Assessing real-time Zika risk in the United States

Abstract

Background: Confirmed local transmission of Zika Virus (ZIKV) in Texas and Florida have heightened the need for early and accurate indicators of self-sustaining transmission in high risk areas across the southern United States. Given ZIKV's low reporting rates and the geographic variability in suitable conditions, a cluster of reported cases may reflect diverse scenarios, ranging from independent introductions to a self-sustaining local epidemic.

Methods: We present a quantitative framework for real-time ZIKV risk assessment that captures uncertainty in case reporting, importations, and vector-human transmission dynamics.

Results: We assessed county-level risk throughout Texas, as of summer 2016, and found that importation risk was concentrated in large metropolitan regions, while sustained ZIKV transmission risk is concentrated in the southeastern counties including the Houston metropolitan region and the Texas-Mexico border (where the sole autochthonous cases have occurred in 2016). We found that counties most likely to detect cases are not necessarily the most likely to experience epidemics, and used our framework to identify triggers to signal the start of an epidemic based on a policymakers propensity for risk.

Conclusions: This framework can inform the strategic timing and spatial allocation of public health resources to combat ZIKV throughout the US, and highlights the need to develop methods to obtain reliable estimates of key epidemiological parameters.

Keywords: Autochthonous transmission risk; Importation risk; ZIKV; Zika.

Fig. 1

ZIKV emergence scenarios. A ZIKV infection could spark (a) a self-limiting outbreak or (b) a growing epidemic. Cases are partitioned into symptomatic (grey) and asymptomatic (black). Arrows indicate new ZIKV importations by infected travelers and vertical dashed lines indicate case reporting events. On the 75th day, these divergent scenarios are almost indistinguishable to public health surveillance, as exactly three cases have been detected in both. By the 100th day, the outbreak (a) has died out with 21 total infections while the epidemic (b) continues to grow with already 67 total infections. Each scenario is a single stochastic realization of the model with R ₀ = 1.1, reporting rate of 10%, and introduction rate of 0.1 case/day

Fig. 2

ZIKV importation and transmission risk estimates across Texas for August 2016. a Color indicates the probability that the next ZIKV import will occur in a given county for each of the 254 Texas counties. Probability is colored on a log scale. The 10 most populous cities in Texas are labeled. Houston’s Harris County has 2.7 times greater chance than Austin’s Travis County of receiving the next imported case. b Estimated county-level transmission risk for ZIKV (See Additional file 1: Figure S7 for seasonal differences). Harris county and Dallas County rank among the top 5 and top 10 for both importation and transmission risk respectively; counties in McAllen and Houston metropolitan area rank among the top 20. Bolded county border indicates counties with recorded local ZIKV transmission

Fig. 3

Real-time risk-assessment for ZIKV transmission. All figures are based on transmission and importation risks estimated for Cameron County, Texas. a Two thousand simulated outbreaks. b Total number of (current) autochthonous cases as a function of the cumulative reported autochthonous cases, under a relatively high (dashed) or low (solid) reporting rate. Ribbons indicate 50% quantiles. c The increasing probability of imminent epidemic expansion as reported autochthonous cases accumulate for a low (solid) and high (dashed) reporting rate. Suppose a policy-maker plans to trigger a public health response as soon as a second case is reported (vertical line). Under a 10% reporting rate, this trigger would correspond to a 49% probability of an ensuing epidemic. Under a 20% reporting rate, the probability would be 25%

Fig. 4

Texas county ZIKV risk assessment. a Probability of an outbreak with at least two reported autochthonous ZIKV cases. b The probability of epidemic expansion at the moment the second autochthonous ZIKV case is reported in a county. White counties never reach two reported cases across all 10,000 simulated outbreaks; light gray counties reach two cases, but never experience epidemics. c Recommended county-level surveillance triggers (number of reported autochthonous cases) indicating that the probability of epidemic expansion has exceeded 50%. White counties indicate that fewer than 1% of the 10,000 simulated outbreaks reached two reported cases. All three maps assume a 20% reporting rate and a baseline importation scenario for August 2016 (81 cases statewide per 90 days) projected from historical arbovirus data.