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Background/Objectives: To analyze the spatial distribution of HPV vaccination coverage in relation to sociodemographic variables in a state of Southern Brazil. Methods: This was an ecological, retrospective study with secondary data from the Department of Information Technology of the Unified Health System/Ministry of Health from 2015 to 2022. The cohort method was used to calculate vaccination coverage. Geographically weighted regression was used for the independent variables. Results: There was a 22.04% reduction in vaccination between the first and second doses. Coverage with the first dose of the vaccine reached 95.17% for the female population, 64.67% for the male population, and 79.57% for both sexes. In 50.62% of cities, coverage exceeded 90% for both sexes. In 80.45% of cities, the recommended coverage for females was achieved. The variable municipal performance was positively significant for the increase in vaccination coverage in 45.45% of the regions for girls, 18.18% for boys, and 36.36% for both sexes. The family health strategy variable was significant in 9.09% of the regions for girls and both sexes. The education variable showed an inverse significance for girls in 40.90%, for boys in 18.18%, and for both sexes in 36.36% of the regions. Conclusions: HPV vaccination declined between the first and second doses, with high first-dose coverage among females and moderate coverage among males. Municipal performance notably impacted coverage, particularly for girls. The family health strategy was relevant in specific regions, while educational factors had a variable effect. Addressing these variables may enhance vaccination coverage and minimize the gap between doses.

Abstract Remote areas, such as the Amazon Forest, face unique geographical challenges of transportation-based access to health services. As transportation to healthcare in most of the Amazon Forest is only possible by rivers routes, any travel time and travel distance estimation is limited by the lack of data sources containing rivers as potential transportation routes. Therefore, we developed an approach to convert the geographical representation of roads and rivers in the Amazon into a combined, interoperable, and reusable dataset. To build the dataset, we processed and combined data from three data sources: OpenStreetMap, HydroSHEDS, and GloRiC. The resulting dataset can consider distance metrics using the combination of streets and rivers as a transportation route network for the Amazon Forest. The created dataset followed the guidelines and attributes defined by OpenStreetMap to leverage its reusability and interoperability possibilities. This new data source can be used by policymakers, health authorities, and researchers to perform time-to-care analysis in the International Amazon region.

Background Snakebite envenoming (SBE) is a neglected tropical disease capable of causing both significant disability and death. The burden of SBE is especially high in low- and middle-income countries. The aim of this study was to perform a geospatial analysis evaluating the association of sociodemographics and access to care indicators on moderate and severe cases of SBE in Brazil. Methods We conducted an ecological, cross-sectional study of SBE in Brazil from 2014 to 2019 using the open access National System Identification of Notifiable Diseases (SINAN) database. We then collected a set of indicators from the Brazil Census of 2010 and performed a Principal Component Analysis to create variables related to health, economics, occupation, education, infrastructure, and access to care. Next, a descriptive and exploratory spatial analysis was conducted to evaluate the geospatial association of moderate and severe events. These variables related to events were evaluated using Geographically Weighted Poisson Regression. T-values were plotted in choropleth maps and considered statistically significant when values were +1.96. Results We found that the North region had the highest number of SBE cases by population (47.83/100,000), death rates (0.18/100,000), moderate and severe rates (22.96/100,000), and proportion of cases that took more than three hours to reach healthcare assistance (44.11%). The Northeast and Midwest had the next poorest indicators. Life expectancy, young population structure, inequality, electricity, occupation, and more than three hours to reach healthcare were positively associated with greater cases of moderate and severe events, while income, illiteracy, sanitation, and access to care were negatively associated. The remaining indicators showed a positive association in some areas of the country and a negative association in other areas. Conclusion Regional disparities in SBE incidence and rates of poor outcomes exist in Brazil, with the North region disproportionately affected. Multiple indicators were associated with rates of moderate and severe events, such as sociodemographic and health care indicators. Any approach to improving snakebite care must work to ensure the timeliness of antivenom administration.

