Weigl Josef
Gesundheitsamt Plön, Schleswig-Holstein, Hamburgerstr. 17/18, 24306 Plön, Deutschland.
Pravent Gesundh. 2020;15(2):89-96. doi: 10.1007/s11553-020-00771-3. Epub 2020 Mar 23.
The phase 3-"mitigation"-of the current pandemic by SARS-CoV‑2 is now imminent also in Germany. Given the high complexity many issues have to be taken into account. Simplification is urgently warranted not to loose focus of the important things to be done.
To look at phase 3 from the endpoint-in this case hospital admission-should facilitate the focus on key variables upstream. Based on a simplified model of approximated and plausible parameters for the overall attack rate (AR), the AR(hospitalization) and the AR(ICU admission), the resources needed are compared with the available resources i.e. number of beds available in general and beds in ICU in particular. The calculations are carried out population-based for Ploen County as well as regionally together with the Kiel metropolitan area.
Since the ARs in the up do date available cohorts are overestimated, considerably lower AR(hospitalization) and AR(ICU) should be expected. An AR(hospitalization) of 10% could not be materialized in Ploen County; one with 5% could. In the regional analysis together with the University Hospital Kiel (UKSH) an AR(hospitalization) of up to 10% is feasible, as also an AR(ICU) of 3%. The kinetics of hospital admissions is, however, dependent from countermeasures in public health as well as admission habits of the family physicians. The available number of beds is determined by beds made available and by the mean duration of hospitalization. The latter depends from the age and underlying conditions of the patients.
System failure has to be averted by clarity in regard to the key parameters and their independent variables. The regional management is crucial and should be coordinated by a so-called bed-coordinator. Close cooperation allover the health care system is needed in alliance with the local health departments.
在德国,新型冠状病毒肺炎(COVID-19)疫情的第三阶段——“缓解”阶段也即将到来。鉴于情况高度复杂,许多问题都必须加以考虑。迫切需要进行简化,以免忽视重要工作的重点。
从终点来看第三阶段——在本案例中为住院治疗——应有助于关注上游的关键变量。基于一个简化模型,该模型包含总体感染率(AR)、住院感染率(AR[住院])和重症监护病房收治感染率(AR[重症监护病房收治])的近似且合理的参数,将所需资源与可用资源进行比较,即一般可用病床数量,尤其是重症监护病房的病床数量。计算以普伦县的人口为基础进行,同时也与基尔都会区一起进行区域层面的计算。
由于最新可用队列中的感染率被高估,预计住院感染率(AR[住院])和重症监护病房收治感染率(AR[重症监护病房收治])会低得多。在普伦县,10%的住院感染率无法实现;5%的可以实现。在与基尔大学医院(UKSH)一起进行的区域分析中,高达10%的住院感染率是可行的,3%的重症监护病房收治感染率也是可行 的。然而,住院治疗的动态情况取决于公共卫生方面的应对措施以及家庭医生的收治习惯。可用病床数量由提供的病床数量和平均住院时间决定。后者取决于患者的年龄和基础疾病。
必须明确关键参数及其自变量,以避免系统故障。区域管理至关重要,应由所谓的病床协调员进行协调。需要与当地卫生部门联合,在整个医疗保健系统内密切合作。