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登革热早期预警系统作为疫情预测工具:一项系统综述。

Dengue Early Warning System as Outbreak Prediction Tool: A Systematic Review.

作者信息

Baharom Mazni, Ahmad Norfazilah, Hod Rozita, Abdul Manaf Mohd Rizal

机构信息

Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, 56000, Malaysia.

出版信息

Risk Manag Healthc Policy. 2022 May 3;15:871-886. doi: 10.2147/RMHP.S361106. eCollection 2022.

Abstract

Early warning system (EWS) for vector-borne diseases is incredibly complex due to numerous factors originating from human, environmental, vector and the disease itself. Dengue EWS aims to collect data that leads to prompt decision-making processes that trigger disease intervention strategies to minimize the impact on a specific population. Dengue EWS may have a similar structural design, functions, and analytical approaches but different performance and ability to predict outbreaks. Hence, this review aims to summarise and discuss the evidence of different EWSs, their performance, and their ability to predict dengue outbreaks. A systematic literature search was performed of four primary databases: Scopus, Web of Science, Ovid MEDLINE, and EBSCOhost. Eligible articles were evaluated using a checklist for assessing the quality of the studies. A total of 17 studies were included in this systematic review. All EWS models demonstrated reasonably good predictive abilities to predict dengue outbreaks. However, the accuracy of their predictions varied greatly depending on the model used and the data quality. The reported sensitivity ranged from 50 to 100%, while specificity was 74 to 94.7%. A range between 70 to 96.3% was reported for prediction model accuracy and 43 to 86% for PPV. Overall, meteorological alarm indicators (temperatures and rainfall) were the most frequently used and displayed the best performing indicator. Other potential alarm indicators are entomology (female mosquito infection rate), epidemiology, population and socioeconomic factors. EWS is an essential tool to support district health managers and national health planners to mitigate or prevent disease outbreaks. This systematic review highlights the benefits of integrating several epidemiological tools focusing on incorporating climatic, environmental, epidemiological and socioeconomic factors to create an early warning system. The early warning system relies heavily on the country surveillance system. The lack of timely and high-quality data is critical for developing an effective EWS.

摘要

由于源自人类、环境、病媒及疾病本身的众多因素,虫媒疾病早期预警系统(EWS)极其复杂。登革热EWS旨在收集数据,以推动迅速的决策过程,触发疾病干预策略,从而将对特定人群的影响降至最低。登革热EWS可能具有相似的结构设计、功能和分析方法,但在预测疫情的表现和能力方面有所不同。因此,本综述旨在总结和讨论不同EWS的证据、它们的表现以及预测登革热疫情的能力。我们对四个主要数据库进行了系统的文献检索:Scopus、科学网、Ovid MEDLINE和EBSCOhost。使用一份评估研究质量的清单对符合条件的文章进行评估。本系统综述共纳入17项研究。所有EWS模型在预测登革热疫情方面均显示出相当不错的预测能力。然而,其预测准确性因所使用的模型和数据质量而有很大差异。报告的敏感性范围为50%至100%,特异性为74%至94.7%。预测模型准确性报告范围为70%至96.3%,阳性预测值为43%至86%。总体而言,气象警报指标(温度和降雨量)是使用最频繁且表现最佳的指标。其他潜在警报指标包括昆虫学(雌蚊感染率)、流行病学、人口和社会经济因素。EWS是支持地区卫生管理人员和国家卫生规划人员减轻或预防疾病爆发的重要工具。本系统综述强调了整合多种流行病学工具的益处,这些工具侧重于纳入气候、环境、流行病学和社会经济因素以创建早期预警系统。早期预警系统严重依赖国家监测系统。缺乏及时和高质量的数据对开发有效的EWS至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21a4/9078425/a0539a848a95/RMHP-15-871-g0001.jpg

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