Travel Surveillance and Genomics Uncover a Hidden Zika Outbreak during the Waning Epidemic

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Summary

The Zika epidemic in the Americas has challenged surveillance and control. As the epidemic appears to be waning, it is unclear whether transmission is still ongoing, which is exacerbated by discrepancies in reporting. To uncover locations with lingering outbreaks, we investigated travel-associated Zika cases to identify transmission not captured by reporting. We uncovered an unreported outbreak in Cuba during 2017, a year after peak transmission in neighboring islands. By sequencing Zika virus, we show that the establishment of the virus was delayed by a year and that the ensuing outbreak was sparked by long-lived lineages of Zika virus from other Caribbean islands. Our data suggest that, although mosquito control in Cuba may initially have been effective at mitigating Zika virus transmission, such measures need to be maintained to be effective. Our study highlights how Zika virus may still be “silently” spreading and provides a framework for understanding outbreak dynamics.

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Highlights

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Travel surveillance and genomics uncovered hidden Zika transmission
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An unreported and 1-year delayed Zika outbreak was detected in Cuba
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Mosquito control may delay, not prevent, Zika virus establishment
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A surveillance framework to detect hidden outbreaks was created

Abstract

A combination of travel surveillance and clinical virus genomic sequencing of infected travelers provides a framework for detecting hidden outbreaks, such as an unreported Zika outbreak in Cuba during 2017.

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Most cited references 50

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First report of autochthonous transmission of Zika virus in Brazil

Camila Zanluca, Vanessa de Melo, Ana Mosimann … (2015)

In the early 2015, several cases of patients presenting symptoms of mild fever, rash, conjunctivitis and arthralgia were reported in the northeastern Brazil. Although all patients lived in a dengue endemic area, molecular and serological diagnosis for dengue resulted negative. Chikungunya virus infection was also discarded. Subsequently, Zika virus (ZIKV) was detected by reverse transcription-polymerase chain reaction from the sera of eight patients and the result was confirmed by DNA sequencing. Phylogenetic analysis suggests that the ZIKV identified belongs to the Asian clade. This is the first report of ZIKV infection in Brazil.

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Abstract: found
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Improving Bayesian population dynamics inference: a coalescent-based model for multiple loci.

Mandev S Gill, Philippe Lemey, Nuno Faria … (2013)

Effective population size is fundamental in population genetics and characterizes genetic diversity. To infer past population dynamics from molecular sequence data, coalescent-based models have been developed for Bayesian nonparametric estimation of effective population size over time. Among the most successful is a Gaussian Markov random field (GMRF) model for a single gene locus. Here, we present a generalization of the GMRF model that allows for the analysis of multilocus sequence data. Using simulated data, we demonstrate the improved performance of our method to recover true population trajectories and the time to the most recent common ancestor (TMRCA). We analyze a multilocus alignment of HIV-1 CRF02_AG gene sequences sampled from Cameroon. Our results are consistent with HIV prevalence data and uncover some aspects of the population history that go undetected in Bayesian parametric estimation. Finally, we recover an older and more reconcilable TMRCA for a classic ancient DNA data set.

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Detecting the impact of temperature on transmission of Zika, dengue, and chikungunya using mechanistic models

Erin A. Mordecai, Jeremy M Cohen, Michelle Evans … (2017)

Recent epidemics of Zika, dengue, and chikungunya have heightened the need to understand the seasonal and geographic range of transmission by Aedes aegypti and Ae. albopictus mosquitoes. We use mechanistic transmission models to derive predictions for how the probability and magnitude of transmission for Zika, chikungunya, and dengue change with mean temperature, and we show that these predictions are well matched by human case data. Across all three viruses, models and human case data both show that transmission occurs between 18–34°C with maximal transmission occurring in a range from 26–29°C. Controlling for population size and two socioeconomic factors, temperature-dependent transmission based on our mechanistic model is an important predictor of human transmission occurrence and incidence. Risk maps indicate that tropical and subtropical regions are suitable for extended seasonal or year-round transmission, but transmission in temperate areas is limited to at most three months per year even if vectors are present. Such brief transmission windows limit the likelihood of major epidemics following disease introduction in temperate zones.

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Author and article information

Contributors

Nathan D. Grubaugh

Scott F. Michael

Kristian G. Andersen

Journal

Journal ID (nlm-ta): Cell

Journal ID (iso-abbrev): Cell

Title: Cell

Publisher: Elsevier Inc.

ISSN (Print): 0092-8674

ISSN (Electronic): 1097-4172

Publication date PMC-release: 22 August 2019

Publication date (Print): 22 August 2019

Publication date (Electronic): 22 August 2019

Volume: 178

Issue: 5

Pages: 1057-1071.e11

Affiliations

[1 ]Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA

[2 ]Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA

[3 ]Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON M5B 1T8, Canada

[4 ]Department of Biological Sciences, Florida Gulf Coast University, Fort Myers, FL 33965, USA

[5 ]Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL 33612, USA

[6 ]Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46556, USA

[7 ]Center for Genome Sciences, US Army Medical Research Institute of Infectious Diseases, Fort Detrick, MD 21702, USA

[8 ]Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ 86011, USA

[9 ]Department of Zoology, University of Oxford, Oxford OX1 3PS, UK

[10 ]Boston Children’s Hospital, Boston, MA 02115, USA

[11 ]Harvard Medical School, Boston, MA 02115, USA

[12 ]Bureau of Epidemiology, Division of Disease Control and Health Protection, Florida Department of Health, Tallahassee, FL 32399, USA

[13 ]Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Miami, FL 33125, USA

[14 ]Department of Pathology, University of Miami Miller School of Medicine, Miami, FL 33136, USA

[15 ]MassBiologics, University of Massachusetts Medical School, Boston, MA 02126, USA

[16 ]Department of Global Health, Boston University School of Public Health, Boston, MA 02118, USA

[17 ]Section of Infectious Diseases, Department of Medicine, Boston Medical Center, Boston, MA 02118, USA

[18 ]School of Civil and Environmental Engineering, UNSW Sydney, Sydney, NSW 2052, Australia

[19 ]Department of Civil Engineering, Johns Hopkins University, Baltimore, MD 21287, USA

[20 ]Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium

[21 ]Division of Infectious Diseases, Department of Medicine, University of Toronto, Toronto, ON M5B 1T8, Canada

[22 ]Scripps Research Translational Institute, La Jolla, CA 92037, USA

Author notes

[∗ ]Corresponding author nathan.grubaugh@ 123456yale.edu

[∗∗ ]Corresponding author smichael@ 123456fgcu.edu

[∗∗∗ ]Corresponding author andersen@ 123456scripps.edu

[23]

These authors contributed equally

[24]

Senior author

[25]

Lead Contact

Article

Publisher ID: S0092-8674(19)30783-4

DOI: 10.1016/j.cell.2019.07.018

PMC ID: 6716374

PubMed ID: 31442400

SO-VID: 54534c87-2d2d-447d-9207-0659ae65ef9f

License:

Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

History

Date received : 19 December 2018

Date revision received : 15 April 2019

Date accepted : 12 July 2019

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