Evidence map›Paper›PMID 30011271›Full record

ArticlePLoS neglected tropical diseases2018

Current challenges and implications for dengue, chikungunya and Zika seroprevalence studies worldwide: A scoping review.

Camille Fritzell, Dominique Rousset, Antoine Adde, Mirdad Kazanji, Maria D Van Kerkhove, Claude Flamand

Open access · goldAbstract readScoping Review
In one paragraph

Article in PLoS neglected tropical diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed, 7 pooled it
22.5field-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

80 citing papers in PubMed, 7 syntheses or guidelines pooled it, 206 citations in OpenAlex.

  1. Pooled it
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  3. Chikungunya seroprevalence in population-based studies: a systematic review and meta-analysis.Archives of public health = Archives belges de sante publique · 2023
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  14. Zika Virus: A Tale of Two Lineages.Pathogens (Basel, Switzerland) · 2025
    Review
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20 more citing papers are in PubMed but not listed here.

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

6 authors at 2 institutions in 2 countries.

Camille FritzellEpidemiology Unit, Institut Pasteur de la Guyane, Cayenne, French Guiana.ORCID 0000-0002-4324-1109
Dominique RoussetNational Reference Laboratory for Arboviruses, Institut Pasteur de la Guyane, Cayenne, French Guiana.
Antoine AddeEpidemiology Unit, Institut Pasteur de la Guyane, Cayenne, French Guiana.
Mirdad KazanjiEpidemiology Unit, Institut Pasteur de la Guyane, Cayenne, French Guiana.
Maria D Van KerkhoveCenter for Global Health, Institut Pasteur de Paris, Paris, France.
Claude FlamandEpidemiology Unit, Institut Pasteur de la Guyane, Cayenne, French Guiana.
Institut Pasteur de la Guyane · GFInstitut Pasteur · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArboviral infections are a public health concern and an escalating problem worldwide. Estimating the burden of these diseases represents a major challenge that is complicated by the large number of unapparent infections, especially those of dengue fever. Serological surveys are thus required to identify the distribution of these diseases and measure their impact. Therefore, we undertook a scoping review of the literature to describe and summarize epidemiological practices, findings and insights related to seroprevalence studies of dengue, chikungunya and Zika virus, which have rapidly expanded across the globe in recent years. METHODOLOGY/PRINCIPAL

findingsRelevant studies were retrieved through a literature search of MEDLINE, WHOLIS, Lilacs, SciELO and Scopus (2000 to 2018). In total, 1389 publications were identified. Studies addressing the seroprevalence of dengue, chikungunya and/or Zika written in English or French and meeting the inclusion and exclusion criteria were included. In total, 147 studies were included, from which 185 data points were retrieved, as some studies used several different samples. Most of the studies were exclusively conducted on dengue (66.5%), but 16% were exclusively conducted on chikungunya, and 7 were exclusively conducted on Zika; the remainder were conducted on multiple arboviruses. A wide range of designs were applied, but most studies were conducted in the general population (39%) and in households (41%). Although several assays were used, enzyme-linked immunosorbent assays (ELISAs) were the predominant test used (77%). The temporal distribution of chikungunya studies followed the virus during its rapid expansion since 2004. The results revealed heterogeneity of arboviruses seroprevalence between continents and within a given country for dengue, chikungunya and Zika viruses, ranging from 0 to 100%, 76% and 73% respectively. CONCLUSIONS/SIGNIFICANCE: Serological surveys provide the most direct measurement for defining the immunity landscape for infectious diseases, but the methodology remains difficult to implement. Overall, dengue, chikungunya and Zika serosurveys followed the expansion of these arboviruses, but there remain gaps in their geographic distribution. This review addresses the challenges for researchers regarding study design biases. Moreover, the development of reliable, rapid and affordable diagnosis tools represents a significant issue concerning the ability of seroprevalence surveys to differentiate infections when multiple viruses co-circulate.

Indexed as

AnimalsAntibodies, ViralChikungunya FeverChikungunya virusDengueDengue VirusHumansSeroepidemiologic StudiesZika VirusZika Virus InfectionAntibodies, Viral

Identifiers

PMID30011271
PMCPMC6062120
OpenAlexW2884353330

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.