2516. Predictors of Zika Virus Disease Severity within Veterans Affairs (VA)
Session: Poster Abstract Session: Virology Potpourri
Saturday, October 6, 2018
Room: S Poster Hall

Background: Historically, Zika virus infection presented as a mild disease. However, more severe disease was reported during recent outbreaks in French Polynesia and more recently within southern regions of North America as well as Central and South America. It is still unclear what predicts more severe manifestations. Here we report on potential predictors of severe Zika virus infection within VA, selected for their role in immunological status.

Methods: We extracted the first positive Zika visit for a patient between February 9, 2016 and April 1, 2017. Each visit was classified by acuity (no ED visit, ED only, observation, ward, ICU [in this order of severity]). Diagnoses were extracted by ICD-9-CM and ICD-10-CM codes. Predictors included history of hepatitis C virus (HCV; a flavivirus) by laboratories, dengue diagnosis, immunocompromising condition diagnosis, gender, age, and history of exposure to dengue endemic region (either through birth, travel, or residency). These predictors were used in a generalized ordered logit model, relaxing the proportional odds assumption, to estimate odds ratios for a higher level of visit acuity over the current or lower levels of acuity. Robust covariance estimates were used.

Results: There were 748 unique patient visits meeting criteria. Distribution of predictors among the patient sample are shown in Table 1. As expected, most were males with a majority only visiting the ED. Wards and ICU were combined due to the small number of ICU visits. Table 2 shows results of model for predictors of higher acuity visits. Age was generally associated with higher levels of acuity. Odds ratios could not be computed for HCV and immunocompromised predictors.

Conclusion: There may be an increased risk of Zika disease severity based on age. We could not rule out associations with other predictors due to the size of our study. Further larger studies are needed to investigate these and other predictors.


Julia Lewis, DO1,2, Kelly Peterson, MS1,2 and Makoto Jones, MD, MS1,2, (1)VA Salt Lake City Health Care System, Salt Lake City, UT, (2)Epidemiology, University of Utah, Salt Lake City, UT


J. Lewis, None

K. Peterson, None

M. Jones, None

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