Introduction: The COVID-19 pandemic stressed the importance of healthcare personnel. However, there is evidence of an increase in violence against them, which brings consequences, such as anxiety. The aim of this study was to analyze the anxiety levels of health professionals who have or not suffered violence during the COVID-19 pandemic, and verify the variables associated with the risk of starting to take medication for anxiety.Methods: We assessed the anxiety profile of health professionals in Brazil through an online questionnaire, using the Generalized Anxiety Disorder 7-item Scale (GAD-7), in relation to groups of participants who have or not suffered violence during the COVID-19 pandemic. We used Cronbach's alpha reliability coefficient to check the consistency of the responses, and the effect size using the r coefficient. Principal Component Analysis was used to verify the differences in anxiety scores between the two groups. Logistic regression analysis was also used to verify the variables associated with the risk of starting medication for anxiety and considered statistically significant when p < 0.05.Results: A total of 1,166 health professionals participated in the study, in which 34.13% had a normal anxiety profile, 40.14% mild, 15.78% moderate, and 9.95% severe. The mean score of the sum of the GAD-7 was 7.03 (SD 5.20). The group that suffered violence had a higher mean (8.40; SD 5.42) compared to the group that did not (5.70; SD 4.60). In addition, the median between both groups was significantly different (7.0 vs. 5.0; p < 0.01). Approximately 18.70% of the participants reported having started taking medication to treat anxiety during the pandemic. The factors that increased the chances of these professionals starting medication for anxiety p < 0.05 were having suffered violence during the pandemic (OR 1.97; 95% CI 1.42–2.77), being nurses (OR 1.61; 95% CI 1.04–2.47) or other types of health professionals (OR 1.58; 95% CI 1.04–2.38), and having a mild (OR 2.11; 95% CI 1.37–3.34), moderate (OR 4.05; 95% CI 2.48–6.71) or severe (OR 9.08; 95% CI 5.39–15.6) anxiety level.Conclusion: Brazilian healthcare professionals who have suffered violence during the pandemic have higher anxiety scores and higher risk to start taking anxiety medication.

Background: The new coronavirus disease (COVID-19) has claimed thousands of lives worldwide and disrupted the health system in many countries. As the national emergency care capacity is a crucial part of the COVID-19 response, we evaluated the Brazilian Health Care System response preparedness against the COVID-19 pandemic.Methods: A retrospective and ecological study was performed with data retrieved from the Brazilian Information Technology Department of the Public Health Care System. The numbers of intensive care (ICU) and hospital beds, general or intensivist physicians, nurses, nursing technicians, physiotherapists, and ventilators from each health region were extracted. Beds per health professionals and ventilators per population rates were assessed. A health service accessibility index was created using a two-step floating catchment area (2SFCA). A spatial analysis using Getis-Ord Gi* was performed to identify areas lacking access to high-complexity centers (HCC).Results: As of February 2020, Brazil had 35,682 ICU beds, 426,388 hospital beds, and 65,411 ventilators. In addition, 17,240 new ICU beds were created in June 2020. The South and Southeast regions have the highest rates of professionals and infrastructure to attend patients with COVID-19 compared with the northern region. The north region has the lowest accessibility to ICUs.Conclusions: The Brazilian Health Care System is unevenly distributed across the country. The inequitable distribution of health facilities, equipment, and human resources led to inadequate preparedness to manage the COVID-19 pandemic. In addition, the ineffectiveness of public measures of the municipal and federal administrations aggravated the pandemic in Brazil.

