COVID-19: Worldwide Profiles during the First 250 Days

Abstract

The present COVID-19 pandemic is happening in a strongly interconnected world. This interconnection explains why it became universal in such a short period of time and why it stimulated the creation of a large amount of relevant open data. In this paper, we use data science tools to explore this open data from the moment the pandemic began and across the first 250 days of prevalence before vaccination started. The use of unsupervised machine learning techniques allowed us to identify three clusters of countries and territories with similar profiles of standardized COVID-19 time dynamics. Although countries and territories in the three clusters share some characteristics, their composition is not homogenous. All these clusters contain countries from different geographies and with different development levels. The use of descriptive statistics and data visualization techniques enabled the description and understanding of where and how COVID-19 was impacting. Some interesting extracted features are discussed and suggestions for future research in this area are also presented.

Effectiveness of COVID-19 Vaccines: Evidence from the First-Year Rollout of Vaccination Programs

“…Due to its high level of contagious and rapid geographical spread, COVID-19 was declared a pandemic on 11 March 2020, less than three months after the first cases were diagnosed [ 1 , 2 ].…”

“…By the end of November 2020, there were more than 62 million confirmed cases and 1.4 million deaths worldwide [ 3 ]. Until then, the pandemic’s impact was mainly correlated with several factors such as the average age of the population, sanitary conditions, health conditions, and public health response restrictions [ 2 ]. However, since December 2020, with the rollout of the first vaccination programs [ 4 ], the vaccination coverage of the population has become another essential factor in understanding the pandemic evolution, slowing down the progress of the disease, reducing the impact of the pandemic, and saving lives [ 5 ].…”

“…Following previous research on the worldwide impact of COVID-19 [ 2 ], this study aims to explore the worldwide influence of vaccination as a tool to control the pandemic and save lives. By providing evidence that vaccines are efficient on a factual data-driven basis, we also hope to contribute to reducing vaccine hesitancy.…”

Health-Related Crises in Tourism Destination Management: A Systematic Review

“…Recent global crises and disasters, both natural and human-induced, such as terrorism, wars, epidemic diseases, natural disasters, political and economic issues, have indeed posed major challenges to the tourism industry worldwide [5]. Specifically, the recent COVID-19 pandemic has led to devastating social and economic consequences, including mobility restrictions, business closures, pay cuts and massive job losses in the global travel and tourism industry [6,7]. Although sustainable development has been a long-discussed issue in tourism, the unprecedented socio-economic impacts brought by the pandemic have led scholars and practitioners alike to question the sustainability of the industry [8,9].…”

Complex system properties in the spreading of COVID-19 pandemic

“…Moreover, by using a toy model for social networks and the so-called small-world network, researchers explained why most COVID-19 infection curves are linear (Thurner, et al, 2020). On the other hand, three clusters of countries and territories with similar profiles of standardized COVID-19 time dynamics were identified by using a machine learning technique (António, et al, 2021). Besides, times series of active and cumulative cases from three countries were analyzed in the context of a continuous effective model based on a modified diffusion equation under Lifshitz scaling to describe some aspects of the SARS-Cov-2 virus diffusion and to reproduce the spreading of the pandemic between two cities of Brazil (Anacleto, et al, 2020).…”