ArticleScience advances2024
Modeling the transmission mitigation impact of testing for infectious diseases.
Article in Science advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed.
- Decentralised rapid diagnostic tests enable cholera diagnosis by non-laboratory health workers during outbreaks in Cameroon.Scientific reports · 2026Article
- Respiratory Viral Co-Infections in Pediatric Patients: Clinical Impact and Implications for Healthcare Practice-A Narrative Review.Healthcare (Basel, Switzerland) · 2026Review
- Identifying the optimal rapid antigen test for screening and determining the end of isolation: A modeling study.PLoS computational biology · 2026Article
- Individual and population level uncertainty interact to determine the performance of outbreak surveillance systems.PLoS computational biology · 2026Article
- A fundamental limit to the effectiveness of traveller screening with molecular tests.Epidemiology and infection · 2025Article
- Enhanced testing can substantially improve defense against several types of respiratory virus pandemic.Epidemics · 2025Article
Corrections and comments
- Update of
Authors and funding
2 authors.
Funding
Abstract
A fundamental question of any program focused on the testing and timely diagnosis of a communicable disease is its effectiveness in reducing transmission. Here, we introduce testing effectiveness (TE)-the fraction by which testing and post-diagnosis isolation reduce transmission at the population scale-and a model that incorporates test specifications and usage, within-host pathogen dynamics, and human behaviors to estimate TE. Using TE to guide recommendations, we show that today's rapid diagnostics should be used immediately upon symptom onset to control influenza A and respiratory syncytial virus but delayed by up to two days to control omicron-era severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Furthermore, while rapid tests are superior to reverse transcription quantitative polymerase chain reaction (RT-qPCR) to control founder-strain SARS-CoV-2, omicron-era changes in viral kinetics and rapid test sensitivity cause a reversal, with higher TE for RT-qPCR despite longer turnaround times. Last, we illustrate the model's flexibility by quantifying trade-offs in the use of post-diagnosis testing to shorten isolation times.
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Registered trials
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 Socratic graph.