Impact of COVID-19 on the Health of the General and More Vulnerable Population and Its Determinants: Health Care and Social Survey–ESSOC, Study Protocol
Metadatos
Mostrar el registro completo del ítemAutor
Sánchez-Cantalejo, Carmen; Rueda, María del Mar; Saez, Marc; Enrique, Iria; Ferri García, Ramón; de La Fuente, Miguel; Villegas, Román; Castro, Luis; Barceló, María Antonia; Daponte-Codina, Antonio; Lorusso, Nicola; Cabrera-León, AndrésEditorial
MDPI
Materia
Public health Health determinants Health inequalities COVID-19 SARS-CoV-2 Vulnerable populations Real-world data Surveys Population registries Machine learning
Fecha
2021-07-31Referencia bibliográfica
Sánchez-Cantalejo C, Rueda MdM, Saez M, Enrique I, Ferri R, Fuente MdL, Villegas R, Castro L, Barceló MA, Daponte-Codina A, Lorusso N, Cabrera-León A. Impact of COVID-19 on the Health of the General and More Vulnerable Population and Its Determinants: Health Care and Social Survey–ESSOC, Study Protocol. International Journal of Environmental Research and Public Health. 2021; 18(15):8120. https://doi.org/10.3390/ijerph18158120
Patrocinador
Andalusian Institute of Statistics and Cartography (IECA); Andalusian School of Public Health (EASP); SUPERA COVID-19 Fund of Santander Universities (SAUN); Conference of Spanish University Rectors (CRUE, Conferencia de Rectores de Universidades Españolas; Spanish National Research Council (CSIC, Consejo Superior de Investigaciones Científicas); COVID-19 Competitive Grant Program from Pfizer Global Medical Grants; IMAG–Maria de Maeztu grant; Ministerio de Ciencia e Innovación, SpainResumen
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.
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