Predicting DHF Incidence in Northern Thailand using Time Series Analysis Technique
This study aimed at developing a forecasting model on the number of Dengue Haemorrhagic Fever (DHF) incidence in Northern Thailand using time series analysis. We developed Seasonal Autoregressive Integrated Moving Average (SARIMA) models on the data collected between 2003-2006 and then validated the models using the data collected between January-September 2007. The results showed that the regressive forecast curves were consistent with the pattern of actual values. The most suitable model was the SARIMA(2,0,1)(0,2,0)12 model with a Akaike Information Criterion (AIC) of 12.2931 and a Mean Absolute Percent Error (MAPE) of 8.91713. The SARIMA(2,0,1)(0,2,0)12 model fitting was adequate for the data with the Portmanteau statistic Q20 = 8.98644 ( x20,95= 27.5871, P>0.05). This indicated that there was no significant autocorrelation between residuals at different lag times in the SARIMA(2,0,1)(0,2,0)12 model.
[1] World Health Organization. Dengue haemorrhagic fever: diagnosis,
treatment, prevention and control (2nd edition). Geneva: World Health
Organization; 1997.
[2] S. Anuradha, N. P. Singh, S. N. Rizvi, S. K. Agarwal, R. Gur, and M. D.
Mathur, "The 1996 outbreak of dengue hemorrhagic fever in Delhi,
India," Southeast Asian J Trop Med Public Health, vol. 29, pp. 503-506,
1998.
[3] J. G. Rigau-Perez, D. J. Gubler, A. V. Vorndam, and G. G. Clark,
"Dengue: literature review and case study of travelers from the United
States 1986-1994," J Travel Med, vol. 4, pp. 65-71, 1997.
[4] D. J. Gubler, "The global pandemic of dengue/dengue haemorrhagic
fever: current status and prospects for the future," Ann Acad Med
Singapore, vol. 27, pp. 227-234, 1998.
[5] W. M. Hammon, A. Rudnick, and G. E. Sather, "Viruses associated with
epidemic hemorrhagic fevers of the Philippines and Thailand," Science,
vol. 131, pp. 1102-1103, 1960.
[6] S. B. Halstead, "Mosquito-borne haemorrhagic fevers of south and
southeast Asia," Bull World Health Organ, vol. 35, pp. 3-15, 1966.
[7] K. Ungchusak, and P. Kunasol, "Dengue haemorrhagic fever in
Thailand, 1987," Southeast Asian J Trop Med Public Health, vol. 19(3),
pp. 487-490, 1988.
[8] P. Barbazan, S. Yoksan, and J. P. Gonzalez, "Dengue hemorrhagic fever
epidemiology in Thailand: description and forecasting of epidemics,"
Microbes Infect, vol. 4(7), pp. 699-705, 2002.
[9] Bureau of Epidemiology, "DHF Situation in Thailand," Ministry of
Public Health, Thailand, 2002.
[10] Department of Medical Science, "DHF Situation in Thailand," Ministry
of Public Health, Thailand, 2007.
[11] C. Bowie, and D. Prothero, "Finding cases of seasonal diseases using
time series analysis," Int. J. Epidemiol, vol. 10, pp. 87-92, 1981.
[12] R. Catalano, and S. Serxner, "Time series designs of potential interest to
epidemiologists," Am. J. Epidemiol, vol. 26, pp. 724-731, 1987.
[13] U. Helfenstein, "The use of transfer function models, intervention
analysis and related time series methods in epidemiology," Int. J.
Epidemiol, vol. 20, pp. 808-815, 1991.
[14] J. Schwartz, C. Spix, G. Touloumi, L. Bacharova, T. Barumamdzadeh,
A. Tertre, T. Pickarksi, A. Leon, A. Ponka, G. Rossi, M. Saez, and J.
Schouten, "Methodological issues in studies of air pollution and daily
counts of deaths or hospital admissions," J. Epidemiol. Community
Health, vol. 50(s), pp. s3-s11, 1996.
[15] J. Schwartz, "The distributed lag between air pollution and daily
deaths," Epidemiology, vol. 11, pp. 320-326, 2000.
