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Rapid mapping of the spatial and temporal intensity of influenza.
Muscatello, David J; Leong, Robert Neil F; Turner, Robin M; Newall, Anthony T.
Afiliação
  • Muscatello DJ; School of Public Health and Community Medicine, University of New South Wales, Sydney, NSW, 2052, Australia. david.muscatello@unsw.edu.au.
  • Leong RNF; School of Public Health and Community Medicine, University of New South Wales, Sydney, NSW, 2052, Australia.
  • Turner RM; School of Public Health and Community Medicine, University of New South Wales, Sydney, NSW, 2052, Australia.
  • Newall AT; University of Otago, PO Box 56, Dunedin, 9054, New Zealand.
Eur J Clin Microbiol Infect Dis ; 38(7): 1307-1312, 2019 Jul.
Article em En | MEDLINE | ID: mdl-31069558
Surveillance of influenza epidemics is a priority for risk assessment and pandemic preparedness, yet representation of their spatiotemporal intensity remains limited. Using the epidemic of influenza type A in 2016 in Australia, we demonstrated a simple but statistically sound adaptive method of mapping epidemic evolution over space and time. Weekly counts of persons with laboratory confirmed influenza type A infections in Australia in 2016 were analysed by official national statistical region. Weekly standardised epidemic intensity was represented by a standard score (z-score) calculated using the standard deviation of below-median counts in the previous 52 weeks. A geographic information system (GIS) was used to present the epidemic progression. There were 79,628 notifications of influenza A infections included. Of these, 79,218 (99.5%) were allocated to a geographical area. The GIS maps indicated areas of elevated epidemic intensity across Australia by week and area that were consistent with the observed start, peak and decline of the epidemic when compared with counts aggregated at the state and territory level. This simple, adaptable approach could improve local level epidemic intelligence in a variety of settings and for other diseases. It may also facilitate increased understanding of geographic epidemic dynamics.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Influenza Humana / Epidemias / Pandemias / Monitoramento Epidemiológico / Análise Espaço-Temporal Tipo de estudo: Diagnostic_studies / Etiology_studies / Risk_factors_studies / Screening_studies Limite: Humans País como assunto: Oceania Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Influenza Humana / Epidemias / Pandemias / Monitoramento Epidemiológico / Análise Espaço-Temporal Tipo de estudo: Diagnostic_studies / Etiology_studies / Risk_factors_studies / Screening_studies Limite: Humans País como assunto: Oceania Idioma: En Ano de publicação: 2019 Tipo de documento: Article