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Multistate foodborne outbreaks pose significant public health risks and require meticulous investigation to identify sources and implement control measures. The Centers for Disease Control and Prevention (CDC) utilizes a dynamic seven-step process for these investigations, integrating data from laboratories, interviews, and environmental assessments to protect public health.Outbreak Detection: The detection of multistate outbreaks typically begins with PulseNet, the CDC's national laboratory...
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Swab Sampling Method for the Detection of Human Norovirus on Surfaces
10:03

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Published on: February 6, 2017

Norovirus disease surveillance using Google Internet query share data.

Rishi Desai1, Aron J Hall, Benjamin A Lopman

  • 1Centers for Disease Control and Prevention, 1600 Clifton Rd. NE, MS-A34, Atlanta, GA 30333, USA. rdesai1@cdc.gov

Clinical Infectious Diseases : an Official Publication of the Infectious Diseases Society of America
|June 21, 2012
PubMed
Summary

Google Internet query share data strongly correlates with norovirus surveillance, enabling early detection of outbreaks. This approach can identify norovirus season onset, peak activity, and new strains effectively.

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EPA Method 1615. Measurement of Enterovirus and Norovirus Occurrence in Water by Culture and RT-qPCR. I. Collection of Virus Samples
10:48

EPA Method 1615. Measurement of Enterovirus and Norovirus Occurrence in Water by Culture and RT-qPCR. I. Collection of Virus Samples

Published on: March 28, 2015

Area of Science:

  • Epidemiology
  • Public Health Surveillance
  • Digital Epidemiology

Background:

  • Norovirus outbreaks pose a significant public health challenge.
  • Traditional surveillance methods can have reporting delays.
  • Internet query data offers a potential real-time monitoring tool.

Purpose of the Study:

  • To evaluate the correlation between Google Internet query share (IQS) data and norovirus surveillance data in the United States.
  • To assess the utility of IQS data for tracking norovirus activity.

Main Methods:

  • Analysis of Google IQS data for gastroenteritis-related search terms.
  • Comparison of IQS data with national and regional norovirus surveillance data.
  • Statistical correlation analysis (R-squared values).

Main Results:

  • Strong correlations were observed between IQS data and national (R² = 0.70) norovirus surveillance.
  • Even stronger correlations were found with regional (R² = 0.74) norovirus surveillance data.
  • IQS data demonstrated potential for tracking norovirus seasonality and activity levels.

Conclusions:

  • Google IQS data is a promising tool for near real-time monitoring of norovirus activity.
  • IQS data can facilitate rapid identification of norovirus season onset and peak activity.
  • This digital epidemiology approach may aid in detecting emerging norovirus strains.