Sensitivity Analysis of Mathematical Model of Coronavirus Disease (COVID-19) Transmission

Resmawan, Resmawan; Yahya, Lailany

doi:10.18860/ca.v6i2.9165

Cited by 42 publications

(36 citation statements)

References 6 publications

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“…Since COVID-19 Pandemic occurred in Indonesia, research on COVID-19 began to be carried out. In the field of mathematical modeling, many experts predict when the pandemic reaches its peak when it ends, and the transmission model of the spread of viruses (Kim et al, 2020;Ndaïrou et al, 2020;Nuraini et al, 2020;Peirlinck et al, 2020;Rahimi & Abadi, 2020;Resmawan & Yahya, 2020;Soewono, 2020;Tang et al, 2020). Whereas in learning mathematics in schools, research on obstacles in the use of e-learning that occurred in schools (Mailizar et al, 2020;Mulenga & Marbán, 2020).…”

Section: Introductionmentioning

confidence: 99%

Challenges During the Pandemic: Use of E-Learning in Mathematics Learning in Higher Education

et al. 2020

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On March 16, 2020, many universities in Indonesia began implementing online-based learning to replace lectures in the classroom. This is done as a way to reduce the transmission of the Covid-19 outbreak in Indonesia. There is an opinion that with the implementation of online learning, especially in mathematics education study programs, there are many obstacles when learning takes place. This study aims to determine the obstacles that arise after the implementation of online learning in mathematics learning in Higher Education. This research is a qualitative case study, assisted by an online survey. The researcher collected data through an online survey consisting of 27 questions. The survey is aimed at lecturers who teach in Mathematics Education study programs in Indonesia. The survey contains structured questions and leads to three parts, namely; basic skills challenges, teaching and learning challenges, and university challenges. The 27 questions contained questions about the ability of platform mastery to support online learning owned by each lecturer. The research involved 26 lecturers from universities in Sumatra, Java, Kalimantan, and Sulawesi. The results of this study reveal that all lecturers affected by the pandemic use a Learning Management System (LMS) based website as a means of online learning. The learning management system-based platform is the most widely used (google class and Edmodo) while video conferencing is the second choice (Zoom and Skype). What is interesting is that the LMS available on campus is less attractive to lecturers. However, there are obstacles faced such as the limitations of writing mathematical symbols and the limited basic capabilities of the learning management system and multimedia software to support online learning.

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Section: Introductionmentioning

confidence: 99%

Challenges During the Pandemic: Use of E-Learning in Mathematics Learning in Higher Education

et al. 2020

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“…Coronavirus Disease adalah penyakit menular yang disebabkan oleh jenis virus corona yang baru ditemukan di Wuhan, Provinsi Hubei, China pada Desember 2019 [1]. Penelitian telah menunjukkan bahwa penyakit ini disebabkan oleh sindrom pernapasan akut parahcoronavirus 2 (SARS-CoV-2) yang kemudian diberi nama Coronavirus Disease 2019 (COVID- 19) oleh World Health Organization (WHO) [2] [3]. Pasien dengan COVID-19 memiliki gejala seperti demam, batuk kering, dan kelelahan pada tahap awal, dan kemudian dapat mengembangkan gangguan pernapasan akut (ARDS), gagal pernapasan, syok, dan beberapa organfailure, yang mungkin fatal [3] [4].…”

Section: Pendahuluanunclassified

“…Pada bagian analisis, kami fokus membahas tentang eksistensi titik kesetimbangan beserta kestabilannya. Pembahasan ini melanjutkan kajian kami sebelumnya terkait analisis sensitifitas yang menunjukkan bahwa parameter intervensi berupa karantina memiliki indeks sensitifitas yang tinggi pada transmisi COVID-19 [19]. Pada bagian akhir diberikan simulasi untuk menunjukkan secara visual, dinamika populasi dan kontribusi intervensi karantina dalam menekan laju transmisi COVID-19.…”

Section: Pendahuluanunclassified

“…Bilangan reproduksi dasar 0 diperoleh dari nilai eigen positif terbesar pada matriks next generation = −1 atau secara matematis dinyatakan sebagai ( −1 )[20]. Adapun matriks next generation diperoleh dari sistem persamaan (1) dan persamaan (3) yang memuat kelas populasi terpapar, kelas populasi terinfeksi tanpa gejala klinis, dan kelas populasi terinfeksi disertai gejala klinis, yaitu nilai eigen positif tersebesar dari matriks[19] dan dapat ditulis:…”

