Abstract
Background The southern United States (US) may be vulnerable to outbreaks of Zika Virus (ZIKV), given the broad distribution of ZIKV vector species and periodic ZIKV introductions by travelers returning from affected regions. If autochthonous (locally-acquired) cases appear within the US, policymakers will seek early and accurate indicators of self-sustaining transmission to inform intervention efforts. However, given ZIKV’s low reporting rates and the geographic variability in both importations and transmission potential, a small cluster of reported cases may reflect diverse scenarios, ranging from multiple self-limiting but independent introductions to a self-sustaining local epidemic.
Methods and Findings We developed a stochastic model that captures variation and uncertainty in ZIKV case reporting, importations, and transmission, and applied it to assess county-level risk throughout the state of Texas. For each of the 254 counties, we estimated the future epidemic risk as a function of reported autochthonous cases and evaluated a national recommendation to trigger interventions immediately following the first two reported cases of locally-transmitted ZIKV. Our analysis suggests that the regions of greatest risk for sustained ZIKV transmission include 21 Texas counties along the Texas-Mexico border, in the Houston Metro Area, and throughout the I-35 Corridor from San Antonio to Waco. Variation in vector habitat suitability drives epidemic risk variation, and can be exacerbated by uncertainty in reporting rate. Upon detection of a second locally transmitted case, the threat of epidemic expansion will depend critically on local vulnerability. For high risk Texas counties, we estimate this likelihood to be 64%, assuming an August 2016 risk projection and a 20% reporting rate.
Conclusions With reliable estimates of key epidemiological parameters, including reporting rates and vector abundance, this framework can help optimize the timing and spatial allocation of public health resources to fight ZIKV in the US.
