Evidence map›Paper›PMID 30173664›Full record

ArticleTheoretical biology & medical modelling2018

A conceptual model for optimizing vaccine coverage to reduce vector-borne infections in the presence of antibody-dependent enhancement.

Biao Tang, Xi Huo, Yanni Xiao, Shigui Ruan, Jianhong Wu

Open access · hybridAbstract read
In one paragraph

Article in Theoretical biology & medical modelling, 2018. 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
1.1field-weighted citation impact, top 20% of its field
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, 14 citations in OpenAlex.

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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

5 authors at 3 institutions in 3 countries.

Biao TangSchool of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, People's Republic of China.
Xi HuoCentre for Disease Modelling, Laboratory for Industrial and Applied Mathematics, York University, Toronto, M3J 1P3, Canada.
Yanni XiaoSchool of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, People's Republic of China.
Shigui RuanDepartment of Mathematics, University of Miami, Coral Gables, 33146, USA.
Jianhong WuCentre for Disease Modelling, Laboratory for Industrial and Applied Mathematics, York University, Toronto, M3J 1P3, Canada. wujh@mathstat.yorku.ca.
York University · CAUniversity of Miami · USXi'an Jiaotong University · CN

Funding

Canada Excellence Research Chairs, Government of Canada 230720Fundamental Research Funds for the Central Universities 08143042International Development Research Center 104519-010National Natural Science Foundation of China 11571273, 11631012National Science Foundation DMS-1412454Natural Sciences and Engineering Research Council of Canada 446610-3
6 · The paper itself

Abstract

backgroundMany vector-borne diseases co-circulate, as the viruses from the same family are also transmitted by the same vector species. For example, Zika and dengue viruses belong to the same Flavivirus family and are primarily transmitted by a common mosquito species Aedes aegypti. Zika outbreaks have also commonly occurred in dengue-endemic areas, and co-circulation and co-infection of both viruses have been reported. As recent immunological cross-reactivity studies have confirmed that convalescent plasma following dengue infection can enhance Zika infection, and as global efforts of developing dengue and Zika vaccines are intensified, it is important to examine whether and how vaccination against one disease in a large population may affect infection dynamics of another disease due to antibody-dependent enhancement.

methodsThrough a conceptual co-infection dynamics model parametrized by reported dengue and Zika epidemic and immunological cross-reactivity characteristics, we evaluate impact of a hypothetical dengue vaccination program on Zika infection dynamics in a single season when only one particular dengue serotype is involved.

resultsWe show that an appropriately designed and optimized dengue vaccination program can not only help control the dengue spread but also, counter-intuitively, reduce Zika infections. We identify optimal dengue vaccination coverages for controlling dengue and simultaneously reducing Zika infections, as well as the critical coverages exceeding which dengue vaccination will increase Zika infections.

conclusionThis study based on a conceptual model shows the promise of an integrative vector-borne disease control strategy involving optimal vaccination programs, in regions where different viruses or different serotypes of the same virus co-circulate, and convalescent plasma following infection from one virus (serotype) can enhance infection against another virus (serotype). The conceptual model provides a first step towards well-designed regional and global vector-borne disease immunization programs.

Indexed as

Models, TheoreticalAnimalsAntibody-Dependent EnhancementDengueDengue VaccinesDengue VirusHumansVaccinationVaccinesZika VirusZika Virus InfectionDengue VaccinesVaccinesAntibody dependent enhancementDengueMathematical modellingOptimized vaccination strategiesZika

Identifiers

PMID30173664
PMCPMC6120075
OpenAlexW2886878777

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.