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.

Loading

Article metrics loading...

The graphs shown below represent data from March 2017
/content/journals/10.4269/ajtmh.2004.71.129
2004-08-01
2018-12-16
Loading full text...

Full text loading...

/deliver/fulltext/14761645/71/2/0700129.html?itemId=/content/journals/10.4269/ajtmh.2004.71.129&mimeType=html&fmt=ahah

References

  1. Reiter P, 2001. Climate change and mosquito-borne disease. Environ Health Perspect 109 : 141–161. [Google Scholar]
  2. Ansari M, Shope R, 1994. Epidemiology of arboviral infections. Public Health Rev 22 : 1–26. [Google Scholar]
  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. [Google Scholar]
  4. Doherty R, Carley J, Best J, 1972. Isolation of Ross River virus in from man. Med J Aust 1 : 1083–1084. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  9. Mudge P, Aaskov J, 1983. Epidemic polyarthritis in Australia, 1980–1981. Med J Aust 17 : 269–273. [Google Scholar]
  10. Fraser J, 1986. Epidemic polyarthritis and Ross River virus disease. Clin Rheum Dis 12 : 369–388. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  17. Tong S, Bi P, Donald K, McMichael A, 2002. Climate variability and Ross River virus transmission. J Epidemiol Community Health 56 : 617–621. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  24. Maelzer D, Hales S, Weinstein P, Zalucki M, Woodward A, 1999. El Niño and arboviral disease prediction. Environ Health Perspect 107 : 817–818. [Google Scholar]
  25. Bowie C, Prothero D, 1981. Finding causes of seasonal diseases using time series analysis. Int J Epidemiol 10 : 87–92. [Google Scholar]
  26. Catalano R, Serxner S, 1987. Time series designs of potential interest to epidemiologists. Am J Epidemiol 26 : 724–731. [Google Scholar]
  27. Helfenstein U, 1986. Box-Jenkins modelling of some viral infectious diseases. Stat Med 5 : 37–47. [Google Scholar]
  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. [Google Scholar]
  29. Helfenstein U, 1996. Box-Jenkins modelling in medical research. Stat Methods Med Res 5 : 3–22. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  37. Allard R, 1998. Use of time-series analysis in infectious disease surveillance. Bull World Health Organ 76 : 327–333. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  41. Selden S, Cameron A, 1996. Changing epidemiology of Ross River virus disease in South Australia. Med J Aust 165 : 313–317. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  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. [Google Scholar]
  53. Stroup D, Thacker S, Herdon J, 1988. Application of multiple time series analysis of spread of communicable disease. Stat Med 7 : 1045–1059. [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.4269/ajtmh.2004.71.129
Loading
/content/journals/10.4269/ajtmh.2004.71.129
Loading

Data & Media loading...

  • Received : 07 Jan 2004
  • Accepted : 10 Mar 2004

Most Cited This Month

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error