Evidence map›Paper›PMID 36467718›Full record

ArticleInfectious Disease Modelling2023

Modelling the impact of timelines of testing and isolation on disease control.

Ao Li, Zhen Wang, Seyed M Moghadas

Abstract read
In one paragraph

Article in Infectious Disease Modelling, 2023. 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

3 authors.

Ao LiAgent-Based Modelling Laboratory, York University, Toronto, Ontario, M3J 1P3, Canada.
Zhen WangAgent-Based Modelling Laboratory, York University, Toronto, Ontario, M3J 1P3, Canada.
Seyed M MoghadasAgent-Based Modelling Laboratory, York University, Toronto, Ontario, M3J 1P3, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Testing and isolation remain a key component of public health responses to both persistent and emerging infectious diseases. Although the value of these measures have been demonstrated in combating recent outbreaks including the COVID-19 pandemic and monkeypox, their impact depends critically on the timelines of testing and start of isolation during the course of disease. To investigate this impact, we developed a delay differential model and incorporated age-since-symptom-onset as a parameter for delay in testing. We then used the model to compare the outcomes of reverse-transcription polymerase chain reaction (RT-PCR) and rapid antigen (RA) testing methods when isolation starts either at the time of testing or at the time of test result. Parameterizing the model with estimates of SARS-CoV-2 infection and diagnostic sensitivity of the tests, we found that the reduction of disease transmission using the RA test can be comparable to that achieved by applying the RT-PCR test. Given constraints and inevitable delays associated with sample collection and laboratory assays in RT-PCR testing post symptom onset, self-administered RA tests with short turnaround times present a viable alternative for timely isolation of infectious cases.

Indexed as

Delay equationsIsolationSimulationsTestingTurnaround time

Identifiers

PMID36467718
PMCPMC9704027

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.