Zika Virus Emergence and Expansion: Lessons Learned from Dengue and Chikungunya May Not Provide All the Answers

Christofferson, Rebecca C.

doi:10.4269/ajtmh.15-0866

Cited by 63 publications

(54 citation statements)

References 31 publications

(43 reference statements)

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“…Thus vector transmission may have a shorter infectious period than sexual transmission. Recovery after infection seems to confer long-term immunity for individuals [22]. There currently exist no cure, no treatment, and no vaccine for ZIKV.…”

Section: Methodsmentioning

confidence: 99%

Estimation of Zika virus prevalence by appearance of microcephaly

Saad-Roy

Driessche

2016

BMC Infect Dis

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BackgroundThere currently is a severe Zika Virus (ZIKV) epidemic in Brazil and other South American countries. Due to international travel, this poses severe public health risk of ZIKV importation to other countries. We estimate the prevalence of ZIKV in an import region by the time a microcephaly case is detected, since microcephaly is presently the most significant indication of ZIKV presence.MethodsWe establish a mathematical model to describe ZIKV spread from a source region to an import region. This model incorporates both vector transmission (between humans and mosquitoes) and sexual transmission (from males to females). We take account of population structure through a contact network for sexually active individuals. Parameter values of our model are either taken from the literature or estimated from travel data.ResultsThis model gives us the probability distribution of time until detection of the first microcephaly case. Based on current field observations, our results also indicate that the percentage of infected pregnant women that results in fetal abnormalities is more likely to be on the smaller end of the 1%–30% spectrum that is currently hypothesized. Our model predicts that for import regions with at least 250,000 people, on average 1,000–12,000 will have been infected by the time of the first detection of microcephaly, and on average 200–1,500 will be infectious at this time. Larger population sizes do not significantly change our predictions.ConclusionsBy the first detection of a microcephaly case, a sizable fraction of the population will have been infected by ZIKV. It is thus clear that adequate surveillance, isolation, and quarantine are needed in susceptible import regions to stop the dissemination of a Zika epidemic.Electronic supplementary materialThe online version of this article (doi:10.1186/s12879-016-2076-z) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

Estimation of Zika virus prevalence by appearance of microcephaly

Saad-Roy

Driessche

2016

BMC Infect Dis

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“…This came as a surprise, as since its first isolation in 1947 in the Zika forest in Uganda [5], the virus was associated with benign disease and had remained mostly unnoticed. Isolated outbreaks have been reported before in Africa and Asia/Oceania but all of them involved small populations [6]. In Brazil Zika virus (ZIKV)…”

Section: Introductionmentioning

confidence: 99%

Zika in Rio de Janeiro: Assessment of basic reproduction number and comparison with dengue outbreaks

Bastos

Villela

Carvalho

et al. 2016

Preprint

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Zika virus infection was declared a public health emergency of international concern in February 2016 in response to the outbreak in Brazil and its suspected link with congenital anomalies. In this study we use notification data and disease natural history parameters to estimate the basic reproduction number (R0) of Zika in Rio de Janeiro, Brazil. We also obtain estimates of R0 of dengue from time series of dengue cases in the outbreaks registered in 2002 and 2012 in the city, when DENV-3 and DENV-4 serotypes respectively, had just emerged. Our estimates of the basic reproduction number for Zika in Rio de Janeiro based on surveillance notifications (R0 = 2.33, 95% CI: 1.97 -2.97) were higher than those obtained for dengue in the city (year 2002: R0 = 1.70 [1.50 -2.02]; year 2012: R0 = 1.25 [1.18 -1.36]). Given the role of Aedes aegypti as vector of both the Zika and dengue viruses, we also derive R0 of Zika as a function of both dengue reproduction number and entomological and epidemiological parameters for dengue and Zika. Using the dengue outbreaks from previous years allowed us to estimate the potential R0 of Zika. Our estimates were closely in agreement with our first Zika's R0 estimation from notification data. Hence, these results validate deriving the potential risk of Zika transmission in areas with recurring dengue outbreaks. Whether transmission routes other than vector-based can sustain a Zika epidemic still deserves attention, but our results suggest that the Zika outbreak in Rio de Janeiro emerged due to population susceptibility and ubiquitous presence of Ae. aegypti.

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“…For instance, Krystosik et al ( 22 ) estimated the combined risk for dengue, Zika, and chikungunya but did not provide disease-specific risk estimates; Costa et al ( 35 ) found associations in the spatial distribution of dengue, Zika, and chikungunya but did not use the information on the diseases’ association to improve the accuracy of the risk estimates. The special characteristics of the joint modeling of cocirculating arboviruses provide an epidemiologic tool for transmission control and disease mitigation ( 36 ). …”

Section: Discussionmentioning

confidence: 99%

Joint Estimation of Relative Risk for Dengue and Zika Infections, Colombia, 2015–2016

Martínez-Bello¹,

López‐Quílez²,

Prieto³

2019

Emerg. Infect. Dis.

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We jointly estimated relative risk for dengue and Zika virus disease (Zika) in Colombia, establishing the spatial association between them at the department and city levels for October 2015–December 2016. Cases of dengue and Zika were allocated to the 87 municipalities of 1 department and the 293 census sections of 1 city in Colombia. We fitted 8 hierarchical Bayesian Poisson joint models of relative risk for dengue and Zika, including area- and disease-specific random effects accounting for several spatial patterns of disease risk (clustered or uncorrelated heterogeneity) within and between both diseases. Most of the dengue and Zika high-risk municipalities varied in their risk distribution; those for Zika were in the northern part of the department and dengue in the southern to northeastern parts. At city level, spatially clustered patterns of dengue high-risk census sections indicated Zika high-risk areas. This information can be used to inform public health decision making.

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Zika Virus Emergence and Expansion: Lessons Learned from Dengue and Chikungunya May Not Provide All the Answers

Cited by 63 publications

References 31 publications

Estimation of Zika virus prevalence by appearance of microcephaly

Estimation of Zika virus prevalence by appearance of microcephaly

Zika in Rio de Janeiro: Assessment of basic reproduction number and comparison with dengue outbreaks

Joint Estimation of Relative Risk for Dengue and Zika Infections, Colombia, 2015–2016

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