IntroductionModeling on infectious diseases is significant to facilitate public health policymaking. There are two main mathematical methods that can be used for the simulation of the epidemic and pre

NIAID Data Ecosystem30

Examples of the results obtained by fitting the catalytic models to data.

传染病动力学模型

先天性风疹综合征流行病学

The best-fitting values for the force of infection and (where appropriate) the sensitivity of the antibody assay, and the CRS incidence per 100,000 live births for each catalytic model The values in p

NIAID Data Ecosystem30

Delay (in days) of the peak of the epidemic wave for adults in Germany as a function of the number of imported cases (column A), the number of CCM1 and CCM2 treatments, R0 and the case detection rate (10%, 30% or 50%).

传染病动力学模型

疫情高峰预测

Delay (in days) of the peak of the epidemic wave for adults in Germany as a function of the number of imported cases (column A), the number of CCM1 and CCM2 treatments, R0 and the case detection rate

NIAID Data Ecosystem30

Transition rates for each health state transition as illustrated in Fig 4.

传染病动力学模型

动物流行病传播

λ is the global force of infection as described in Eqs (1) and (3), ρ is the latency rate for exposed animals E, γ is the recovery rate for infectious animals I, σ and μ denote the maternal and active

NIAID Data Ecosystem30

pone.0319417.t011 - SEIQRS model analysis and optimal control with two delays

资源简介：

相关数据集