Weather Variability and the Incidence of Cryptosporidiosis: Comparison of Time Series Poisson Regression and SARIMA Models

Annals of Epidemiology

Volumn 17, Issue 9, 2007, Pages 679-688

  Hu, Wenbiao ^a   Tong, Shilu ^a   Mengersen, Kerrie ^a   Connell, Des ^a  

^a QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

Author keywords

Cryptosporidiosis; Poisson Regression; SARIMA; Time Series; Weather

Indexed keywords

ADULT; AKAIKE INFORMATION CRITERION; ANALYTICAL ERROR; ARTICLE; AUSTRALIA; CORRELATION ANALYSIS; CRYPTOSPORIDIOSIS; DISEASE TRANSMISSION; FEMALE; HUMAN; INCIDENCE; INFECTION CONTROL; LOW TEMPERATURE; MAJOR CLINICAL STUDY; MALE; POISSON REGRESSION MODEL; PREDICTION; PRIORITY JOURNAL; REGRESSION ANALYSIS; ROOT MEAN SQUARE ERROR; SEASONAL AUTO REGRESSION INTEGRATED MOVING AVERAGE MODEL; STATISTICAL MODEL; TEMPERATURE SENSITIVITY; TIME SERIES ANALYSIS; WEATHER;

CRYPTOSPORIDIOSIS; EPIDEMIOLOGIC STUDIES; HUMANS; MODELS, STATISTICAL; POISSON DISTRIBUTION; QUEENSLAND; TIME FACTORS; WEATHER;

EID: 34548041200     PISSN: 10472797     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.annepidem.2007.03.020     Document Type: Article

References (50)

