Evidence map›Paper›PMID 33977079›Full record

ArticleResults in physics2021

Mathematical modeling of the COVID-19 pandemic with intervention strategies.

Subhas Khajanchi, Kankan Sarkar, Jayanta Mondal, Kottakkaran Sooppy Nisar, Sayed F Abdelwahab

Open access · goldAbstract read
In one paragraph

Article in Results in physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed
10.6field-weighted citation impact, top 1% 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

49 citing papers in PubMed, 137 citations in OpenAlex.

  1. Economic Impact Evaluation of COVID-19 Public Health Management Across Countries.The International journal of health planning and management · 2026
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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

5 authors at 5 institutions in 2 countries.

Subhas KhajanchiDepartment of Mathematics, Presidency University, 86/1 College Street, Kolkata 700073, India.
Kankan SarkarDepartment of Mathematics, Malda College, Malda, West Bengal 732101, India.
Jayanta MondalDepartment of Mathematics, Diamond Harbour Women's University, Diamond Harbour Road, Sarisha 743368, India.
Kottakkaran Sooppy NisarDepartment of Mathematics, College of Arts and Science, Prince Sattam bin Abdulaziz University, Wadi Al-Dawaser 11991, Saudi Arabia.
Sayed F AbdelwahabDepartment of Pharmaceutics and Industrial Pharmacy, College of Pharmacy, Taif University, PO Box 11099, Taif 21944, Saudi Arabia.
Diamond Harbour Women's University · INJadavpur University · INPresidency University · INPrince Sattam Bin Abdulaziz University · SATaif University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mathematical modeling plays an important role to better understand the disease dynamics and designing strategies to manage quickly spreading infectious diseases in lack of an effective vaccine or specific antivirals. During this period, forecasting is of utmost priority for health care planning and to combat COVID-19 pandemic. In this study, we proposed and extended classical SEIR compartment model refined by contact tracing and hospitalization strategies to explain the COVID-19 outbreak. We calibrated our model with daily COVID-19 data for the five provinces of India namely, Kerala, Karnataka, Andhra Pradesh, Maharashtra, West Bengal and the overall India. To identify the most effective parameters we conduct a sensitivity analysis by using the partial rank correlation coefficients techniques. The value of those sensitive parameters were estimated from the observed data by least square method. We performed sensitivity analysis for

Indexed as

Basic reproduction numberIndiaModel predictionPower lawSensitivity analysis

Identifiers

PMID33977079
PMCPMC8101006
OpenAlexW3157607700

What OpenQuestion holds

Textmetadata
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.