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Objective: To evaluate the differential impact of arboviral infections, specifically dengue virus, chikungunya virus, and Zika virus, on women in Brazil, with a focus on sex- and age-disaggregated analyses.

Methods: A comprehensive epidemiological and geospatial data analysis was conducted utilizing data from Brazil's national health data system, including the disease notification system (Sistema de Informação de Agravos de Notificação) and mortality information system (Sistema de Informação sobre Mortalidade), covering national and municipal level data. Arboviral case notification rates were analyzed using generalized linear mixed models with negative binomial regression, stratified by sex, age group, and year. Geospatial visualizations mapped the case rate distribution highlighting the top municipalities with the most female case rate and hospitalizations rate. All analyses were implemented in the statistical software R.

Results: Significant sex- and age-stratified differences were observed in the arbovirus notification rates for dengue virus, chikungunya virus, and Zika virus over the past seven years, with consistently higher rates among women compared to men. Stratified analyses revealed that females aged 20-59 years, particularly those of reproductive age, bore a disproportionately higher burden across all three viruses. The low serotyping resolution for the dengue virus constrained further granular analysis, particularly for severe outcomes such as hospitalizations and mortality based on dengue serotype.

Conclusion: Sex- and age-disaggregated epidemiological surveillance is critical to inform public health policies and interventions targeting arboviral diseases. This study underscores the necessity of incorporating sex-specific data analyses to optimize responses for vulnerable female populations. Geospatial visualizations reveal infection hotspots, providing actionable insights for region-specific interventions to improve health outcomes in Brazil.

Objective: To analyze the time trend of indicators from the Vigitel data collection operation between 2006 and 2023.

Methods: A methodological study that analyzed the temporal trend of three Vigitel operation indicators: eligibility rate, response rate and refusal rate, as well as the number of contacts answered according to days of the week and times of day. A series of linear regressions was used to identify temporal variations for the entire period (2006 to 2023) and for the final five years of this period (2018 to 2023).

Results: During the 17 editions analyzed, there was a decrease in the eligibility rate (-3.26 pp/year; p < 0.001) with the greatest magnitude in the most recent period (-12.23 pp/year; p = 0.010). Although the inclusion of mobile phones in the register in 2023 has mitigated the drop in eligibility, especially in recent years, the reduction has remained high (-10.43 pp/year; p = 0.020). The response rate also fell over the entire period (-0.78; p < 0.001) and, together with the fall in eligibility, represents an obstacle to the sustainability of the survey. On the other hand, the refusal rate also fell (-0.23 pp/year; p = 0.030), indicating the consistent quality of the system's operation. The number of contacts answered was concentrated on weekdays and between 9am and 8pm.

Conclusions: An analysis of the data from the Vigitel survey suggests that the methodology used has become fatigued, with reductions in eligibility and response rates over the years. Only the refusal rate, despite being far from its lowest levels, remains at satisfactory levels. The search for alternatives that make participation more convenient for the respondent is an important path for surveys of this nature, with a view to maintaining the quality of health surveillance in the country.

[This corrects the article doi: 10.11606/s1518-8787.2025059005816].

Objectives: To analyze the geographic access of children with congenital Zika syndrome (CZS), residing in the city of Rio de Janeiro between 2015 and 2017, to rehabilitation services.

Methods: Ecological study, based on spatial analysis. Commute maps were constructed using QGis 3.36.3 and the distances, time and cost between rehabilitation services and the homes of children with CZS, in the city of Rio de Janeiro, reported between 2015 and 2017 in the Registry System of Public Health Events.

Results: 47 children were identified, 6 died. Among the 41 survivors, 17 were followed up in primary and secondary health care (PHC and SHC), 10 only in PHC, 7 only in SHC, and 7 had no follow-up record. CZS cases were more frequent in the north and west zones of the city. 143 trajectories followed by the 36 children between home and a rehabilitation service were identified; 147 commutes, followed 1 to 106 times; the majority destined for 3 units (n = 17 - 47.0%). The largest number of trajectories and commutes were among residents in the north and west zones of the city, poorer regions, with greater distances, cost, and time spent traveling between home and the health unit.

Conclusions: The variation in trajectories, the number of recorded commutes, and the number of units included in the trajectories suggest the complexity of the children's clinical condition, from basic care in PHC to procedures with greater technological density in specialized care.

Objective: To estimate the caloric share of ultra-processed foods (% UPF) in the 5,570 Brazilian municipalities.

Methods: The estimation of % UPF in municipalities was performed using a statistical prediction model based on data from 46,164 individuals aged over >10 years who participated in the Household Budget Survey (HBS 2017-2018). Multiple linear regression was used to estimate the average % UPF (measured through two 24-hour dietary recalls) based on predictor variables (sex, age, income, education, race/color, urbanity, federative units, and geographic location). The model's adequacy was assessed through residual analysis and by comparing predicted values with those directly measured in POF 2017-2018 using Lin's concordance correlation coefficient (CCC). The linear coefficients obtained from the multiple linear regression model were applied to the sociodemographic data from the 2010 Census (measured similarly to POF) to estimate the % UPF for each municipality.

Results: The statistical model proved adequate, showing normally distributed residuals and a CCC of 0.87, indicating almost perfect agreement. There was heterogeneity in the distribution of % UPF estimates, ranging from 5.75% in Aroeiras do Itaim (PI) to 30.5% in Florianópolis (SC). % UPF estimates were higher (>20%) in municipalities from the South region and the state of São Paulo. Capitals had higher estimates of caloric contribution from ultra-processed foods compared to other municipalities in their states.

Conclusions: The predictive model revealed differences in % UPF among Brazilian municipalities. The generated estimates can contribute to monitoring ultra-processed food consumption at the municipal level and support the development of public policies focused on promoting healthy eating.

[This corrects the article doi: 10.11606/s1518-8787.2020054005728] [This corrects the article doi: 10.11606/s1518-8787.2024058005728].

[This corrects the article doi: 10.11606/s1518-8787.2024058005729] [This corrects the article doi: 10.11606/s1518-8787.2024058005729].

[This corrects the article doi: 10.11606/s1518-8787.2020054005997].

Epidemiological data shows that the consumption of animal-based foods in high-income countries is excessive and harmful to health. But the association between poverty and protein deficiency is frequent, both in scientific literature and in the documents of multilateral organizations. There is a conceptual trap in this link, which consists of focusing on one nutrient and not on the whole dietary pattern. In 1974, in a text that has become a classic of nutrition science, Donald McLaren has already highlighted the mistake made by multilateral development organizations in focusing their efforts on protein supply-often in industrialized forms-without considering that, in most cases, once energy needs are met, protein deficiency is unlikely to occur. Data from the 2017-2018 Consumer Expenditure Survey helps to dispel this myth: even among the poorest 20% of the Brazilian population, the proportion of those with insufficient protein intake is tiny.

[This corrects the article doi: 10.11606/s1518-8787.2024058005462].