Evidence of sylvatic yellow fever was first reported in Atlantic Forest areas in Espírito Santo, Brazil, during a yellow fever virus (YFV) outbreak in 1931. An entomological survey was conducted in six forest sites during and after an outbreak reported ~80 years after the last case in the area. Among 10,658 mosquitoes of 78 species, Haemagogus leucocelaenus, and Hg. janthinomys/capricornii were considered the main vectors as they had a relatively high abundance, co-occurred in essentially all areas, and showed high YFV infection rates. Sabethes chloropterus, Sa. soperi, Sa. identicus, Aedes aureolineatus, and Shannoniana fluviatilis may have a secondary role in transmission. This is the first report of Sa. identicus, Ae. aureolineatus, and Sh. fluviatilis infected with YFV. Our study emphasizes the importance of entomological monitoring and maintenance of high vaccination coverage in receptive areas to YFV transmission.

The Oropouche virus (OROV) has been circulating in the Amazon region since the 1960s, with a progressive increase in outbreaks and human cases reported in Brazil and neighboring countries. In the Rio de Janeiro state, there has been a significant rise in suspected cases of arboviruses, with only 30% of laboratory tests confirming infections with dengue, Zika, or chikungunya viruses. The investigation of OROV virus circulation in the Rio de Janeiro state was initiated and confirmed in April 2024. Our study aimed to retrospectively investigate OROV infections in dengue-suspected cases with inconclusive diagnosis in order to better understand the temporal and geographic introduction of OROV in the Rio de Janeiro state. Municipalities from Rio de Janeiro with arbovirus-like fever cases but a low percentage of dengue-positive RT-PCR test confirmations were identified in the laboratory database. Samples were selected for testing OROV infections using real-time RT-PCR as recommended by the Brazilian Ministry of Health. Municipalities in the Middle Paraíba region of the state showed 93% negative tests results for dengue, Zika, and chikungunya starting in September 2023. A total of 118 positive cases of Oropouche were recorded in the state of Rio de Janeiro between March and July 2024. Moreover, by genome sequencing of eight strains, it was shown that OROV circulating in Rio de Janeiro belongs to recently emergent M₁L₂S₂ lineage. Our findings retrospectively revealed a concentration of cases in the Middle Paraíba region and an outbreak in the rural village of Cacaria, located in the municipality of Piraí. According to our data, this region is the first area with sustained transmission in the Rio de Janeiro state.

Background: Urban arbovirus transmission is spatially and temporally heterogeneous. Estimating the risk of dengue through statistical models that consider simultaneous variability in space and time provides more realistic estimates of transmission dynamics, facilitating the identification of priority areas for intervention focused on surveillance and control. These models also enable predictions to support timely interventions for arboviruses like dengue, chikungunya, and Zika. Methodology/principal findings: We analyzed dengue case reports by epidemiological week and neighborhood in Natal, RN from 2015 to 2018. Temporal conditional autoregressive models were fitted using the Integrated Nested Laplace Approximation method. The predictors included a set of entomological, climatic and sociosanitary indicators with temporal lags, along with structures of temporal and spatial dependence. Additionally, we used an offset term to represent the expected number of dengue cases per neighborhood at each epidemiological week, under the hypothesis of homogeneity in the occurrence of cases across the municipality. We forecasted dengue case counts for the subsequent four weeks, addressing both zero occurrences and fluctuations during non-zero periods. Weekly risk dynamics were visualized through predictive maps, enabling the timely identification of neighborhoods with high and persistent dengue risk, that is, areas consistently exhibiting a high number of dengue cases that remained concentrated in the same location for several weeks. The optimal model revealed a significant rise in dengue occurrence probability during the observation week, associated with increased cases in the previous week, the Aedes egg positivity index from the prior four weeks, and the mean daytime temperature 6–8 weeks earlier. Dengue risk also rose with a one-standard-deviation increase in the density of the impoverished population per occupied area and the mean Aedes egg density index from the preceding 3–5 weeks. Conclusions/significance: The proposed Bayesian space-time analysis can contribute to the operational control of dengue and Aedes aegypti by identifying priority areas and forecasting dengue cases for the next four weeks. It also quantifies the effects of entomological, sociosanitary, climatic and demographic indicators on both the likelihood of dengue occurrence and the intensity of outbreaks.