[16] T. Slini, K. Karatzas, and N. Moussiopoulos, "Statistical analysis of
environmental data as the basis of forecasting: an air quality apllication,"
Sci Total Environ, vol. 288(3), pp. 227-237, 2002.
[17] National Statistical Office, "The population and area data in Thailand,"
Avalable online http://portal.nso.go.th, 2007
[18] Thai Meteorological Department, "The climatic data in Thailand,"
Avalable online : http://www.tmd.go.th, 2007.
[19] S. Makridakis, S. C. Wheelwrigth, and R. J. Hyndman, "Forecasting:
methods and applications," Prentice Hall, 1998.
[20] A. S. Weigend, and N. A. Gershenfeld, "Time series prediction:
forecasting the future and understanding the past," Addison-Wesley,
1996.
[21] A. Guisan, and N. Zimmermann, "Predictive habitat distribution models
in ecology," Ecol. Model, vol. 135, pp. 147-186, 2000.
[22] S. J├ÿrgensen, "25 years of ecological modelling by ecological
modelling," Ecol. Model, vol. 126, pp. 95-99, 2000.
[23] S. J├ÿrgensen, "Ecological modelling: editorial overview 2000-2005,"
Ecol. Model, vol. 188, pp. 137-144, 2005.
[24] R. Woodruff, C. Guest, M. Garner, N. Becker, J. Lindesay, T. Carvan,
and K. Ebi, "Predicting Ross River virus epidemics from regional
weather data," Epidemiology, vol. 13, pp. 384-393, 2002.
[25] H. Teklehaimanot, M. Lipsitch, A. Teklehaimanot, and J. Schwartz,
"Weather-based prediction of Plasmodium falciparum malaria in
epidemic-prone regions of Ethiopia I patterns of lagged weather effects
reflect biological mechanisms," Malar. J, vol. 3, pp. 41. 2004.
[26] H. Teklehaimanot, J. Schwartz, A. Teklehaimanot, and M. Lipsitch,
"Weather-based prediction of Plasmodium falciparum malaria in
epidemic-prone regions of Ethiopia II weather-based prediction systems
perform comparably to early detection systems in identifying times for
interventions," Malar. J, vol. 3, pp. 44. 2004.
[27] K. Linthicum, A. Anyamba, C. Tucker, P. Kelley, M. F. Myers, and C.
Peters, "Climate and satellite indicators to forecast Rift Valley fever
epidemics in Kenya," Science, vol. 285, pp. 347-348, 1999.
[28] T. Abeku, S. deVlas, G. Borsboom, A. Teklehaimanot, A. Kebede, D.
Olana, G. van Oortamrssen, and J. Habbema, "Forecasting malaria
incidence from historical morbidity patterns in epidemic-prone areas of
Ethiopia: a simple seasonal adjustment method performs best," Trop.
Med. Int. Health, vol. 7, pp. 851-857, 2002.
[29] W. Hu, N. Nicholls, M. Lindsay, P. Dale, A. McMichael, J. Mackenzie,
and S. Tong, "Development of a predictive model for Ross River virus
disease in Brisbane," Am. J. Trop. Med. Hyg, vol. 71, pp. 129-137, 2004.
[30] G. Box, and G. Jenkins, "Time-series Analysis: Forecasting and Control
," Holden-Day (Maidenhead McGraw-Hill), 1970.
[31] K. Yurekli, A. Kurunc, and F. Ozturk, "Application of linear stochastic
models to monthly flow data of Kelkit Stream," Ecol. Model, vol. 183,
pp. 67-75, 2005.
[32] U. Helfenstein, "Box-Jenkins modelling of some viral infectious
diseases," Stat. Med, vol. 5, pp. 37-47, 1986.
[33] R. Allard, "Use of time-series analysis in infectious disease
surveillance," Bull. World Health Organ, vol. 76, pp. 327-333, 1998.
[34] W. Wei, "Time Series Analysis," Addison-Wesley Publishing Company
Inc., Now York, 1990.
[1] World Health Organization. Dengue haemorrhagic fever: diagnosis,
treatment, prevention and control (2nd edition). Geneva: World Health
Organization; 1997.
