On evaluating the effectiveness of quarantine measures and forecasting the end of the epidemic
( Pp. 69-75)
More about authors
Natalia V. Kontsevaya
Cand. Sci. (Econ.), Associate Professor, Associate Professor of the Department of Mathematics
Financial University under the Government of the Russian Federation
Moscow, Russian Federation
Financial University under the Government of the Russian Federation
Moscow, Russian Federation
Abstract:
The World today is facing a pandemic and countries are trying to optimize their behavior strategies. The main tool of struggle is quarantine. To model the scale of an epidemic, it is necessary to estimate the reproductive number R0, defined as the expected number of cases of infection. It is proposed to interpret R0 as a denominator of geometric progression, since the most infectious person becomes at the end of the incubation period, which on average is 5 days. During the same time, the number of infected people approximately doubles. The quarantine composed of two incubation periods in China was successful. It took three incubation periods to reduce the number of active cases in Italy. Russia has not yet overcome the predicted boundaries of isolation measures, so the effectiveness of quarantine is in the focus of attention. The effectiveness of quarantine measures can be evaluated by selecting the reduction of R0 as the optimization criterion. The method of bringing the initial data for countries to zero, i.e. to the appearance of a «zero» patient, is shown. Then the effectiveness of the restriction period is estimated in the change of R0 at the edges of the time series, which makes it possible to predict the timing of the end of epidemics.
How to Cite:
Natalia V.K., (2020), ON EVALUATING THE EFFECTIVENESS OF QUARANTINE MEASURES AND FORECASTING THE END OF THE EPIDEMIC. Economic Problems and Legal Practice, 3 => 69-75.
Reference list:
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Beyli N. Matematika v biologii i meditsine // M.: Mir, 1970. 327 s.
Buzin P. Kak matematika pomogaet borot sya s epidemiyami // URL: https://nplus1.ru/material/2019/12/26/epidemic-math
Grishunina YU.B., Kontarov N.A. i dr. Modelirovanie epidemicheskoy situatsii s uchetom vneshnikh riskov // Epidemiologiya i Vaktsinoprofilaktika, 2014, 5 (78): 61-66.
Leonenko V.N. Matematicheskaya epidemiologiya: uchebno-metodicheskoe posobie po vypolneniyu laboratornykh rabot. // SPb.: Universitet ITMO, 2018
Leonov V.P. Primenenie statistiki v stat yakh i dissertatsiyakh po meditsine i biologii. CHast II. Istoriya biometrii i ee primeneniya v Rossii // Mezhd. ZH. Med. Praktiki , 1999, N 4, s. 7-19.
Sychev I. Istoriya mirovykh epidemiy, ch.3 // URL: https://habr.com/ru/post/399439/
Kermack, W.O. and McKendrick, A.G. Contributions to the Mathematical Theory of Epidemics. Proceedings of the Royal Society of London, 1927 - A, 115, 700-721.
Bol shaya Meditsinskaya Entsiklopediya (BME), pod redaktsiey Petrovskogo B.V., 3-e izdanie, t.28: Ekonomo - YAshchur, 1986
Entsiklopedicheskiy slovar Brokgauza i Efrona. Rossiya, Sankt-Peterburg, 1890-1907, t. XXII (1897): Opeka - Outsayder, Ospoprivivanie - s. 309-316.
Beyli N. Matematika v biologii i meditsine // M.: Mir, 1970. 327 s.
Buzin P. Kak matematika pomogaet borot sya s epidemiyami // URL: https://nplus1.ru/material/2019/12/26/epidemic-math
Grishunina YU.B., Kontarov N.A. i dr. Modelirovanie epidemicheskoy situatsii s uchetom vneshnikh riskov // Epidemiologiya i Vaktsinoprofilaktika, 2014, 5 (78): 61-66.
Leonenko V.N. Matematicheskaya epidemiologiya: uchebno-metodicheskoe posobie po vypolneniyu laboratornykh rabot. // SPb.: Universitet ITMO, 2018
Leonov V.P. Primenenie statistiki v stat yakh i dissertatsiyakh po meditsine i biologii. CHast II. Istoriya biometrii i ee primeneniya v Rossii // Mezhd. ZH. Med. Praktiki , 1999, N 4, s. 7-19.
Sychev I. Istoriya mirovykh epidemiy, ch.3 // URL: https://habr.com/ru/post/399439/
Keywords:
modeling epidemics, the coronavirus, the effectiveness of quarantine, the exponential model, the reproductive number.
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