OBJECTIVE: The purpose of the study was to explore and model the relationship between meteorological variables and meningococcal disease notifications in Auckland during an ongoing group B meningococcal disease epidemic. METHODS: An ecological study design was used to investigate the relationship between 1,097 notified cases of meningococcal disease from January 1992 to December 1998 among residents of Auckland's three health districts and various meteorological variables. Descriptive epidemiology and Poisson regression modelling were used to describe this relationship. FINDINGS: The study found that the occurrence of meningococcal disease varied with season, increased with high humidity and cooler temperatures and appeared to decline with prolonged periods of heavy rain. Poisson regression analysis showed a significant relationship between the expected number of cases developing meningococcal disease on a given day and season and temperature. DISCUSSION: The results of the modelling analysis provide the initial work for the future development of a predictive tool to forecast the magnitude and duration of the annual peak in meningococcal disease incidence using routine notification data and meteorological recordings, thus allowing for better management of the public health workload and interventions, and the appropriate timing of media campaigns.
OBJECTIVE: The purpose of the study was to explore and model the relationship between meteorological variables and meningococcal disease notifications in Auckland during an ongoing group B meningococcal disease epidemic. METHODS: An ecological study design was used to investigate the relationship between 1,097 notified cases of meningococcal disease from January 1992 to December 1998 among residents of Auckland's three health districts and various meteorological variables. Descriptive epidemiology and Poisson regression modelling were used to describe this relationship. FINDINGS: The study found that the occurrence of meningococcal disease varied with season, increased with high humidity and cooler temperatures and appeared to decline with prolonged periods of heavy rain. Poisson regression analysis showed a significant relationship between the expected number of cases developing meningococcal disease on a given day and season and temperature. DISCUSSION: The results of the modelling analysis provide the initial work for the future development of a predictive tool to forecast the magnitude and duration of the annual peak in meningococcal disease incidence using routine notification data and meteorological recordings, thus allowing for better management of the public health workload and interventions, and the appropriate timing of media campaigns.
Authors: Ashleigh R Tuite; Laura M Kinlin; Stefan P Kuster; Frances Jamieson; Jeffrey C Kwong; Allison McGeer; David N Fisman Journal: PLoS One Date: 2010-11-17 Impact factor: 3.240
Authors: F Vescio; L Busani; L Mughini Gras; C Fazio; A Neri; L Avellis; G Rezza; P Stefanelli Journal: Epidemiol Infect Date: 2014-10-13 Impact factor: 4.434
Authors: Laura M Kinlin; C Victor Spain; Victoria Ng; Caroline C Johnson; Alexander N J White; David N Fisman Journal: Am J Epidemiol Date: 2009-01-22 Impact factor: 4.897