International Journal of Biometeorology

, Volume 50, Issue 6, pp 385–391 | Cite as

A time series analysis of the relationship of ambient temperature and common bacterial enteric infections in two Canadian provinces

  • Manon FleuryEmail author
  • Dominique F. Charron
  • John D. Holt
  • O. Brian Allen
  • Abdel R. Maarouf
Original Article


The incidence of enteric infections in the Canadian population varies seasonally, and may be expected to be change in response to global climate changes. To better understand any potential impact of warmer temperature on enteric infections in Canada, we investigated the relationship between ambient temperature and weekly reports of confirmed cases of three pathogens in Canada: Salmonella, pathogenic Escherichia coli and Campylobacter, between 1992 and 2000 in two Canadian provinces. We used generalized linear models (GLMs) and generalized additive models (GAMs) to estimate the effect of seasonal adjustments on the estimated models. We found a strong non-linear association between ambient temperature and the occurrence of all three enteric pathogens in Alberta, Canada, and of Campylobacter in Newfoundland-Labrador. Threshold models were used to quantify the relationship of disease and temperature with thresholds chosen from 0 to −10°C depending on the pathogen modeled. For Alberta, the log relative risk of Salmonella weekly case counts increased by 1.2%, Campylobacter weekly case counts increased by 2.2%, and E. coli weekly case counts increased by 6.0% for every degree increase in weekly mean temperature. For Newfoundland-Labrador the log relative risk increased by 4.5% for Campylobacter for every degree increase in weekly mean temperature.


Foodborne disease Ambient temperature Time series analysis Climate change Canada 



We thank Alberta Public Health and Newfoundland and Labrador Centre for Health Information for the use of their notifiable disease data for this study. We also thank the cCASHh study for their support and collaboration and James R. Ferguson, a geographical consultant, for preparing the map for this article.


  1. Aramini J, McLean M, Wilson J et al (2000) Drinking water quality and health care utilization for gastrointestinal illness in greater Vancouver. Health Canada: Population and Public Health Branch. OctoberGoogle Scholar
  2. Bentham G, Langford IH (1995) Climate change and the incidence of food poisoning in England and Wales. Int J Biometeorol 39:81–86CrossRefPubMedGoogle Scholar
  3. Bentham G, Langford IH (2001) Environmental temperatures and the incidence of food poisoning in England and Wales. Int J Biometeorol 45:22–26CrossRefPubMedGoogle Scholar
  4. Brumback BA, Ryan LM, Schwartz, J, Neas L, Stark P, Burge H (2000) Transitional regression models, with application to environmental time series. J Am Stat Assoc 95:16–27CrossRefGoogle Scholar
  5. Canadian Integrated Surveillance Report (2003) Salmonella, Campylobacter, pathogenic E. coli and Shigella, from 1996–1999. Canadian Communicable Disease Report 2951Google Scholar
  6. Canadian Medical Association Journal (2003) Food irradiation: Let’s do it (editorial). Can Med Assoc J 162:5Google Scholar
  7. Dominici F, McDermott A, Zeger SL, Samet JM (2002) On the use of generalized additive models in time-series studies of air pollution and health. Am J Epidemiol 156:193–203CrossRefPubMedGoogle Scholar
  8. D’Souza RM, Becker NG, Hall G, Moodie KBA (2004) Does ambient temperature affect foodborne disease? Epidemiology 15:86–92CrossRefPubMedGoogle Scholar
  9. Environment Canada (2002) “The Climate of Newfoundland.” The Green Lane (Dartmouth, Nova Scotia)
  10. Hall GV, D’Souza RM, Kirk MD (2002) Foodborne disease in the new millennium: out of the frying pan and into the fire? Med J Aust 177:614–618PubMedGoogle Scholar
  11. Hastie TJ, Tibshirani R (1990) Generalized additive models. Chapman and Hall, LondonGoogle Scholar
  12. Isaacs S, Leber C, Michel P (1998) The distribution of foodborne disease by risk setting—Ontario. Can Commun Dis Rep 24:61–64PubMedGoogle Scholar
  13. Kovats S, Edwards S, Hajat S, Armstrong BG, Ebi KL, Menne B (2004) The effect of temperature on food poisoning: a time-series analysis of salmonellosis in ten European countries. Epidemiol Infect 132:443–453CrossRefPubMedGoogle Scholar
  14. Mackey BM, Kerridge AL (1988) The effect of incubation temperature and inoculum size on growth of salmonellae in minced beef. Int J Food Microbiol 6:57–65CrossRefPubMedGoogle Scholar
  15. Mathsoft (1999) S-PLUS 2000 guide to statistics, vol 1. Data Analysis Products Division, Mathsoft, Seattle, WAGoogle Scholar
  16. Ramsay TO, Burnett R, Krewski D (2003) Exploring bias in a generalized additive model for spatial air pollution data. Environ Health Perspect 110:1283–1288CrossRefGoogle Scholar
  17. Statistics Canada (2002) Population and dwelling counts, for Canada, Provinces and Territories, 2001 and 1996 censuses. Statistical Reference Centre, Ottawa, ON,
  18. Ulm K, Salanti G (2003) Estimation of the general threshold limit values for dust. Int Arch Occup Environ Health 76:233–240PubMedGoogle Scholar
  19. Woods SN (2004) Stable and efficient multiple smoothing parameter estimation for generalized additive models. J Am Stat Assoc 99:673–686CrossRefGoogle Scholar

Copyright information

© ISB 2006

Authors and Affiliations

  • Manon Fleury
    • 1
    Email author
  • Dominique F. Charron
    • 1
  • John D. Holt
    • 2
  • O. Brian Allen
    • 2
  • Abdel R. Maarouf
    • 3
  1. 1.Foodborne, Waterborne and Zoonotic Infections DivisionPublic Health Agency of CanadaGuelphCanada
  2. 2.Department of Mathematics and StatisticsUniversity of GuelphGuelphCanada
  3. 3.Meterological Service of CanadaEnvironment CanadaTorontoCanada

Personalised recommendations