[2] S. Anuradha, N. P. Singh, S. N. Rizvi, S. K. Agarwal, R. Gur, and M. D.
Mathur, "The 1996 outbreak of dengue hemorrhagic fever in Delhi,
India," Southeast Asian J Trop Med Public Health, vol. 29, pp. 503-506,
1998.
[3] J. G. Rigau-Perez, D. J. Gubler, A. V. Vorndam, and G. G. Clark,
"Dengue: literature review and case study of travelers from the United
States 1986-1994," J Travel Med, vol. 4, pp. 65-71, 1997.
[4] D. J. Gubler, "The global pandemic of dengue/dengue haemorrhagic
fever: current status and prospects for the future," Ann Acad Med
Singapore, vol. 27, pp. 227-234, 1998.
[5] W. M. Hammon, A. Rudnick, and G. E. Sather, "Viruses associated with
epidemic hemorrhagic fevers of the Philippines and Thailand," Science,
vol. 131, pp. 1102-1103, 1960.
[6] S. B. Halstead, "Mosquito-borne haemorrhagic fevers of south and
southeast Asia," Bull World Health Organ, vol. 35, pp. 3-15, 1966.
[7] K. Ungchusak, and P. Kunasol, "Dengue haemorrhagic fever in
Thailand, 1987," Southeast Asian J Trop Med Public Health, vol. 19(3),
pp. 487-490, 1988.
[8] P. Barbazan, S. Yoksan, and J. P. Gonzalez, "Dengue hemorrhagic fever
epidemiology in Thailand: description and forecasting of epidemics,"
Microbes Infect, vol. 4(7), pp. 699-705, 2002.
[9] Bureau of Epidemiology, "DHF Situation in Thailand," Ministry of
Public Health, Thailand, 2002.
[10] Department of Medical Science, "DHF Situation in Thailand," Ministry
of Public Health, Thailand, 2007.
[11] C. Bowie, and D. Prothero, "Finding cases of seasonal diseases using
time series analysis," Int. J. Epidemiol, vol. 10, pp. 87-92, 1981.
[12] R. Catalano, and S. Serxner, "Time series designs of potential interest to
epidemiologists," Am. J. Epidemiol, vol. 26, pp. 724-731, 1987.
[13] U. Helfenstein, "The use of transfer function models, intervention
analysis and related time series methods in epidemiology," Int. J.
Epidemiol, vol. 20, pp. 808-815, 1991.
[14] J. Schwartz, C. Spix, G. Touloumi, L. Bacharova, T. Barumamdzadeh,
A. Tertre, T. Pickarksi, A. Leon, A. Ponka, G. Rossi, M. Saez, and J.
Schouten, "Methodological issues in studies of air pollution and daily
counts of deaths or hospital admissions," J. Epidemiol. Community
Health, vol. 50(s), pp. s3-s11, 1996.
[15] J. Schwartz, "The distributed lag between air pollution and daily
deaths," Epidemiology, vol. 11, pp. 320-326, 2000.
[16] T. Slini, K. Karatzas, and N. Moussiopoulos, "Statistical analysis of
environmental data as the basis of forecasting: an air quality apllication,"
Sci Total Environ, vol. 288(3), pp. 227-237, 2002.
[17] National Statistical Office, "The population and area data in Thailand,"
Avalable online http://portal.nso.go.th, 2007
[18] Thai Meteorological Department, "The climatic data in Thailand,"
Avalable online : http://www.tmd.go.th, 2007.
[19] S. Makridakis, S. C. Wheelwrigth, and R. J. Hyndman, "Forecasting:
methods and applications," Prentice Hall, 1998.
[20] A. S. Weigend, and N. A. Gershenfeld, "Time series prediction:
forecasting the future and understanding the past," Addison-Wesley,
1996.
[21] A. Guisan, and N. Zimmermann, "Predictive habitat distribution models
in ecology," Ecol. Model, vol. 135, pp. 147-186, 2000.
[22] S. J├ÿrgensen, "25 years of ecological modelling by ecological
modelling," Ecol. Model, vol. 126, pp. 95-99, 2000.
