Electromyography as a tool to motion analysis for people with Amyotrophic Lateral Sclerosis: A protocol for a systematic review.

Biomechanical analysis of human movement plays an essential role in understanding functional changes in people with Amyotrophic Lateral Sclerosis (ALS), providing information on muscle impairment. Studies suggest that surface electromyography (sEMG) may be able to quantify muscle activity, identify levels of fatigue, assess muscle strength, and monitor variation in limb movement. In this article, a systematic review protocol will analyze the psychometric properties of the sEMG regarding the clinical data on the skeletal muscles of people with ALS. This protocol uses the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodological tool. A specific field structure was defined to reach each phase. Nine scientific databases (PubMed, Web of Science, Embase, Elsevier, IEEE, Google Scholar, SciELO, PEDro, LILACS E CENTRAL) were searched. The framework developed will extract data (i.e. study information, sample information, sEMG information, intervention, and outcomes) from the selected studies using a rigorous approach. The data will be described quantitatively using frequency and trend analysis methods, and heterogeneity between the included studies will be assessed using the I2 test. The risk of bias will be summarized using the most recent prediction model risk of bias assessment tool. Be sure to include relevant statistics here, such as sample sizes, response rates, P values or Confidence Intervals. Be specific (by stating the value) rather than general (eg, "there were differences between the groups"). This protocol will map out the construction of a systematic review that will identify and synthesize the advances in movement analysis of people with ALS through sEMG, using data extracted from articles.

Digital dual test syphilis/HIV detection based on Fourier Descriptors of Cyclic Voltammetry curves.

BACKGROUND: Effective and timely detection is vital for mitigating the severe impacts of Sexually Transmitted Infections (STI), including syphilis and HIV. Cyclic Voltammetry (CV) sensors have shown promise as diagnostic tools for these STI, offering a pathway towards cost-effective solutions in primary health care settings. OBJECTIVE: This study aims to pioneer the use of Fourier Descriptors (FDs) in analyzing CV curves as 2D closed contours, targeting the simultaneous detection of syphilis and HIV. METHODS: Raw CV signals are filtered, resampled, and transformed into 2D closed contours for FD extraction. Essential shape characteristics are captured through selected coefficients. A complementary geometrical analysis further extracts features like curve areas and principal axes lengths from CV curves. A Mahalanobis Distance Classifier is employed for differentiation between patient and control groups. RESULTS: The evaluation of the proposed method revealed promising results with classification performance metrics such as Accuracy and F1-Score consistently achieving values rounded to 0.95 for syphilis and 0.90 for HIV. These results underscore the potential efficacy of the proposed approach in differentiating between patient and control samples for STI detection. CONCLUSION: By integrating principles from biosensors, signal processing, image processing, machine learning, and medical diagnostics, this study presents a comprehensive approach to enhance the detection of both syphilis and HIV. This setts the stage for advanced and accessible STI diagnostic solutions.

Assessment of the Clinical and Functional Health Status of Patients with Amyotrophic Lateral Sclerosis during the COVID-19 Pandemic in Brazil Using Telemedicine.

This study aimed to monitor the clinical and functional progression of patients with amyotrophic lateral sclerosis (ALS) and adjust ventilatory support during the COVID-19 pandemic in Brazil using telemedicine. This longitudinal case series included five evaluations from January 2019 to June 2021. The first and second assessments were performed in person and consisted of pulmonary function, respiratory muscle strength, functionality (ALS Functional Rating Scale-Revised [ALSFRS-R]) and disease staging (King's College criteria). The use of non-invasive ventilation (NIV), ALSFRS-R, and disease staging were assessed in the third, fourth, and fifth assessments during the COVID-19 pandemic, using telemedicine. The rate of functional decline was calculated by the difference in the total score of ALSFRS-R between evaluations. A cutoff of 0.77 in the ALSFRS-R was used to characterize the speed of functional decline. Eleven patients (mean age of 51 years, eight males) were assessed. The total score of the ALSFRS-R (p < 0.01) and its motor domain (p < 0.01) reduced significantly during the pandemic. NIV prescription increased from 54.4% to 83.3%. Telemedicine helped with the clinical and functional follow-up of patients with ALS.

