Evidence map›Paper›PMID 33748803›Full record

ReviewThe Lancet. Microbe2021

Perfect as the enemy of good: tracing transmissions with low-sensitivity tests to mitigate SARS-CoV-2 outbreaks.

Lee Kennedy-Shaffer, Michael Baym, William P Hanage

Abstract readReview
In one paragraph

Review in The Lancet. Microbe, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. The importance of prevalence and pre-test probability on the microbiological diagnosis of SARS-CoV-2: the case of Spain in 2020.Revista espanola de quimioterapia : publicacion oficial de la Sociedad Espanola de Quimioterapia · 2023
    Article
  4. An Assessment of a Rapid SARS-CoV-2 Antigen Test in Bangladesh.The American journal of tropical medicine and hygiene · 2022
    Article
  5. Article
  6. Use of clinical data to augment healthcare worker contact tracing during the COVID-19 pandemic.Journal of the American Medical Informatics Association : JAMIA · 2021
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Lee Kennedy-ShafferCenter for Communicable Disease Dynamics, and Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA.
Michael BaymDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
William P HanageCenter for Communicable Disease Dynamics, and Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA.

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI LIPSITCH, MARC · 2009 to 2018
$26.4M
Deep sequencing of pathogens to precisely define transmission networks using rare variantsR01AI128344 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI HANAGE, WILLIAM · 2017 to 2021
$3.4M
Evolutionary Tradeoffs in Antibiotic ResistanceR35GM133700 · NIGMS · HARVARD MEDICAL SCHOOL · PI BAYM, MICHAEL · 2019 to 2023
$2.4M
ACL HHS U01IP001121NCIRD CDC HHS U01 IP001121NIGMS NIH HHS R35 GM133700NIGMS NIH HHS U54 GM088558
6 · The paper itself

Abstract

Throughout the COVID-19 pandemic, governments and individuals have attempted a wide variety of strategies to limit the damage of the pandemic on human lives, population health, and economies. Contact tracing has been a commonly used strategy, and various approaches have been proposed and attempted. We summarise some methods of contact tracing and testing, considering the resources demanded by each and how features of SARS-CoV-2 transmission affect their effectiveness. We also propose an approach focusing on tracing transmission events, which can be particularly effective when superspreading events play a large role in transmission. Accounting for the best available evidence on a pathogen and for the availability of resources can make control strategies more effective, even if they are not perfect.

Indexed as

COVID-19SARS-CoV-2Contact TracingDisease OutbreaksHumansPandemics

Identifiers

PMID33748803
PMCPMC7954468

What OpenQuestion holds

Textmetadata
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.