Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
A superspreading event (SSEV) is an event in which an infectious disease is spread much more than usual, while an unusually contagious organism infected with a disease is known as a superspreader. In the context of a human-borne illness, a superspreader is an individual who is more likely to infect others, compared with a typical infected person. Such superspreaders are of particular concern in epidemiology. Some cases of superspreading conform to the 80/20 rule, where approximately 20% of infected individuals are responsible for 80% of transmissions, although superspreading can still be said to occur when superspreaders account for a higher or lower percentage of transmissions. In epidemics with such superspreader events, the majority of individuals infect relatively few secondary contacts. The degree to which superspreading contributes to an epidemic is often quantified by the t20 metric, which denotes the proportion of infections attributable to the most infectious 20% of the population. SSEVs are shaped by multiple factors including a decline in herd immunity, nosocomial infections, virulence, viral load, misdiagnosis, airflow dynamics, immune suppression, and co-infection with another pathogen. Although loose definitions of superspreader events exist, some effort has been made at defining what qualifies as a superspreader event (SSEV). Lloyd-Smith et al. (2005) define a protocol to identify a superspreader event as follows: estimate the effective reproductive number, R, for the disease and population in question; construct a Poisson distribution with mean R, representing the expected range of Z due to stochasticity without individual variation; define an SSEV as any infected person who infects more than Z(n) others, where Z(n) is the nth percentile of the Poisson(R) distribution. This protocol defines a 99th-percentile SSEV as a case which causes more infections than would occur in 99% of infectious histories in a homogeneous population.
[2]Paolo Prandoni, [3]LCAV, EPFL
In [1]:
import matplotlib.pyplot as plt
import numpy as np
import scipy.signal as sp
import seaborn as sns
sns.set()
In [2]:
plt.rcParams["figure.figsize"] = (14,4)
The basic reproduction number[4]¶
The propagation mechanism of an epidemic such as the one caused by
SARS-CoV-2 virus can be roughly modeled, at least in its inital phase,
as a process in which each infected individ