OBJECTIVE: To analyze the consumption of drugs for Alzheimer’s disease on the Brazilian private market and its geographical distribution from 2014 to 2020. METHODS: National data from the Brazilian National System of Controlled Product Management were used, regarding sales of donepezil, galantamine, rivastigmine, and memantine from January 2014 to December 2020. Sales data were used as a proxy for drug consumption and expressed as defined daily dose/1,000 inhabitants/year at national, regional, federative unit and microregion levels. RESULTS: Drug consumption went from 5,000 defined daily doses/1,000 inhabitants, in 2014, to more than 16,000/1,000 inhabitants, in 2020, and all federative units showed positive variation. The Brazilian Northeast had the highest cumulative consumption in the period but displayed microregional disparities while the North region had the lowest consumption. Donepezil and memantine were the most consumed drugs, with the highest growth in consumption from 2014 to 2020. CONCLUSION: The consumption of medicines indicated to treat Alzheimer’s disease tripled in Brazil between 2014 and 2020, which may relate to the increase in the prevalence of the disease in the country, greater access to health services, and inappropriate use. This challenges managers and healthcare providers due to population aging and the increased prevalence of chronic-degenerative diseases.

Poverty in Brazil persists as a significant challenge for society, addressing not only fundamental moral concerns but also the need to promote conditions conducive to economic and social development. The complexity of the problem, characterized by multiple factors beyond income, includes historical inequalities, unequal economic structures, and limited access to resources and public services. Despite advancements in recent decades, the increase in poverty between 2014 and 2016, driven by growing income inequality, underscores the fragility of these advances. The rise in poverty rates in the Metropolitan Region of the state of Rio de Janeiro, where affluent areas coexist with deprived communities, becomes a cause for concern, exacerbated by factors such as lack of decent employment, educational precarity and socio-economic impacts of the pandemic. Confronting these issues, a detailed analysis using data from the Continuous National Household Sample Survey (Continuous PNAD) of 2012, 2016 and 2020 highlights the formality of employment as a crucial factor in poverty reduction in the region. The transition from informality to formality is associated with significant gains in poverty reduction, surpassing even the impact of the educational level of the head of the household. Results from Bayesian logistic regression show that formality decreases the likelihood of individuals and their families having per capita household income below the poverty line. This research emphasizes the need for comprehensive public policies in the state of Rio de Janeiro, aiming to promote economic opportunities, improve the quality of education and invest in infrastructure, underscoring the importance of enhancing employment ties as an effective strategy in the fight against poverty.

The COVID-19 pandemic had a significant impact on Brazil, although its effects were not homogeneous across the country. Socioeconomic disparities may influence epidemiological patterns during health emergencies, which impact population mental health. This study aimed to analyze the consumption of psychoactive medicines during the COVID-19 pandemic in Brazil and to characterize its spatiotemporal dynamics, identifying associated social, economic, and demographic factors. We used publicly available retail pharmacies dispensing data from January 2018 to September 2021 across Brazil’s municipalities. A statistical model was developed based on indicators of infrastructure, human capital, and labor and income. Generalized additive models were used to characterize the spatiotemporal distribution of drug consumption. In September 2021, average consumption in municipalities reporting COVID-19–related deaths was 22% higher than in municipalities with no reported deaths. Among the most frequently consumed medicines during the study period, second-generation antidepressants were predominant. Life expectancy, employment and education showed positive linear associations with consumption, whereas inadequate water supply and sanitation were inversely associated. Municipality income was positively associated with average consumption of psychoactive medicines, but those with a very high-income development index showed more complex dynamics. Our results suggest that COVID-19 mortality was associated with psychotropic medicines consumption and indicate the need to address socioeconomic vulnerability as a key component of public health emergency response. The COVID-19 pandemic had a significant impact on Brazil, although its effects were not homogeneous across the country. Socioeconomic disparities may influence epidemiological patterns during health emergencies, impacting population mental health. This study aimed to analyze the consumption of psychoactive medicines during the COVID-19 pandemic in Brazil and to characterize its spatiotemporal dynamics, identifying associated social, economic, and demographic factors. We used publicly available data from retail pharmacy dispensing from January 2018 to September 2021 across Brazilian municipalities. A statistical model was developed based on indicators of infrastructure, human capital, labor, and income. Generalized additive models were used to characterize the spatiotemporal distribution of drug consumption. In September 2021, average consumption in municipalities reporting COVID-19–related deaths was 22% higher than in municipalities with no reported deaths. Among the most frequently consumed medicines during the study period, second-generation antidepressants were predominant. Life expectancy, employment, and education showed positive linear associations with consumption, whereas inadequate water supply and sanitation were inversely associated. Municipality income was positively associated with the average consumption of psychoactive medicines, but those with a very high human development index for income showed more complex dynamics. Our results suggest that COVID-19 mortality was associated with psychotropic medicine consumption and indicate the need to address socioeconomic vulnerability as a key component of public health emergency responses.