Wyniki wyszukiwania - BazTech

1

Zastosowanie języka programowania Python do modelowania rozprzestrzeniania się epidemii

Koziej Krzysztof, Kazimierska-Drobny Katarzyna

Studia i Materiały Informatyki Stosowanej

|

2023

|

T. 15, nr 2

10--17

PL

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.

EN

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.

2

Trend and prediction of COVID-19 outbreak in Iran: SEIR and ANFIS model

Shafiekhani Sajad, Khalilabad Touraj Harati, Rafiei Sima, Sadeghi Vahid, Jafari Amir Homayoun, Gheibi Nematollah

Polish Journal of Medical Physics and Engineering

|

2021

|

Vol. 27, Iss. 3

241--249

EN

Background: Mathematical and predictive modeling approaches can be used in COVID-19 crisis to forecast the trend of new cases for healthcare management purposes. Given the COVID-19 disease pandemic, the prediction of the epidemic trend of this disease is so important. Methods: We constructed an SEIR (Susceptible-Exposed-Infected-Recovered) model on the COVID-19 outbreak in Iran. We estimated model parameters by the data on notified cases in Iran in the time window 1/22/2020 – 20/7/2021. Global sensitivity analysis is performed to determine the correlation between epidemiological variables and SEIR model parameters and to assess SEIR model robustness against perturbation to parameters. We Combined Adaptive Neuro- Fuzzy Inference System (ANFIS) as a rigorous time series prediction approach with the SEIR model to predict the trend of COVID-19 new cases under two different scenarios including social distance and non-social distance. Results: The SEIR and ANFIS model predicted new cases of COVID-19 for the period February 7, 2021, till August 7, 2021. Model predictions in the non-social distancing scenario indicate that the corona epidemic in Iran may recur as an immortal oscillation and Iran may undergo a recurrence of the third peak. Conclusion: Combining parametrized SEIR model and ANFIS is effective in predicting the trend of COVID-19 new cases in Iran.

3

Stability analysis of fractional order SEIR model for malaria disease in Khyber Pakhtunkhwa

Badshah Noor, Akbar Haji

Demonstratio Mathematica

|

2021

|

Vol. 54, nr 1

326--334

EN

We discussed stability analysis of susceptible-exposed-infectious-removed (SEIR) model for malaria disease through fractional order and check that malaria is epidemic or endemic in Khyber Pakhtunkhwa (Pakistan). We show that the model has two types of equilibrium points and check their stability through Routh-Hurwitz criterion. We find basic reproductive number using next-generation method. Finally, numerical simulations are also presented.

4

Dynamika rozwoju epidemii w zamkniętej populacji dla wybranych patogenów

Janik M.

Prace Naukowe Akademii im. Jana Długosza w Częstochowie. Technika, Informatyka, Inżynieria Bezpieczeństwa

|

2016

|

T. 4

225--232

PL

W pracy przeprowadzono symulacje rozwoju epidemii dla kilku wybranych patogenów chorobotwórczych: odry, świnki, ospy wietrznej, ptasiej grypy oraz eboli. Badania przeprowadzono dla niewielkiej odizolowanej populacji liczącej 1000 osobników. Do analizy wykorzystano model SEIR. Obliczenia przeprowadzone zostały w arkuszu kalkulacyjnym.

EN

The paper presents simulations of the development of the epidemic for a number of selected pathogens: measles, mumps, chicken pox, avian flu and ebola. The study was conducted for small an isolated population of 1000 individuals. For the analysis, the epidemic model SEIR was used. The calculations were made in a spreadsheet.