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Analisis Dinamik Model Transmisi COVID-19 dengan Melibatkan Intervensi Karantina

2021

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ABSTRAKMakalah ini membahas dinamika transmisi COVID-19 dengan melibatkan intervensi karantina. Model dikonstruksi dengan melibatkan tiga kelas penyebab infeksi, yaitu kelas manusia terpapar, kelas manusia terinfeksi tanpa gejala klinis, dan kelas manusia terinfeksi disertai gejala klinis. Variabel yang merepresentasikan intervensi karantina untuk menekan pertumbuhan infeksi juga dipertimbangkan pada model. Selanjutnya, analisis model difokuskan pada eksistensi titik kesetimbangan dan simulasi numerik untuk menunjukkan dinamika populasi secara visual. Model yang dikonstruksi membentuk model SEAQIR yang memiliki dua titik kesetimbangan, yaitu titik kesetimbangan bebas penyakit dan titik kesetimbangan endemik. Analisis kestabilan menunjukkan bahwa titik kesetimbangan bebas penyakit bersifat stabil asimtotik lokal pada saat R01 dan tidak stabil pada saat R01. Simulasi numerik menunjukkan bahwa peningkatan intervensi berupa karantina dapat berkontribusi memperlambat transmisi COVID-19 sehingga diharapkan dapat mencegah terjadinya wabah pada populasi.ABSTRACTThis paper discusses the dynamics of COVID-19 transmission by involving quarantine interventions. The model was constructed by involving three classes of infectious causes, namely the exposed human class, asymptotically infected human class, and symptomatic infected human class. Variables were representing quarantine interventions to suppress infection growth were also considered in the model. Furthermore, model analysis is focused on the existence of equilibrium points and numerical simulations to visually showed population dynamics. The constructed model forms the SEAQIR model which has two equilibrium points, namely a disease-free equilibrium point and an endemic equilibrium point. The stability analysis showed that the disease-free equilibrium point was locally asymptotically stable at R01 and unstable at R01. Numerical simulations showed that increasing interventions in the form of quarantine could contribute to slowing the transmission of COVID-19 so that it is hoped that it can prevent outbreaks in the population.

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“…In their work, they used normalized forward sensitivity analysis to discover parameters that have high impact on the basic reproduction number 0 R of Hepatitis B model which must be targeted by intervention strategies. It is worthy to note that sensitivity Analysis of models in mathematical epidemiology aims to study the effect of each parameters of the model [7,8,9,10]. Helena [11] explained that sensitivity indices was used to measure the relative change in a variable when a parameter changes.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity Analysis of Hepatitis B Virus Epidemic Model

Akinboro

Kehinde

Alao

et al. 2020

ARJOM

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The aim of this work is to carry out detailed sensitivity analysis of each parameter in order to know their relative importance in the epidemiological model. This mathematical model for hepatitis B virus is a system of non-linear differential equations which represents the interaction between diseases classes and other epidemiological parameters. The disease free equilibrium points and basic reproduction number of the cases were analyzed using the next generation matrix method. Sensitivity analysis of with respect to the model parameters was carried out using normalized forward sensitivity index with graphical illustrations for clarity on the effects of these parameters. This analysis showed transmission rate as the most sensitive parameter which means a reduction to zero of the transmission rate could lead to eradicating HBV infection. It was deduced that sensitivity analysis of these model parameters gives an insight into how best the spread of Hepatitis B Virus could be curtailed.

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Sensitivity Analysis of Mathematical Model of Coronavirus Disease (COVID-19) Transmission

Cited by 42 publications

References 6 publications

Challenges During the Pandemic: Use of E-Learning in Mathematics Learning in Higher Education

Challenges During the Pandemic: Use of E-Learning in Mathematics Learning in Higher Education

Analisis Dinamik Model Transmisi COVID-19 dengan Melibatkan Intervensi Karantina

Sensitivity Analysis of Hepatitis B Virus Epidemic Model

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