The arrival of Zika Virus (ZIKV) to the Americas was swift and
unprecedented in scope. As it made its way across South America, into
Mexico, and the United States, two surprising aspects of ZIKV infection
became clear: ZIKV infection leads to devastating birth defects and it
is readily transmitted sexually. The first, discovery of the teratogenic
effects of ZIKV infection, was surprising because other flaviviruses
such as Dengue virus and Yellow fever virus, which are spread by the
same vectors and have otherwise similar symptomatology, do not seem to
affect the developing fetus. The second observation of sexual
transmission was surprising for similar reasons, but it also forced
mathematical epidemiologists to adapt their ample toolbox for ZIKV.
While the importance of these sexual transmissions is undeniable
considering the birth defects associated with the virus, their
statistical importance are much harder to estimate given that we have to
parse out sexual transmissions from vectored transmissions in routinely
collected incidence data. Here we demonstrate the consequences of
sexual transmission of Zika and give some policy recommendations on
screening and surveillance.
Ben Althouse has brought his enjoyment of the dynamic, intellectually challenging and inherently collaborative nature of the scientific process to the IDM Epidemiology team as a Research Scientist, where he will explore pneumococcal pneumonia vaccines, the dynamics of enteric diseases, and the role of complex human contact structures on disease transmission. He was an Omidyar Fellow at the Santa Fe Institute, holds a PhD in Epidemiology and a Master of Science in Biostatistics from the Johns Hopkins Bloomberg School of Public Health where he was awarded an NSF Graduate Research Fellowship, and holds Bachelor of Science degrees in Mathematics and Biochemistry from the University of Washington. His previous work has included mathematical modeling of sylvatic dengue virus transmission in nonhuman primates in Senegal, examining the role of antimicrobial use on the evolution of drug resistance, using Twitter as a model system of co-infection dynamics, and using novel data sources (such as Google searches, Twitter, and Wikipedia article views) for population-level surveillance of infectious and chronic diseases. Ben is an Affiliate Faculty member in the Department of Biology at New Mexico State University, Las Cruces, and an Affiliate Assistant Professor at the Information School at UW. Please find details in his profile at http://www.benalthouse.com/academics/AlthouseCV.pdf
