Andalusian School of Public Health (EASP, Escuela Andaluza de Salud Pública), 18080 Granada, Spain.
Institute of Biosanitary Research, ibs.Granada. (IBS-E-10), 18080 Granada, Spain.
Int J Environ Res Public Health. 2021 Jul 31;18(15):8120. doi: 10.3390/ijerph18158120.
This manuscript describes the rationale and protocol of a real-world data (RWD) study entitled Health Care and Social Survey (ESSOC, Encuesta Sanitaria y Social). The study's objective is to determine the magnitude, characteristics, and evolution of the COVID-19 impact on overall health as well as the socioeconomic, psychosocial, behavioural, occupational, environmental, and clinical determinants of both the general and more vulnerable population. The study integrates observational data collected through a survey using a probabilistic, overlapping panel design, and data from clinical, epidemiological, demographic, and environmental registries. The data will be analysed using advanced statistical, sampling, and machine learning techniques. The study is based on several measurements obtained from three random samples of the Andalusian (Spain) population: general population aged 16 years and over, residents in disadvantaged areas, and people over the age of 55. Given the current characteristics of this pandemic and its future repercussions, this project will generate relevant information on a regular basis, commencing from the beginning of the State of Alarm. It will also establish institutional alliances of great social value, explore and apply powerful and novel methodologies, and produce large, integrated, high-quality and open-access databases. The information described here will be vital for health systems in order to design tailor-made interventions aimed at improving the health care, health, and quality of life of the populations most affected by the COVID-19 pandemic.
本手稿描述了一项真实世界数据(RWD)研究的原理和方案,该研究题为健康护理和社会调查(ESSOC,Encuesta Sanitaria y Social)。该研究的目的是确定 COVID-19 对整体健康以及社会经济、心理社会、行为、职业、环境和临床因素的影响的规模、特征和演变,包括一般人群和更脆弱人群。该研究整合了通过使用概率性、重叠面板设计的调查收集的观测数据,以及来自临床、流行病学、人口统计学和环境登记处的数据。数据将使用先进的统计、抽样和机器学习技术进行分析。该研究基于从西班牙安达卢西亚地区的三个随机人群样本中获得的多项测量:16 岁及以上的一般人群、弱势地区的居民和 55 岁以上的人群。鉴于当前大流行的特点及其未来的影响,该项目将从警报状态开始定期生成相关信息。它还将建立具有重要社会价值的机构联盟,探索和应用强大而新颖的方法,并生成大型、综合、高质量和开放获取的数据库。这里描述的信息对于卫生系统来说至关重要,以便设计针对受 COVID-19 大流行影响最大的人群的量身定制的干预措施,以改善他们的医疗保健、健康和生活质量。