ArticleRoyal Society open science2021
Cost and social distancing dynamics in a mathematical model of COVID-19 with application to Ontario, Canada.
Article in Royal Society open science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- A Retrospective Study of the Effects of COVID-19 Non-Pharmaceutical Interventions on Influenza in Canada.Infectious disease reports · 2025Article
- Adaptive human behavior and delays in information availability autonomously modulate epidemic waves.PNAS nexus · 2025Article
- Predicting Covid-19 pandemic waves with biologically and behaviorally informed universal differential equations.Heliyon · 2024Article
- Pharmaceutical and non-pharmaceutical interventions for controlling the COVID-19 pandemic.Royal Society open science · 2023Article
- Cost-effectiveness analysis of COVID-19 variants effects in an age-structured model.Scientific reports · 2023Article
- Multiple cohort study of hospitalized SARS-CoV-2 in-host infection dynamics: Parameter estimates, identifiability, sensitivity and the eclipse phase profile.Journal of theoretical biology · 2023Article
- Mathematical Modeling of COVID-19 Transmission and Intervention in South Korea: A Review of Literature.Yonsei medical journal · 2023Review
- Social distancing as a public-good dilemma for socio-economic cost: An evolutionary game approach.Heliyon · 2022Article
- Controlling Multiple COVID-19 Epidemic Waves: An Insight from a Multi-scale Model Linking the Behaviour Change Dynamics to the Disease Transmission Dynamics.Bulletin of mathematical biology · 2022Article
- Studying the mixed transmission in a community with age heterogeneity: COVID-19 as a case study.Infectious Disease Modelling · 2022Article
- Article
- 'Distant socializing,' not 'social distancing' as a public health strategy for COVID-19.Pathogens and global health · 2021Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A mathematical model of COVID-19 is presented where the decision to increase or decrease social distancing is modelled dynamically as a function of the measured active and total cases as well as the perceived cost of isolating. Along with the cost of isolation, we define an overburden healthcare cost and a total cost. We explore these costs by adjusting parameters that could change with policy decisions. We observe that two disease prevention practices, namely increasing isolation activity and increasing incentive to isolate do not always lead to optimal health outcomes. We demonstrate that this is due to the fatigue and cost of isolation. We further demonstrate that an increase in the number of lock-downs, each of shorter duration can lead to minimal costs. Our results are compared with case data in Ontario, Canada from March to August 2020 and details of expanding the results to other regions are presented.
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.