Evidence map›Paper›PMID 33854079›Full record

ArticleScientific reports2021

A compartmental model that predicts the effect of social distancing and vaccination on controlling COVID-19.

Mohammadali Dashtbali, Mehdi Mirzaie

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
8.1field-weighted citation impact, top 2% of its field
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

39 citing papers in PubMed, 1 synthesis or guideline pooled it, 102 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Mohammadali DashtbaliDepartment of Applied Mathematics, Faculty of Mathematical Sciences, Tarbiat Modares University, Jalal Al-Ahmad High Way, Tehran, Iran.
Mehdi MirzaieDepartment of Applied Mathematics, Faculty of Mathematical Sciences, Tarbiat Modares University, Jalal Al-Ahmad High Way, Tehran, Iran. mirzaie@modares.ac.ir.
Tarbiat Modares University · IR

Funding

Tarbiat Modares University IG-39706
6 · The paper itself

Abstract

The understanding of the interaction between disease dynamics and human behavior is an important and essential point to control infectious. Disease outbreak can be influenced by social distancing and vaccination. In this study, we introduce two compartmental models to derive the epidemic curve and analyze the individual's behavior in spreading and controlling the COVID-19 epidemic. The first model includes Susceptible, Exposed, Infectious, Hospitalized, Recovered and Death compartments and in the second model, we added a new compartment namely, semi-susceptible individuals that are assumed to be more immune than the susceptible. A comparison of the two models shows that the second model provides a better fit to the daily infected cases from Egypt, Belgium, Japan, Nigeria, Italy, and Germany released by WHO. Finally, we added a vaccinated term to the model to predict how vaccination could control the epidemic. The model was applied on the record data from WHO.

Indexed as

Physical DistancingCommunicable Disease ControlCOVID-19COVID-19 VaccinesDatabases, FactualDisease OutbreaksForecastingHumansInfection ControlModels, TheoreticalPandemicsSARS-CoV-2VaccinationWorld Health OrganizationCOVID-19 Vaccines

Identifiers

PMID33854079
PMCPMC8046797
OpenAlexW3149267640

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.