.

Henry Bayly, Madison Stoddard, Debra Van Egeren, Eleanor J Murray, Julia Raifman, Arijit Chakravarty, Laura F White

Abstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Henry BaylyDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
Madison StoddardFractal Therapeutics, Cambridge, MA, USA.
Debra Van EgerenStanford University, Palo Alto, CA, USA.
Eleanor J MurrayDepartment of Epidemiology, Boston University School of Public Health, Boston, MA, USA.
Julia RaifmanDepartment of Health Law, Policy and Management, Boston University School of Public Health, Boston, MA, USA.
Arijit Chakravarty *Fractal Therapeutics, Cambridge, MA, USA.
Laura F White *Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA. lfwhite@bu.edu.

Funding

Maximizing Investigators' Research Award (R35)R35GM141821 · NIGMS · BOSTON UNIVERSITY MEDICAL CAMPUS · PI WHITE, LAURA FORSBERG · 2021 to 2025
$1.8M
NIGMS NIH HHS R35 GM141821NIH HHS R35GM141821
6 · The paper itself

Abstract

Contact tracing forms a crucial part of the public-health toolbox in mitigating and understanding emergent pathogens and nascent disease outbreaks. Contact tracing in the United States was conducted during the pre-Omicron phase of the ongoing COVID-19 pandemic. This tracing relied on voluntary reporting and responses, often using rapid antigen tests due to lack of accessibility to PCR tests. These limitations, combined with SARS-CoV-2's propensity for asymptomatic transmission, raise the question "how reliable was contact tracing for COVID-19 in the United States"? We answered this question using a Markov model to examine the efficiency with which transmission could be detected based on the design and response rates of contact tracing studies in the United States. Our results suggest that contact tracing protocols in the U.S. are unlikely to have identified more than 1.65% (95% uncertainty interval: 1.62-1.68%) of transmission events with PCR testing and 1.00% (95% uncertainty interval 0.98-1.02%) with rapid antigen testing. When considering a more robust contact tracing scenario, based on compliance rates in East Asia with PCR testing, this increases to 62.7% (95% uncertainty interval: 62.6-62.8%). We did not assume presence of asymptomatic transmission or superspreading, making our estimates upper bounds on the actual percentages traced. These findings highlight the limitations in interpretability for studies of SARS-CoV-2 disease spread based on U.S. contact tracing and underscore the vulnerability of the population to future disease outbreaks, for SARS-CoV-2 and other pathogens.

Indexed as

COVID-19SARS-CoV-2Contact TracingDisease OutbreaksHumansPandemicsUnited StatesContact tracingCOVID-19Infectious disease epidemiologyInfectious disease transmissionSARS-CoV-2

Identifiers

PMID38395830
PMCPMC10893709

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.