Mark and recapture

Mark and recapture is a method commonly used in ecology to estimate an animal population's size where it is impractical to count every individual.[1] A portion of the population is captured, marked, and released. Later, another portion will be captured and the number of marked individuals within the sample is counted. Since the number of marked individuals within the second sample should be proportional to the number of marked individuals in the whole population, an estimate of the total population size can be obtained by dividing the number of marked individuals by the proportion of marked individuals in the second sample. The method assumes, rightly or wrongly, that the probability of capture is the same for all individuals.[2] Other names for this method, or closely related methods, include capture-recapture, capture-mark-recapture, mark-recapture, sight-resight, mark-release-recapture, multiple systems estimation, band recovery, the Petersen method,[3] and the Lincoln method.

Another major application for these methods is in epidemiology,[4] where they are used to estimate the completeness of ascertainment of disease registers. Typical applications include estimating the number of people needing particular services (e.g. services for children with learning disabilities, services for medically frail elderly living in the community), or with particular conditions (e.g. illegal drug addicts, people infected with HIV, etc.).[5]

  1. ^ "Mark-Recapture".
  2. ^ Cite error: The named reference Southwood was invoked but never defined (see the help page).
  3. ^ Krebs, Charles J. (2009). Ecology (6th ed.). Pearson Benjamin Cummings. p. 119. ISBN 978-0-321-50743-3.
  4. ^ Chao, A.; Tsay, P. K.; Lin, S. H.; Shau, W. Y.; Chao, D. Y. (2001). "The applications of capture-recapture models to epidemiological data". Statistics in Medicine. 20 (20): 3123–3157. doi:10.1002/sim.996. PMID 11590637. S2CID 78437.
  5. ^ Allen; et al. (2019). "Estimating the Number of People Who Inject Drugs in A Rural County in Appalachia". American Journal of Public Health. 109 (3): 445–450. doi:10.2105/AJPH.2018.304873. PMC 6366498. PMID 30676803.