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Updated: Jul 31, 2025

Swab Sampling Method for the Detection of Human Norovirus on Surfaces

Swab Sampling Method for the Detection of Human Norovirus on Surfaces

Published on: February 6, 2017

Predicting Norovirus in England Using Existing and Emerging Syndromic Data: Infodemiology Study.

Nikola Ondrikova^1,2,3, John P Harris⁴, Amy Douglas⁵

¹Institute of Infection, Ecological and Veterinary Sciences, University of Liverpool, Liverpool, United Kingdom.

Journal of Medical Internet Research

|May 8, 2023

Summary

This summary is machine-generated.

Predicting norovirus outbreaks in England is possible using syndromic surveillance and online search data. Vomiting and gastroenteritis symptoms are key predictors, though effectiveness varies by region and age group.

Keywords:

Google Trends Granger causality framework Wikipedia big data communicable disease disease spread gastroenteritis gastroenterologist gastroenterology infection control infection prevention infectious disease infodemiology infoveillance internal medicine internet data mental model model norovirus predict prediction surveillance syndromic data syndromic surveillance transmission trend variable importance viral viral disease viral infection virus web-based data

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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

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Last Updated: Jul 31, 2025

Swab Sampling Method for the Detection of Human Norovirus on Surfaces

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Published on: February 6, 2017

Detection and Genogrouping of Noroviruses from Children's Stools By Taqman One-step RT-PCR

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Published on: July 22, 2012

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

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
Data Science

Background:

Norovirus causes a significant global burden of gastroenteritis, affecting all ages.
Currently, no licensed vaccine or antiviral treatment exists for norovirus.
Effective early warning systems are crucial for nonpharmaceutical prevention and control strategies.

Purpose of the Study:

To evaluate the predictive power of syndromic surveillance and emerging data sources for norovirus activity in England.
To assess the utility of internet searches and Wikipedia page views in predicting norovirus trends across different age groups.

Main Methods:

Utilized existing syndromic surveillance and emerging data (internet searches, Wikipedia views).
Employed Granger causality to assess temporal precedence of variables against norovirus laboratory reports.
Applied random forest modeling to determine variable importance based on mean square error and node purity.

Main Results:

Syndromic surveillance data proved valuable in predicting norovirus laboratory reports in England.
Wikipedia page views offered limited additional predictive improvement over Google Trends and existing syndromic data.
Predictive relevance varied significantly across age groups and geographic regions, with some models explaining up to 60% of variance.

Conclusions:

Existing and emerging data can aid in predicting norovirus activity in specific English regions and age groups.
Vomiting, gastroenteritis symptoms, and historical search terms like 'stomach flu' were significant predictors.
Variations in public health practices and information-seeking behaviors influence predictor relevance; internet search data offers insights into public understanding for communication strategies.