Evidence map›Paper›PMID 41519879›Full record

ArticleScientific reports2026

SEIRV epidemiological model for COVID 19 with Holling type II functional response.

Sajal Chakroborty, Fahad Mostafa

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Sajal ChakrobortyDepartment of Mathematical Sciences, Worcester Polytechnic Institute, Worcester, MA, USA.
Fahad MostafaSchool of Mathematical and Natural Sciences, and Julie Ann Wrigley Global Futures Laboratory, Arizona State University, Tempe, USA. Fahad.Mostafa@asu.edu.

Funding

Arizona State University P001500
6 · The paper itself

Abstract

Data-driven mathematical models are recognized as a significant tool for understanding infectious disease dynamics and have been valuable in public health research for an extended period of time. In this paper, we develop an SEIRV model that includes susceptible, exposed, infectious, and vaccinated populations to investigate the dynamics of the SARS-CoV-2 virus. We incorporate a Holling type-II functional response in our model, which has been widely useful in studying ecological systems. This approach enables us to conduct comprehensive analysis by integrating analytical, computational, and statistical tools, providing a deeper understanding of the spread of SARS-CoV-2. We derive a closed-form mathematical expression to compute the basic reproduction number, calculate predictive intervals for it, and analyze the sensitivity of some parameters to understand the spread of the disease.

Indexed as

COVID-19Epidemiological ModelsBasic Reproduction NumberHumansPandemicsSARS-CoV-2COVID 19EpidemiologyHolling type-II functional responseInfectious diseaseMCMC samplingParameter estimationPublic health research toolSERIV model

Identifiers

PMID41519879
PMCPMC12868722

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.