Modeling Zika Virus Transmission Dynamics: Parameter Estimates, Disease Characteristics, and Prevention

Munsur Rahman,Kidist Bekele-Maxwell,Leanna L Cates,Naveen K Vaidya,H T Banks

doi:10.1038/s41598-019-46218-4

Munsur Rahman, Kidist Bekele-Maxwell + Show 3 more

Open Access

https://doi.org/10.1038/s41598-019-46218-4

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Abstract

Because of limited data, much remains uncertain about parameters related to transmission dynamics of Zika virus (ZIKV). Estimating a large number of parameters from the limited information in data may not provide useful knowledge about the ZIKV. Here, we developed a method that utilizes a mathematical model of ZIKV dynamics and the complex-step derivative approximation technique to identify parameters that can be estimated from the available data. Applying our method to epidemic data from the ZIKV outbreaks in French Polynesia and Yap Island, we identified the parameters that can be estimated from these island data. Our results suggest that the parameters that can be estimated from a given data set, as well as the estimated values of those parameters, vary from Island to Island. Our method allowed us to estimate some ZIKV-related parameters with reasonable confidence intervals. We also computed the basic reproduction number to be from 2.03 to 3.20 across islands. Furthermore, using our model, we evaluated potential prevention strategies and found that peak prevalence can be reduced to nearly 10% by reducing mosquito-to-human contact by at least 60% or increasing mosquito death by at least a factor of three of the base case. With these preventions, the final outbreak-size is predicted to be negligible, thereby successfully controlling ZIKV epidemics.

Highlights

For the data considered here, the standard errors along with sensitivity results suggest that the data sets do not contain sufficient information to estimate more than three parameters in islands of French Polynesia and more than two parameters in Yap island with a reasonable degree of certainty attached to the estimates (Table 2)
We developed a sensitivity analysis based method, which utilizes the transmission dynamics model of Zika virus (ZIKV) infection and the recently expanded complex-step approximation technique[22,33], to identify parameters that can be estimated from the available limited data set
Implementing our technique to seven island data, we identified that these data sets do not contain sufficient information to estimate more than three parameters in islands of French Polynesia and more than two parameters in Yap island with a reasonable degree of certainty attached to the estimates

Summary

Introduction

There is a lack of detailed evaluation on potential ZIKV control strategies Such studies based on prior analysis of parameter estimation and validation could inform future data collection strategy, including those involving prevention measures, such as outbreak planning or assessment of potential countermeasures, thereby helping to decrease the potentiality of this infectious disease to become a pandemic. We formulated mathematical models of transmission dynamics of ZIKV infection and employed complex-step derivative based sensitivity analysis to identify the parameters that can be estimated from a given limited data. Our techniques allowed us to estimate some ZIKV-related parameters with reasonable confidence intervals Using these estimated parameters, we computed the basic reproduction number and performed model analysis to study the disease dynamics as well as the effect of prevention programs on disease outcomes

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