Ensemble-imbalance-based classification for amyotrophic lateral sclerosis prognostic prediction: identifying short-survival patients at diagnosis.

Prognosticating Amyotrophic Lateral Sclerosis (ALS) presents a formidable challenge due to patients exhibiting different onset sites, progression rates, and survival times. In this study, we have developed and evaluated Machine Learning (ML) algorithms that integrate Ensemble and Imbalance Learning techniques to classify patients into Short and Non-Short survival groups based on data collected during diagnosis. We aimed to identify individuals at high risk of mortality within 24 months of symptom onset through analysis of patient data commonly encountered in daily clinical practice. Our Ensemble-Imbalance approach underwent evaluation employing six ML algorithms as base classifiers. Remarkably, our results outperformed those of individual algorithms, achieving a Balanced Accuracy of 88% and a Sensitivity of 96%. Additionally, we used the Shapley Additive Explanations framework to elucidate the decision-making process of the top-performing model, pinpointing the most important features and their correlations with the target prediction. Furthermore, we presented helpful tools to visualize and compare patient similarities, offering valuable insights. Confirming the obtained results, our approach could aid physicians in devising personalized treatment plans at the time of diagnosis or serve as an inclusion/exclusion criterion in clinical trials.

Artificial intelligence applied to analyzes during the pandemic: COVID-19 beds occupancy in the state of Rio Grande do Norte, Brazil.

The COVID-19 pandemic is already considered one of the biggest global health crises. In Rio Grande do Norte, a Brazilian state, the RegulaRN platform was the health information system used to regulate beds for patients with COVID-19. This article explored machine learning and deep learning techniques with RegulaRN data in order to identify the best models and parameters to predict the outcome of a hospitalized patient. A total of 25,366 bed regulations for COVID-19 patients were analyzed. The data analyzed comes from the RegulaRN Platform database from April 2020 to August 2022. From these data, the nine most pertinent characteristics were selected from the twenty available, and blank or inconclusive data were excluded. This was followed by the following steps: data pre-processing, database balancing, training, and test. The results showed better performance in terms of accuracy (84.01%), precision (79.57%), and F1-score (81.00%) for the Multilayer Perceptron model with Stochastic Gradient Descent optimizer. The best results for recall (84.67%), specificity (84.67%), and ROC-AUC (91.6%) were achieved by Root Mean Squared Propagation. This study compared different computational methods of machine and deep learning whose objective was to classify bed regulation data for patients with COVID-19 from the RegulaRN Platform. The results have made it possible to identify the best model to help health professionals during the process of regulating beds for patients with COVID-19. The scientific findings of this article demonstrate that the computational methods used applied through a digital health solution, can assist in the decision-making of medical regulators and government institutions in situations of public health crisis.

Half dose ChAdOx1 nCoV-19 vaccine was equivalent to full doses to reduce moderate and severe COVID-19 cases.

Objectives: Previously, we presented the effectiveness of ChAdOx1 nCoV-19 half-dose (HD) immunization for preventing new COVID-19 cases. Here, we evaluated the administration of an HD of ChAdOx1 nCoV-19 in the primary immunization protocol (up to two doses) in reducing moderate and severe cases, hospitalizations, and deaths when compared to the administration of full doses (FD) after a long-term follow-up. Methods: We evaluated data from 29,469 participants between January 2021 and November 2022 who received an HD or FD vaccine and crossed this information with their medical records to identify those who developed moderate or severe cases. All participants were classified into four groups according to their immunization status and followed 500 days after the last vaccine administration. Results: The propensity-score matching analysis indicates that the administration of the two HDs of ChAdOx1 nCoV-19 was equivalent to the use of two FDs to reduce moderate and severe COVID-19 cases. The relative risk of being infected and developing moderate or severe conditions after the administration of at least one HD or FD was similar 150 or 500 days after the administration of the immunizers. Conclusion: Administering two HDs can be used safely as a cost-effective alternative to the primary immunization protocol.

