Key Challenges in Modelling an Epidemic - What have we Learned from the COVID-19 Epidemic so Far

Zdr Varst. 2020 Jun 25;59(3):117-119. doi: 10.2478/sjph-2020-0015. eCollection 2020 Sep.

Abstract

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.

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: COVID-19 modelling; epidemiological aspects; model quality; statistical recommendations.

Publication types

  • Editorial