<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The new coronavirus has spread around the world at an unprecedented speed. Understanding patterns of disease spread is an important contribution to controlling any epidemic, and today’s mathematical methods offer a plethora of proven models to choose from. We provide a brief overview of epidemiological concepts, papers pertaining to mathematical modelling, and present a robust, simple mathematical model to model incidence of COVID-19 cases in Croatia during the first year of the disease. For our models, we chose logistic, Gumbel and Richards functions, with parameters generated using the Levenberg-Marquardt iterative method of nonlinear regression. In conclusion, all three models provided adequate estimation of incidence curve and final number of infected during the chosen time period, with relatively minor differences depending on chosen parameters of significance. The model using the logistic function proved to be the most applicable to available data. While no model can give the answers to ending the pandemic, this approach can provide a simple prognostic tool to evaluate interventions and estimate disease spread.</p>
</abstract>

The new coronavirus has spread around the world at an unprecedented speed. Understanding patterns of disease spread is an important contribution to controlling any epidemic, and today’s mathematical methods offer a plethora of proven models to choose from. We provide a brief overview of epidemiological concepts, papers pertaining to mathematical modelling, and present a robust, simple mathematical model to model incidence of COVID-19 cases in Croatia during the first year of the disease. For our models, we chose logistic, Gumbel and Richards functions, with parameters generated using the Levenberg-Marquardt iterative method of nonlinear regression. In conclusion, all three models provided adequate estimation of incidence curve and final number of infected during the chosen time period, with relatively minor differences depending on chosen parameters of significance. The model using the logistic function proved to be the most applicable to available data. While no model can give the answers to ending the pandemic, this approach can provide a simple prognostic tool to evaluate interventions and estimate disease spread.

The first year of covid-19 in croatia - a mathematical model

Geotechnical Faculty of the University of Zagreb

Croatian Regional Development Journal

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"The first year of covid-19 in croatia - a mathematical model"}

The new coronavirus has spread around the world at an unprecedented speed. Understanding patterns of disease spread is an important contribution to controlling...

The first year of covid-19 in croatia - a mathematical model

Data publikacji: 02 lut 2022

Zakres stron: 32 - 44

Otrzymano: 20 wrz 2021

Przyjęty: 30 wrz 2021

DOI: https://doi.org/10.2478/crdj-2021-0012

Słowa kluczowe
COVID-19, mathematical modelling, Croatia

© 2021 Tibor Rodiger et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The first year of covid-19 in croatia - a mathematical model

Data publikacji: 02 lut 2022

Zakres stron: 32 - 44

Otrzymano: 20 wrz 2021

Przyjęty: 30 wrz 2021

DOI: https://doi.org/10.2478/crdj-2021-0012

Słowa kluczoweCOVID-19, mathematical modelling, Croatia

© 2021 Tibor Rodiger et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Słowa kluczowe
COVID-19, mathematical modelling, Croatia