Cori Anne, Donnelly Christl A, Dorigatti Ilaria, Ferguson Neil M, Fraser Christophe, Garske Tini, Jombart Thibaut, Nedjati-Gilani Gemma, Nouvellet Pierre, Riley Steven, Van Kerkhove Maria D, Mills Harriet L, Blake Isobel M
Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London W2 1PG, UK.
Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7FZ, UK.
Philos Trans R Soc Lond B Biol Sci. 2017 May 26;372(1721). doi: 10.1098/rstb.2016.0371.
Following the detection of an infectious disease outbreak, rapid epidemiological assessment is critical for guiding an effective public health response. To understand the transmission dynamics and potential impact of an outbreak, several types of data are necessary. Here we build on experience gained in the West African Ebola epidemic and prior emerging infectious disease outbreaks to set out a checklist of data needed to: (1) quantify severity and transmissibility; (2) characterize heterogeneities in transmission and their determinants; and (3) assess the effectiveness of different interventions. We differentiate data needs into individual-level data (e.g. a detailed list of reported cases), exposure data (e.g. identifying where/how cases may have been infected) and population-level data (e.g. size/demographics of the population(s) affected and when/where interventions were implemented). A remarkable amount of individual-level and exposure data was collected during the West African Ebola epidemic, which allowed the assessment of (1) and (2). However, gaps in population-level data (particularly around which interventions were applied when and where) posed challenges to the assessment of (3). Here we highlight recurrent data issues, give practical suggestions for addressing these issues and discuss priorities for improvements in data collection in future outbreaks.This article is part of the themed issue 'The 2013-2016 West African Ebola epidemic: data, decision-making and disease control'.
在检测到传染病爆发后,快速的流行病学评估对于指导有效的公共卫生应对至关重要。为了解疫情的传播动态和潜在影响,需要几种类型的数据。在此,我们借鉴在西非埃博拉疫情以及先前的新发传染病爆发中获得的经验,列出一份数据清单,用于:(1)量化严重程度和传播性;(2)描述传播中的异质性及其决定因素;(3)评估不同干预措施的有效性。我们将数据需求分为个体层面的数据(例如报告病例的详细清单)、暴露数据(例如确定病例可能的感染地点/方式)和人群层面的数据(例如受影响人群的规模/人口统计学特征以及干预措施的实施时间/地点)。在西非埃博拉疫情期间收集了大量的个体层面和暴露数据,这使得能够对(1)和(2)进行评估。然而,人群层面数据的缺口(特别是关于何时何地应用了哪些干预措施)给(3)的评估带来了挑战。在此,我们突出反复出现的数据问题,针对解决这些问题给出实用建议,并讨论未来疫情中数据收集改进的优先事项。本文是主题为“2013 - 2016年西非埃博拉疫情:数据、决策与疾病控制”的特刊的一部分。