1921
Volume 71, Issue 2
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645

Abstract

This paper describes the development of an empirical model to forecast epidemics of Ross River virus (RRV) disease using the multivariate seasonal auto-regressive integrated moving average (SARIMA) technique in Brisbane, Australia. We obtained computerized data on notified RRV disease cases, climate, high tide, and population sizes in Brisbane for the period 1985–2001 from the Queensland Department of Health, the Australian Bureau of Meteorology, the Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model was developed and validated by dividing the data file into two data sets: the data between January 1985 and December 2000 were used to construct a model, and those between January and December 2001 to validate it. The SARIMA models show that monthly precipitation (β = 0.004, = 0.031) was significantly associated with RRV transmission. However, there was no significant association between other climate variables (e.g., temperature, relative humidity, and high tides) and RRV transmission. The predictive values in the model were generally consistent with actual values (root mean square percentage error = 0.94%). Therefore, this model may have applications as a decision supportive tool in disease control and risk-management planning programs.

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2004-08-01
2017-09-19
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References

  1. Reiter P, 2001. Climate change and mosquito-borne disease. Environ Health Perspect 109 : 141–161.
  2. Ansari M, Shope R, 1994. Epidemiology of arboviral infections. Public Health Rev 22 : 1–26.
  3. Doherty R, Whitehead R, Gorman B, 1963. The isolation of a third group A arbovirus in Australia, with preliminary observations on its relationship to epidemic polyarhritis. Aust J Sci 26 : 183–184.
  4. Doherty R, Carley J, Best J, 1972. Isolation of Ross River virus in from man. Med J Aust 1 : 1083–1084.
  5. Aaskov J, Mataika J, Lawrence G, Rabukawaqa V, Tucker M, Miles J, Dalglish D, 1981. An epidemic of Ross River virus infection in Fiji, 1979. Am J Trop Med Hyg 30 : 1053–1059.
  6. Rosen L, Gubler D, Bennett P, 1981. Epidemic polyarthritis (Ross River) virus infection in the Cook Islands. Am J Trop Med Hyg 30 : 1294–1302.
  7. Mackenzie J, Brook A, Hall R, Johansen C, Lindsay M, Philips D, Ritchie S, Russell R, Smith D, 1998. Arboviruses in the Australian region, 1990 to 1998. Comm Dis Intell 22 : 93–100.
  8. Johansen CA, van den Hurk AF, Ritchie SA, Zborowski P, Nisbet DJ, Paru R, Bockarie MJ, Macdonald J, Drew AC, Khromkh TI, Mackenzie JS, 2000. Isolation of Japanese encephalitis virus from mosquitoes (Diptera: Culicidae) collected in the Western Province of Papua New Guinea, 1997–1998. Am J Trop Med Hyg 62 : 631–638.
  9. Mudge P, Aaskov J, 1983. Epidemic polyarthritis in Australia, 1980–1981. Med J Aust 17 : 269–273.
  10. Fraser J, 1986. Epidemic polyarthritis and Ross River virus disease. Clin Rheum Dis 12 : 369–388.
  11. Flexman J, Smith D, Mackenzie J, Fraser J, Bass S, Hueston L, Lindsay M, Cunningham A, 1998. A comparison of the diseases caused by Ross River virus and Barmah Forest virus. Med J Aust 169 : 159–163.
  12. Australian Department of Health and Aged Care, 2004. National Notifiable Diseases Surveillance System: http://www1.health.gov.au/cda/source/rpt-4.cfm. Accessed March 2, 2004.
  13. Russell R, 2002. Ross River virus: ecology and distribution. Annu Rev Entomol 47 : 1–31.
  14. Tong S, Bi P, Hayes J, Donald K, Mackenzie J, 2001. Geographic variation of notified Ross River virus infections in Queensland, Australia, 1985–1996. Am J Trop Med Hyg 65 : 171–176.
  15. Russell R, 1998. Vectors versus humans in Australia - Who is on top down under? An update on vector-borne disease and research on vectors in Australia. J Vector Ecol 23 : 1–46.
  16. Harley D, Sleigh A, Ritchie S, 2001. Ross River virus transmission, infection, and disease: a cross-disciplinary review. Clin Microbiol Rev 14 : 909–932.
  17. Tong S, Bi P, Donald K, McMichael A, 2002. Climate variability and Ross River virus transmission. J Epidemiol Community Health 56 : 617–621.
  18. Mackenzie J, Lindsay M, Daniels P, 2000. The effect of climate on the incidence of vector-borne viral diseases in Australia: the potential value of seasonal forecasting. Hammer G, Nicholls N, Mitchell C, eds. Applications of Seasonal Climate Forecasting in Agriculture and Natural Ecosystems. Dordrecht, The Netherlands: Kluwer Academic Publishers, 429–452.
  19. Mackenzie J, Lindsay M, Broom A, 2000. The effect of climate and weather on the transmission of Ross River and Murray Valley encephalitis viruses. Microbiol Aust 21 : 20–25.
  20. Lindsay M, Broom A, Wright A, Johansen C, Mackenzie J, 1993. Ross river virus isolation from the mosquitoes in arid regions of western Australia: implication of vertical transmission as a means of persistence of the virus. Am J Trop Med Hyg 49 : 686–696.
  21. McMichael A, Haines A, Kovats R, Slooff R, 1996. Climate Changes and Human Health. Geneva: World Health Organization.
