ArticleViruses2022
Modelling the Impact of Mass Testing to Transition from Pandemic Mitigation to Endemic COVID-19.
Article in Viruses, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 14 citations in OpenAlex.
- A policy roadmap for sustainable mass-testing.Health affairs scholar · 2025Article
- Optimization of Screening Strategies for COVID-19: Scoping Review.JMIR public health and surveillance · 2024Article
- Factors associated with delayed diagnosis of symptomatic adult COVID-19 cases presenting to primary care: a population-wide study during transition from Delta to Omicron BA.1 in Singapore.The Lancet regional health. Western Pacific · 2023Article
- Real-life evaluation of a rapid antigen test (DPP SARS-CoV-2 Antigen) for COVID-19 diagnosis of primary healthcare patients, in the context of the Omicron-dominant wave in Brazil.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2023Article
- Performance Evaluation of Five Rapid At-Home COVID-19 Antigen Tests against the Omicron Variant.Microbiology spectrum · 2023Article
- Article
- Detection of hospital environmental contamination during SARS-CoV-2 Omicron predominance using a highly sensitive air sampling device.Frontiers in public health · 2022Article
- Time Analysis of an Emergent Infection Spread Among Healthcare Workers: Lessons Learned from Early Wave of SARS-CoV-2.International journal of general medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As countries transition from pandemic mitigation to endemic COVID-19, mass testing may blunt the impact on the healthcare system of the liminal wave. We used GeoDEMOS-R, an agent-based model of Singapore's population with demographic distributions and vaccination status. A 250-day COVID-19 Delta variant model was run at varying maximal rapid antigen test sensitivities and frequencies. Without testing, the number of infections reached 1,021,000 (899,400-1,147,000) at 250 days. When conducting fortnightly and weekly mass routine rapid antigen testing 30 days into the outbreak at a maximal test sensitivity of 0.6, this was reduced by 12.8% (11.3-14.5%) and 25.2% (22.5-28.5%). An increase in maximal test sensitivity of 0.2 results a corresponding reduction of 17.5% (15.5-20.2%) and 34.4% (30.5-39.1%). Within the maximal test sensitivity range of 0.6-0.8, test frequency has a greater impact than maximal test sensitivity with an average reduction of 2.2% in infections for each day removed between tests in comparison to a 0.43% average reduction per 1% increase in test frequency. Our findings highlight that mass testing using rapid diagnostic tests can be used as an effective intervention for countries transitioning from pandemic mitigation to endemic COVID-19.
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.