Evidence map›Paper›PMID 37700711›Full record

ArticleJournal of the Royal Society, Interface2023

Extending susceptible-infectious-recovered-susceptible epidemics to allow for gradual waning of immunity.

Mohamed El Khalifi, Tom Britton

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
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  3. Infinitesimal homeostasis in mass-action systems.Journal of mathematical biology · 2026
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  11. Dynamics in a behavioral-epidemiological model for individual adherence to a nonpharmaceutical intervention.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
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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.

Mohamed El KhalifiDepartment of Mathematics, Stockholm University, Stockholm, Sweden.ORCID 0000-0001-5157-5267
Tom BrittonDepartment of Mathematics, Stockholm University, Stockholm, Sweden.ORCID 0000-0002-9228-7357

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Susceptible-infectious-recovered-susceptible (SIRS) epidemic models assume that individual immunity wanes in one leap, from complete immunity to complete susceptibility. For many diseases immunity on the contrary wanes gradually, something that has become even more evident during COVID-19 pandemic where also recently infected have a reinfection risk, and booster vaccines are given to increase immunity. Here, a novel mathematical model is presented allowing for the gradual decay of immunity following linear or exponential waning functions. The two new models and the SIRS model are compared assuming all three models have the same cumulative immunity. When no intervention is put in place, we find that the long-term prevalence is higher for the models with gradual waning. If aiming for herd immunity by continuous vaccination, it is shown that larger vaccine quantities are required when immunity wanes gradually compared with results obtained from the SIRS model, and this difference is the biggest for the most realistic assumption of exponentially waning of immunity. For parameter choices fitting to COVID-19, the critical amount of vaccine supply is about 50% higher if immunity wanes linearly, and more than 150% higher when immunity wanes exponentially, when compared with the classic SIRS epidemic model.

Indexed as

Communicable DiseasesCOVID-19HumansImmunity, HerdPandemicsSystemic Inflammatory Response Syndromeherd immunityimmunity waningSIRS epidemicvaccination

Identifiers

PMID37700711
PMCPMC10498349

What OpenQuestion holds

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LicenceCC BY
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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.