Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, 345 Galvin Hall, Notre Dame, IN 46556, USA.
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD 21205, USA.
Sci Data. 2018 Apr 24;5:180073. doi: 10.1038/sdata.2018.73.
Despite a long history of mosquito-borne virus epidemics in the Americas, the impact of the Zika virus (ZIKV) epidemic of 2015-2016 was unexpected. The need for scientifically informed decision-making is driving research to understand the emergence and spread of ZIKV. To support that research, we assembled a data set of key covariates for modeling ZIKV transmission dynamics in Colombia, where ZIKV transmission was widespread and the government made incidence data publically available. On a weekly basis between January 1, 2014 and October 1, 2016 at three administrative levels, we collated spatiotemporal Zika incidence data, nine environmental variables, and demographic data into a single downloadable database. These new datasets and those we identified, processed, and assembled at comparable spatial and temporal resolutions will save future researchers considerable time and effort in performing these data processing steps, enabling them to focus instead on extracting epidemiological insights from this important data set. Similar approaches could prove useful for filling data gaps to enable epidemiological analyses of future disease emergence events.
尽管美洲地区长期存在蚊媒病毒流行,但 2015-2016 年寨卡病毒(ZIKV)疫情的影响仍出人意料。科学决策的需求推动了对 ZIKV 出现和传播的研究。为了支持这项研究,我们收集了一组哥伦比亚寨卡病毒传播动力学建模的关键协变量数据集,该国的寨卡病毒传播广泛,政府公开提供了发病数据。在 2014 年 1 月 1 日至 2016 年 10 月 1 日期间,每周在三个行政级别上,我们整理了时空寨卡病毒发病数据、九个环境变量和人口统计数据,并将其整合到一个可下载的数据库中。这些新数据集和我们以可比的时空分辨率识别、处理和整合的数据集将为未来的研究人员节省大量执行这些数据处理步骤的时间和精力,使他们能够专注于从这个重要数据集中提取流行病学见解。类似的方法可能有助于填补数据空白,从而能够对未来疾病的出现事件进行流行病学分析。