Consumption of antibiotics in Brazil - an analysis of sales data between 2014 and 2019.

BACKGROUND: Antibiotic consumption is a driver for the increase of antimicrobial resistance. The objective of this study is to analyze variations in antibiotic consumption and its appropriate use in Brazil from 2014 to 2019. METHODS: We conducted a time series study using the surveillance information system database (SNGPC) from the Brazilian Health Regulatory Agency. Antimicrobials sold in retail pharmacies were evaluated. All antimicrobials recorded for systemic use identified by the active ingredient were eligible. Compounded products and formulations for topic use (dermatological, gynecological, and eye/ear treatments) were excluded. The number of defined daily doses (DDDs)/1,000 inhabitants/day for each antibiotic was attributed. The number of DDDs per 1,000 inhabitants per day (DDIs) was used as a proxy for consumption. Results were stratified by regions and the average annual percentage change in the whole period studied was estimated. We used the WHO Access, Watch, and Reserve (AWaRe) framework to categorize antimicrobial drugs. RESULTS: An overall increase of 30% in consumption from 2014 to 2019 was observed in all Brazilian regions. Amoxicillin, azithromycin and cephalexin were the antimicrobials more consumed, with the Southeast region responsible for more than 50% of the antibiotic utilization. Among all antimicrobials analyzed 45.0% were classified as watch group in all Brazilian regions. CONCLUSION: We observed a significant increase in antibiotics consumption from 2014 to 2019 in Brazil restricted to the Northeast and Central West regions. Almost half of the antibiotics consumed in Brazil were classified as watch group, highlighting the importance to promote rational use in this country.

A Survey of MPSoC Management toward Self-Awareness.

Managing Multi-Processor Systems-on-Chip (MPSoCs) is becoming increasingly complex as demands for advanced capabilities rise. This complexity is due to the involvement of more processing elements and resources, leading to a higher degree of heterogeneity throughout the system. Over time, management schemes have evolved from simple to autonomous systems with continuous control and monitoring of various parameters such as power distribution, thermal events, fault tolerance, and system security. Autonomous management integrates self-awareness into the system, making it aware of its environment, behavior, and objectives. Self-Aware Cyber-Physical Systems-on-Chip (SA-CPSoCs) have emerged as a concept to achieve highly autonomous management. Communication infrastructure is also vital to SoCs, and Software-Defined Networks-on-Chip (SDNoCs) can serve as a base structure for self-aware systems-on-chip. This paper presents a survey of the evolution of MPSoC management over the last two decades, categorizing research works according to their objectives and improvements. It also discusses the characteristics and properties of SA-CPSoCs and explains why SDNoCs are crucial for these systems.

[Feeling analysis on allergen immunotherapy on Twitter using an unsupervised machine learning model]. / Análisis de sentimientos acerca de la inmunoterapia con alérgenos en Twitter mediante un modelo de aprendizaje automático no supervisado.

OBJECTIVE: Analyze feelings about allergen-specific immunotherapy on Twitter using the VADER model VADER (Valence Aware Dictionary and sEntiment Reasoner) model. METHODS: tweets related to specific allergen immunotherapy were obtained through the Twitter Application Programming Interface (API). The keywords "allergy shot" were used between January 1, 2012, and December 31, 2022. The data was processed by removing URLs, usernames, hashtags, multiple spaces, and duplicate tweets. Subsequently, a sentiment analysis was performed using the VADER model. RESULTS: A total of 34,711 tweets were retrieved, of which 1928 were eliminated. Of the remaining 32,783 tweets, 32.41% expressed a negative sentiment, 31.11% expressed a neutral sentiment, and 36.47% expressed a positive sentiment, with an average polarity of 0.02751 (neutral) over the 11-year period. CONCLUSIONS: The average polarity of tweets about allergen-specific immunotherapy is neutral over the 11 years analyzed. There was an annual increase in the average polarity over the years, with 2017, 2018, and 2022 having positive polarity averages. Additionally, the number of tweets decreased over time.

OBJETIVO: Analizar los sentimientos acerca de la inmunoterapia alérgeno-específica en Twitter mediante el modelo VADER (Valence Aware Dictionary and sEntiment Reasoner). MÉTODOS: Se utilizaron tweets relacionados con la inmunoterapia alérgeno-específica obtenidos a través del API (Application Programming Interface) de Twitter. Se incorporaron las palabras clave "allergy shot" en el período comprendido entre el 1 de enero de 2012 y el 31 de diciembre de 2022. Los datos obtenidos fueron procesados, eliminando las URL, nombres de usuarios, hashtags, espacios múltiples y tweets duplicados. Posteriormente, se realizó un análisis de sentimientos utilizando el modelo VADER. RESULTADOS: Se recolectaron 34,711 tweets, de los que se eliminaron 1928. De los 32,783 tweets restantes, se encontró que el 32.41% de los usuarios expresó un sentimiento negativo, el 31.11% un sentimiento neutral y el 36.47% un sentimiento positivo, con una media de polaridad de 0.02751 (neutral) a lo largo de los 11 años. CONCLUSIONES: La polaridad media de los tweets acerca de la inmunoterapia alérgeno-específica es neutral a lo largo de los 11 años analizados. Existe un aumento anual en la polaridad media positiva a lo largo de los años, sobre todo entre 2017, 2018 y 2022. La cantidad de tweets disminuyó con el tiempo.