Text mining analysis to understand the impact of online news on public health response: case of syphilis epidemic in Brazil.

Background: To effectively combat the rising incidence of syphilis, the Brazilian Ministry of Health (MoH) created a National Rapid Response to Syphilis with actions aimed at bolstering epidemiological surveillance of acquired, congenital syphilis, and syphilis during pregnancy complemented with communication activities to raise population awareness and to increase uptake of testing that targeted mass media outlets from November 2018 to March 2019 throughout Brazil, and mainly areas with high rates of syphilis. This study analyzes the volume and quality of online news content on syphilis in Brazil between 2015 and 2019 and examines its effect on testing. Methods: The collection and processing of online news were automated by means of a proprietary digital health ecosystem established for the study. We applied text data mining techniques to online news to extract patterns from categories of text. The presence and combination of such categories in collected texts determined the quality of news that were analyzed to classify them as high-, medium-and low-quality news. We examined the correlation between the quality of news and the volume of syphilis testing using Spearman's Rank Correlation Coefficient. Results: 1,049 web pages were collected using a Google Search API, of which 630 were categorized as earned media. We observed a steady increase in the number of news on syphilis in 2015 (n = 18), 2016 (n = 26), and 2017 (n = 42), with a substantial rise in the number of news in 2018 (n = 107) and 2019 (n = 437), although the relative proportion of high-quality news remained consistently high (77.6 and 70.5% respectively) and in line with similar years. We found a correlation between news quality and syphilis testing performed in primary health care with an increase of 82.32, 78.13, and 73.20%, respectively, in the three types of treponemal tests used to confirm an infection. Conclusion: Effective communication strategies that lead to dissemination of high quality of information are important to increase uptake of public health policy actions.

The prevalence of risk for hearing impairment in newborns with congenital syphilis in a newborn hearing screening program (NHS).

Objective: To study the prevalence of risk for hearing impairment in neonates with congenital syphilis in a newborn hearing screening program. Study design: The study design is retrospective, documentary, and is cross-sectional. The sample consisted of newborns who were born between January 2019 and December 2021 and who underwent neonatal hearing screening in a public maternity hospital. Demographic data and the presence and specification of risk indicators for hearing impairment (RIHL) were collected. In retest cases, the results and the final score were also collected. For data analysis, the Kruskal-Wallis and Conover-Iman post-hoc tests were used, comparing the groups that passed and failed the hearing screening that had RIHL, using a significance level of p of <0.5. Results: Among the RIHL observed in the sample, prematurity was more frequent in newborns who passed the screening (55.26%) than in those who failed the test (45.67%). Congenital syphilis was the ninth most frequent RIHL (8.04%) among the newborns who passed the test and the 15th factor (3.03%), with the highest occurrence in those who failed the hearing screening. When comparing the two groups (pass and fail), we found significant differences (p < 0.05) between them. Conclusion: Congenital syphilis was the ninth risk indicator for the most common hearing impairment and, in isolation, did not present a risk for failure in neonatal hearing screening. Notably, congenital syphilis can cause late hearing loss during child development. Thus, there is an indication of audiological monitoring of these neonates.

Evaluation of massive education in prison health: a perspective of health care for the person deprived of freedom in Brazil.

Education, with an emphasis on prison health, has acted as a policy inducing changes in work processes, which the Brazilian National Health System (SUS) has used, and which is present in permanent health education, which promotes health care for people deprived of liberty. This article aims to present an analysis of the impacts of the strategy of massive education on prison health in Brazil from the perspective of health professionals and other actors operating in the Brazilian prison system. The data used in the study come from a questionnaire consisting of 37 questions applied nationwide between March and June 2022. Responses were collected from students who completed the course "Health Care for People Deprived of Freedom" of the learning pathway "Prison System", available in the Virtual Learning Environment of the Brazilian Health System (AVASUS). This course was offered nationally, whose adhesion (enrollment) occurred spontaneously, i.e., the course was not a mandatory. The data collected allowed us to analyze the impacts of massive education on prison health. The study also shows that the search for the course is made by several areas of knowledge, with a higher incidence in the health area, but also in other areas, such as humanities, which also work directly with the guarantee of the rights of people deprived of liberty, which are professionals in the areas of social work, psychology, and education. The analysis based on the data suggests that the massive education mediated by technology through the courses of the learning pathway, besides disseminating knowledge-following the action plan of the 2030 Agenda of the United Nations Educational, Scientific and Cultural Organization (UNESCO)-, are an effective tool to promote resilience in response to prison health and care demands of people deprived of liberty.

