Evidence map›Paper›PMID 38250900›Full record

ReviewVaccines2024

Development of Vaccines against Emerging Mosquito-Vectored Arbovirus Infections.

Nicola Principi, Susanna Esposito

Open access · goldAbstract readReview
In one paragraph

Review in Vaccines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
11.9field-weighted citation impact, top 1% 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

13 citing papers in PubMed, 22 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

2 authors at 2 institutions in 1 country.

Nicola PrincipiUniversità degli Studi di Milano, 20122 Milan, Italy.ORCID 0000-0002-3468-5568
Susanna EspositoPediatric Clinic, Department of Medicine and Surgery, University of Parma, 43126 Parma, Italy.ORCID 0000-0003-4103-2837
University of Milan · ITUniversity of Parma · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Among emergent climate-sensitive infectious diseases, some mosquito-vectored arbovirus infections have epidemiological, social, and economic effects. Dengue virus (DENV), West Nile virus (WNV), and Chikungunya virus (CHIKV) disease, previously common only in the tropics, currently pose a major risk to global health and are expected to expand dramatically in the near future if adequate containment measures are not implemented. The lack of safe and effective vaccines is critical as it seems likely that emerging mosquito-vectored arbovirus infections will be con-trolled only when effective and safe vaccines against each of these infections become available. This paper discusses the clinical characteristics of DENV, WNV, and CHIKV infections and the state of development of vaccines against these viruses. An ideal vaccine should be able to evoke with a single administration a prompt activation of B and T cells, adequate concentrations of protecting/neutralizing antibodies, and the creation of a strong immune memory capable of triggering an effective secondary antibody response after new infection with a wild-type and/or mutated infectious agent. Moreover, the vaccine should be well tolerated, safe, easily administrated, cost-effective, and widely available throughout the world. However, the development of vaccines against emerging mosquito-vectored arbovirus diseases is far from being satisfactory, and it seems likely that it will take many years before effective and safe vaccines for all these infections are made available worldwide.

Indexed as

arbovirus infectionChikungunya virus diseasedenguemosquitovaccinesWest Nile virus disease

Identifiers

PMID38250900
PMCPMC10818606
OpenAlexW4390877180

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.