Background:No other disease has killed more than ischemic heart disease (IHD) for the past few years globally. Despite the advances in cardiology, the response time for starting treatment still leads patients to death because of the lack of healthcare coverage and access to referral centers. Objectives:To analyze the spatial disparities related to IHD mortality in the Parana state, Brazil. Methods:An ecological study using secondary data from Brazilian Health Informatics Department between 2013–2017 was performed to verify the IHD mortality. An spatial analysis was performed using the Global Moran and Local Indicators of Spatial Association (LISA) to verify the spatial dependency of IHD mortality. Lastly, multivariate spatial regression models were also developed using Ordinary Least Squares and Geographically Weighted Regression (GWR) to identify socioeconomic indicators (aging, income, and illiteracy rates), exam coverage (catheterization, angioplasty, and revascularization rates), and access to health (access index to cardiologists and chemical reperfusion centers) significantly correlated with IHD mortality. The chosen model was based on p < 0.05, highest adjusted R² and lowest Akaike Information Criterion. Results:A total of 22,920 individuals died from IHD between 2013–2017. The spatial analysis confirmed a positive spatial autocorrelation global between IDH mortality rates (Moran’s I: 0.633, p < 0.01). The LISA analysis identified six high-high pattern clusters composed by 66 municipalities (16.5%). GWR presented the best model (Adjusted R²: 0.72) showing that accessibility to cardiologists and chemical reperfusion centers, and revascularization and angioplasty rates differentially affect the IHD mortality rates geographically. Aging and illiteracy rate presented positive correlation with IHD mortality rate, while income ratio presented negative correlation (p < 0.05). Conclusion:Regions of vulnerability were unveiled by the spatial analysis where sociodemographic, exam coverage and accessibility to health variables impacted differently the IHD mortality rates in Paraná state, Brazil. Highlights The increase in ischemic heart disease mortality rates is related to geographical disparities. The IHD mortality is differentially associated to socioeconomic factors, exam coverage, and access to health. Higher accessibility to chemical reperfusion centers did not necessarily improve patient outcomes in some regions of the state. Clusters of high mortality rate are placed in regions with low amount of cardiologists, income and schooling.

BackgroundThe increase in violence against health professionals in the COVID-19 pandemic makes it necessary to identify the predictors of violence, in order to prevent these events from happening.ObjectiveEvaluating the prevalence and analyzing the variables involved in the occurrence of violence against health professionals during the COVID-19 pandemic in Brazil.MethodThis is a cross-sectional study conducted online involving Brazilian health professionals during the COVID-19 pandemic. The data were collected through a structured questionnaire (Google Online Form) sent to health professionals on social networks and analyzed through logistic regression by using sociodemographic variables. The set of grouped variables was assigned to the final model when p ResultsThe predictors of violence in the adjusted regression model were the following: being a nursing technician / assistant; having been working for less than 20 years; working for over 37 hours a week; having suffered violence before the pandemic; having been contaminated with COVID-19; working in direct contact with patients infected by the virus; and having family members who have suffered violence. The network created with professionals who suffered violence demonstrated that the aggressions occurred mainly in the workplace, with an indication of psycho-verbal violence. In cases in which the aggressors were close people, aggressions were non-verbal and happened both in public and private places. The assaults practiced by strangers occurred in public places.ConclusionsViolence against health professionals occurs implicitly and explicitly, with consequences that can affect both their psychosocial well-being and the assistance given to their patients and families.

Abstract Background The coronavirus 2019 (COVID-19) pandemic impacted cancer health care in several countries, with delays in the detection and treatment of breast and cervical cancer. The objective of this study is to analyze and compare the screening, diagnosis and treatment of breast and cervical cancer in the pre-COVID period and during the COVID-19 period. Methods Cross-sectional study with secondary data collected from the Mortality Information System (SIM), Hospital Information System (SIH), Ambulatory Information System (SIA) and the Oncology Panel (PO) of breast cancer notifications with ICD C50.0 to C50.9 and cervix ICD C53.0 to C53.9, The analyzed period before the pandemic was from March 1 to October 1, 2019, and during the pandemic from March 1 to October 1, 2020. The period from 2013 to 2022 was also analyzed with the same information, including the number of diagnoses, treatments, and deaths from breast cancer and cervical cancer. The study population consisted of Brazilian women aged 25 to 70 years. In order to compare categorical variables between periods, the Chi-Square or Fisher’s Exact tests, and Mann-Whitney U tests were applied, and the Poisson Regression model was applied to model the number of reported cases of COVID-19 and the amount of procedures. Results There was a decrease in the number of mammograms and cytopathological exams during COVID-19, as well as a decrease in cases of breast and cervical cancer. The Poisson regression showed that the increase in the number of COVID-19 cases caused a decrease in the number of breast cytopathological examinations, cervical-vaginal cytopathological examinations/microflora and screening, diagnosis, initiation of treatment for breast cancer and deaths from this disease. Meanwhile, in some regions of Brazil, as the number of Covid-19 increased, there was a significantly increase in the number of mammograms performed and cervical cancer diagnoses. Conclusions The COVID-19 period in 2020 significantly impacted screening, diagnosis, treatment for breast and cervical cancer.