Computational methods applied to syphilis: where are we, and where are we going?

Syphilis is an infectious disease that can be diagnosed and treated cheaply. Despite being a curable condition, the syphilis rate is increasing worldwide. In this sense, computational methods can analyze data and assist managers in formulating new public policies for preventing and controlling sexually transmitted infections (STIs). Computational techniques can integrate knowledge from experiences and, through an inference mechanism, apply conditions to a database that seeks to explain data behavior. This systematic review analyzed studies that use computational methods to establish or improve syphilis-related aspects. Our review shows the usefulness of computational tools to promote the overall understanding of syphilis, a global problem, to guide public policy and practice, to target better public health interventions such as surveillance and prevention, health service delivery, and the optimal use of diagnostic tools. The review was conducted according to PRISMA 2020 Statement and used several quality criteria to include studies. The publications chosen to compose this review were gathered from Science Direct, Web of Science, Springer, Scopus, ACM Digital Library, and PubMed databases. Then, studies published between 2015 and 2022 were selected. The review identified 1,991 studies. After applying inclusion, exclusion, and study quality assessment criteria, 26 primary studies were included in the final analysis. The results show different computational approaches, including countless Machine Learning algorithmic models, and three sub-areas of application in the context of syphilis: surveillance (61.54%), diagnosis (34.62%), and health policy evaluation (3.85%). These computational approaches are promising and capable of being tools to support syphilis control and surveillance actions.

Digital health solution for monitoring and surveillance of Amyotrophic Lateral Sclerosis in Brazil.

Amyotrophic Lateral Sclerosis (ALS) is a complex and rare neurodegenerative disease given its heterogeneity. Despite being known for many years, few countries have accurate information about the characteristics of people diagnosed with ALS, such as data regarding diagnosis and clinical features of the disease. In Brazil, the lack of information about ALS limits data for the research progress and public policy development that benefits people affected by this health condition. In this context, this article aims to show a digital health solution development and application for research, intervention, and strengthening of the response to ALS in the Brazilian Health System. The proposed solution is composed of two platforms: the Brazilian National ALS Registry, responsible for the data collection in a structured way from ALS patients all over Brazil; and the Brazilian National ALS Observatory, responsible for processing the data collected in the National Registry and for providing a monitoring room with indicators on people diagnosed with ALS in Brazil. The development of this solution was supported by the Brazilian Ministry of Health (MoH) and was carried out by a multidisciplinary team with expertise in ALS. This solution represents a tool with great potential for strengthening public policies and stands out for being the only public database on the disease, besides containing innovations that allow data collection by health professionals and/or patients. By using both platforms, it is believed that it will be possible to understand the demographic and epidemiological data of ALS in Brazil, since the data will be able to be analyzed by care teams and also by public health managers, both in the individual and collective monitoring of people living with ALS in Brazil.

Analyzing a national health surveillance strategy to reduce mother-to-child transmission of syphilis: The case of Brazilian investigation committees.

Objectives: This study aimed to analyze the relevance of investigation committees in eliminating mother-to-child transmission of syphilis in Brazil. Methods: Questionnaires and interviews were conducted with health managers of 25 Brazilian Federative Units and Brazil's Federal District. Data were analyzed using Bardin's content analysis technique and subsequently compared with the global prescriptions for syphilis response of the Pan American Health Organization, World Health Organization, and recent research publications examining the course of syphilis in Brazil, in Brazilian regions, and globally. Results: While the investigation committees drew on the successful experience of those in reducing maternal mortality, which helped the country achieve the Millennium Development Goals, they are not demonstrated to be sufficient for preventing mother-to-child transmission of syphilis. The committees' systematic and bureaucratic agenda has not been efficient in managing avoidable factors for syphilis, nor do they operate in the scope of the integration of surveillance and care actions, as recommended by the health policy. Conclusion: The committees' model needs to be reviewed in the context of Brazil's National Health System. The research process should be rescaled in order to remain a cornerstone for the induction of health policy that integrates surveillance and healthcare across Brazilian Federative Units. The advancement toward an automated case management model becomes relevant for the country to meet global commitments to eliminate congenital syphilis transmission and achieve the goals outlined in the 2030 Agenda.

