Publications by authors named "S Osorio"
Background: The minimum mortality temperature (MMT) or MMT percentile (MMTP) is an indicator of population susceptibility to nonoptimum temperatures. MMT and MMTP change over time; however, the changing directions show region-wide heterogeneity. We examined the heterogeneity of temporal changes in MMT and MMTP across multiple communities and in multiple countries.
View Article and Find Full Text PDFBackground: We quantify the mortality burden and economic loss attributable to nonoptimal temperatures for cold and heat in the Central and South American countries in the Multi-City Multi-Country (MCC) Collaborative Research Network.
Methods: We collected data for 66 locations from 13 countries in Central and South America to estimate location-specific temperature-mortality associations using time-series regression with distributed lag nonlinear models. We calculated the attributable deaths for cold and heat as the 2.
Article Synopsis
- The study investigates how daily rainfall characteristics—like intensity, duration, and frequency—affect mortality rates from all causes, cardiovascular issues, and respiratory problems across 34 countries from 1980 to 2020.
- It utilizes a time series analysis to evaluate the association between daily mortality and rainfall events that occur at different return periods (one, two, and five years), including the effects of extreme rainfall with a 14-day lag.
- The results indicate that extreme rainfall events (five-year return period) correlate with increased mortality rates, particularly for respiratory cases, while moderate rainfall shows protective effects, and the impact varies based on climate and vegetation.
Background: Heterogeneity in temperature-mortality relationships across locations may partly result from differences in the demographic structure of populations and their cause-specific vulnerabilities. Here we conduct the largest epidemiological study to date on the association between ambient temperature and mortality by age and cause using data from 532 cities in 33 countries.
Methods: We collected daily temperature and mortality data from each country.
Article Synopsis
- * A study involving 781 untreated stage A CLL patients compared five different risk scoring methods to see which best predicted disease progression, also assessing the impact of including the IGHV2 subset as a poor prognostic factor.
- * All five risk scores performed similarly in identifying low to high-risk patients, with CLL-IPI showing the best results, and findings indicate that incorporating IGHV2 could enhance the accuracy of these risk assessments.