统计建模用于识别泰国最南端省份两次大规模爆发的奇孔古尼亚高风险地区
Lumpoo Ammatawiyanon1, Phattrawan Tongkumchum1, Don McNeil1
1Department of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Pattani Campus, Pattani, 94000, Thailand.
Scientific reports
|November 4, 2023
概括
奇孔古尼亚热 (CHIKF) 在泰国南部重新出现,显示出10年的流行周期. 统计模型确定了高风险地区,指导了未来针对这一公共卫生威胁的预防策略.
科学领域:
- 流行病学 流行病学
- 公共卫生 公共卫生
- 统计建模 统计建模
背景情况:
- chikungunya热 (CHIKF) 构成了严重的公共卫生威胁,因为它在泰国南部重新出现.
- 识别地理流行病模式和高风险地区对于有效控制至关重要.
研究的目的:
- 确定泰国南部CHIKF的地理流行模式.
- 为了确定CHIKF疫情的高风险地点.
- 分析CHIKF感染的流行周期和特征.
主要方法:
- 利用泰国疾病预防和控制办公室 (2008-2020) 的数据.
- 应用了物流模型来检测CHIKF事件.
- 采用日志线性回归模型来确定数据精制后的发病率.
主要成果:
- 在2008-2010年和2018-2020年期间确定了两个大规模的CHIKF疫情,这表明了10年的周期.
- 青少年和工作年龄组最常感染,而老年人患病率最高.
- 第一次疫情影响了39个分区 (主要是Narathiwat),第二次影响了15个分区 (主要是Pattani).
结论:
- 结合后勤和日志线性模型的两步方法有效地识别CHIKF疫情地区.
- 调查结果为开发CHIKF监测策略和主动管理计划提供了基础.
- 了解流行病模式是减轻 Chikungunya 热病对公共卫生的影响的关键.
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