Selected article for: "cumulative number and incubation period"

Author: Mark Hernandez; Lauren E Milechin; Shakti K Davis; Rich DeLaura; Kajal T Claypool; Albert Swiston
Title: The Impact of Host-Based Early Warning on Disease Outbreaks
  • Document date: 2020_3_8
  • ID: 8874c8jp_9
    Snippet: Another important component of the SEIR model is the basic reproduction number â„› 2 which is often included as a basic property of any given pathogen [15] . â„› 2 represents the average number of additional infections caused by each infectious individual, assuming there are no control interventions. In a fixed population represented in the SEIR model, the reproduction number can be calculated from parameters in the model as â„› 2 = 0 . The solut.....
    Document: Another important component of the SEIR model is the basic reproduction number ℛ 2 which is often included as a basic property of any given pathogen [15] . ℛ 2 represents the average number of additional infections caused by each infectious individual, assuming there are no control interventions. In a fixed population represented in the SEIR model, the reproduction number can be calculated from parameters in the model as ℛ 2 = 0 . The solutions of the SEIR model are functions of the number of individuals in each compartment with respect to time, i.e., # , # , # , and # . We solve this numerically by using an ODE solver in MATLAB®. An example output of the full SEIR model is shown in Figure 2a . Here, we begin with a population of N = 1000 people (roughly equivalent to a large battalion), and consider a scenario where 300 individuals are exposed to some pathogen at time, = 0 ( #42 = 700, #42 = 300, #42 = #42 = 0). If we assume a particular infectious pathogen has a contact rate, = 0.75, with an incubation period of two days, = 0.5, and an infectious period of five days, = 0.2 (similar properties to a highly contagious flu virus), the solution to the SEIR model shows that nearly the entire population will contract the disease over the course of a month. Figure 2b focuses on the number of cumulative infections, a metric for assessing the overall size of the outbreak over time. This baseline condition, in which no public health policy is in effect, represents the most severe outcome from an infectious disease outbreak. author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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