Predicting Fluctuating Rates of Hospitalizations in Relation to Influenza Epidemics and Meteorological Factors
Publication Date
June 16, 2016
Journal
PLOS ONE
Authors
Radia Spiga, Mireille Batton Hubert & Marianne Sarazin
Volume
11
Issue
6
Pages
e0157492
DOI
https://dx.plos.org/10.1371/journal.pone.0157492
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0157492
Scopus
84976439555
Mendeley
http://www.mendeley.com/research/predicting-fluctuating-rates-hospitalizations-relation-influenza-epidemics-meteorological-factors
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Mendeley | Further Information

{"title"=>"Predicting fluctuating rates of hospitalizations in relation to influenza epidemics and meteorological factors", "type"=>"journal", "authors"=>[{"first_name"=>"Radia", "last_name"=>"Spiga", "scopus_author_id"=>"57189997577"}, {"first_name"=>"Mireille", "last_name"=>"Batton-Hubert", "scopus_author_id"=>"12797959000"}, {"first_name"=>"Marianne", "last_name"=>"Sarazin", "scopus_author_id"=>"8735787600"}], "year"=>2016, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"610922221", "sgr"=>"84976439555", "scopus"=>"2-s2.0-84976439555", "issn"=>"19326203", "doi"=>"10.1371/journal.pone.0157492"}, "id"=>"e4c23572-007c-3602-9886-3becaeebda29", "abstract"=>"Introduction In France, rates of hospital admissions increase at the peaks of influenza epidemics. Predicting influenza-associated hospitalizations could help to anticipate increased hospital activity. The purpose of this study is to identify predictors of influenza epidemics through the analysis of meteorological data, and medical data provided by general practitioners. Methods Historical data were collected from Meteo France, the Sentinelles network and hospitals' information systems for a period of 8 years (2007-2015). First, connections between meteorological and medical data were estimated with the Pearson correlation coefficient, Principal component analysis and classification methods (Ward and k-means). Epidemic states of tested weeks were then predicted for each week during a one-year period using linear discriminant analysis. Finally, transition probabilities between epidemic states were calculated with the Markov Chain method. Results High correlations were found between influenza-associated hospitalizations and the variables: Sentinelles and emergency department admissions, and anti-correlations were found between hospitalizations and each of meteorological factors applying a time lag of: -13, -12 and -32 days respectively for temperature, absolute humidity and solar radiation. Epidemic weeks were predicted accurately with the linear discriminant analysis method; however there were many misclassifications about intermediate and non-epidemic weeks. Transition probability to an epidemic state was 100% when meteorological variables were below: 2° C, 4 g/m3 and 32 W/m2 , respectively for temperature, absolute humidity and solar radiation. This probability was 0% when meteorological variables were above: 6° C, 5.8g/m3 and 74W/m2 Conclusion These results confirm a good correlation between influenza-associated hospitalizations, meteorological factors and general practitioner's activity, the latter being the strongest predictor of hospital activity. © 2016 Spiga et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.", "link"=>"http://www.mendeley.com/research/predicting-fluctuating-rates-hospitalizations-relation-influenza-epidemics-meteorological-factors", "reader_count"=>6, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>1, "Student > Ph. D. Student"=>1, "Student > Postgraduate"=>2, "Student > Master"=>2}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>1, "Student > Ph. D. Student"=>1, "Student > Postgraduate"=>2, "Student > Master"=>2}, "reader_count_by_subject_area"=>{"Mathematics"=>1, "Medicine and Dentistry"=>1, "Agricultural and Biological Sciences"=>2, "Veterinary Science and Veterinary Medicine"=>1, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>2}, "Mathematics"=>{"Mathematics"=>1}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "group_count"=>0}

Scopus | Further Information

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