Conopídeos (Diptera: Conopidae) parasitando Centris (Heterocentris) analis (Fabricius) (Hymenoptera: Apidae, Centridini)

Parasites of adult bees are almost exclusively flies and the most important of them are conopids. This note registers for the first time the association of species of Physocephala (Diptera: Conopidae) with Centris (Heterocentris) analis (Fabricius). From 26 females and nine males of the host species found dead inside trap-nests on the campus of the University of São Paulo, Ribeirão Preto, Brazil, 35 parasitoids were obtained belonging to nine species of Physocephala. The data show that C. analis is a host to several conopid flies, and suggest that such parasitoids can play an important role in population control of this bee species.Parasitas de abelhas adultas são quase exclusivamente moscas e dentre os mais importantes estão os conopídeos. Nesta comunicação relata-se pela primeira vez a associação de espécies de Physocephala (Diptera: Conopidae) com Centris (Heterocentris) analis (Fabricius). De uma amostra de 26 fêmeas e nove machos da espécie hospedeira encontrados mortos em ninhos-armadilha vazios, no campus da Universidade de São Paulo, Ribeirão Preto, SP, emergiram 35 parasitóides pertencentes a nove espécies de Physocephala. Os dados mostram que C. analis é hospedeiro para várias espécies de conopídeos e sugerem que tais parasitóides podem desempenhar um papel importante na regulação populacional dessa espécie de abelha.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

Honey and propolis production, hygiene and defense behaviors of two generations of Africanized honey bees

Phenotypic characters of honeybees, relevant to beekeepers, can be evaluated by studying correlations between them, and the correlated characteristics can be evaluated in the short term to assist in monitoring of annual genetic progress. This work therefore aims to evaluate the production of honey and propolis, the hygiene and defensive behaviours of two generations of Africanized Apis mellifera (Hymenoptera, Apidae), to estimate the correlations between them and their heritability. We used 30 Langstroth beehives in apiaries in Marechal Cândido Rondon, Paraná State, Brazil. We used a method of drilling pupae to evaluate hygiene behaviour and the velveteen ball method to test defensive behaviour. We selected ten colonies which had the best honey and propolis production, and which produced F1 queens that were then transferred to beehives at an experimental farm, in order to observe honey and propolis production, hygiene and defence behaviours of their female offspring. The estimated differences for each characteristic between the generations, the correlations between them within each generation and their heritability suggest that selection of colonies based on propolis production was more efficient at maintaining this high production than was selection based on honey production according to the performance of the colonies for this characteristic. The selected behavioural characteristics can be used to enhance performance, but not for improving yield characteristics evaluated

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. Methods: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. Findings: The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. Interpretation: Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. Funding: Bill & Melinda Gates Foundation

Mortalidade por violências: aplicação de técnicas de análise exploratória em área metropolitana da região sudeste do Brasil, 1979-1987 Mortality due to violence: application of exploratory analysis techniques on data from an urban area of southeastern Brazil, 1979-1987

Realizou-se análise exploratória das taxas brutas de mortalidade por causas externas, nos municípios da Baixada Fluminense e no Município do Rio de Janeiro, Brasil, no período de 1979 a 1987. Objetivou-se verificar a tendência da mortalidade na área e período especificados para investigar a premissa de que a violência vem crescendo. Os resultados obtidos mostraram que as taxas de mortalidade apresentaram tendência de crescimento não linear ao longo de todo o período. Observou-se decréscimo de 1979 a 1983, seguido de crescimento a partir de 1984 quando as taxas atingem patamares mais elevados.<br>An exploratory analysis of gross death rates due to external reasons was carried out in the area of the "Baixada Fluminense", and in the Rio de Janeiro city, covering the 1979 -1987 period. The main goal was to verify mortality trends in the area and period of time specified, in an attempt to investigate a premiss according to wich violence rates have been increasing. Results obtained have show that death rates presented tendency to a non-linear increase throughout this period. A decrease was observed from 1979 to 1983, followed by an increase, since 1984, on to a higher level