Background Patients in serious condition due to COVID-19 often require special care in intensive care units (ICUs). This disease has affected over 758 million people and resulted in 6.8 million deaths worldwide. Additionally, the progression of the disease may vary from individual to individual, that is, it is essential to identify the clinical parameters that indicate a good prognosis for the patient. Machine learning (ML) algorithms have been used for analyzing complex medical data and identifying prognostic indicators. However, there is still an urgent need for a model to elucidate the predictors related to patient outcomes. Therefore, this research aimed to verify, through ML, the variables involved in the discharge of patients admitted to the ICU due to COVID-19. Methods In this study, 126 variables were collected with information on demography, hospital length stay and outcome, chronic diseases and tumors, comorbidities and risk factors, complications and adverse events, health care, and vital indicators of patients admitted to an ICU in southern Brazil. These variables were filtered and then selected by a ML algorithm known as decision trees to identify the optimal set of variables for predicting patient discharge using logistic regression. Finally, a confusion matrix was performed to evaluate the model’s performance for the selected variables. Results Of the 532 patients evaluated, 180 were discharged: female (16.92%), with a central venous catheter (23.68%), with a bladder catheter (26.13%), and with an average of 8.46- and 23.65-days using bladder catheter and submitted to mechanical ventilation, respectively. In addition, the chances of discharge increase by 14% for each additional day in the hospital, by 136% for female patients, 716% when there is no bladder catheter, and 737% when no central venous catheter is used. However, the chances of discharge decrease by 3% for each additional year of age and by 9% for each other day of mechanical ventilation. The performance of the training data presented a balanced accuracy of 0.81, sensitivity of 0.74, specificity of 0.88, and the kappa value was 0.64. The test performance had a balanced accuracy of 0.85, sensitivity 0.75, specificity 0.95, and kappa value of 0.73. The McNemar test found that there were no significant differences in the error rates in the training and test data, suggesting good classification. This work showed that female, the absence of a central venous catheter and bladder catheter, shorter mechanical ventilation, and bladder catheter duration were associated with a greater chance of hospital discharge. These results may help develop measures that lead to a good prognosis for the patient.

Objective: Despite significant advancements in understanding risk factors and treatment strategies, ischemic heart disease (IHD) remains the leading cause of mortality worldwide, particularly within specific regions in Brazil, where the disease is a burden. Therefore, the aim of this study was to estimate the risk of hospitalization and mortality from IHD in the state of Paraná (Brazil), using spatial analysis to identify areas with higher risk based on socioeconomic, demographic and health variables. Methods: This is an ecological study based on secondary and retrospective IHD hospitalization and mortality data obtained from the Brazilian Hospitalization and Mortality Information Systems during the 2010–2021 period. Data were analyzed for 399 municipalities and 22 health regions in the state of Paraná. To assess the spatial patterns of the disease and identify relative risk (RR) areas, we constructed a risk model by Bayesian inference using the R-INLA and SpatialEpi packages in R software. Results: A total of 333,229 hospitalizations and 73,221 deaths occurred in the analyzed period, and elevated RR of hospitalization (RR = 27.412, CI 21.801; 34.466) and mortality (RR = 15.673, CI 2.148; 114.319) from IHD occurred in small-sized municipalities. In addition, medium-sized municipalities also presented elevated RR of hospitalization (RR = 6.533, CI 1.748; 2.006) and mortality (RR = 6.092, CI 1.451; 2.163) from IHD. Hospitalization and mortality rates were higher in white men aged 40–59 years. A negative association was found between Municipal Performance Index (IPDM) and IHD hospitalization and mortality. Conclusion: Areas with increased risk of hospitalization and mortality from IHD were found in small and medium-sized municipalities in the state of Paraná, Brazil. These results suggest a deficit in health care attention for IHD cases in these areas, potentially due to a low distribution of health care resources.

