Key challenges in modelling an epidemic - what have we learned from the COVID-19 epidemic so far

Eržen, Ivan (author), Kamenšek, Tina (author), Fošnarič, Miha (author), Žibert, Janez (author)

Mathematical modelling can be useful for predicting how infectious diseases progress, enabling us to show the likely outcome of an epidemic and help inform public health interventions. Different modelling techniques have been used to predict and simulate the spread of COVID-19, but they have not always been useful for epidemiologists and decision-makers. To improve the reliability of the modelling results, it is very important to critically evaluate the data used and to check whether or not due regard has been paid to the different ways in which the disease spreads through the population. As building an epidemiological model that is reliable enough and suits the current epidemiological situation within a country or region, certain criteria must be met in the modelling process. It might be necessary to use a combination of two or more different types of models in order to cover all aspects of epidemic modelling. If we want epidemiological models to be a useful tool in combating the epidemic, we need to engage experts from epidemiology, data science and statistics.

• Language: English
• Keywords: COVID-19 modelling, epidemiological aspects, statistical recommendations, model quality
• Work type: Article
• Typology: 1.03 - Other scientific articles
• Organization: ZF - Faculty of Health Sciences
• Publication status: Published
• Publication version: Version of Record
• Year: 2020
• Number of pages: Str. 117-119
• Numbering: Letn. 59, št. 3
• PID: 20.500.12556/RUL-122029
• UDC: 614
• ISSN on article: 0351-0026
• URN: URN:NBN:SI:doc-X38F9R18
• DOI: 10.2478/sjph-2020-0015
• COBISS.SI-ID: 21450243

Copyright

V članku navedeno: "© National Institute of Public Health, Slovenia." Na pristajalni strani članka navedeno: "© 2020 Ivan Eržen et al., published by Sciendo. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0" (https://content.sciendo.com/view/journals/sjph/59/3/article-p117.xml, 3. 3. 2021)

• Publication date in RUL: 17.11.2020

Record is a part of a journal

• Title: Zdravstveno varstvo. Slovenian journal of public health
• Publisher: Zavod LRS za zdravstveno varstvo, Republiški zdravstveni center, Zavod LRS za zdravstveno varstvo, Republiški zdravstveni center, Univerzitetni zavod za zdravstveno in socialno varstvo, Inštitut za varovanje zdravja Republike Slovenije, Nacionalni inštitut za javno zdravje
• ISSN: 0351-0026
• COBISS.SI-ID: 3287810

Licences

• License: CC BY-NC-ND 3.0, Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported
• Link: http://creativecommons.org/licenses/by-nc-nd/3.0/
• Description: You are free to reproduce and redistribute the material in any medium or format. You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. You may not use the material for commercial purposes. If you remix, transform, or build upon the material, you may not distribute the modified material. You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
• Licensing start date: 25.06.2020

Secondary language

• Language: Slovenian
• Title: Ključni izzivi pri modeliranju epidemije - dosedanje izkušnje pri modeliranju epidemije COVID-19

Abstract

Matematično modeliranje je lahko koristno za napovedovanje razvoja nalezljivih bolezni, saj s prikazom možnih izidov epidemije pomaga oblikovati javnozdravstvene ukrepe. Za napovedovanje in simulacijo širjenja v času epidemije COVID-19 so bile uporabljene različne tehnike modeliranja, vendar vse niso bile vedno koristne za epidemiologe in odločevalce. Da bi bili rezultati modeliranja zanesljivejši, je zelo pomembno kritično ovrednotiti uporabljene podatke ter preveriti, ali so bili upoštevani različni načini širjenja bolezni v populaciji ali ne. Izdelava dobrega epidemiološkega modela, ki je dovolj zanesljiv in ustreza trenutnim epidemiološkim razmeram v državi ali regiji, je zahtevna, zato je treba pri modeliranju slediti določenim kriterijem. Smiselno bi bilo tudi kombinirati dve različni vrsti modelov. Modeliranje bi bilo tako zanesljivejše, saj bi upoštevalo različne predpostavke. Če želimo, da bodo epidemiološki modeli koristno orodje v boju proti epidemiji, morajo pri modeliranju sodelovati strokovnjaki z različnih področij, predvsem epidemiologije, podatkovne znanosti in statistike

• Keywords: modeliranje COVID-19, epidemiološki pogled na modeliranje, priporočene statistične metode, kakovost modelov