Open AccessLOGISTIC MODEL DEVELOPMENT FOR PREDICTION OF COVID-19 INFECTED INDIVIDUALS: CASE STUDY IN CENTRAL JAVA PROVINCE, INDONESIA
Author(s) -
Okky Widya Arditya,
Widowati Widowati,
Sutimin Sutimin,
R. Heru Tjahjana,
Priyo Sidik Sasongko
Publication year - 2021
Publication title -
journal of fundamental mathematics and applications
Language(s) - English
Resource type - Journals
eISSN - 2621-6035
pISSN - 2621-6019
DOI - 10.14710/jfma.v4i1.8385
Subject(s) - covid-19 , distancing , pandemic , intervention (counseling) , logistic regression , transmission (telecommunications) , java , logistic function , computer science , medicine , disease , infectious disease (medical specialty) , telecommunications , machine learning , psychiatry , programming language
In early 2020, covid-19 spread fast in the worldwide and cause the high death. The disease started from the Asian region which resulted in a viral pandemic in 2020. In order to anticipate the increasing of the cases, a strategy is needed to inhibit its transmission. The mathematical model approach is important tool for predicting of covid-19 spread in populations. In this paper we propose and analyze the dynamical behaviour of a developed logistic model by considering the effect of the contact patterns in reducing the covid-19 spread process. To verify the developed logistic model, numerical simulation was given with case study of covid-19 spread for patients under supervision in Central Java Province, Indonesia. Based on simulation results, it was found that physical distancing can reduce the growth of the covid-19 spread for patient under supervision. It can be seen from the number of covid-19 spread for patients under supervision with physical distancing intervention smaller compared to without physical distancing intervention.