论文标题
为Covid-19的预测和医疗保健计划优化了数学模型
Mathematical model optimized for prediction and health care planning for COVID-19
论文作者
论文摘要
客观的。 COVID-19大流行已威胁要崩溃医院和ICU服务，并影响了非杂化患者的护理计划。目的是开发一种数学模型，旨在优化Covid-19患者与住院和ICU入院需求有关的预测。 设计。前瞻性研究。环境。格拉纳达省（西班牙）。人口。连续的Covid-199患者住院，入院，入院，康复并从2020年3月15日至9月22日死亡。研究变量。感染SARS-COV-2并住院或入院ICU的患者人数进行了COVID-19。 结果。医院报告的数据用于开发一种数学模型，该数学模型反映了与COVID-19的不同利益群体之间人口的流动。该工具使我们能够根据社会健康限制措施分析不同的情况，并预测被感染，住院和入院的人数到2021年5月。 结论。该数学模型能够预测预测Covid-19的演变的预测，以预测患病率，医院和ICU护理需求的峰值，以及可以加强非卵泡患者护理的时期出现。
Objective. The COVID-19 pandemic has threatened to collapse hospital and ICU services, and it has affected the care programs for non-COVID patients. The objective was to develop a mathematical model designed to optimize predictions related to the need for hospitalization and ICU admission by COVID-19 patients. Design. Prospective study. Setting. Province of Granada (Spain). Population. Consecutive COVID-19 patients hospitalized, admitted to ICU, recovered and died from March 15 to September 22, 2020. Study variables. The number of patients infected with SARS-CoV-2 and hospitalized or admitted to ICU for COVID-19. Results. The data reported by hospitals was used to develop a mathematical model that reflects the flow of the population among the different interest groups in relation to COVID-19. This tool has allowed us to analyse different scenarios based on socio-health restriction measures, and to forecast the number of people infected, hospitalized and admitted to the ICU until May 2021. Conclusions. The mathematical model is capable of providing predictions on the evolution of the COVID-19 sufficiently in advance as to anticipate the peaks of prevalence and hospital and ICU care demands, and also the appearance of periods in which the care for non-COVID patients could be intensified.
