论文标题
新型冠状病毒（COVID-19）和SARS爆发
Spatiotemporal fluctuation scaling law and metapopulation modeling of the novel coronavirus (COVID-19) and SARS outbreaks
论文作者
论文摘要
我们比较分析了2019年新闻冠状病毒（Covid-19）和SARS爆发的时空波动，以了解其流行病学特征。从方法上讲，我们引入了TPL（Taylor Power Law）来表征其时空异质性/稳定性和Hubbell（2001）统一的生物多样性中性理论（UNTB）[特别是Harris等。 （2015）HDP-MSN模型（分层dirichlet过程多站点中性模型）]近似于冠状病毒感染的群体。首先，TPL分析表明，冠状病毒似乎具有特定的异质性/稳定性缩放参数（TPL-B）的累积感染略超过2，或者对于每日增量感染的1次超过1，这表明它们可能具有混乱，不稳定的爆发。另一个TPL参数（M0）（即感染临界阈值）取决于病毒种类（COVID-19/SARS），时间（疾病阶段），空间（区域）和公共卫生干预措施（例如，Quartines and Mobility Control）。 M0测量感染水平，其中感染是随机的（泊松分布），下面感染遵循均匀分布，如果M0重合或低于Allee效应水平，可能会死亡。发现Covid-19爆发的风险似乎是SARS的两倍，并且感染阈值可能是由于其杀伤力低于SARS，因为较低的死亡率可以促进病原体的存活和传播。其次，MetAcmunity UNTB中立性测试似乎适合于近似冠状病毒感染的量产。具体而言，从中性理论借用的两个参数θ和m可用于通过局部传染与通过迁移感染来评估感染的相对意义，这两种都可能取决于时间，空间，病毒种类，尤其是公共卫生的干预措施。
We comparatively analyzed the spatiotemporal fluctuations of the 2019-novel coronavirus (COVID-19) and SARS outbreaks to understand their epidemiological characteristics. Methodologically, we introduced TPL (Taylor power law) to characterize their spatiotemporal heterogeneity/stability and Hubbell (2001) unified neutral theory of biodiversity (UNTB) [specifically Harris et al. (2015) HDP-MSN model (hierarchical Dirichlet process multi-site neutral model)] to approximate the metapopulation of coronavirus infections. First, TPL analysis suggested that the coronaviruses appear to have a specific heterogeneity/stability scaling parameter (TPL-b) slightly exceeding 2 for cumulative infections or exceeding 1 for daily incremental infections, suggesting their potentially chaotic, unstable outbreaks. Another TPL parameter (M0) (i.e., infection critical threshold) depends on virus kinds (COVID-19/SARS), time (disease-stages), space (regions) and public-health interventions (e.g., quarantines and mobility control). M0 measures the infection level, at which infections are random (Poisson distribution) and below which infections follow uniform distribution and may die off if M0 coincides or below the level of Allee effects. It was found that COVID-19 outbreak seems nearly twice more risky than SARS, and the lower infection threshold may be due to its lower lethality than SARS since lower fatality rates can facilitate the survival and spread of pathogen. Second, metacommunity UNTB neutrality testing seems appropriate for approximating metapopulation of coronavirus infections. Specifically, two parameters θ and M, borrowed from neutral theory, may be used to assess the relative significance of infection through local contagion vs. infection through migration, both of which may depend on time, space, virus kinds, and particularly public-health interventions.
