Evidence map›Paper›PMID 27296630›Full record

ArticleParasites & vectors2016

Analysis of age-dependent trends in Ov16 IgG4 seroprevalence to onchocerciasis.

Allison Golden, Dunia Faulx, Michael Kalnoky, Eric Stevens, Lindsay Yokobe, Roger Peck, Potochoziou Karabou, Méba Banla, Ramakrishna Rao, Kangi Adade and 5 more

Open access · goldAbstract read
In one paragraph

Article in Parasites & vectors, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
6.0field-weighted citation impact, top 3% 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

43 citing papers in PubMed, 55 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Identification and Characterization ofPathogens (Basel, Switzerland) · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

15 authors at 2 institutions in 1 country.

Allison GoldenDiagnostics Global Program, PATH, Seattle, WA, USA.
Dunia FaulxDiagnostics Global Program, PATH, Seattle, WA, USA.
Michael KalnokyDiagnostics Global Program, PATH, Seattle, WA, USA.
Eric StevensDiagnostics Global Program, PATH, Seattle, WA, USA.
Lindsay YokobeDiagnostics Global Program, PATH, Seattle, WA, USA.
Roger PeckDiagnostics Global Program, PATH, Seattle, WA, USA.
Potochoziou KarabouNational Onchocerciasis Control Programme, Kara, Togo.
Méba BanlaOnchocerciasis Reference Laboratory, National Institute of Hygiene, Sokodé, Togo.
Ramakrishna RaoWashington University, St. Louis, MO, USA.
Kangi AdadeNational Onchocerciasis Control Programme, Kara, Togo.
Richard G GantinOnchocerciasis Reference Laboratory, National Institute of Hygiene, Sokodé, Togo.
Kossi KomlanOnchocerciasis Reference Laboratory, National Institute of Hygiene, Sokodé, Togo.
Peter T SoboslayOnchocerciasis Reference Laboratory, National Institute of Hygiene, Sokodé, Togo.
Tala de Los SantosDiagnostics Global Program, PATH, Seattle, WA, USA.
Gonzalo J DomingoDiagnostics Global Program, PATH, Seattle, WA, USA. gdomingo@path.org.
Program for Appropriate Technology in Health · USWashington University in St. Louis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiagnostics provide a means to measure progress toward disease elimination. Many countries in Africa are approaching elimination of onchocerciasis after successful implementation of mass drug administration programs as well as vector control. An understanding of how markers for infection such as skin snip microfilaria and Onchocerca volvulus-specific seroconversion perform in near-elimination settings informs how to best use these markers.

methodsAll-age participants from 35 villages in Togo were surveyed in 2013 and 2014 for skin snip Onchocerca volvulus microfilaria and IgG4 antibody response by enzyme-linked immunosorbent assay (ELISA) to the Onchocerca volvulus-specific antigen Ov16. A Gaussian mixture model applying the expectation-maximization (EM) algorithm was used to determine seropositivity from Ov16 ELISA data. For a subset of participants (n = 434), polymerase chain reaction (PCR) was performed on the skin snips taken during surveillance.

resultsWithin the 2,005 participants for which there was Ov16 ELISA data, O. volvulus microfilaremia prevalence and Ov16 seroprevalence were, 2.5 and 19.7 %, respectively, in the total population, and 1.6 and 3.6 % in children under 11. In the subset of 434 specimens for which ELISA, PCR, and microscopy data were generated, it was found that in children under 11 years of age, the anti-Ov16 IgG4 antibody response demonstrate a sensitivity and specificity of 80 and 97 %, respectively, against active infections as determined by combined PCR and microscopy on skin snips. Further analysis was performed in 34 of the 35 villages surveyed. These villages were stratified by all-age seroprevalence into three clusters: < 15 %; 15-20 %; and > 20 %. Age-dependence of seroprevalence for each cluster was best reflected by a two-phase force-of-infection (FOI) catalytic model. In all clusters, the lower of the two phases of FOI was associated with a younger age group, as reflected by the seroconversion rates for each phase. The age at which transition from lower to higher seroconversion, between the two phases of FOI, was found to be highest (older) for the cluster of villages with < 15 % seroprevalence and lowest (younger) for the cluster with the highest all-age seroprevalence.

conclusionsThe anti-Ov16 IgG4 antibody response is an accurate marker for active infection in children under 11 years of age in this population. Applying Ov16 surveillance to a broader age range provides additional valuable information for understanding progression toward elimination and can inform where targeted augmented interventions may be needed. Clustering of villages by all-age sero-surveillance allowed application of a biphasic FOI model to differentiate seroconversion rates for different age groups within the village cluster categories.

Indexed as

AgingSeroepidemiologic StudiesAdolescentAdultCarrier ProteinsChildChild, PreschoolFemaleHelminth ProteinsHumansImmunoglobulin GMaleMiddle AgedOnchocerciasisTogoYoung AdultCarrier ProteinsHelminth ProteinsImmunoglobulin GOvd protein, Onchocerca volvulusDiagnosticsIgG4Neglected tropical diseasesOnchocerciasisSeroconversion

Identifiers

PMID27296630
PMCPMC4907250
OpenAlexW2419939377

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.