Matthias Hans Belau, Juliane Boenecke, Jonathan Ströbele, Mirko Himmel, Daria Dretvić, Ummul-Khair Mustafa, Katharina Sophia Kreppel, Elingarami Sauli, Johanna Brinkel, Ulfia Annette Clemen, Thomas Clemen, Wolfgang Streit, Jürgen May, Amena Almes Ahmad, Ralf Reintjes, Heiko Becher
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We aimed to develop and evaluate an integrated risk assessment framework to enhance early detection and risk assessment of potential dengue outbreaks in settings with limited routine surveillance and diagnostic capacity.</p><p><strong>Methods: </strong>Our risk assessment framework utilizes the combination of various methodological components: We first focused on (I) identifying relevant clinical signals based on a case definition for suspected dengue, (II) refining the signal for potential dengue diagnosis using contextual data, and (III) determining the public health risk associated with a verified dengue signal across various hazard, exposure, and contextual indicators. We then evaluated our framework using (i) historical clinical signals with syndromic and laboratory-confirmed disease information derived from WHO's Epidemic Intelligence from Open Sources (EIOS) technology using decision tree analyses, and (ii) historical dengue outbreak data from Tanzania at the regional level from 2019 (6,795 confirmed cases) using negative binomial regression analyses adjusted for month and region. Finally, we evaluated a test signal across all steps of our integrated framework to demonstrate the implementation of our multi-method approach.</p><p><strong>Results: </strong>The result of the suspected case refinement algorithm for clinically defined syndromic cases was consistent with the laboratory-confirmed diagnosis (dengue yes or no). Regression between confirmed dengue fever cases in 2019 as the dependent variable and a site-specific public health risk score as the independent variable showed strong evidence of an increase in dengue fever cases with higher site-specific risk (rate ratio = 2.51 (95% CI = [1.76, 3.58])).</p><p><strong>Conclusions: </strong>The framework can be used to rapidly determine the public health risk of dengue outbreaks, which is useful for planning and prioritizing interventions or for epidemic preparedness. 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引用次数: 0
摘要
背景:登革热是世界上最重要的再次出现但被忽视的传染病之一。我们的目标是制定和评估一个综合风险评估框架,以便在常规监测和诊断能力有限的环境中加强对潜在登革热疫情的早期发现和风险评估。方法:我们的风险评估框架结合了各种方法组成部分:我们首先侧重于(I)根据疑似登革热的病例定义识别相关临床信号,(II)使用背景数据精炼潜在登革热诊断的信号,以及(III)确定与各种危害、暴露和背景指标中经过验证的登革热信号相关的公共卫生风险。然后,我们使用以下方法评估了我们的框架:(i)使用决策树分析从世卫组织开放来源流行病情报(EIOS)技术获得的综合征和实验室确诊疾病信息的历史临床信号,以及(ii)使用对月份和地区进行调整的负二项回归分析,使用2019年坦桑尼亚区域一级的历史登革热暴发数据(6,795例确诊病例)。最后,我们在集成框架的所有步骤中评估了测试信号,以演示我们的多方法方法的实现。结果:临床确定的综合征病例疑似病例细化算法结果与实验室确诊诊断(登革热是或否)一致。将2019年登革热确诊病例作为因变量与特定地点公共卫生风险评分作为自变量进行回归分析,结果显示,具有较高特定地点风险的登革热病例有所增加(比率比= 2.51 (95% CI =[1.76, 3.58]))。结论:该框架可用于快速确定登革热暴发的公共卫生风险,这对规划和确定干预措施的优先次序或流行病防范很有用。它还允许在适应目标疾病和地理环境方面具有灵活性。
Integrated rapid risk assessment for dengue fever in settings with limited diagnostic capacity and uncertain exposure: Development of a methodological framework for Tanzania.
Background: Dengue fever is one of the world's most important re-emerging but neglected infectious diseases. We aimed to develop and evaluate an integrated risk assessment framework to enhance early detection and risk assessment of potential dengue outbreaks in settings with limited routine surveillance and diagnostic capacity.
Methods: Our risk assessment framework utilizes the combination of various methodological components: We first focused on (I) identifying relevant clinical signals based on a case definition for suspected dengue, (II) refining the signal for potential dengue diagnosis using contextual data, and (III) determining the public health risk associated with a verified dengue signal across various hazard, exposure, and contextual indicators. We then evaluated our framework using (i) historical clinical signals with syndromic and laboratory-confirmed disease information derived from WHO's Epidemic Intelligence from Open Sources (EIOS) technology using decision tree analyses, and (ii) historical dengue outbreak data from Tanzania at the regional level from 2019 (6,795 confirmed cases) using negative binomial regression analyses adjusted for month and region. Finally, we evaluated a test signal across all steps of our integrated framework to demonstrate the implementation of our multi-method approach.
Results: The result of the suspected case refinement algorithm for clinically defined syndromic cases was consistent with the laboratory-confirmed diagnosis (dengue yes or no). Regression between confirmed dengue fever cases in 2019 as the dependent variable and a site-specific public health risk score as the independent variable showed strong evidence of an increase in dengue fever cases with higher site-specific risk (rate ratio = 2.51 (95% CI = [1.76, 3.58])).
Conclusions: The framework can be used to rapidly determine the public health risk of dengue outbreaks, which is useful for planning and prioritizing interventions or for epidemic preparedness. It further allows for flexibility in its adaptation to target diseases and geographical contexts.
期刊介绍:
PLOS Neglected Tropical Diseases publishes research devoted to the pathology, epidemiology, prevention, treatment and control of the neglected tropical diseases (NTDs), as well as relevant public policy.
The NTDs are defined as a group of poverty-promoting chronic infectious diseases, which primarily occur in rural areas and poor urban areas of low-income and middle-income countries. Their impact on child health and development, pregnancy, and worker productivity, as well as their stigmatizing features limit economic stability.
All aspects of these diseases are considered, including:
Pathogenesis
Clinical features
Pharmacology and treatment
Diagnosis
Epidemiology
Vector biology
Vaccinology and prevention
Demographic, ecological and social determinants
Public health and policy aspects (including cost-effectiveness analyses).