Geographical and temporal distribution of human giardiasis in Ontario, Canada

BackgroundGiardia is the most frequently identified intestinal parasite in North America. Although information on geographical distribution of giardiasis is critical in identifying communities at high risk, little has been done in this area. Therefore, the objective of this study was to investigate the geographical and temporal distribution of human giardiasis in Ontario in order to identify possible high risk areas and seasons. Two spatial scales of analyses and two disease measures were used with a view to identifying the best of each in assessing geographical patterns of giardiasis in Ontario. Global Moran's I and Moran Local Indicators of Spatial Associations were used to test for evidence of global and local spatial clustering, respectively.ResultsThere were seasonal patterns with summer peaks and a significant (P < 0.001) decreasing temporal trend. Significant (P < 0.05) global spatial clustering of high rates was observed at the Census Sub-division spatial scale but not at the Census Division scale. The Census Sub-division scale was a better scale of analyses but required spatial empirical Bayesian smoothing of the rates. A number of areas with significant local clustering of giardiasis rates were identified.ConclusionsThe study identified spatial and temporal patterns in giardiasis distribution. This information is important in guiding decisions on disease control strategies. The study also showed that there is benefit in performing spatial analyses at more than one spatial scale to assess geographical patterns in disease distribution and that smoothing of disease rates for mapping in small areas enhances visualization of spatial patterns.

[1]  J. Isaac-Renton,et al.  Longitudinal studies of Giardia contamination in two community drinking water supplies: cyst levels, parasite viability, and health impact , 1996, Applied and environmental microbiology.

[2]  Jack Cuzick,et al.  Small-area studies: purpose and methods , 1996 .

[3]  J. Roberts,et al.  Giardiasis surveillance--United States, 1992-1997. , 2000, MMWR. CDC surveillance summaries : Morbidity and mortality weekly report. CDC surveillance summaries.

[4]  A. Staines,et al.  Health event data , 2001 .

[5]  G. Craun,et al.  Waterborne outbreaks of giardiasis. Current status. , 1984 .

[6]  J Siemiatycki,et al.  The problem of multiple inference in studies designed to generate hypotheses. , 1985, American journal of epidemiology.

[7]  D. Clayton,et al.  Empirical Bayes estimates of age-standardized relative risks for use in disease mapping. , 1987, Biometrics.

[8]  S H Heisterkamp,et al.  Disease mapping using empirical Bayes and Bayes methods on mortality statistics in The Netherlands. , 1993, Statistics in medicine.

[9]  Mortality Mapping in Hong Kong, 1979-83 and 1984-88: Feasibility Study and the Patterns of Cancers , 1995, Asia-Pacific journal of public health.

[10]  Charles J. Greenberg,et al.  ArcView GIS Version 3.1. , 1999 .

[11]  A. Gelman,et al.  All maps of parameter estimates are misleading. , 1999, Statistics in medicine.

[12]  L. Bernardinelli,et al.  Bayesian methods for mapping disease risk , 1996 .

[13]  Flanagan Pa.  Giardia--diagnosis, clinical course and epidemiology. A review. , 1992 .

[14]  S D Walter,et al.  The analysis of regional patterns in health data. II. The power to detect environmental effects. , 1992, American journal of epidemiology.

[15]  D K Wagener,et al.  Geographic variations in US asthma mortality: small-area analyses of excess mortality, 1981-1985. , 1990, American journal of epidemiology.

[16]  Robert Haining,et al.  Spatial Statistics and the Analysis of Health Data , 1998 .

[17]  Roger Marshall,et al.  A Review of Methods for the Statistical Analysis of Spatial Patterns of Disease , 1991 .

[18]  E. Brown,et al.  Giardia lamblia; the incidence and results of infestation of children in residential nurseries. , 1948, Archives of disease in childhood.

[19]  S D Walter.  The analysis of regional patterns in health data. I. Distributional considerations. , 1992, American journal of epidemiology.

[20]  W. Tobler.  A Computer Movie Simulating Urban Growth in the Detroit Region , 1970 .

[21]  D. Griffith,et al.  The boundary value problem in spatial statistical analysis. , 1983, Journal of regional science.

[22]  Jian Huang,et al.  A bayesian approach to replication of linkage findings , 1999, Genetic epidemiology.

[23]  L Bernardinelli,et al.  Bayesian estimates of disease maps: how important are priors? , 1995, Statistics in medicine.

[24]  J. Wakefield,et al.  Spatial epidemiology: methods and applications. , 2000 .

[25]  L Bernardinelli,et al.  Empirical Bayes versus fully Bayesian analysis of geographical variation in disease risk. , 1992, Statistics in medicine.

[26]  P A Flanagan,et al.  Giardia--diagnosis, clinical course and epidemiology. A review. , 1992, Epidemiology and infection.

[27]  K J Rothman,et al.  No Adjustments Are Needed for Multiple Comparisons , 1990, Epidemiology.

[28]  W. Brown.  Giardia and giardiasis: Biology, pathogenesis, and epidemiology , 1986 .

[29]  G. Craun.  Waterborne Outbreaks of Giardiasis , 1984 .

[30]  J. Aramini,et al.  Waterborne cryptosporidiosis outbreak, North Battleford, Saskatchewan, Spring 2001. , 2001, Canada communicable disease report = Releve des maladies transmissibles au Canada.

[31]  Angela Lee,et al.  Perspectives on … Environmental Systems Research Institute, Inc , 1997 .

[32]  J F Bithell,et al.  A classification of disease mapping methods. , 2000, Statistics in medicine.

[33]  富士通オフィス機器.  Microsoft Excel 2000 , 2001 .

[34]  E. Lesaffre,et al.  Disease mapping and risk assessment for public health. , 1999 .

[35]  A. Molesworth,et al.  Geographical analysis of communicable disease data. , 2001 .

[36]  John E. Bennett,et al.  Principles and practice of infectious diseases. Vols 1 and 2. , 1979 .