Search results
Results from the WOW.Com Content Network
For example, if a contact network can be approximated with an Erdős–Rényi graph with a Poissonian degree distribution, and the disease spreading parameters are as defined in the example above, such that is the transmission rate per person and the disease has a mean infectious period of , then the basic reproduction number is = [22] [23 ...
In infectious disease modelling, a who acquires infection from whom (WAIFW) matrix is a matrix that describes the rate of transmission of infection between different groups in a population, such as people of different ages. [1]
The serial interval in the epidemiology of communicable (infectious) diseases is the time between successive cases in a chain of transmission. [1]The serial interval is generally estimated from the interval between clinical onsets (if observable), in which case it is the 'clinical onset serial interval'.
Chain of infection; the chain of events that lead to infection. There is a general chain of events that applies to infections, sometimes called the chain of infection [14] or transmission chain. The chain of events involves several steps – which include the infectious agent, reservoir, entering a susceptible host, exit and transmission to new ...
The following outline is provided as an overview of and topical guide to concepts related to infectious diseases in humans.. Infection – transmission, entry/invasion after evading/overcoming defense, establishment, and replication of disease-causing microscopic organisms (pathogens) inside a host organism, and the reaction of host tissues to them and to the toxins they produce.
Cross-species transmission is the most significant cause of disease emergence in humans and other species. [citation needed] Wildlife zoonotic diseases of microbial origin are also the most common group of human emerging diseases, and CST between wildlife and livestock has appreciable economic impacts in agriculture by reducing livestock productivity and imposing export restrictions. [2]
In this scenario, the evolution of the disease predicted by compartmental equations deviates significantly from the observed results. These uncertainties may even cause the epidemic to end earlier than predicted by the compartmental equations. As a special case, one obtains the usual logistic function by assuming =.
For example, the dead body of an individual who died of Ebola remains very infectious for up to a week. [ 4 ] A related concept is the shedding period , which is the time interval during which a host or patient excretes the pathogenic organism through saliva, urine, feces or other bodily fluids.