  Zika virus (ZIKV), a disease spread primarily through the Aedes aegypti
mosquito, was identified in Brazil in 2015 and was declared a global health
emergency by the World Health Organization (WHO). Epidemiologists often use
common state-level attributes such as population density and temperature to
determine the spread of disease. By applying techniques from topological data
analysis, we believe that epidemiologists will be able to better predict how
ZIKV will spread. We use the Vietoris-Rips filtration on high-density mosquito
locations in Brazil to create simplicial complexes, from which we extract
homology group generators. Previously epidemiologists have not relied on
topological data analysis to model disease spread. Evaluating our model on ZIKV
case data in the states of Brazil demonstrates the value of these techniques
for the improved assessment of vector-borne diseases.
