Usefulness of open data to determine the incidence of COVID-19 and its relationship with atmospheric variables in Spain during the 2020 lockdown.

The SARS-CoV-2 pandemic and the spread of the COVID-19 disease led to a lockdown being imposed in Spain to minimise contagion from 16 March 2020 to 1 May 2020. Over this period, measures were taken to reduce population mobility (a key factor in disease transmission). The scenario thus created enabled us to examine the impact of factors other than mobility (in this case, meteorological conditions) on the incidence of the disease, and thus to identify which environmental variables played the biggest role in the pandemic's evolution. Worthy of note, the data required to perform the study was entirely extracted from governmental open data sources. The present work therefore demonstrates the utility of such data to conduct scientific research of interest to society, leading to studies that are also fully reproducible. The results revealed a relationship between temperatures and the spread of COVID-19. The trend was that of a slightly lower disease incidence as the minimum temperature rises, i.e. the lower the minimum temperature, the greater the number of cases. Furthermore, a link was found between the incidence of the disease and other variables, such as altitude and proximity to the sea. There were no indications, however, in the study's data, of a relationship between incidence and precipitation or wind.

Toxoplasma gondii infection in hospitalized people living with HIV in Spain, 1997 to 2015.

Toxoplasma gondii infection was one of the most frequent AIDS-defining conditions in HIV-infected individuals until the advent of combination antiretroviral therapy. We aimed to assess the clinical load, coinfection, and mortality, as well as time trends for people living with HIV and hospitalized with Toxoplasma gondii infection, in Spain from 1997 to 2015. Retrospective observational analysis using the Spanish National Registry of Hospital Discharges. Information was retrieved for the study period using the International Classification of Diseases, 9th revision. There were 66,451,094 hospital admissions in Spain from 1997 to 2015, including 472,269 (0.71%) in people living with HIV. Toxoplasma gondii infection was registered in 9006 of these (overall prevalence 1.91%), making it the fifth most common opportunistic infection in hospitalized HIV-positive patients. Prevalence of Toxoplasma gondii infection declined in this group from 4.2% in 1997 to 0.8% in 2015 (p < 0.001), while mean age increased, from 35 years in 1997 to 44 years in 2015. The overall in-hospital mortality rate declined from 13.5% in 1997 to 8.9% in 2015, and it was higher in the concomitant presence of bacterial pneumonia (28.9% vs. 10.2%, p < 0.001), cryptosporidiosis (26.9% vs. 11.5%; p = 0.03), cytomegalovirus disease (18.2% vs. 11.2%, p < 0.001), Pneumocystis jiroveci pneumonia (31.5% vs. 10.5%, p < 0.001), leukoencephalopathy (19.8% vs. 11.78% p < 0.001), and wasting syndrome (29.3% vs 10.9%; p < 0.001). Toxoplasma gondii infection prevalence has significantly declined among hospitalized HIV-infected patients in Spain during the last two decades, coinciding with the widespread use of combination antiretroviral therapy.

Estimation of parameters in sewage sludge by near-infrared reflectance spectroscopy (NIRS) using several regression tools.

Sewage sludge application to agricultural soils is a common practice in several countries in the European Union. Nevertheless, the application dose constitutes an essential aspect that must be taken into account in order to minimize environmental impacts. In this study, near infrared reflectance spectroscopy (NIRS) was used to estimate in sewage sludge samples several parameters related to agronomic and environmental issues, such as the contents in organic matter, nitrogen and other nutrients, metals and carbon fractions, among others. In our study (using 380 biosolid samples), two regression models were fitted: the common partial least square regression (PLSR) and the penalized signal regression (PSR). Using PLSR, NIRS became a feasible tool to estimate several parameters with good goodness of fit, such as total organic matter, total organic carbon, total nitrogen, water-soluble carbon, extractable organic carbon, fulvic acid-like carbon, electrical conductivity, Mg, Fe and Cr, among other parameters, in sewage sludge samples. For parameters such as C/N ratio, humic acid-like carbon, humification index, the percentage of humic acid-like carbon, the polymerization ratio, P, K, Cu, Pb, Zn, Ni and Hg, the performance of NIRS calibrations developed with PLSR was not sufficiently good. Nevertheless, the use of PSR provided successful calibrations for all parameters.