Abstract
We present different data analytic methodologies that have been applied in order to understand the evolution of the first wave of the Coronavirus disease 2019 in the Republic of Cyprus and the effect of different intervention measures that have been taken by the government. Change point detection has been used in order to estimate the number and locations of changes in the behaviour of the collected data. Count time series methods have been employed to provide short term projections and a number of various compartmental models have been fitted to the data providing with long term projections on the pandemic’s evolution and allowing for the estimation of the effective reproduction number.
Highlights
We present different data analytic methodologies that have been applied in order to understand the evolution of the first wave of the Coronavirus disease 2019 in the Republic of Cyprus and the effect of different intervention measures that have been taken by the government
This manuscript contains the work of this group, including results from statistical and mathematical models used to understand the epidemiology of the first wave of COVID-19 in Cyprus, which spans from the beginning of March till the end of May 2020
We examine six consecutive fortnight periods, for each of which we draw 10,000 steps of the used Markov chain Monte Carlo algorithm, discard the first 2000 steps as burn-in and use the remaining ones to approximate the posterior distributions of α, β and Rt
Summary
We present different data analytic methodologies that have been applied in order to understand the evolution of the first wave of the Coronavirus disease 2019 in the Republic of Cyprus and the effect of different intervention measures that have been taken by the government. Lacking a scientific unit specialised in epidemics and other infectious health hazards, a diverse group of experts from various disciplines, including epidemiologists, clinicians, statisticians and data scientists was formed with the aim of trying to understand the evolution of the COVID-19 pandemic in Cyprus and of assisting the Cypriot government in informed decision making. This manuscript contains the work of this group, including results from statistical and mathematical models used to understand the epidemiology of the first wave of COVID-19 in Cyprus, which spans from the beginning of March till the end of May 2020. Besides providing a comprehensive data analysis, we illustrate the importance of mathematical models to epidemiology
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