Feasible modelling and prediction of COVID-19 outbreaks

Beschreibung

We formulate the ill-posedness of inverse problems of estimation and prediction for covid19 outbreaks from the statistical and mathematical perspectives. These leave us with a plenty of possible statistical regularizations, thus generating plethora of sub-problems. We can mention as examples stability and sensitivity of peak estimation or estimation of parameters of SIR (Susceptible-Infected-Removed) model. We also illustrate that several country-specific covariates, e.g. social structure, or air pollution, etc. can play a crucial way in regularization of the estimators. We will illustrate this on example of Chile, where start of exponential growth, grounded on microbiological-epidemiological model was severely underestimated. Moreover, in a specific country, one can define several social groups which can contribute to whole country epidemiological curves. For parametric models of epidemic curves, each parameter has its own specific sensitivity, and naturally, the more sensitive parameter deserves a special attention. E.g. in SIR model, parameter beta is more sensitive than parameter gamma. In simple exponential epidemic growth model, beta parameter is more sensitive than a parameter. We provide sensitivity and illustrate it on the country specific data. We also discuss on statistical quality of COVID-19 incidence prediction, where we justify an exponential curve considering the microbial growth in ideal conditions for epidemic. We model number of infected in Iowa State, USA, Hubei Province in China, New York State, USA. All empirical data justifies an exponential growth curve for initial prediction. We also discuss covid19 prediction in Chile and Slovak Republic. References: Stehlik, M, J. Kiselak, Dinamarca, A. Li, Y. and Ying, Y. On covid19 outbreaks predictions: issues on stability, parameter sensitivity and precision, Stochastic Analysis and Applications DOI: 10.1080/07362994.2020.1802291

Zeitraum	19 Aug. 2020
Ereignistitel	SciTech Central COVID-19, Online Konferenz
Veranstaltungstyp	Konferenz
Ort	ÖsterreichAuf Karte anzeigen