A tale of two epicentres: Lombardy and New York City at the outbreak of the Coronavirus pandemic

The paper explores the tale of two 'epicentres' - metropolitan New York and Lombardy - and seeks to depict the socio-demographic patterns that characterise the worst cases of infection, hospitalisation, and death during the first six months of the Covid-19 pandemic in 2020. By drawing upon secondary data concerning sub-territorial units within the two regions - ZIP-code level and counties in New York and municipalities in Italy - the paper compares the characteristics of the two areas in an effort to understand both how they became the original major epicentres and how their experiences of the pandemic differed. We suspected initially that the pandemic in Lombardy was a function of a complex constellation of variables, such as the age of the population, the unexpected emergence of the virus, and features of the local health system. In New York, the pattern seemed to fit a more familiar dynamic, the kind one would expect from the course that most pandemics take: the poor suffer the worst. The paper tries to extend the understanding of the complex and not univocal mix of social variables that can facilitate the spread of a pandemic and make its effects extreme.

Spatiotemporal evolution, pattern of diffusion, and influencing factors of the COVID-19 epidemic in Hainan Province, China.

Within 1 month after the first case occurred in Hainan Province, China, the number of confirmed cases rose to 168, and there was no increase in almost 3 months. As the southernmost province and a famous tourist destination in China, its regular economic exchanges and high-intensity population movements may affect the spread of the epidemic. It is of great theoretical and practical significance to investigate the spatiotemporal evolution, the pattern of diffusion, and factors influencing the coronavirus disease 2019 (COVID-19) epidemic in Hainan Province. Basic and geographic information of confirmed COVID-19 cases was obtained from government websites and other official media. We examined the groups of infection and calculated the diffusion ratio to demonstrate the trend of the epidemic. Map drawing, spatial analysis, and partial least squares regression were used to express the spatiotemporal evolution, the pattern of diffusion, and factors affecting the epidemic. Furthermore, we have made recommendations on the formulation and adaptation of possible future preventive steps. Results show that the COVID-19 epidemic in Hainan Province has substantial spatial heterogeneity but minimal distribution. The tourist city and central city have formed a dual-core pattern for the spread of the epidemic, which could extend to other similar regions. Population density, mobility, and level of urban development have been the major factors of epidemic distribution in the study area.