Document Detail

Syndromic surveillance models using Web data: The case of scarlet fever in the UK.
MedLine Citation:
PMID:  22360741     Owner:  NLM     Status:  In-Data-Review    
Recent research has shown the potential of Web queries as a source for syndromic surveillance, and existing studies show that these queries can be used as a basis for estimation and prediction of the development of a syndromic disease, such as influenza, using log linear (logit) statistical models. Two alternative models are applied to the relationship between cases and Web queries in this paper. We examine the applicability of using statistical methods to relate search engine queries with scarlet fever cases in the UK, taking advantage of tools to acquire the appropriate data from Google, and using an alternative statistical method based on gamma distributions. The results show that using logit models, the Pearson correlation factor between Web queries and the data obtained from the official agencies must be over 0.90, otherwise the prediction of the peak and the spread of the distributions gives significant deviations. In this paper, we describe the gamma distribution model and show that we can obtain better results in all cases using gamma transformations, and especially in those with a smaller correlation factor.
Loukas Samaras; Elena García-Barriocanal; Miguel-Angel Sicilia
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Informatics for health & social care     Volume:  37     ISSN:  1753-8165     ISO Abbreviation:  Inform Health Soc Care     Publication Date:  2012 Mar 
Date Detail:
Created Date:  2012-02-24     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101475011     Medline TA:  Inform Health Soc Care     Country:  England    
Other Details:
Languages:  eng     Pagination:  106-24     Citation Subset:  IM    
Ministry of Employment and Social Insurance , General Secretariat of Social Security, Department of National Security Registries and Internet , Athens.
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