[23] S. J├ÿrgensen, "Ecological modelling: editorial overview 2000-2005,"
Ecol. Model, vol. 188, pp. 137-144, 2005.
[24] R. Woodruff, C. Guest, M. Garner, N. Becker, J. Lindesay, T. Carvan,
and K. Ebi, "Predicting Ross River virus epidemics from regional
weather data," Epidemiology, vol. 13, pp. 384-393, 2002.
[25] H. Teklehaimanot, M. Lipsitch, A. Teklehaimanot, and J. Schwartz,
"Weather-based prediction of Plasmodium falciparum malaria in
epidemic-prone regions of Ethiopia I patterns of lagged weather effects
reflect biological mechanisms," Malar. J, vol. 3, pp. 41. 2004.
[26] H. Teklehaimanot, J. Schwartz, A. Teklehaimanot, and M. Lipsitch,
"Weather-based prediction of Plasmodium falciparum malaria in
epidemic-prone regions of Ethiopia II weather-based prediction systems
perform comparably to early detection systems in identifying times for
interventions," Malar. J, vol. 3, pp. 44. 2004.
[27] K. Linthicum, A. Anyamba, C. Tucker, P. Kelley, M. F. Myers, and C.
Peters, "Climate and satellite indicators to forecast Rift Valley fever
epidemics in Kenya," Science, vol. 285, pp. 347-348, 1999.
[28] T. Abeku, S. deVlas, G. Borsboom, A. Teklehaimanot, A. Kebede, D.
Olana, G. van Oortamrssen, and J. Habbema, "Forecasting malaria
incidence from historical morbidity patterns in epidemic-prone areas of
Ethiopia: a simple seasonal adjustment method performs best," Trop.
Med. Int. Health, vol. 7, pp. 851-857, 2002.
[29] W. Hu, N. Nicholls, M. Lindsay, P. Dale, A. McMichael, J. Mackenzie,
and S. Tong, "Development of a predictive model for Ross River virus
disease in Brisbane," Am. J. Trop. Med. Hyg, vol. 71, pp. 129-137, 2004.
[30] G. Box, and G. Jenkins, "Time-series Analysis: Forecasting and Control
," Holden-Day (Maidenhead McGraw-Hill), 1970.
[31] K. Yurekli, A. Kurunc, and F. Ozturk, "Application of linear stochastic
models to monthly flow data of Kelkit Stream," Ecol. Model, vol. 183,
pp. 67-75, 2005.
[32] U. Helfenstein, "Box-Jenkins modelling of some viral infectious
diseases," Stat. Med, vol. 5, pp. 37-47, 1986.
[33] R. Allard, "Use of time-series analysis in infectious disease
surveillance," Bull. World Health Organ, vol. 76, pp. 327-333, 1998.
[34] W. Wei, "Time Series Analysis," Addison-Wesley Publishing Company
Inc., Now York, 1990.
@article{"International Journal of Medical, Medicine and Health Sciences:50814", author = "S. Wongkoon and M. Pollar and M. Jaroensutasinee and K. Jaroensutasinee", title = "Predicting DHF Incidence in Northern Thailand using Time Series Analysis Technique", abstract = "This study aimed at developing a forecasting model on the number of Dengue Haemorrhagic Fever (DHF) incidence in Northern Thailand using time series analysis. We developed Seasonal Autoregressive Integrated Moving Average (SARIMA) models on the data collected between 2003-2006 and then validated the models using the data collected between January-September 2007. The results showed that the regressive forecast curves were consistent with the pattern of actual values. The most suitable model was the SARIMA(2,0,1)(0,2,0)12 model with a Akaike Information Criterion (AIC) of 12.2931 and a Mean Absolute Percent Error (MAPE) of 8.91713. The SARIMA(2,0,1)(0,2,0)12 model fitting was adequate for the data with the Portmanteau statistic Q20 = 8.98644 ( x20,95= 27.5871, P>0.05). This indicated that there was no significant autocorrelation between residuals at different lag times in the SARIMA(2,0,1)(0,2,0)12 model.
", keywords = "Dengue, SARIMA, Time Series Analysis, Northern Thailand.", volume = "1", number = "8", pages = "472-5", }
