Evidence map›Paper›PMID 30073032›Full record

ArticleComputational and mathematical methods in medicine2018

A Note on the Risk of Infections Invading Unaffected Regions.

Marcos Amaku, Francisco Antonio Bezerra Coutinho, Margaret Armstrong, Eduardo Massad

Abstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2018. 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

4 authors.

Marcos AmakuSchool of Medicine, University of Sao Paulo, Sao Paulo, Brazil.ORCID 0000-0003-4752-6774
Francisco Antonio Bezerra CoutinhoSchool of Medicine, University of Sao Paulo, Sao Paulo, Brazil.
Margaret ArmstrongSchool of Applied Mathematics, Fundação Getúlio Vargas, Rio de Janeiro, Brazil.
Eduardo MassadSchool of Medicine, University of Sao Paulo, Sao Paulo, Brazil.ORCID 0000-0002-7200-2916

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present two probabilistic models to estimate the risk of introducing infectious diseases into previously unaffected countries/regions by infective travellers. We analyse two distinct situations, one dealing with a directly transmitted infection (measles in Italy in 2017) and one dealing with a vector-borne infection (Zika virus in Rio de Janeiro, which may happen in the future). To calculate the risk in the first scenario, we used a simple, nonhomogeneous birth process. The second model proposed in this paper provides a way to calculate the probability that local mosquitoes become infected by the arrival of a single infective traveller during his/her infectiousness period. The result of the risk of measles invasion of Italy was of 93% and the result of the risk of Zika virus invasion of Rio de Janeiro was of 22%.

Indexed as

Disease OutbreaksRiskAnimalsBrazilFemaleMaleMosquito VectorsZika VirusZika Virus Infection

Identifiers

PMID30073032
PMCPMC6057402

What OpenQuestion holds

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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.