PDF(Pubmed)
Abstract：
BACKGROUND: Dengue infection ranges from asymptomatic to severe and life-threatening, with no specific treatment available. Vector control is crucial for interrupting its transmission cycle. Accurate estimation of outbreak timing and location is essential for efficient resource allocation. Timely and reliable notification systems are necessary to monitor dengue incidence, including spatial and temporal distributions, to detect outbreaks promptly and implement effective control measures.
METHODS: We proposed an integrated two-step methodology for real-time spatiotemporal cluster detection, accounting for reporting delays. In the first step, we employed space-time nowcasting modeling to compensate for lags in the reporting system. Subsequently, anomaly detection methods were applied to assess adverse risks. To illustrate the effectiveness of these detection methods, we conducted a case study using weekly dengue surveillance data from Thailand.
RESULTS: The developed methodology demonstrated robust surveillance effectiveness. By combining space-time nowcasting modeling and anomaly detection, we achieved enhanced detection capabilities, accounting for reporting delays and identifying clusters of elevated risk in real-time. The case study in Thailand showcased the practical application of our methodology, enabling timely initiation of disease control activities.
CONCLUSIONS: Our integrated two-step methodology provides a valuable approach for real-time spatiotemporal cluster detection in dengue surveillance. By addressing reporting delays and incorporating anomaly detection, it complements existing surveillance systems and forecasting efforts. Implementing this methodology can facilitate the timely initiation of disease control activities, contributing to more effective prevention and control strategies for dengue in Thailand and potentially other regions facing similar challenges.
METHODS: We proposed an integrated two-step methodology for real-time spatiotemporal cluster detection, accounting for reporting delays. In the first step, we employed space-time nowcasting modeling to compensate for lags in the reporting system. Subsequently, anomaly detection methods were applied to assess adverse risks. To illustrate the effectiveness of these detection methods, we conducted a case study using weekly dengue surveillance data from Thailand.
RESULTS: The developed methodology demonstrated robust surveillance effectiveness. By combining space-time nowcasting modeling and anomaly detection, we achieved enhanced detection capabilities, accounting for reporting delays and identifying clusters of elevated risk in real-time. The case study in Thailand showcased the practical application of our methodology, enabling timely initiation of disease control activities.
CONCLUSIONS: Our integrated two-step methodology provides a valuable approach for real-time spatiotemporal cluster detection in dengue surveillance. By addressing reporting delays and incorporating anomaly detection, it complements existing surveillance systems and forecasting efforts. Implementing this methodology can facilitate the timely initiation of disease control activities, contributing to more effective prevention and control strategies for dengue in Thailand and potentially other regions facing similar challenges.
摘要：
背景：登革热感染范围从无症状到严重和危及生命，没有具体的治疗方法。矢量控制对于中断其传输周期至关重要。准确估计爆发时间和位置对于有效的资源分配至关重要。及时可靠的通报系统是监测登革热发病率所必需的,包括空间和时间分布，及时发现疫情，实施有效的控制措施。
方法：我们提出了一种用于实时时空簇检测的集成两步方法，考虑报告延误。第一步,我们采用了时空临近预报模型来补偿报告系统中的滞后。随后，异常检测方法用于评估不良风险。为了说明这些检测方法的有效性，我们使用泰国的每周登革热监测数据进行了案例研究.
结果：所开发的方法证明了可靠的监测有效性。通过结合时空临近预报建模和异常检测，我们实现了增强的检测能力，考虑报告延迟并实时识别高风险集群。泰国的案例研究展示了我们方法的实际应用，能够及时启动疾病控制活动。
结论：我们的综合两步方法为登革热监测中的实时时空簇检测提供了一种有价值的方法。通过解决报告延迟和结合异常检测，它补充了现有的监测系统和预测工作。实施这种方法可以促进疾病控制活动的及时启动，为泰国和其他可能面临类似挑战的地区制定更有效的登革热预防和控制策略。
方法：我们提出了一种用于实时时空簇检测的集成两步方法，考虑报告延误。第一步,我们采用了时空临近预报模型来补偿报告系统中的滞后。随后，异常检测方法用于评估不良风险。为了说明这些检测方法的有效性，我们使用泰国的每周登革热监测数据进行了案例研究.
结果：所开发的方法证明了可靠的监测有效性。通过结合时空临近预报建模和异常检测，我们实现了增强的检测能力，考虑报告延迟并实时识别高风险集群。泰国的案例研究展示了我们方法的实际应用，能够及时启动疾病控制活动。
结论：我们的综合两步方法为登革热监测中的实时时空簇检测提供了一种有价值的方法。通过解决报告延迟和结合异常检测，它补充了现有的监测系统和预测工作。实施这种方法可以促进疾病控制活动的及时启动，为泰国和其他可能面临类似挑战的地区制定更有效的登革热预防和控制策略。