1. Rose J.B., Huffman D.E., and Gennaccaro A. Risk and control of waterborne cryptosporidiosis. FEMS Microbiol Rev 26 (2002) 113-123
2. Meinhardt P.L., Casemore D.P., and Miller K.B. Epidemiologic aspects of human cryptosporidiosis and the role of waterborne transmission. Epidemiol Rev 18 (1996) 118-136
3. Current W., and Garcia L. Cryptosporidiosis. Clin Microbiol Rev 4 (1991) 328-358
4. Australian Department of Health and Aged Care. National Notifiable Diseases Surveillance System. Available at: http://www1.health.gov.au/cda/Source/CDA-index.cfm. Accessed October 10, 2006.
5. O'Donoghue P.J. Cryptosporidium and cryptosporidiosis in man and animals. Int J Parasitol 25 (1995) 139-195
6. Rose J.B. Environmental ecology of Cryptosporidium and public health implications. Annu Rev Public Health 18 (1997) 135-161
7. Naumova E., Christodouleas J., Hunter P., and Syed Q. Effect of precipitation on seasonal variability in cryptosporidiosis recorded by the North West England surveillance system in 1990-1999. J Water Health 3 (2005) 185-196
8. Bowie C., and Prothero D. Finding causes of seasonal diseases using time series analysis. Int J Epidemiol 10 (1981) 87-92
9. Catalano R., and Serxner S. Time series designs of potential interest to epidemiologists. Am J Epidemiol 26 (1987) 724-731
10. Helfenstein U. Box-Jenkins modelling of some viral infectious diseases. Stat Med 5 (1986) 37-47
11. Helfenstein U. The use of transfer function models, intervention analysis and related time series methods in epidemiology. Int J Epidemiol 20 (1991) 808-815
12. Helfenstein U. Box-Jenkins modelling in medical research. Stat Methods Med Res 5 (1996) 3-22
13. Checkley W., Epstein L., Gilman R., Figueroa D., Gama R., Patz J., et al. Effect of El Niño and ambient temperature on hospital admissions for diarrhoeal disease in Peruvian children. Lancet 355 (2000) 442-450
14. Clancy L., Goodman P., Sinclair H., and Dockery D. Effect of air-pollution control on death rates in Dublin, Ireland: an intervention study. Lancet 360 (2002) 1184-1185
15. Dominici F., McDermott A., Zeger S., and Samet J. On the use of generalized additive models in time-series studies of air pollution and health. Am J Epidemiol 156 (2002) 193-203
16. Hajat S., and Haines A. Associations of cold temperatures with GP consultations for respiratory and cardiovascular disease amongst the elderly in London. Int J Epidemiol 31 (2002) 825-830
17. Pope C., Burnett R., Thun M., Calle E., Krewski D., Ito K., et al. Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. JAMA 287 (2002) 1132-1141
18. Borghi J., Guinness L., Ouedraogo J., and Curtis V. Is hygiene promotion cost-effective? A case study in Burkina Faso. Trop Med Int Health 7 (2002) 960-969
19. Abeku T., deVlas S., Borsboom G., Teklehaimanot A., Kebede A., Olana D., et al. Forecasting malaria incidence from historical morbidity patterns in epidemic-prone areas of Ethiopia: a simple seasonal adjustment method performs best. Trop Med Int Health 7 (2002) 851-857
20. Allard R. Use of time-series analysis in infectious disease surveillance. Bull World Health Organ 76 (1998) 327-323
21. Nobre F., Monteiro A., Telles P., and Williamson G. Dynamic linear model and SARIMA: a comparison of their forecasting performance in epidemiology. Stat Med 20 (2001) 3051-3069
22. Tobias A., Diaz J., Saez M., and Alberdi J. Use of poisson regression and box-jenkins models to evaluate the short-term effects of environmental noise levels on daily emergency admissions in Madrid, Spain. Eur J Epidemiol 17 (2001) 765-771
23. Zeger S. A regression model for time series of counts. Biometrika 75 (1988) 621-629
24. Campbell M. Time series regression for counts: an investigation into the relationship between Sudden Infant Death Syndrome and environmental temperature. J Royal Stat Soc A 157 (1994) 191-208
25. Hu W., Nicholls N., Lindsay M., Dale P., McMichael A., Mackenzie J., et al. Development of a predictive model for Ross River virus disease in Brisbane, Australia. Am J Trop Med Hyg 71 (2004) 129-137
26. Australian Bureau of Statistics. 2001 census basic. [electronic resource] (2002), Australian Bureau of Statistics, Canberra
27. McMichael A., Campbell-Lendrum D., and Corvalan C. Climate change and human health: risks and responses (2003), World Health Organisation, Geneva
28. Li X., Atwill E., Dunbar L., Jones T., Hook J., and Tate K. Seasonal temperature fluctuations induces rapid inactivation of Cryptosporidium parvum. Environ Sci Technol 15 (2005) 4484-4489
29. Chatfield C. The analysis of time series: theory and practice (1975), Chapman & Hall, London
30. Tabachnick B., and Fidell L. Using multivariate statistics (1996), Harper Collins College Publishers, New York
31. SAS Institute Inc. SAS /STAT software changes and enhancements through release 6.12. Cary (NC): 1997.
32. Gelman A., Carlin J., Stern H., and Rubin D. Bayesian data analysis (1995), Chapman & Hall, London
33. SAS I. SAS /STAT software changes and enhancements through release 6.12. Cary (NC): 1997.
34. Statistical Package for the Social Sciences. SPSS 10 Guide to DATA analysis (1997), Prentice-Hall Inc, Upper Saddle River (NJ)
35. Venables W., and Ripley B. Modern applied statistics with S-PLUS (1999), Springer, New York
36. Statistical Package for the Social Sciences. SPSS Trends (1997), Prentice-Hall Inc, Upper Saddle River (NJ)
37. Dodd S., Bassi A., Bodger K., and Williamson P. A comparison of multivariable regression models to analyse cost data. J Eval Clin Pract 12 (2006) 76-86
38. Oh C., and Morzuch B. Evaluating time-series models to forecast the demand for tourism in Singapore: comparing within-sample and postsample results. J Travel Res 43 (2005) 404-413
39. Kuhn L., Davidson L., and Durkin M. Use of Poisson regression and time series analysis for detecting changes over time in rates of child injury following a prevention program. Am J Epidemiol 140 (1994) 943-955
40. Mark W. Epidemiology: study design and data analysis (1999), Chapman & Hall, London
41. Davis R., Dunsmuir W., and Wang Y. On autocorrelation in a Poisson regression model. Biometrika 87 (2000) 491-505
42. Tobias A., Saez M., Galan I., and Campbell M. Sensitivity analysis of common statistical models used to study the short-term effects of air pollution on health. Int J Biometeorol 47 (2003) 227-229
43. Armitage P., Berry G., and Matthews J. Statistical methods in medical research (2002), Blackwell Science, Carlton, Australia:
44. Yurekli K., Kurunc A., and Ozturk F. Application of linear stochastic models to monthly flow data of Kelkit Stream. Ecol Model 183 (2005) 67-75
45. Box G., and Jenkins G. Time-series analysis: forecasting and control (1970), McGraw-Hill, Maidenhead (UK)
46. Linthicum K., Anyamba A., Tucker C., Kelley P., Myers M.F., and Peters C. Climate and satellite indicators to forecast Rift Valley fever epidemics in Kenya. Science 285 (1999) 347-348
47. Wei W. Time series analysis (1990), Addison-Wesley, New York
48. Stafford R., Neville G., Towner C., and McCall B. A community outbreak of Cryptosporidium infection associated with a swimming pool complex. Commun Dis Intell 24 (2000) 236-239
49. Lemmon J., McAnulty J., and Bawden-Smith J. Outbreak of cryptosporidiosis linked to an indoor swimming pool. Med J Aust 165 (1996) 613-616
50. Peterson T., and Koput K. Time aggregation bias in hazard-rete models with covariates. Sociol Methods Res 21 (1992) 25-51