Schmidt Felicitas, Hauptmann Christian, Kohlenz Walter, Gasser Philipp, Hartmann Sascha, Daunderer Michael, Weiler Thomas, Nowak Lorenz
Asklepios Lung Clinic Munich-Gauting, Gauting, Germany.
Führungsgruppe Katastrophenschutz im Rettungsdienstbereich Fürstenfeldbruck, Fürstenfeldbruck, Germany.
Front Health Serv. 2021 Nov 16;1:718668. doi: 10.3389/frhs.2021.718668. eCollection 2021.
The current pandemic requires hospitals to ensure care not only for the growing number of COVID-19 patients but also regular patients. Hospital resources must be allocated accordingly. To provide hospitals with a planning model to optimally allocate resources to intensive care units given a certain incidence of COVID-19 cases. The analysis included 334 cases from four adjacent counties south-west of Munich. From length of stay and type of ward [general ward (NOR), intensive care unit (ICU)] probabilities of case numbers within a hospital at a certain time point were derived. The epidemiological situation was simulated by the effective reproduction number , the infection rates in mid-August 2020 in the counties, and the German hospitalization rate. Simulation results are compared with real data from 2nd and 3rd wave (September 2020-May 2021). With = 2, a hospitalization rate of 17%, mitigation measures implemented on day 9 (i.e., 7-day incidence surpassing 50/100,000), the peak occupancy was reached on day 22 (155.1 beds) for the normal ward and on day 25 (44.9 beds) for the intensive care unit. A higher led to higher occupancy rates. Simulated number of infections and intensive care unit occupancy was concordant in validation with real data obtained from the 2nd and 3rd waves in Germany. Hospitals could expect a peak occupancy of normal ward and intensive care unit within ~5-11 days after infections reached their peak and critical resources could be allocated accordingly. This delay (in particular for the peak of intensive care unit occupancy) might give options for timely preparation of additional intensive care unit resources.
当前的疫情大流行要求医院不仅要确保为越来越多的新冠肺炎患者提供治疗，还要照顾普通患者。医院资源必须相应地进行分配。为了给医院提供一个规划模型，以便在新冠肺炎病例有一定发病率的情况下，将资源最优地分配到重症监护病房。该分析纳入了慕尼黑西南部四个相邻县的334例病例。根据住院时间和病房类型（普通病房（NOR）、重症监护病房（ICU）），得出了医院在某一时刻病例数的概率。通过有效繁殖数、2020年8月中旬各县的感染率以及德国的住院率来模拟疫情形势。将模拟结果与2020年9月至与2021年5月第二波和第三波疫情的实际数据进行比较。当有效繁殖数为2、住院率为17%、在第9天实施缓解措施（即7天发病率超过50/10万）时，普通病房在第22天达到最高占用率（155.1张床位），重症监护病房在第25天达到最高占用率（44.9张床位）。更高的有效繁殖数导致更高的占用率。模拟的感染人数和重症监护病房占用率与从德国第二波和第三波疫情中获得的实际数据验证结果一致。医院可以预计，在感染达到峰值后的约5 - 11天内，普通病房和重症监护病房将达到最高占用率，从而可以相应地分配关键资源。这种延迟（特别是重症监护病房占用率的峰值）可能为及时准备额外的重症监护病房资源提供选择。
