Evidence map›Paper›PMID 42256448›Full record

ArticleBollettino della Unione matematica italiana (2008)2026

Epidemicity conditions in spatial models of infectious diseases.

Marino Gatto, Cristiano Trevisin, Lorenzo Mari, Damiano Pasetto, Enrico Bertuzzo, Renato Casagrandi, Andrea Rinaldo

Abstract read
In one paragraph

Article in Bollettino della Unione matematica italiana (2008), 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

7 authors.

Marino GattoDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Via G. Ponzio 34/5, Milan, 20133 Italy.ORCID 0000-0001-8063-9178
Cristiano TrevisinLaboratory of Ecohydrology, École Polytechnique Fédérale de Lausanne, Station 2, Lausanne, 1015 Switzerland.
Lorenzo MariDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Via G. Ponzio 34/5, Milan, 20133 Italy.
Damiano PasettoDepartment of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice, Via Torino 155, Venezia Mestre, 30170 Italy.
Enrico BertuzzoDepartment of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice, Via Torino 155, Venezia Mestre, 30170 Italy.
Renato CasagrandiDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Via G. Ponzio 34/5, Milan, 20133 Italy.
Andrea RinaldoLaboratory of Ecohydrology, École Polytechnique Fédérale de Lausanne, Station 2, Lausanne, 1015 Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We review the work that has been conducted in the past years to understand when and why significant epidemics may arise even though a disease is not bound to become endemic in the long run i.e. subthreshold outbreaks. In particular, we describe the methods that allow the analysis of such outbreaks not only in time but also in space. To that end, we introduce a broad class of spatially explicit mathematical models of water- and air-borne diseases. These models consist of coupled ordinary differential or difference equations. The spatial coupling is obtained via suitable networks that describe connectivity via waterways or human mobility, or both (multiplex networks). We derive exact epidemicity conditions under which the disease-free equilibrium, although asymptotically stable, may be characterized by bursts of infections possibly coalescing, epitomized by transient increases of the infected compartments given suitable perturbations. The growth of infections is quantified by means of

Indexed as

EpidemiologyReactivityReproduction numberSpace-explicit models

Identifiers

PMID42256448
PMCPMC13233924

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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.