Evidence map›Paper›PMID 32986701›Full record

ArticlePLoS neglected tropical diseases2020

Leveraging multiple data types to estimate the size of the Zika epidemic in the Americas.

Sean M Moore, Rachel J Oidtman, K James Soda, Amir S Siraj, Robert C Reiner, Christopher M Barker, T Alex Perkins

Abstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

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  16. The Remote Emerging Disease Intelligence-NETwork.Frontiers in microbiology · 2022
    Article
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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

7 authors.

Sean M MooreDepartment of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, Indiana, United States of America.ORCID 0000-0001-9062-6100
Rachel J OidtmanDepartment of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, Indiana, United States of America.
K James SodaDepartment of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, Indiana, United States of America.
Amir S SirajDepartment of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, Indiana, United States of America.ORCID 0000-0002-9275-0380
Robert C ReinerInstitute for Health Metrics and Evaluation, Seattle, Washington, United States of America.
Christopher M BarkerDepartment of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, Davis, California, United States of America.
T Alex PerkinsDepartment of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, Indiana, United States of America.

Funding

Methods for Reducing Spatial Uncertainty and Bias in Disease SurveillanceR01AI102939 · NIAID · JOHNS HOPKINS UNIVERSITY · PI LESSLER, JUSTIN · 2013 to 2017
$4.6M
NIAID NIH HHS R01 AI102939
6 · The paper itself

Abstract

Several hundred thousand Zika cases have been reported across the Americas since 2015. Incidence of infection was likely much higher, however, due to a high frequency of asymptomatic infection and other challenges that surveillance systems faced. Using a hierarchical Bayesian model with empirically-informed priors, we leveraged multiple types of Zika case data from 15 countries to estimate subnational reporting probabilities and infection attack rates (IARs). Zika IAR estimates ranged from 0.084 (95% CrI: 0.067-0.096) in Peru to 0.361 (95% CrI: 0.214-0.514) in Ecuador, with significant subnational variability in every country. Totaling infection estimates across these and 33 other countries and territories, our results suggest that 132.3 million (95% CrI: 111.3-170.2 million) people in the Americas had been infected by the end of 2018. These estimates represent the most extensive attempt to determine the size of the Zika epidemic in the Americas, offering a baseline for assessing the risk of future Zika epidemics in this region.

Indexed as

AmericasAsymptomatic InfectionsBayes TheoremEcuadorEpidemicsHumansIncidencePeruZika VirusZika Virus Infection

Identifiers

PMID32986701
PMCPMC7544039

What OpenQuestion holds

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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.