Basic reproduction number

is the average number of people infected from one other person. For example, Ebola has an of two, so on average, a person who has Ebola will pass it on to two other people.

In epidemiology, the basic reproduction number, or basic reproductive number (sometimes called basic reproduction ratio or basic reproductive rate), denoted (pronounced R nought or R zero),[1] of an infection is the expected number of cases directly generated by one case in a population where all individuals are susceptible to infection.[2] The definition assumes that no other individuals are infected or immunized (naturally or through vaccination). Some definitions, such as that of the Australian Department of Health, add the absence of "any deliberate intervention in disease transmission".[3] The basic reproduction number is not necessarily the same as the effective reproduction number (usually written [t for time], sometimes ),[4] which is the number of cases generated in the current state of a population, which does not have to be the uninfected state. is a dimensionless number (persons infected per person infecting) and not a time rate, which would have units of time−1,[5] or units of time like doubling time.[6]

is not a biological constant for a pathogen as it is also affected by other factors such as environmental conditions and the behaviour of the infected population. values are usually estimated from mathematical models, and the estimated values are dependent on the model used and values of other parameters. Thus values given in the literature only make sense in the given context and it is not recommended to compare values based on different models.[7] does not by itself give an estimate of how fast an infection spreads in the population.

The most important uses of are determining if an emerging infectious disease can spread in a population and determining what proportion of the population should be immunized through vaccination to eradicate a disease. In commonly used infection models, when the infection will be able to start spreading in a population, but not if . Generally, the larger the value of , the harder it is to control the epidemic. For simple models, the proportion of the population that needs to be effectively immunized (meaning not susceptible to infection) to prevent sustained spread of the infection has to be larger than .[8] This is the so-called Herd immunity threshold or herd immunity level. Here, herd immunity means that the disease cannot spread in the population because each infected person, on average, can only transmit the infection to less than one other contact.[9] Conversely, the proportion of the population that remains susceptible to infection in the endemic equilibrium is . However, this threshold is based on simple models that assume a fully mixed population with no structured relations between the individuals. For example, if there is some correlation between people's immunization (e.g., vaccination) status, then the formula may underestimate the herd immunity threshold.[9]

Graph of herd immunity threshold vs basic reproduction number with selected diseases

The basic reproduction number is affected by several factors, including the duration of infectivity of affected people, the contagiousness of the microorganism, and the number of susceptible people in the population that the infected people contact.[10]

  1. ^ Milligan GN, Barrett AD (2015). Vaccinology : an essential guide. Chichester, West Sussex: Wiley Blackwell. p. 310. ISBN 978-1-118-63652-7. OCLC 881386962.
  2. ^ Cite error: The named reference Fraser was invoked but never defined (see the help page).
  3. ^ Becker NG, Glass K, Barnes B, Caley P, Philp D, McCaw JM, et al. (April 2006). "The reproduction number". Using Mathematical Models to Assess Responses to an Outbreak of an Emerged Viral Respiratory Disease. National Centre for Epidemiology and Population Health. ISBN 1-74186-357-0. Archived from the original on February 1, 2020. Retrieved February 1, 2020.
  4. ^ Adam D (July 2020). "A guide to R - the pandemic's misunderstood metric". Nature. 583 (7816): 346–348. Bibcode:2020Natur.583..346A. doi:10.1038/d41586-020-02009-w. PMID 32620883.
  5. ^ Jones J. "Notes On R0" (PDF). Stanford University.
  6. ^ Siegel E. "Why 'Exponential Growth' Is So Scary For The COVID-19 Coronavirus". Forbes. Retrieved March 19, 2020.
  7. ^ Delamater PL, Street EJ, Leslie TF, Yang YT, Jacobsen KH (January 2019). "Complexity of the Basic Reproduction Number (R0)". Emerging Infectious Diseases. 25 (1): 1–4. doi:10.3201/eid2501.171901. PMC 6302597. PMID 30560777.
  8. ^ Fine, P.; Eames, K.; Heymann, D. L. (April 1, 2011). "'Herd Immunity': A Rough Guide". Clinical Infectious Diseases. 52 (7): 911–916. doi:10.1093/cid/cir007. PMID 21427399.
  9. ^ a b Hiraoka, Takayuki; K. Rizi, Abbas; Kivelä, Mikko; Saramäki, Jari (May 12, 2022). "Herd immunity and epidemic size in networks with vaccination homophily". Physical Review E. 105 (5): L052301. arXiv:2112.07538. Bibcode:2022PhRvE.105e2301H. doi:10.1103/PhysRevE.105.L052301. PMID 35706197. S2CID 245130970.
  10. ^ Cite error: The named reference Vegvari was invoked but never defined (see the help page).

© MMXXIII Rich X Search. We shall prevail. All rights reserved. Rich X Search