Evidence map›Paper›PMID 32348302›Full record

ArticlePLoS neglected tropical diseases2020

New estimates of the Zika virus epidemic attack rate in Northeastern Brazil from 2015 to 2016: A modelling analysis based on Guillain-Barré Syndrome (GBS) surveillance data.

Daihai He, Shi Zhao, Qianying Lin, Salihu S Musa, Lewi Stone

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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 10 papers.

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10citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Daihai HeDepartment of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China.ORCID 0000-0003-3253-654X
Shi ZhaoDepartment of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China.ORCID 0000-0001-8722-6149
Qianying LinDepartment of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China.
Salihu S MusaDepartment of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China.ORCID 0000-0001-6335-2335
Lewi StoneMathematical Science, School of Science, RMIT University, Melbourne, Victoria, Australia.ORCID 0000-0002-6465-579X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBetween January 2015 and August 2016, two epidemic waves of Zika virus (ZIKV) disease swept the Northeastern (NE) region of Brazil. As a result, two waves of Guillain-Barré Syndrome (GBS) were observed concurrently. The mandatory reporting of ZIKV disease began region-wide in February 2016, and it is believed that ZIKV cases were significantly under-reported before that. The changing reporting rate has made it difficult to estimate the ZIKV infection attack rate, and studies in the literature vary widely from 17% to > 50%. The same applies to other key epidemiological parameters. In contrast, the diagnosis and reporting of GBS cases were reasonably reliable given the severity and easy recognition of the disease symptoms. In this paper, we aim to estimate the real number of ZIKV cases (i.e., the infection attack rate) and their dynamics in time, by scaling up from GBS surveillance data in NE Brazil. METHODOLOGY: A mathematical compartmental model is constructed that makes it possible to infer the true epidemic dynamics of ZIKV cases based on surveillance data of excess GBS cases. The model includes the possibility that asymptomatic ZIKV cases are infectious. The model is fitted to the GBS surveillance data and the key epidemiological parameters are inferred by using a plug-and-play likelihood-based estimation. We make use of regional weather data to determine possible climate-driven impacts on the reproductive number [Formula: see text], and to infer the true ZIKV epidemic dynamics. FINDINGS AND

conclusionsThe GBS surveillance data can be used to study ZIKV epidemics and may be appropriate when ZIKV reporting rates are not well understood. The overall infection attack rate (IAR) of ZIKV is estimated to be 24.1% (95% confidence interval: 17.1%-29.3%) of the population. By examining various asymptomatic scenarios, the IAR is likely to be lower than 33% over the two ZIKV waves. The risk rate from symptomatic ZIKV infection to develop GBS was estimated as ρ = 0.0061% (95% CI: 0.0050%-0.0086%) which is significantly less than current estimates. We found a positive association between local temperature and the basic reproduction number, [Formula: see text]. Our analysis revealed that asymptomatic infections affect the estimation of ZIKV epidemics and need to also be carefully considered in related modelling studies. According to the estimated effective reproduction number and population wide susceptibility, we comment that a ZIKV outbreak would be unlikely in NE Brazil in the near future.

Indexed as

EpidemicsEpidemiological MonitoringBasic Reproduction NumberBrazilGuillain-Barre SyndromeHumansIncidenceModels, TheoreticalWeatherZika Virus Infection

Identifiers

PMID32348302
PMCPMC7213748

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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.