Abstract: SARS-CoV-2 virus is currently one of the most
infectious pathogens for humans. It started in China at the end of
2019 and now it is spread in all over the world. The origin and
diffusion of the SARS-CoV-2 epidemic, is analysed based on the
discussion of viral phylogeny theory. With the aim of understanding
the spread of infection in the affected countries, it is crucial to
modelize the spread of the virus and simulate its activity. In this
paper, the prediction of coronavirus outbreak is done by using SIR
model without vital dynamics, applying different numerical technique
solving ordinary differential equations (ODEs). We find out that ABM
and MRT methods perform better than other techniques and that the
activity of the virus will decrease in April but it never cease (for
some time the activity will remain low) and the next cycle will start
in the middle July 2020 for Norway and Denmark, and October 2020
for Sweden, and September for Finland.
Abstract: In this work, we consider a deterministic model for
the transmission of leptospirosis which is currently spreading in the
Thai population. The SIR model which incorporates the features of
this disease is applied to the epidemiological data in Thailand. It is
seen that the numerical solutions of the SIR equations are in good
agreement with real empirical data. Further improvements are
discussed.
Abstract: Identifying parameters in an epidemic model is one
of the important aspect of modeling. In this paper, we suggest a
method to identify the transmission rate by using the multistage
Adomian decomposition method. As a case study, we use the data of
the reported dengue fever cases in the city of Shah Alam, Malaysia.
The result obtained fairly represents the actual situation. However, in
the SIR model, this method serves as an alternative in parameter
identification and enables us to make necessary analysis for a smaller
interval.