  22. Tong S, Bi P, Parton K, Hobbs J, McMichael A, 1998. Climate variability and transmission of epidemic polyarthritis (letter). Lancet 351 : 1100.
  23. Woodruff R, Guest C, Garner M, Becker N, Lindesay J, Carvan T, Ebi K, 2002. Predicting Ross River virus epidemics from regional weather data. Epidemiology 13 : 384–393.
  24. Maelzer D, Hales S, Weinstein P, Zalucki M, Woodward A, 1999. El Niño and arboviral disease prediction. Environ Health Perspect 107 : 817–818.
  25. Bowie C, Prothero D, 1981. Finding causes of seasonal diseases using time series analysis. Int J Epidemiol 10 : 87–92.
  26. Catalano R, Serxner S, 1987. Time series designs of potential interest to epidemiologists. Am J Epidemiol 26 : 724–731.
  27. Helfenstein U, 1986. Box-Jenkins modelling of some viral infectious diseases. Stat Med 5 : 37–47.
  28. Helfenstein U, 1991. The use of transfer function models, intervention analysis and related time series methods in epidemiology. Int J Epidemiol 20 : 808–815.
  29. Helfenstein U, 1996. Box-Jenkins modelling in medical research. Stat Methods Med Res 5 : 3–22.
  30. Checkley W, Epstein L, Gilman R, Figueroa D, Gama R, Patz J, Black R, 2000. Effect of El Niño and ambient temperature on hospital admissions for diarrhoeal disease in peruvian children. Lancet 355 : 442–450.
  31. Clancy L, Goodman P, Sinclair H, Dockery D, 2002. Effect of air-pollution control on death rates in Dublin, Ireland: an intervention study. Lancet 360 : 1184–1185.
  32. Dominici F, McDermott A, Zeger S, Samet J, 2002. On the use of generalized additive models in time-series studies of air pollution and health. Am J Epidemiol 156 : 193–203.
  33. Hajat S, Haines A, 2002. Associations of cold temperatures with GP consultations for respiratory and cardiovascular disease amongst the elderly in London. Int J Epidemiol 31 : 825–830.
  34. Pope C, Burnett R, Thun M, Calle E, Krewski D, Ito K, Thurston G, 2002. Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. JAMA 287 : 1132–1141.
  35. Borghi J, Guinness L, Ouedraogo J, Curtis V, 2002. Is hygiene promotion cost-effective? A case study in Burkina Faso. Trop Med Int Health 7 : 960–969.
  36. Abeku T, deVlas S, Borsboom G, Teklehaimanot A, Kebede A, Olana D, van Oortamrssen G, Habbema J, 2002. 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 : 851–857.
  37. Allard R, 1998. Use of time-series analysis in infectious disease surveillance. Bull World Health Organ 76 : 327–333.
  38. Nobre F, Monteiro A, Telles P, Williamson G, 2001. Dynamic linear model and SARIMA: a comparison of their forecasting performance in epidemiology. Stat Med 20 : 3051–3069.
  39. Australian Bureau of Statistics, 2002. 2001 Census Basic (Electronic resource). Canberra: Australian Bureau of Statistics.
  40. Rich G, McKechnie J, McPhan I, Richards B, 1993. Laboratory diagnosis of Ross River virus infection. Comm Dis Intel 17 : 103–107.
  41. Selden S, Cameron A, 1996. Changing epidemiology of Ross River virus disease in South Australia. Med J Aust 165 : 313–317.
  42. Chatfield C, 1975. The Analysis of Time Series: Theory and Practice. London: Chapman & Hall.
  43. Venables W, Ripley B, 1999. Modern Applied Statistics with S-PLUS. New York: Springer.
  44. Box G, Jenkins G, 1970. Time-Series Analysis: Forecasting and Control. San Francisco: Holden-Day.
  45. Tong S, Hu W, 2001. Climate variation and incidence of Ross River virus in Cairns, Australia: a time series analysis. Environ Health Perspect 109 : 1271–1273.
  46. Makridakes S, Wheelwright S, Hyndman R, 1998. Forecasting: Methods and Applications. New York: John Wiley & Sons, Inc.
  47. Statistical Package for the Social Sciences, 1997. SPSS Trends. Upper Saddle River, NJ: Prentice-Hall, Inc.
  48. Lindsay M, Mackenzie J, Condon R, 1993. Ross River virus outbreaks in western Australia: epidemiological aspects and the role of environmental factors. Ewan C, ed. Health in the Greenhouse: The Medical and Environmental Health Effects of Global Climate Change. Canberra: AGPS, 85–100.
  49. Mackenzie J, Lindsay M, Coelen R, Broom A, Hall R, Smith D, 1994. Arboviruses causing human disease in the Australasian zoogeographic region. Arch Virol 136 : 447–467.
  50. Lindsay M, Mackenzie J, 1996. Vector-borne viral diseases and climate change in the Australia region: major concerns and public health response. Curson P, Guest C, Jackson E, eds. Climate Change and Human Health in the Asia-Pacific region. Canberra: Australian Medical Association and Greenpeace International, 47–62.
  51. Bouma M, Sondorp HE, van der Kaay J, 1994. Health and climate change (letter). Lancet 343 : 302.
  52. Russell R, 1995. Arboviruses and their vectors in Australia: an update on the ecology and epidemiology of some mosquito-borne arboviruses. Med Vet Entomol 83 : 141–158.
  53. Stroup D, Thacker S, Herdon J, 1988. Application of multiple time series analysis of spread of communicable disease. Stat Med 7 : 1045–1059.
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  • Received : 07 Jan 2004
  • Accepted : 10 Mar 2004

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