Effects of a self-care educational program via telerehabilitation on quality of life and caregiver burden in amyotrophic lateral sclerosis: a single-blinded randomized clinical trial protocol.

Introduction: The implementation of a telerehabilitation protocol for self-care in the routine of caregivers of individuals with amyotrophic lateral sclerosis (ALS) has been associated with reduced levels of stress and improved quality of life. Moreover, it may reduce the difficulty of traveling to perform physical or other self-care activities. Thus, this study designed a clinical trial protocol to investigate the effects of a self-care education program via telerehabilitation on the burden and quality of life of caregivers of individuals with ALS. Methods: This single-blinded randomized clinical trial will recruit 26 caregivers and randomly allocate them to the experimental (EG = 13) or control group (CG = 13). The EG will receive an informative booklet and participate in a 6-week synchronous telerehabilitation program with a neuropsychologist, nutritionist, and physiotherapist to discuss physical and mental health. The CG will receive an informative booklet on self-care and physical activity and weekly phone calls for 6 weeks to solve questions about the booklet. Outcomes will include the caregiver burden (Zarit scale), quality of life (World Health Organization Quality of Life BREF), pain (McGill Pain Questionnaire), stress (Perceived Stress Scale), and depression (Beck Depression Inventory), which will be evaluated at the baseline after the six-week program and 30 days after the program. Additionally, we will assess daily the nocturnal awakenings, sleep patterns, level of physical activity, and heart rate variability. Discussion: This study aimed to investigate the effectiveness of telerehabilitation for caregivers of individuals with ALS. If effective, this program could be disseminated among health professionals, increasing the possibility of remotely monitoring individuals with difficulty performing physical activities. Trial registration number: NCT05884034 (clinicaltrials.gov).

Digital Alternative Communication for Individuals with Amyotrophic Lateral Sclerosis: What We Have.

Amyotrophic Lateral Sclerosis is a disease that compromises the motor system and the functional abilities of the person in an irreversible way, causing the progressive loss of the ability to communicate. Tools based on Augmentative and Alternative Communication are essential for promoting autonomy and improving communication, life quality, and survival. This Systematic Literature Review aimed to provide evidence on eye-image-based Human-Computer Interaction approaches for the Augmentative and Alternative Communication of people with Amyotrophic Lateral Sclerosis. The Systematic Literature Review was conducted and guided following a protocol consisting of search questions, inclusion and exclusion criteria, and quality assessment, to select primary studies published between 2010 and 2021 in six repositories: Science Direct, Web of Science, Springer, IEEE Xplore, ACM Digital Library, and PubMed. After the screening, 25 primary studies were evaluated. These studies showcased four low-cost, non-invasive Human-Computer Interaction strategies employed for Augmentative and Alternative Communication in people with Amyotrophic Lateral Sclerosis. The strategies included Eye-Gaze, which featured in 36% of the studies; Eye-Blink and Eye-Tracking, each accounting for 28% of the approaches; and the Hybrid strategy, employed in 8% of the studies. For these approaches, several computational techniques were identified. For a better understanding, a workflow containing the development phases and the respective methods used by each strategy was generated. The results indicate the possibility and feasibility of developing Human-Computer Interaction resources based on eye images for Augmentative and Alternative Communication in a control group. The absence of experimental testing in people with Amyotrophic Lateral Sclerosis reiterates the challenges related to the scalability, efficiency, and usability of these technologies for people with the disease. Although challenges still exist, the findings represent important advances in the fields of health sciences and technology, promoting a promising future with possibilities for better life quality.