Background: Mortality resulting from coronary artery disease (CAD) among women is a complex issue influenced by many factors that encompass not only biological distinctions but also sociocultural, economic, and healthcare-related components. Understanding these factors is crucial to enhance healthcare provisions. Therefore, this study seeks to identify the social and clinical variables related to the risk of mortality caused by CAD in women aged 50 to 79 years old in Paraná state, Brazil, between 2010 and 2019. Methods: This is an ecological study based on secondary data sourced from E-Gestor, IPARDES, and DATASUS. We developed a model that integrates both raw and standardized coronary artery disease (CAD) mortality rates, along with sociodemographic and healthcare service variables. We employed Bayesian spatiotemporal analysis with Markov Chain Monte Carlo simulations to assess the relative risk of CAD mortality, focusing specifically on women across the state of Paraná. Results: A total of 14,603 deaths from CAD occurred between 2010 and 2019. Overall, temporal analysis indicates that the risk of CAD mortality decreased by around 22.6% between 2010 (RR of 1.06) and 2019 (RR of 0.82). This decline was most prominent after 2014. The exercise stress testing rate, accessibility of cardiology centers, and IPARDES municipal performance index contributed to the reduction of CAD mortality by approximately 4%, 8%, and 34%, respectively. However, locally, regions in the Central-West, Central-South, Central-East, and Southern regions of the Central-North parts of the state exhibited risks higher-than-expected. Conclusion: In the last decade, CAD-related deaths among women in Paraná state decreased. This was influenced by more exercise stress testing, better access to cardiology centers, improved municipal performance index. Yet, elevated risks of deaths persist in certain regions due to medical disparities and varying municipal development. Therefore, prioritizing strategies to enhance women’s access to cardiovascular healthcare in less developed regions is crucial.

Introduction Emergency medicine (EM) is a growing field in Sub-Saharan Africa. Characterising the current capacity of hospitals to provide emergency care is important in identifying gaps and future directions of growth. This study aimed to characterise the ability of emergency units (EU) to provide emergency care in the Kilimanjaro region in Northern Tanzania.Methods This was a cross-sectional study conducted at 11 hospitals with emergency care capacity in three districts in the Kilimanjaro region of Northern Tanzania assessed in May 2021. An exhaustive sampling approach was used, whereby all hospitals within the three-district area were surveyed. Hospital representatives were surveyed by two EM physicians using the Hospital Emergency Assessment tool developed by the WHO; data were analysed in Excel and STATA.Results All hospitals provided emergency services 24 hours a day. Nine had a designated area for emergency care, four had a core of fixed providers assigned to the EU, two lacked a protocol for systematic triage. For Airway and Breathing interventions, oxygen administration was adequate in 10 hospitals, yet manual airway manoeuvres were only adequate in six and needle decompression in two. For Circulation interventions, fluid administration was adequate in all facilities, yet intraosseous access and external defibrillation were each only available in two. Only one facility had an ECG readily available in the EU and none was able to administer thrombolytic therapy. For trauma interventions, all facilities could immobilise fractures, yet lacked interventions such as cervical spinal immobilisation and pelvic binding. These deficiencies were primarily due to lack of training and resources.Conclusion Most facilities perform systematic triage of emergency patients, though major gaps were found in the diagnosis and treatment of acute coronary syndrome and initial stabilisation manoeuvres of patients with trauma. Resource limitations were primarily due to equipment and training deficiencies. We recommend the development of future interventions in all levels of facilities to improve the level of training.