Evidence map›Paper›PMID 32404100›Full record

ArticleTheoretical biology & medical modelling2020

Modelling the effect of a dengue vaccine on reducing the evolution of resistance against antibiotic due to misuse in dengue cases.

Ana Kurauchi, Claudio Jose Struchiner, Annelies Wilder-Smith, Eduardo Massad

Abstract read
In one paragraph

Article in Theoretical biology & medical modelling, 2020. 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.

  1. Review
  2. Article
  3. Review
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.

Ana KurauchiSchool of Medicine, University of Sao Paulo, Sao Paulo, Brazil.
Claudio Jose StruchinerSchool of Applied Mathematics, Fundacao Getulio Vargas, Rua Praia de Botafogo 190, Rio de Janeiro, CEP - 22250-900, Brazil.
Annelies Wilder-SmithDepartment of Disease Control, London School of Hygiene and Tropical Medicine, London, UK.
Eduardo MassadSchool of Medicine, University of Sao Paulo, Sao Paulo, Brazil. edmassad@dim.fm.usp.br.ORCID 0000-0002-7200-2916

Funding

H2020 Excellent Science 734584
6 · The paper itself

Abstract

backgroundThis paper intends to check whether and how a hypothetical dengue vaccine could contribute to issue of evolution of bacteria resistance against antibiotics by reducing the number of patients that would inappropriately being treated with antibiotics.

methodsWe use a new mathematical model that combines, in a novel way, two previously published papers, one on the evolution of resistance against antibiotics and one classical Ross-Macdonald model for dengue transmission.

resultsThe model is simulated numerically and reproduces a real case of evolution of resistance against antibiotics. In addition the model shows that the use of a hypothetical dengue vaccine could help to curb the evolution of resistance against an antibiotic inappropriately used in dengue patients. Both the increase in the proportion of resistant bacteria due to the misuse of antibiotics in dengue cases as a function of the fraction of treated patients and the reduction of that proportion as a function of vaccination coverage occur in a highly non-linear fashion.

conclusionThe use of a dengue vaccine is helpful in reducing the rate of evolution of antibiotic resistance in a scenario of misuse of the antibiotics in dengue patients.

Indexed as

DengueDengue VaccinesDengue VirusDrug Resistance, ViralAnti-Bacterial AgentsHumansModels, TheoreticalVaccinationAnti-Bacterial AgentsDengue VaccinesAntibiotic resistanceDengueMathematical modelsVaccine

Identifiers

PMID32404100
PMCPMC7218541

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.