Weigl Josef
Gesundheitsamt Plön, Schleswig-Holstein, Hamburgerstr. 17/18, 24306 Plön, Deutschland.
Pravent Gesundh. 2020;15(2):97-101. doi: 10.1007/s11553-020-00775-z. Epub 2020 Mar 30.
The pandemic phase 3-mitigation-by the SARS-Coronavirus‑2 is currently taking on speed in Germany. Skewed distributions of key epidemiological parameters of the virus and patient care are a challenge for the control of the outbreak as well as keeping the system functional.
The skewed parameters-pre-patency period, incubation period, duration of viral shedding and time to admission to hospital-are analyzed in regard to their impact and possible countermeasures.
The skewed distributions are exclusively time related variables. They are a handicap for outbreak control as well patient management. Optimization between residual open flanks and the efforts to close them is difficult. The main stakeholders are the local health departments, the diagnostic laboratories, the health care infrastructure and finally the citizens in regard to the burden due to non-pharmaceutical interventions including quarantine and isolation. The duration of quarantine and isolation should urgently be shortened for health care workers (HCW) as well as people in critical infrastructure by ready (re-) testing. Calculated risks have to be taken within a phase 3 of a pandemic to keep a system going.
The skewed distributions are a special challenge for infectious disease control. In the case of ending quarantine and isolation in phase 3 of the pandemic, they should be judged specifically in regard to the client/patient. Cumulative distribution functions are very helpful in this regard.
严重急性呼吸综合征冠状病毒2(SARS-CoV-2)引发的大流行在德国正进入第三阶段——缓解阶段,且形势愈演愈烈。病毒关键流行病学参数以及患者护理的分布不均,给疫情控制和维持系统运转带来了挑战。
分析了偏态参数——暴露前期、潜伏期、病毒脱落持续时间和入院时间——的影响及可能的应对措施。
偏态分布完全是与时间相关的变量。它们对疫情控制和患者管理均造成了阻碍。在剩余开放侧翼与封闭这些侧翼的努力之间进行优化很困难。主要利益相关者包括地方卫生部门、诊断实验室、医疗保健基础设施,最后还有公民,因为他们要承受包括检疫和隔离在内的非药物干预措施带来的负担。应通过即时(重新)检测,紧急缩短医护人员以及关键基础设施领域人员的检疫和隔离时间。在大流行的第三阶段,必须承担计算出的风险以维持系统运转。
偏态分布对传染病控制而言是一项特殊挑战。在大流行第三阶段结束检疫和隔离时,应根据客户/患者的具体情况进行判断。累积分布函数在这方面非常有用。