Barts NHS Trust, London, United Kingdom.
Health Data Research UK, University College London, London, United Kingdom.
PLoS One. 2020 Aug 13;15(8):e0237298. doi: 10.1371/journal.pone.0237298. eCollection 2020.
We aimed to model the impact of coronavirus (COVID-19) on the clinical academic response in England, and to provide recommendations for COVID-related research.
A stochastic model to determine clinical academic capacity in England, incorporating the following key factors which affect the ability to conduct research in the COVID-19 climate: (i) infection growth rate and population infection rate (from UK COVID-19 statistics and WHO); (ii) strain on the healthcare system (from published model); and (iii) availability of clinical academic staff with appropriate skillsets affected by frontline clinical activity and sickness (from UK statistics).
Clinical academics in primary and secondary care in England.
Equivalent of 3200 full-time clinical academics in England.
Four policy approaches to COVID-19 with differing population infection rates: "Italy model" (6%), "mitigation" (10%), "relaxed mitigation" (40%) and "do-nothing" (80%) scenarios. Low and high strain on the health system (no clinical academics able to do research at 10% and 5% infection rate, respectively.
Number of full-time clinical academics available to conduct clinical research during the pandemic in England.
In the "Italy model", "mitigation", "relaxed mitigation" and "do-nothing" scenarios, from 5 March 2020 the duration (days) and peak infection rates (%) are 95(2.4%), 115(2.5%), 240(5.3%) and 240(16.7%) respectively. Near complete attrition of academia (87% reduction, <400 clinical academics) occurs 35 days after pandemic start for 11, 34, 62, 76 days respectively-with no clinical academics at all for 37 days in the "do-nothing" scenario. Restoration of normal academic workforce (80% of normal capacity) takes 11, 12, 30 and 26 weeks respectively.
Pandemic COVID-19 crushes the science needed at system level. National policies mitigate, but the academic community needs to adapt. We highlight six key strategies: radical prioritisation (eg 3-4 research ideas per institution), deep resourcing, non-standard leadership (repurposing of key non-frontline teams), rationalisation (profoundly simple approaches), careful site selection (eg protected sites with large academic backup) and complete suspension of academic competition with collaborative approaches.
本研究旨在构建模型以评估冠状病毒(COVID-19)对英国临床学术响应的影响,并为 COVID-19 相关研究提供建议。
本研究构建了一个用于确定英国临床学术能力的随机模型,其中纳入了以下几个关键因素,这些因素会影响临床学术人员在 COVID-19 大流行期间进行研究的能力:(i)感染增长率和人群感染率(来源于英国 COVID-19 统计数据和世界卫生组织);(ii)医疗系统压力(来源于已发表的模型);(iii)具备适当技能的临床学术人员的可用性受到临床一线活动和疾病的影响(来源于英国统计数据)。
英国初级和二级保健机构中的临床学术人员。
相当于英国的 3200 名全职临床学术人员。
COVID-19 的四种政策方法具有不同的人群感染率:“意大利模式”(6%)、“缓解”(10%)、“放松缓解”(40%)和“不作为”(80%)情景。医疗系统压力低和高(分别在感染率为 10%和 5%时,没有临床学术人员能够进行研究)。
在英国大流行期间能够进行临床研究的全职临床学术人员数量。
在“意大利模式”、“缓解”、“放松缓解”和“不作为”情景下,自 2020 年 3 月 5 日起,持续时间(天)和峰值感染率(%)分别为 95(2.4%)、115(2.5%)、240(5.3%)和 240(16.7%)。在大流行开始后第 35 天,学术界几乎完全枯竭(减少 87%,<400 名临床学术人员),在“不作为”情景下,有 37 天完全没有临床学术人员。在 11、12、30 和 26 周后,临床学术人员分别恢复到正常学术劳动力的 80%、80%、80%和 80%。
大流行 COVID-19 破坏了系统层面所需的科学。国家政策可以缓解,但学术社区需要适应。我们强调了六个关键策略:激进的优先级排序(例如,每个机构 3-4 个研究思路)、深度资源配置、非标准领导力(重新利用关键非一线团队)、合理化(采用非常简单的方法)、仔细选择站点(例如,有大型学术后备力量的受保护站点)和采用协作方法完全暂停学术竞争。