Osteoporosis screening using machine learning and electromagnetic waves.

Osteoporosis is a disease characterized by impairment of bone microarchitecture that causes high socioeconomic impacts in the world because of fractures and hospitalizations. Although dual-energy X-ray absorptiometry (DXA) is the gold standard for diagnosing the disease, access to DXA in developing countries is still limited due to its high cost, being present only in specialized hospitals. In this paper, we analyze the performance of Osseus, a low-cost portable device based on electromagnetic waves that measures the attenuation of the signal that crosses the medial phalanx of a patient's middle finger and was developed for osteoporosis screening. The analysis is carried out by predicting changes in bone mineral density using Osseus measurements and additional common risk factors used as input features to a set of supervised classification models, while the results from DXA are taken as target (real) values during the training of the machine learning algorithms. The dataset consisted of 505 patients who underwent osteoporosis screening with both devices (DXA and Osseus), of whom 21.8% were healthy and 78.2% had low bone mineral density or osteoporosis. A cross-validation with k-fold = 5 was considered in model training, while 20% of the whole dataset was used for testing. The obtained performance of the best model (Random Forest) presented a sensitivity of 0.853, a specificity of 0.879, and an F1 of 0.859. Since the Random Forest (RF) algorithm allows some interpretability of its results (through the impurity check), we were able to identify the most important variables in the classification of osteoporosis. The results showed that the most important variables were age, body mass index, and the signal attenuation provided by Osseus. The RF model, when used together with Osseus measurements, is effective in screening patients and facilitates the early diagnosis of osteoporosis. The main advantages of such early screening are the reduction of costs associated with exams, surgeries, treatments, and hospitalizations, as well as improved quality of life for patients.

Salus Platform: A Digital Health Solution Tool for Managing Syphilis Cases in Brazil-A Comparative Analysis.

(1) Introduction: Syphilis is a sexually transmitted infection (STI) that constitutes a serious public health problem in Brazil and worldwide; (2) Methods: This was a descriptive and exploratory study that sought to analyze and compare the characteristics of Brazilian health systems with a new platform (Salus) developed by the Laboratory of Technological Innovation in Health in the scope of notification and management of disease data, including syphilis. In addition, this analysis aimed to assess whether Salus fully meets the necessary data management fields and can be indicated as a tool to improve health management in the context of syphilis in Brazil. (3) Results: In this study, the Salus functionalities were demonstrated and compared with the current Brazilian systems by discovering the existing gaps in the evaluated systems. The gaps found may explain the delay in meeting demands, the difficulty of making routine therapeutic follow-ups, in addition to interference with the vital purpose of follow-up in the epidemiological surveillance of diseases. As a result, Salus demonstrates functionalities that surpass all others and meet case management demands in a superior way to the systems currently used in the country. (4) Conclusions: The Brazilian health information systems related to the response to syphilis do not fulfill the purpose for which they were developed. Instead, they contribute to the fragmentation of health data and information, delays in diagnosis, incomplete case management, and loss of data due to inconsistencies and inadequate reporting. In addition, they are systems without interconnection, which do not articulate epidemiological surveillance actions with primary health care. All these factors may be obscuring accurate data on syphilis in Brazil, resulting in high and unnecessary public spending and late care for users of the Unified Health System (SUS).

Interventions of Brazil's more doctors program through continuing education for Primary Health Care.

Introduction: Brazil's More Doctors Program, in its training axis, aims to improve medical training for Primary Health Care through interventions related to the reality of the territory. The research presented here analyzed the interventions implemented by Brazil's More Doctors Program physicians, members of the Family Health Continuing Education Program, and the relationship with Primary Health Care programmatic actions. Methodology: The research conducted made use of Text and Data Mining and content analysis. In total, 2,159 reports of interventions from 942 final papers were analyzed. The analysis process was composed of the formation of the corpus; exploration of the materials through text mining; and analysis of the results by inference and interpretation. Results: It was observed that 57% of the physicians worked in the Northeast Region, which was also the region with the most interventions (66.8%). From the analysis of the bigrams, trigrams, and quadrigrams, four constructs were formed: "women's health," "child health," "chronic non-communicable diseases," and "mental health." Terms related to improving access, quality of care, teamwork, and reception were also present among the N-grams. Discussion: The interventions carried out are under the programmatic actions recommended by the Brazilian Ministry of Health for Primary Health Care, also addressing cross-cutting aspects such as Reception, Teamwork, Access Improvement, and Quality of Care, which suggests that the training experience in the Family Health Continuing Education Program reflects on the way these professionals act.

