A model to assess the accuracy of detecting arboviruses in mosquito pools

Christopher J. Vitek, Stephanie L. Richards, Heather L. Robinson, Chelsea T. Smartt

Research output: Contribution to journalArticlepeer-review

Abstract

Vigilant surveillance of virus prevalence in mosquitoes is essential for risk assessment and outbreak prediction. Accurate virus detection methods are essential for arbovirus surveillance. We have developed a model to estimate the probability of accurately detecting a virus-positive mosquito from pooled field collections using standard molecular techniques. We discuss several factors influencing the probability of virus detection, including the number of virions in the sample, the total sample volume, and the portion of the sample volume that is being tested. Our model determines the probability of obtaining at least 1 virion in the sample that is tested. The model also determines the optimal sample volume that is required in any test to ensure a desired probability of virus detection is achieved, and can be used to support the accuracy of current tests or to optimize existing techniques.

Original languageEnglish
Pages (from-to)374-378
Number of pages5
JournalJournal of the American Mosquito Control Association
Volume25
Issue number3
DOIs
StatePublished - Sep 2009
Externally publishedYes

Keywords

  • Arboviruses
  • Infection
  • Probability of detection
  • Surveillance

Fingerprint

Dive into the research topics of 'A model to assess the accuracy of detecting arboviruses in mosquito pools'. Together they form a unique fingerprint.

Cite this