Forecasting of Dengue Haemorrhagic Fever by Descriptive Statistics and Time-Series Analysis and Risk Assessment in Phetchabun Province, 2015 - Kanyaprasit, Kamol (Journal of Health Science of Thailand, 2017)
Dengue haemorrhagic fever (DHF) is an importance infectious diseases in Thailand. Dengue control policy includes early prevention, diagnosis and prompt treatment. Using the epidemiologic data with descriptive statistics to forecast and predict DHF is a suitable method to monitor and control the disease. The objective of this study was to forcast DHF situation in Petchabun province for 2019 by using incidence data collected between 2010 and 2015. The statistical methods utilized to analyze the data was the time series analysis: triple exponential smoothing or Winter’s model in Statistical Program, with three smoothing constants: alpha (level)=0.96, gamma (trend)=0.34, and delta (seasonal)=1, as well as the risk assessment method. Detailed descriptive data for 2015 were also presented. It was found that there were 286 DHF patients reported in 2015 (with incidence rate of 28.72 per 100,000 population) with no mortality. The most common age group was between 10-14 years old (127.97 per 100,000 population). The overall trend was below 5-year-average median line. In July 2015, there was an increase in the incidence but still lower that the 5 year average. In 2010 - 2015, there continued to have DHF cases reported in all districts of the province. The incidence was fluctuated with alternately increasing trend in one year and declining in two years; and the peaks were observed in rainy season. In the forecasting for DHF incidence in 2016 with the assumption of unchanged geographic environment, it was predicted that up to mid-2016 there should be 842 cases with the peak in June (estimated 447 cases). There were 5 high risk disctricts which included Lom Sak, Mueang Phetchabun, Wichian Buri, Si Thep and Nong Phai; and 6 medium risk districts: Chon Daen, Lom Kao, Bueng Sam Phan, Nam Nao, Wang Pong and Khao Kho. The author recommended that situation forcasting should be an appropriate measure to improve preparedness for DHF prevention and control; and capacity building on this matter should be strongly promoted by Ministry of Public Health.