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    Wyświetlanie 1-4 z 4
    Tytuł:
    Zastosowanie języka programowania Python do modelowania rozprzestrzeniania się epidemii
    Application of Python programming language for modeling the evolution of epidemic
    Autorzy:
    Koziej, Krzysztof
    Kazimierska-Drobny, Katarzyna
    Powiązania:
    https://bibliotekanauki.pl/articles/41205831.pdf
    Data publikacji:
    2023
    Wydawca:
    Uniwersytet Kazimierza Wielkiego w Bydgoszczy
    Tematy:
    Python
    modele epidemii
    rozwiązania numeryczne
    SIS
    SIR
    SIRS
    SEIR
    models of epidemic
    numerical solutions
    Opis:
    Niniejszy artykuł przedstawia numeryczne rozwiązania wybranych modeli rozprzestrzeniania się epidemii w języku programowania Python. Rozwiązania oparto na modelach epidemii SIS, SIR, SIRS oraz SEIR. Do rozwiązań numerycznych w języku Python wykorzystano biblioteki NumPy, SciPy oraz Matplotlib.
    This article presents numerical solutions of selected epidemic spread models in the Python programming language. The solutions were base on the SIS, SIR, SIRS and SEIR epidemic models. NumPy, SciPy and Matplotlib libraries were used for numerical solutions in Python.
    Źródło:
    Studia i Materiały Informatyki Stosowanej; 2023, 15, 2; 10-17
    1689-6300
    Pojawia się w:
    Studia i Materiały Informatyki Stosowanej
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Logistics of Sanitary Teams Activities
    Autorzy:
    Pytlak, R.
    Suski, D.
    Zawadzki, T.
    Stecz, W.
    Powiązania:
    https://bibliotekanauki.pl/articles/409391.pdf
    Data publikacji:
    2015
    Wydawca:
    Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
    Tematy:
    Epidemic models
    Forrester’s models of sanitary activities
    Model calibration
    Optimal management of sanitary activities
    Opis:
    We describe the information system that has been built for the support sanitary teams. The system is aimed at supporting analytical work which must be carried out when there is a risk of epidemic outbreak. It is meant to provide tools for predicting the size of an epidemic on the basis of the actual data collected during its course. Since sanitary teams try to control the size of the epidemics such a tool must model also sanitary teams activities. As a result a model for the prediction can be quite complicated in terms of the number of equations it contains. Furthermore, since a model is based on several parameters there must be a tool for finding these parameters on the basis on the actual data corresponding to the epidemic evolution. The paper describes the proposition of such a system. It presents, in some details, the main components of the system. In particular, the environment for building complex models (containing not only the epidemic model but also activities of sanitary teams trying to inhibit the epidemic) is discussed. Then, the module for a model calibration is presented. The module is a part of server for solving optimal control problems and can be accessed via Internet. Finally, we show how optimal control problems can be constructed with the aim of the efficient epidemic management. Some optimal control problems related to that issue are discussed and numerical results of its solution are presented.
    Źródło:
    Research in Logistics & Production; 2015, 5, 4; 393-406
    2083-4942
    2083-4950
    Pojawia się w:
    Research in Logistics & Production
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    System wspomagania pracy służb sanitarnych
    Support System of sanitary teams work
    Autorzy:
    Pytlak, R.
    Zawadzki, T.
    Suski, D.
    Stecz, W.
    Powiązania:
    https://bibliotekanauki.pl/articles/1378308.pdf
    Data publikacji:
    2014
    Wydawca:
    Polskie Wydawnictwo Ekonomiczne
    Tematy:
    modele epidemiczne
    modele Forrestera aktywności służb sanitarnych
    kalibracja modeli
    epidemic models
    Forrester’s models of sanitary activities
    model calibration
    Opis:
    We describe the information system that has been built for the support sanitary teams. The system is aimed at supporting analytical work which must be carried out when there is a risk of epidemic outbreak. It is meant to provide tools for predicting the size of an epidemic on the basis of the actual data collected during its course. Since sanitary teams try to control the size of the epidemics such a tool must model also sanitary teams activities. As a result a model for the prediction can be quite complicated in terms of the number of equations it contains. Furthermore, since a model is based on several parameters there must be a tool for finding these parameters on the basis on the actual data corresponding to the epidemic evolution. The paper describes the proposition of such a system. It presents, in some details, the main components of the system. In particular, the environment for building complex models (containing not only the epidemic model but also activities of sanitary teams trying to inhibit the epidemic) is discussed. Then, the module for a model calibration is presented. The module is a part of server for solving optimal control problems and can be accessed via Internet. Finally, we show how optimal control problems can be constructed with the aim of the efficient epidemic management. Some optimal control problems related to that issue are discussed and numerical results of its solution are presented.
    Źródło:
    Gospodarka Materiałowa i Logistyka; 2014, 11; 19-28
    1231-2037
    Pojawia się w:
    Gospodarka Materiałowa i Logistyka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Epidemie i pandemie chorób zakaźnych
    Epidemics and pandemics of infectious diseases
    Autorzy:
    Gliński, Zdzisław
    Żmuda, Andrzej
    Powiązania:
    https://bibliotekanauki.pl/articles/22039813.pdf
    Data publikacji:
    2020
    Wydawca:
    Krajowa Izba Lekarsko-Weterynaryjna
    Tematy:
    epidemie
    pandemie
    historia
    modele matematyczne
    choroby zakaźne
    rozwój epidemii
    epidemic
    pandemic
    history
    development
    mathematical models
    Opis:
    Throughout the course of civilization, epidemics and pandemics have ravaged humanity, destroyed animal breeding and horticulture, and has also changed the course of history. It has been estimated that Justinian plague has affected half of the population of Europe and killed in three pandemics 50 million people, the avian-borne flu (Spanish flu), resulted in 50 million deaths worldwide in the years 1918–1919, and recently the COVID-19 is officially a pandemic, after barreling through 114 countries in just three months. In the past, rinderpest has hit Europe with three long panzootics, African swine fever (ASF), is still a threat to both the swine production industry and the health of wild boar populations. Several molecular changes occur in the pathogen that may trigger an epidemic or even pandemic. These include increase of virulence, introduction into a novel host, and changes in host susceptibility to the pathogen. Once the infectious disease threat reaches an epidemic or pandemic level, the goal of the response is to mitigate its impact and reduce its incidence, morbidity and mortality as well as disruptions to economic, political, and social systems. An epidemic curve shows progression of illnesses in an outbreak over time and the SIR, SI, SIRD and SEIR represent the simplest compartmental models that enable simplify the mathematical modelling of epidemics. This article throws a light on changing ideas in epidemiology of infectious diseases.
    Źródło:
    Życie Weterynaryjne; 2020, 95, 09; 554-560
    0137-6810
    Pojawia się w:
    Życie Weterynaryjne
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
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