Subject

Computational Epidemiology

Course Title

Computational Epidemiology
Computational epidemiology

Code

m23_s_021

Study Programme

—

Organizer of the study programme (unit, institute, department or division)

Faculty of Computer Science and Engineering

Degree level (first, second, third cycle)

Second cycle

Academic year / semester

10 / Summer

Number of ECTS credits

Teacher

Lasko Basnarkov

Prerequisites for enrolling in the course

—

10.

Objectives of the course programme (competences)

Students will become familiar with the basic models for the spread of infectious diseases, such as SIR and SIS. They will study the population-based versions of the models as well as those based on agents. By doing so, students will gain the ability to solve the models using numerical simulations. From the models, conclusions can be drawn about the course of the epidemic—such as its extinction or continued spread—as well as the study of possible effects of various vaccination scenarios.

11.

Course content

Basic population-based SIR and SIS epidemic models. Simulation of SIR and SIS population models. Determination of the epidemic threshold and the basic reproduction number. Simulation of agent-based models for describing the spread of infection through complex networks. More complex epidemic models. Simulation of vaccination scenarios. Parameter estimation of the models based on observations.

12.

Learning methods

Lectures, projects, discussions and workshops

13.

Total available time

6 ECTS x 30 hours = 180 hours

14.

Distribution of available time

60 + 0 + 45 + 45 + 30 = 180 hours

15.

Forms of teaching activities

15.1.	Lectures - theoretical instruction	60 hours
15.2.	Exercises (laboratory, auditory), seminars, teamwork	0 hours

16.

Other forms of activities

16.1.	Project assignments	45 hours
16.2.	Independent assignments	45 hours
16.3.	Home study	30 hours

17.

Assessment method

17.1.	Tests	15 points
17.2.	Seminar paper / project (presentation: written and oral)	45 points
17.3.	Activities and learning	15 points
17.4.	Final exam	0 points

18.

Grading criteria (points / grade)

up to 50 points	5 (five) (F)
from 51 to 60 points	6 (six) (E)
from 61 to 70 points	7 (seven) (D)
from 71 to 80 points	8 (eight) (C)
from 81 to 90 points	9 (nine) (B)
from 91 to 100 points	10 (ten) (A)

19.

Requirement for obtaining a signature and taking the final exam

Activities completed 15

20.

Language of instruction

Macedonian and English

21.

Method for monitoring the quality of teaching

internal evaluation and survey mechanism

22.

Literature

22.1.	Required literature 1. F. Brauer, C. Castillo-Chavez, Z. Feng \| Mathematical Models in Epidemiology \| Springer \| 2019 2. Ellen Kuhl \| Computational Epidemiology - Data-Driven Modeling of COVID-19 \| Springer \| 2021 3. O. Diekmann, J. A. P. Heesterbeek \| Mathematical epidemiology of infectious diseases \| Wiley \| 2000
22.2.	Additional literature No. Author Title Publisher Year