Analysis of the Impact of Communication Campaigns under the Project "Syphilis No": A National Tool for Inducing and Promoting Health.

Syphilis is increasingly prevalent around the world as a result of complex factors. In Brazil, the government declared a syphilis epidemic in 2016 and then set a strategic agenda to respond to this serious public health problem. In a joint effort, Brazil's Federal Court of Accounts (TCU) recommended that novel and diversified health communication strategies should be developed, which the "Syphilis No" project (SNP) later conducted through nationwide mass communication campaigns. We performed exploratory data analysis to identify and understand the results of three health communication campaigns by considering syphilis data trends in Brazil. The SNP, by using traditional and innovative means of communication, focused on multiple target audiences to encourage behavior changes through awareness and syphilis knowledge acquisition via the internet. In addition, the SNP disseminated information on syphilis testing, prevention, and treatment through social media and multiple media outlets. We observed that the period of the health campaigns corresponded to the period when the syphilis testing uptake increased and the number of reported cases dropped. Thus, our findings indicate that public health responses could substantially benefit from the use of health communication campaigns as a tool for health promotion, education, and transformation.

Development of a Cyclic Voltammetry-Based Method for the Detection of Antigens and Antibodies as a Novel Strategy for Syphilis Diagnosis.

The improvement of laboratory diagnosis is a critical step for the reduction of syphilis cases around the world. In this paper, we present the development of an impedance-based method for detecting T. pallidum antigens and antibodies as an auxiliary tool for syphilis laboratory diagnosis. We evaluate the voltammetric signal obtained after incubation in carbon or gold nanoparticle-modified carbon electrodes in the presence or absence of Poly-L-Lysine. Our results indicate that the signal obtained from the electrodes was sufficient to distinguish between infected and non-infected samples immediately (T0') or 15 min (T15') after incubation, indicating its potential use as a point-of-care method as a screening strategy.

Sentiment Analysis in Understanding the Potential of Online News in the Public Health Crisis Response.

This study analyzes online news disseminated throughout the pre-, during-, and post-intervention periods of the "Syphilis No!" Project, which was developed in Brazil between November 2018 and March 2019. We investigated the influence of sentiment aspects of news to explore their possible relationships with syphilis testing data in response to the syphilis epidemic in Brazil. A dictionary-based technique (VADER) was chosen to perform sentiment analysis considering the Brazilian Portuguese language. Finally, the data collected were used in statistical tests to obtain other indicators, such as correlation and distribution analysis. Of the 627 news items, 198 (31.58%) were classified as a sentiment of security (TP2; stands for the news type 2), whereas 429 (68.42%) were classified as sentiments that instilled vulnerability (TP3; stands for the news type 3). The correlation between the number of syphilis tests and the number of news types TP2 and TP3 was verified from (i) 2015 to 2017 and (ii) 2018 to 2019. For the TP2 type news, in all periods, the p-values were greater than 0.05, thus generating inconclusive results. From 2015 to 2017, there was an ρ = 0.33 correlation between TP3 news and testing data (p-value = 0.04); the years 2018 and 2019 presented a ρ = 0.67 correlation between TP3 news and the number of syphilis tests performed per month, with p-value = 0.0003. In addition, Granger's test was performed between TP3 news and syphilis testing, which resulted in a p-value = 0.002, thus indicating the existence of Granger causality between these time series. By applying natural language processing to sentiment and informational content analysis of public health campaigns, it was found that the most substantial increase in testing was strongly related to attitude-inducing content (TP3).