Modeling the spread of the Zika virus using topological data analysis

• Published in: PloS one Vol. 13; no. 2; p. e0192120
• Main Authors: Lo, Derek, Park, Briton
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 13-02-2018; Public Library of Science (PLoS)
• Subjects: Aedes aegypti; Aquatic insects; Biology and life sciences; Culicidae; Data analysis; Disease prevention; Disease spread; Disease transmission; Epidemiology; Estimates; Flavivirus; Global health; Guillain-Barre syndrome; Homology; Humans; Medicine and Health Sciences; Microcephaly; Models, Theoretical; Mosquitoes; Parameter estimation; People and places; Physical Sciences; Population density; Public health; Rain; Research and Analysis Methods; Researchers; Spatial data; Studies; Time series; Vector-borne diseases; Vectors (Biology); Viruses; Zika virus; Zika Virus Infection - transmission; Brazil; United States > US; Connecticut
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0192120

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.