Cryptococcus is an important fungal pathogen worldwide, causing serious clinical manifestations that can affect immunocompetent patients and can be particularly severe for immunocompromised patients. The Cryptococcus gattii s.s. (AFLP4/VGI), Cryptococcus tetragattii (AFLP/VGIV), Cryptococcus neoformans, and Cryptococcus deneoformans have been isolated from both clinical and environmental sources in Europe. We aim to quantify the people in Europe and the entire Mediterranean area who are under risk associated with each of the three fungal pathogens in a spatially explicit way, generating a series of maps and population statistics per country. Niche modeling was applied to estimate the potential distribution of each fungal pathogen, then these models were overlapped with a map of population density to estimate risk levels. The potential number of people per risk level and per country was quantified using a map of population count per pixel. Prevalence of HIV per country was also included in the analysis to quantify the HIV‐infected population under potential risk. People under risk associated with exposure to C. gattii species (C. gattii s.s. and C. tetragattii) reached 137.65 million, whereas those exposed to C. neoformans and C. deneoformans were 268.58 and 360.78 million people, respectively. More than a half million HIV‐infected patients are exposed to each of the two species of the C. neoformans species complex, and more than 200,000 to the C. gattii species complex. The present results can be useful for public health planning by European governments, focusing on the provision of inputs for a “screen‐and‐treat” approach, availability of medical resources, and continuous monitoring programs in risk zones.

In 2018 the fungal pathogen Cryptococcus bacillisporus (AFLP5/VGIII) was isolated for the first time in Chile, representing the only report in a temperate region in South America. We reconstructed the colonization process of C. bacillisporus in Chile, estimating the phylogenetic origin, the potential spread zone, and the population at risk. We performed a phylogenetic analysis of the strain and modeled the environmental niche of the pathogen projecting its potential spread zone into the new colonized region. Finally, we generated risk maps and quantified the people under potential risk. Phylogenetic analysis showed high similarity between the Chilean isolate and two clonal clusters from California, United States and Colombia in South America. The pathogen can expand into all the temperate Mediterranean zone in central Chile and western Argentina, exposing more than 12 million people to this pathogen in Chile. This study has epidemiological and public health implications for the response to a potential C. bacillisporus outbreak, optimizing budgets, routing for screening diagnosis, and treatment implementation.

Contrasting effects have been identified in association of weather (temperature and humidity) and pollutant gases with COVID‐19 infection, which could be derived from the influence of lockdowns and season change. The influence of pollutant gases and climate during the initial phases of the pandemic, before the closures and the change of season in the northern hemisphere, is unknown. Here, we used a spatial‐temporal Bayesian zero‐inflated‐Poisson model to test for short‐term associations of weather and pollutant gases with the relative risk of COVID‐19 disease in China (first outbreak) and the countries with more cases during the initial pandemic (the United States, Spain and Italy), considering also the effects of season and lockdown. We found contrasting association between pollutant gases and COVID‐19 risk in the United States, Italy, and Spain, while in China it was negatively associated (except for SO 2 ). COVID‐19 risk was positively associated with specific humidity in all countries, while temperature presented a negative effect. Our findings showed that short‐term associations of air pollutants with COVID‐19 infection vary strongly between countries, while generalized effects of temperature (negative) and humidity (positive) with COVID‐19 was found. Our results show novel information about the influence of pollution and weather on the initial outbreaks, which contribute to unravel the mechanisms during the beginning of the pandemic.

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