ArticleOmega2021
Optimising the assignment of swabs and reagent for PCR testing during a viral epidemic.
Article in Omega, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- A machine learning approach for diagnostic and prognostic predictions, key risk factors and interactions.Health services & outcomes research methodology · 2025Article
- Article
- Solving Patient Allocation Problem during an Epidemic Dengue Fever Outbreak by Mathematical Modelling.Healthcare (Basel, Switzerland) · 2022Article
- Optimization in the Context of COVID-19 Prediction and Control: A Literature Review.IEEE access : practical innovations, open solutions · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Early large-scale swab testing is a fundamental tool for health authorities to assess the prevalence of a virus and enact appropriate mitigation measures during an epidemic. The COVID-19 pandemic has shown that the availability of chemical reagent required to carry out the tests is often a bottleneck in increasing a country's testing capacity. Further, demand is unevenly spread between more affected regions (which require more tests they can perform) and less affected ones (which have spare capacity). These issues hint at the opportunity of increasing test capacity via the optimal allocation of swabs and reagent to laboratories. We prove that this is the case, proposing an Integer Programming formulation to maximise the number of tests a country can perform and validating our approach on both real-life data from Italy and synthetic instances. Our results show that increased inter-regional collaboration and a steadier supply of reagent (i.e., coming from local production sites rather than international shipments) can dramatically increase testing capacity. Accordingly, we propose short-term and long-term recommendations for policy makers and health authorities.
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.