Evidence map›Paper›PMID 32887338›Full record

ArticleSensors (Basel, Switzerland)2020

A COVID-19-Based Modified Epidemiological Model and Technological Approaches to Help Vulnerable Individuals Emerge from the Lockdown in the UK.

Dario Ortega Anderez, Eiman Kanjo, Ganna Pogrebna, Omprakash Kaiwartya, Shane D Johnson, John Alan Hunt

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

6 authors.

Dario Ortega AnderezSchool of Science and Technology, Nottingham Trent University, Nottingham NG11 8NS, UK.
Eiman KanjoSchool of Science and Technology, Nottingham Trent University, Nottingham NG11 8NS, UK.ORCID 0000-0002-1720-0661
Ganna PogrebnaBusiness School, The University of Sydney, Abercrombie Building H70, Darlington, NSW 2006, Australia.
Omprakash KaiwartyaSchool of Science and Technology, Nottingham Trent University, Nottingham NG11 8NS, UK.ORCID 0000-0001-9669-8244
Shane D JohnsonJill Dando Institute, University College London (UCL), 35 Tavistock Square, London WC1H 9EZ, UK.
John Alan HuntMedical Technologies Innovation Facility, Nottingham Trent University, Nottingham NG11 8NS, UK.ORCID 0000-0002-5168-4778

Funding

Nottingham Trent University 00-11-22
6 · The paper itself

Abstract

COVID-19 has shown a relatively low case fatality rate in young healthy individuals, with the majority of this group being asymptomatic or having mild symptoms. However, the severity of the disease among the elderly as well as in individuals with underlying health conditions has caused significant mortality rates worldwide. Understanding this variance amongst different sectors of society and modelling this will enable the different levels of risk to be determined to enable strategies to be applied to different groups. Long-established compartmental epidemiological models like SIR and SEIR do not account for the variability encountered in the severity of the SARS-CoV-2 disease across different population groups. The objective of this study is to investigate how a reduction in the exposure of vulnerable individuals to COVID-19 can minimise the number of deaths caused by the disease, using the UK as a case study. To overcome the limitation of long-established compartmental epidemiological models, it is proposed that a modified model, namely SEIR-v, through which the population is separated into two groups regarding their vulnerability to SARS-CoV-2 is applied. This enables the analysis of the spread of the epidemic when different contention measures are applied to different groups in society regarding their vulnerability to the disease. A Monte Carlo simulation (100,000 runs) along the proposed SEIR-v model is used to study the number of deaths which could be avoided as a function of the decrease in the exposure of vulnerable individuals to the disease. The results indicate a large number of deaths could be avoided by a slight realistic decrease in the exposure of vulnerable groups to the disease. The mean values across the simulations indicate 3681 and 7460 lives could be saved when such exposure is reduced by 10% and 20% respectively. From the encouraging results of the modelling a number of mechanisms are proposed to limit the exposure of vulnerable individuals to the disease. One option could be the provision of a wristband to vulnerable people and those without a smartphone and contact-tracing app, filling the gap created by systems relying on smartphone apps only. By combining very dense contact tracing data from smartphone apps and wristband signals with information about infection status and symptoms, vulnerable people can be protected and kept safer.

Indexed as

Models, TheoreticalVulnerable PopulationsContact TracingCoronavirus InfectionsCOVID-19Disease OutbreaksDisease Transmission, InfectiousHealth Planning GuidelinesHealth Services Needs and DemandHumansInfection ControlInventionsPandemicsPneumonia, ViralPreventive Health ServicesPublic Healthcontact tracingcoronavirusCOVID-19epidemiological modelinfection spread modellingpersonal protective equipment

Identifiers

PMID32887338
PMCPMC7506567

What OpenQuestion holds

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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.