Spatio-temporal analysis of pneumonia and influenza hospitalizations in Ontario, Canada

  • Eric J. Crighton | Eric.Crighton@uottawa.ca Department of Geography, University of Ottawa, Ottawa, ON, Canada.
  • Susan J. Elliott School of Geography and Geology, McMaster University, Hamilton, ON, Canada.
  • Pavlos Kanaroglou School of Geography and Geology, McMaster University, Hamilton, ON, Canada.
  • Rahim Moineddin Department of Family and Community Medicine, University of Toronto, Toronto, ON; Department of Public Health Sciences, University of Toronto, Toronto, ON, Canada.
  • Ross E.G. Upshur Department of Family and Community Medicine, University of Toronto, Toronto, ON; Department of Public Health Sciences, University of Toronto, Toronto, ON; Primary Care Research Unit, Sunnybrook and Women’s College Health Sciences Centre, Toronto, ON, Canada.

Abstract

Pneumonia and influenza represent a significant public health and health care system burden that is expected to increase with the aging of developed nations’ populations. The burden of these illnesses is far from uniform however, with recent studies showing that they are both highly spatially and temporally variable. We have combined spatial and time-series analysis techniques to examine pneumonia and influenza hospitalizations in the province of Ontario, Canada, to determine how temporal patterns vary over space, and how spatial patterns of hospitalizations vary over time. Knowledge of these patterns can provide clues to disease aetiology and inform the effective management of health care system resources. Spatial analysis revealed significant clusters of high hospitalization rates in northern and rural counties (Moran’s I = 0.186; P <0.05), while county level time series analysis demonstrated significant upward trends in rates in almost a quarter of the counties (P <0.05), and significant seasonality in all but one county (Fisher-Kappa and Barlett Kolmogorov Smirnov tests significant at the level P <0.01). Areas of weak seasonality were typically seen in rural areas with high rates of hospitalizations. The highest levels of spatial clustering of pneumonia and influenza hospitalizations were found to occur in months when rates were lowest. The findings provide evidence of spatio-temporal interaction over the study period, with marked spatial variability in temporal patterns, and temporal variability in spatial patterns. Results point to the need for the effective allocation of services and resources based on regional and seasonal demands, and more regionally focused prevention strategies. This research represents an important step towards understanding the dynamic nature of these illnesses, and sets the stage for the application of spatio-temporal modelling techniques to explain them.

Downloads

Download data is not yet available.
Published
2008-05-01
Section
Original Articles
Keywords:
pneumonia, influenza, hospitalization, spatio-temporal analysis, Ontario, Canada.
Statistics
Abstract views: 1172

PDF: 446
Share it

PlumX Metrics

PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.

How to Cite
Crighton, E. J., Elliott, S. J., Kanaroglou, P., Moineddin, R., & Upshur, R. E. (2008). Spatio-temporal analysis of pneumonia and influenza hospitalizations in Ontario, Canada. Geospatial Health, 2(2), 191-202. https://doi.org/10.4081/gh.2008.243