Transmission Dynamics of Zika Virus in Island Populations: A Modelling Analysis of the 2013–14 French Polynesia Outbreak

Kucharski, Adam J.; Funk, Sebastian; Eggo, Rosalind M; Mallet, Henri‐Pierre; Edmunds, W. John; Nilles, Eric J.

doi:10.1371/journal.pntd.0004726

Cited by 240 publications

(216 citation statements)

References 38 publications

Supporting

Mentioning

190

Contrasting

Order By: Relevance

“…Susceptible (S) men and women are at risk of becoming asymptomatically exposed (E) to Zika by either vector-borne or sexual routes, from which they transition to become infectious (I). The duration of infectiousness to mosquitoes ranges from 4–7 days (16). After this phase, women recover (R), but men remain infectious to their female partners (J) for an additional 15–180 days (17).…”

Section: Methodsmentioning

confidence: 99%

Evaluating Vaccination Strategies for Zika Virus in the Americas

Durham

Fitzpatrick

Ndeffo-Mbah

et al. 2018

Annals of Internal Medicine

View full text Add to dashboard Cite

Background Mosquito-borne and sexually-transmitted Zika virus infection has become widespread across Central and South America as well as in the Caribbean. Over 30 Zika vaccine candidates are under active development. Objective To quantify the impact of Zika vaccine prioritization of females aged 9–49, followed by males aged 9–49, on the incidence of prenatal Zika infections. Design We developed a compartmental model of Zika transmission between mosquitoes and humans calibrated to empirical estimates of country-specific mosquito density. Mosquitoes were stratified into susceptible, exposed, or infected classes; humans were stratified into susceptible, exposed, infected, recovered, or vaccinated classes. We further incorporated age-specific rates of fertility, Zika sexual transmission, and country-specific demographics. Setting 34 countries or territories in the Americas with documented Zika outbreaks. Target population Males and females aged 9–49. Interventions Age- and gender-targeted immunization using a Zika vaccine with efficacy ranging from 60–90%. Measurements Annual prenatal Zika infections Results For a base-case vaccine efficacy of 75% and vaccination coverage of 90%, immunizing females aged 9–49, the WHO target population, would reduce the incidence of prenatal infections by at least 94%, depending on the country-specific Zika attack rate. In regions where an outbreak is not expected for at least ten years, vaccination of females aged 15–29 is more efficient than vaccinating women over 30 years. Limitations Population-level modeling may not capture all local and neighborhood-level heterogeneity in mosquito abundance or Zika incidence. Conclusions A Zika vaccine of moderate to high efficacy has the potential of virtually eliminating prenatal infections through a combination of direct protection and transmission reduction. Efficiency of age-specific Zika vaccination targeting depends on timing of future outbreaks. Funding National Institutes of Health

show abstract

Section: Methodsmentioning

confidence: 99%

Evaluating Vaccination Strategies for Zika Virus in the Americas

Durham

Fitzpatrick

Ndeffo-Mbah

et al. 2018

Annals of Internal Medicine

View full text Add to dashboard Cite

show abstract

“…Modeling has increasingly been viewed as a useful tool to quantify these complex transmission systems by integrating various data sources and specifying nonlinear mechanistic relationships and feedbacks. Numerous recent efforts at combating mosquito-borne diseases have directly incorporated the use of mathematical models, such as in planning for Zika and chikungunya response (Moulay et al, 2011, 2012a; Christofferson et al, 2016; Alex Perkins et al, 2016; Kucharski et al, 2016; Ferguson et al, 2016a), and evaluation of potential vaccine candidates (Chao et al, 2012; WHO-VMI, 2012; Aguiar et al, 2016; Ferguson et al, 2016b). …”

Section: Introductionmentioning

confidence: 99%

Practical unidentifiability of a simple vector-borne disease model: Implications for parameter estimation and intervention assessment

Kao

Eisenberg

2018

Epidemics

View full text Add to dashboard Cite

Mathematical modeling has an extensive history in vector-borne disease epidemiology, and is increasingly used for prediction, intervention design, and understanding mechanisms. Many studies rely on parameter estimation to link models and data, and to tailor predictions and counterfactuals to specific settings. However, few studies have formally evaluated whether vector-borne disease models can properly estimate the parameters of interest given the constraints of a particular dataset. Identifiability analysis allows us to examine whether model parameters can be estimated uniquely—a lack of consideration of such issues can result in misleading or incorrect parameter estimates and model predictions. Here, we evaluate both structural (theoretical) and practical identifiability of a commonly used compartmental model of mosquito-borne disease, using the 2010 dengue epidemic in Taiwan as a case study. We show that while the model is structurally identifiable, it is practically unidentifiable under a range of human and mosquito time series measurement scenarios. In particular, the transmission parameters form a practically identifiable combination and thus cannot be estimated separately, potentially leading to incorrect predictions of the effects of interventions. However, in spite of the unidentifiability of the individual parameters, the basic reproduction number was successfully estimated across the unidentifiable parameter ranges. These identifiability issues can be resolved by directly measuring several additional human and mosquito life-cycle parameters both experimentally and in the field. While we only consider the simplest case for the model, we show that a commonly used model of vector-borne disease is unidentifiable from human and mosquito incidence data, making it diﬃcult or impossible to estimate parameters or assess intervention strategies. This work illustrates the importance of examining identifiability when linking models with data to make predictions and inferences, and particularly highlights the importance of combining laboratory, field, and case data if we are to successfully estimate epidemiological and ecological parameters using models.

show abstract

“…A Zika-infected person infects on average about two to five additional people when mosquitoes are the vector for transmission [8]. This quantity is the basic reproduction number ( R 0 ), and it can be estimated from the observed incidence of reported cases if we have information on the generation time, which is the average time from infection of one individual to the next individual.…”

mentioning

confidence: 99%