It has been more than one year since Chinese authorities identified a deadly new strain of coronavirus, SARS-CoV-2. Since then, the scientific work regarding the transmission risk factors of COVID-19 has been intense. The relationship between COVID-19 and environmental conditions is becoming an increasingly popular research topic. Based on the findings of the early research, we focused on the community of Madrid, Spain, which is one of the world’s most significant pandemic hotspots. We employed different multivariate statistical analyses, including principal component analysis, analysis of variance, clustering, and linear regression models. Principal component analysis was employed in order to reduce the number of risk factors down to three new components that explained 71% of the original variance. Cluster analysis was used to delimit the territory of Madrid according to these new risk components. An ANOVA test revealed different incidence rates between the territories delimited by the previously identified components. Finally, a set of linear models was applied to demonstrate how environmental factors present a greater influence on COVID-19 infections than socioeconomic dimensions. This type of local research provides valuable information that could help societies become more resilient in the face of future pandemics.

This research aims to synthesize the theoretical field on climate migrations by identifying the main thematic lines that make up the area of study, as well as to analyze their temporal evolution, geographic distribution, and impact. For this purpose, a thematic analysis of the abstracts of 1,048 scientific articles has been carried out by applying natural language processing techniques. The analyses consisted of the application of a clustering strategy based on high dimensionality vectors generated from the texts through the application of neural networks based on BERT architecture. The results show that the research on climate migrations is composed of a total of 15 distinct themes. It has also been found that each thematic line is different in their volume, temporal evolution, geographic distribution, and impact. This knowledge offers a privileged position to strengthen the development of the discipline by providing greater perspective to researchers and knowledge about the field of study itself.