Evidence map›Paper›PMID 42005604›Full record

ArticleInfectious Disease Modelling2026

Long-run logistics-based control of non-immunizing infectious diseases.

Dmitry Tsadikovich

Abstract read
In one paragraph

Article in Infectious Disease Modelling, 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

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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

1 author.

Dmitry TsadikovichDepartment of Management, Bar-Ilan University, Ramat-Gan, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-immunizing infectious diseases cannot be eradicated and therefore generate persistent health and intervention costs over time. Steering such diseases toward a stable endemic equilibrium is a natural long-run policy objective. This paper contributes by formulating an integrated infinite-horizon SIS-inventory control model to capture the spread of non-immunizing infectious diseases. Inventory is governed by a controllable replenishment rate that influences the recovery rate, directly linking logistical capacity to epidemiological outcomes. We derive regime-dependent trajectories implied by the Pontryagin Maximum Principle and establish conditions for the existence, reachability, and saddle-type local stability of steady states under three tractable pure replenishment regimes: zero, moderate, and maximum. We find that zero replenishment fails to support convergence to the disease-free equilibrium and leads to persistence of infection, whereas maximum replenishment yields a unique endemic steady state. In contrast, moderate replenishment may generate multiple equilibria. Threshold effects emerge, showing that insufficient replenishment can undermine system stabilization. Numerical experiments illustrate transition dynamics, convergence speeds, and sensitivity to key parameters, yielding practical insights for long-run epidemic management.

Indexed as

Long-term planningNon-immunizing infectious diseasesOptimal controlSIS epidemic-inventory dynamic modelStability analysis

Identifiers

PMID42005604
PMCPMC13091113

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.