Evidence map›Paper›PMID 30285863›Full record

ArticleBMC medicine2018

Projecting the end of the Zika virus epidemic in Latin America: a modelling analysis.

Kathleen M O'Reilly, Rachel Lowe, W John Edmunds, Philippe Mayaud, Adam Kucharski, Rosalind M Eggo, Sebastian Funk, Deepit Bhatia, Kamran Khan, Moritz U G Kraemer and 8 more

Abstract read
In one paragraph

Article in BMC medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 4 pooled it
–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

43 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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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

18 authors.

Kathleen M O'ReillyDepartment of Disease Control, London School of Hygiene & Tropical Medicine, London, UK. kathleen.oreilly@lshtm.ac.uk.ORCID 0000-0002-4892-8022
Rachel LoweCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0003-3939-7343
W John EdmundsCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Philippe MayaudDepartment of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0001-5730-947X
Adam KucharskiCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Rosalind M EggoCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0002-0362-6717
Sebastian FunkCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0002-2842-3406
Deepit BhatiaDivision of Infectious Diseases, University of Toronto, Toronto, ON, Canada.
Kamran KhanDivision of Infectious Diseases, University of Toronto, Toronto, ON, Canada.
Moritz U G KraemerHarvard Medical School, Harvard University, Boston, MA, USA.ORCID 0000-0001-8838-7147
Annelies Wilder-SmithDepartment of Disease Control, London School of Hygiene & Tropical Medicine, London, UK.
Laura C RodriguesDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Patricia BrasilInstituto Nacional de Infectologia Evandro Chagas/Fiocruz, Rio de Janeiro, Brazil.
Eduardo MassadSchool of Applied Mathematics, Fundacao Getulio Vargas, Rio de Janeiro, Brazil.
Thomas JaenischDepartment for Infectious Diseases and Parasitology, Department for Infectious Diseases, University of Heidelberg, Heidelberg, Germany.
Simon CauchemezMathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Paris, France.
Oliver J BradyCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0002-3235-2129
Laith YakobDepartment of Disease Control, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0001-8639-4511

Funding

RESEARCH TRAINING IN PEDIATRIC EMERGENCY MEDICINET32HD040128 · NICHD · CHILDREN'S HOSPITAL BOSTON · PI Kenneth D. Mandl · 2001 to 2026
$5.0M
A Platform for Modeling the Global Impact of Climate Change on Infectious DiseaseR01LM010812 · NLM · BOSTON CHILDREN'S HOSPITAL · PI BROWNSTEIN, JOHN S. · 2010 to 2015
$2.5M
An Approach for Estimating Foodborne Illnesses and Assessing Risk FactorsR01LM011965 · NLM · BOSTON CHILDREN'S HOSPITAL · PI BROWNSTEIN, JOHN S., NSOESIE, ELAINE O. · 2015 to 2018
$1.4M
Horizon 2020 734584Medical Research Council MC_PC_15097NICHD NIH HHS T32 HD040128NLM NIH HHS R01 LM010812NLM NIH HHS R01 LM011965Wellcome TrustWellcome Trust 206250/Z/17/ZWellcome Trust 206471/Z/17/Z
6 · The paper itself

Abstract

backgroundZika virus (ZIKV) emerged in Latin America and the Caribbean (LAC) region in 2013, with serious implications for population health in the region. In 2016, the World Health Organization declared the ZIKV outbreak a Public Health Emergency of International Concern following a cluster of associated neurological disorders and neonatal malformations. In 2017, Zika cases declined, but future incidence in LAC remains uncertain due to gaps in our understanding, considerable variation in surveillance and the lack of a comprehensive collation of data from affected countries.

methodsOur analysis combines information on confirmed and suspected Zika cases across LAC countries and a spatio-temporal dynamic transmission model for ZIKV infection to determine key transmission parameters and projected incidence in 90 major cities within 35 countries. Seasonality was determined by spatio-temporal estimates of Aedes aegypti vectorial capacity. We used country and state-level data from 2015 to mid-2017 to infer key model parameters, country-specific disease reporting rates, and the 2018 projected incidence. A 10-fold cross-validation approach was used to validate parameter estimates to out-of-sample epidemic trajectories.

resultsThere was limited transmission in 2015, but in 2016 and 2017 there was sufficient opportunity for wide-spread ZIKV transmission in most cities, resulting in the depletion of susceptible individuals. We predict that the highest number of cases in 2018 would present within some Brazilian States (Sao Paulo and Rio de Janeiro), Colombia and French Guiana, but the estimated number of cases were no more than a few hundred. Model estimates of the timing of the peak in incidence were correlated (p < 0.05) with the reported peak in incidence. The reporting rate varied across countries, with lower reporting rates for those with only confirmed cases compared to those who reported both confirmed and suspected cases.

conclusionsThe findings suggest that the ZIKV epidemic is by and large over within LAC, with incidence projected to be low in most cities in 2018. Local low levels of transmission are probable, but the estimated rate of infection suggests that most cities have a population with high levels of herd immunity.

Indexed as

EpidemicsModels, TheoreticalAnimalsHumansIncidenceLatin AmericaWorld Health OrganizationZika VirusZika Virus InfectionConnectivityEpidemicLatin America and the CaribbeanMathematical modellingZika virus

Identifiers

PMID30285863
PMCPMC6169075

What OpenQuestion holds

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Registered trials

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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.