Statistical Modeling for Incidence Rate of Victims from Conflict Situation in Southernmost Provinces of Thailand

Abstract

The 19 years prolonged period of conflict situation from 2004 until the current year (2022) in the southern provinces of Thailand including Pattani Yala Narathiwat and parts of Songkhla has been affecting on the daily life of people in the area. The cumulative number of incidents, deaths, injuries, widows, and orphans is going to be large. Therefore, this study aimed to investigate the statistical modelling of the injury-date rate and to visualize the injury-date rate in the Deep South provinces of Thailand. The secondary data between 2004 and 2020 were obtained from the Deep South Coordination Center (DSCC), Prince of Songkla University, Pattani Campus. The study areas were sub-districts in Pattani, Yala, Narathiwat, and four districts of Songkhla. The total number of individual observations was 26,938. After managing the individual data into counted data, there were 8,975 observations. The outcome of this study was the injury-death rates per 100,000 population and determinants were year, sub-district, gender, and age. In descriptive analysis, frequency, percentage, minimum, maximum, mean, median and standard deviation were used. In univariate analysis, the ANOVA test was used to test the association between outcome and each determinant. A log-linear regression model was used to investigate the adjusted mean of the injury-death rate by its factors. The results found that the injury-death rate declined sharply from 2007 to 2020 by 48%. The overall mean of injury-death rate was 64.45 cases per 100,000 population. The young males were more vulnerable than the females. Pattani was a riskier area than other provinces. Half of the sub-districts (53.91%) in Pattani had an injury-death rate above the overall mean. More than 60% of the sub-districts, that showed the injury-death rate higher the overall mean, occurred in rural areas of all provinces, except Songkhla, which had no red area. The information from the current study would be useful to the government or other sections for preparing and planning the readiness of health care, compensation, and economic development in the southernmost provinces of Thailand.