Evidence map›Paper›PMID 38668894›Full record

ArticleJournal of mathematical biology2024

An immuno-epidemiological model with waning immunity after infection or vaccination.

Georgi Angelov, Raimund Kovacevic, Nikolaos I Stilianakis, Vladimir M Veliov

Abstract read
In one paragraph

Article in Journal of mathematical biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

4 authors.

Georgi AngelovInstitute of Statistics and Mathematical Methods in Economics, Vienna University of Technology, Vienna, Austria.
Raimund KovacevicDepartment for Economy and Health, University for Continuing Education Krems, Krems an der Donau, Austria.
Nikolaos I StilianakisEuropean Commission, Joint Research Centre (JRC), Ispra, Italy. nikolaos.stilianakis@ec.europa.eu.ORCID 0000-0002-3808-265X
Vladimir M VeliovInstitute of Statistics and Mathematical Methods in Economics, Vienna University of Technology, Vienna, Austria.

Funding

Austrian Science Fund No I 4571-N
6 · The paper itself

Abstract

In epidemics, waning immunity is common after infection or vaccination of individuals. Immunity levels are highly heterogeneous and dynamic. This work presents an immuno-epidemiological model that captures the fundamental dynamic features of immunity acquisition and wane after infection or vaccination and analyzes mathematically its dynamical properties. The model consists of a system of first order partial differential equations, involving nonlinear integral terms and different transfer velocities. Structurally, the equation may be interpreted as a Fokker-Planck equation for a piecewise deterministic process. However, unlike the usual models, our equation involves nonlocal effects, representing the infectivity of the whole environment. This, together with the presence of different transfer velocities, makes the proved existence of a solution novel and nontrivial. In addition, the asymptotic behavior of the model is analyzed based on the obtained qualitative properties of the solution. An optimal control problem with objective function including the total number of deaths and costs of vaccination is explored. Numerical results describe the dynamic relationship between contact rates and optimal solutions. The approach can contribute to the understanding of the dynamics of immune responses at population level and may guide public health policies.

Indexed as

Communicable DiseasesMathematical ConceptsModels, ImmunologicalVaccinationComputer SimulationEpidemicsEpidemiological ModelsHumans92-1092D3093C2093C95

Identifiers

PMID38668894
PMCPMC11052727

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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.