{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,3,8]],"date-time":"2024-03-08T09:11:40Z","timestamp":1709889100796},"reference-count":0,"publisher":"National Institute of Public Health NIH (National Research Institute)","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Przegl Epidemiol"],"abstract":"<p><strong>ABSTRACT<\/strong><br \/>The article highlights the problem of salmonellosis among the population of the Kharkov region, Ukraine.\u00a0Three time series were used for calculations: a series of incidence rates for men, a series of incidence rates\u00a0for women and a series of incidence rates for the general population, each of the series was an ordered set of\u00a0monthly values from December 2015 to December 2018. It was revealed that the most effective tool for analyzing\u00a0these statistical data is the use of the autoregressive moving average model (ARIMA). The following steps\u00a0were used: identification and replacement of outliers, the use of smoothing and decomposition of the series.\u00a0The developed model allows you to explicitly indicate the order of the model using the arima () function or\u00a0automatically generate a set of optimal values (p, d, q) using the auto.arima () function. The validated model\u00a0allows to calculate the predicted values of the incidence of salmonellosis for 50 days. In certain cases, models\u00a0of exponential smoothing are able to give forecasts that are not inferior in accuracy to forecasts obtained using\u00a0more complex models.<\/p>\n<p><strong>STRESZCZENIE<\/strong><br \/>W artykule opisano problem infekcji salmonelozy w \u015bwiecie, a tak\u017ce konieczno\u015b\u0107 przewidywania chor\u00f3b zaka\u017anych\u00a0na przyk\u0142adzie wyst\u0119powania salmonelozy w\u015br\u00f3d ludno\u015bci obwodu Charkowskiego, Ukraina. Do oblicze\u0144\u00a0zosta\u0142y wykorzystane trzy tymczasowe szeregi: szereg poziomu zachorowalno\u015bci m\u0119\u017cczyzn, szereg poziomu\u00a0zachorowalno\u015bci kobiet i szereg poziomu wyst\u0119powania w og\u00f3lnej populacji, Ka\u017cdy z rz\u0119d\u00f3w stanowi\u0142 uporz\u0105dkowany\u00a0zestaw miesi\u0119cznych warto\u015bci od grudnia 2015 do grudnia 2018 roku. Stwierdzono, \u017ce najbardziej\u00a0skutecznym narz\u0119dziem do analizy tych danych statystycznych jest wykorzystanie modelu autoregresyjnej\u00a0\u015bredniej krocz\u0105cej (ARIMA). Zosta\u0142y wykorzystane takie kroki: identyfikacja i wymiana odstaj\u0105cych, wykorzystanie\u00a0wyg\u0142adzania i dekompozycja szereg\u00f3w. Opracowany model pozwala okre\u015bli\u0107 kolejno\u015b\u0107 modelu za\u00a0pomoc\u0105 funkcji arima() lub automatycznie wygenerowa\u0107 zestaw optymalnych warto\u015bci (p, d, q) za pomoc\u0105\u00a0funkcji auto.arima(). Zatwierdzony model pozwala na obliczenie prognozy warto\u015bci cz\u0119sto\u015bci wyst\u0119powania\u00a0salmonelozy na 50 dni. W niekt\u00f3rych przypadkach modele wyg\u0142adzania wyk\u0142adniczego s\u0105 w stanie generowa\u0107\u00a0prognozy tak dok\u0142adne, jak te uzyskiwane przy u\u017cyciu bardziej z\u0142o\u017conych modeli.<\/p><\/jats:p>","DOI":"10.32394\/pe.74.27","type":"journal-article","created":{"date-parts":[[2020,10,26]],"date-time":"2020-10-26T14:16:39Z","timestamp":1603721799000},"page":"346-354","source":"Crossref","is-referenced-by-count":3,"title":["Forecasting of salmonellosis epidemic proces in Ukraine using autoregressive integrated moving average model"],"prefix":"10.32394","volume":"74","author":[{"given":"S","family":"Bohdanov","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Y","family":"Polyvianna","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"T","family":"Chumachenko","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"D","family":"Chumaczenko","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"17323","published-online":{"date-parts":[[2020,10,19]]},"container-title":["Przeglad Epidemiologiczny"],"original-title":["Prognoza epidemicznego procesu salmonelozy na Ukrainie za pomoc\u0105 modelu rejestracji autoregresyjnej \u015bredniej przesuwnej"],"link":[{"URL":"https:\/\/www.przeglepidemiol.pzh.gov.pl\/pdf-180941-101504","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.przeglepidemiol.pzh.gov.pl\/pdf-180941-101504","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,8]],"date-time":"2024-03-08T08:45:47Z","timestamp":1709887547000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.przeglepidemiol.pzh.gov.pl\/Forecasting-of-salmonellosis-epidemic-proces-in-Ukraine-using-autoregressive-integrated,180941,0,2.html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,19]]},"references-count":0,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2020]]}},"alternative-id":["180941"],"URL":"https:\/\/doi.org\/10.32394\/pe.74.27","relation":{},"ISSN":["0033-2100","2545-1898"],"issn-type":[{"value":"0033-2100","type":"print"},{"value":"2545-1898","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10,19]]}}}