Statistical Tools for West Nile Virus Disease Analysis

Matthew J. Ward, Meytar Sorek-Hamer, Krishna Karthik Vemuri, Nicholas B. DeFelice

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations

Abstract

West Nile virus (WNV) is the most widespread arbovirus in the world and endemic to much of the United States. Its range continues to expand as land use patterns change, creating more habitable environments for the mosquito vector. Though WNV is endemic, the year-to-year risk is highly variable, thus making it difficult to understand the risk for human spillover events. Abatement districts monitor for infected mosquitoes to help understand these potential risks and to help guide our understanding of the risk posed by these observed infected mosquitoes. Creating optimal monitoring networks will provide more informed decision-making tools for abatement districts and policy makers. Investment in these monitoring networks that capture robust observations on mosquito infection rates will allow for environmentally informed inference systems to help guide decision-making and WNV risk. In turn, enhanced decision-making tools allow for faster response times of more targeted and economical surveillance and mosquito population reduction efforts and the overall reduction of WNV transmission. Here we discuss the data streams, their processing, and specifically three ways to calculate WNV infection rates in mosquitoes.

Original languageEnglish
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages171-191
Number of pages21
DOIs
StatePublished - 2023

Publication series

NameMethods in Molecular Biology
Volume2585
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029

Keywords

  • Arbovirus
  • Disease forecast modelling
  • Flavivirus
  • Mosquito control
  • Mosquito-borne disease
  • Vector-borne disease
  • West Nile virus
  • Zoonosis

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