A new strategy for treating drug-resistant focal aware seizures: thalamic specific nuclei deep brain stimulation. Illustrative case.

BACKGROUND: Focal aware seizures (FASs) are relatively common and frequently pharmaco-resistant. If the seizure onset zone (SOZ) is in eloquent cortical areas, making resective surgery risky and inadvisable, deep brain stimulation (DBS) of the anterior nucleus of the thalamus, which is efficacious in less than half of the cases, has been the main alternative. New targets should be searched to address this deficiency. The present study aims to determine if DBS of different thalamic specific nuclei can modulate the abnormal electrical activity of the SOZ located in their respective cortical projection areas. Herein, the authors present the first patient in an ongoing trial. OBSERVATIONS: A 60-year-old female patient presented with 25-year history of pharmaco-resistant focal aware visual seizures frequently evolving to focal impaired awareness seizures. The SOZ was in the right occipital lobe (positron emission tomography-computed tomography/video electroencephalography). Magnetic resonance imaging was normal. She underwent ipsilateral lateral geniculate nucleus (LGN) DBS procedure. After a 24-month follow-up, seizure frequency decreased by 97%, improving quality of life and daily functioning without complications. LESSONS: This is the first time the LGN has been targeted in humans. The results support the hypothesis that led to this study. This strategy represents a paradigm shift in the way of treating pharmaco-resistant FASs not amenable to resective surgery.

Context-Aware Statistical Dead Reckoning for Localization in IoT Scenarios.

The current trends in 5G and 6G systems anticipate vast communication capabilities and the deployment of massive heterogeneous connectivity with more than a million internet of things (IoT) and other devices per square kilometer and up to ten million gadgets in 6G scenarios. In addition, the new generation of smart industries and the energy of things (EoT) context demand novel, reliable, energy-efficient network protocols involving massive sensor cooperation. Such scenarios impose new demands and opportunities to cope with the ever-growing cooperative dense ad hoc environments. Position location information (PLI) plays a crucial role as an enabler of several location-aware network protocols and applications. In this paper, we have proposed a novel context-aware statistical dead reckoning localization technique suitable for high dense cooperative sensor networks, where direct angle and distance estimations between peers are not required along the route, as in other dead reckoning-based localization approaches, but they are obtainable from the node's context information. Validation of the proposed technique was assessed in several scenarios through simulations, achieving localization errors as low as 0.072 m for the worst case analyzed.

Antimicrobial Consumption from 2017 to 2021 in East Trinidad and Tobago: A Study in the English-Speaking Caribbean.

An antimicrobial consumption (AMC) study was performed in Trinidad and Tobago at the Eastern Regional Health Authority (ERHA). A retrospective, cross-sectional survey was conducted from 1 November 2021 to 30 March 2022. Dosage and package types of amoxicillin, azithromycin, co-amoxiclav, cefuroxime, ciprofloxacin, levofloxacin, moxifloxacin, nitrofurantoin and co-trimoxazole were investigated. Consumption was measured using the World Health Organization's Antimicrobial Resistance and Consumption Surveillance System methodology version 1.0, as defined daily doses (DDD) per 1000 population per day (DID). They were also analyzed using the 'Access', 'Watch' and 'Reserve' classifications. In the ERHA, AMC ranged from 6.9 DID to 4.6 DID. With regards to intravenous formulations, the 'Watch' group displayed increased consumption, from 0.160 DID in 2017 to 0.238 DID in 2019, followed by a subsequent drop in consumption with the onset of the COVID-19 pandemic. Oral co-amoxiclav, oral cefuroxime, oral azithromycin and oral co-trimoxazole were the most highly consumed antibiotics. The hospital started off as the higher consumer of antibiotics, but this changed to the community. The consumption of 'Watch' group antibiotics increased from 2017 to 2021, with a drop in consumption of 'Access' antibiotics and at the onset of COVID-19. Consumption of oral azithromycin was higher in 2021 than 2020.

Mindfulness-Based Intervention and Sexuality: A Systematic Review.

INTRODUCTION: Mindfulness has generated considerable interest in the last two decades in clinical and research settings. The efficacy of mindfulness has been evaluated for the sexual dysfunctions recognized by the DSM-5 and other sexual problems, such as compulsive sexual behavior disorder (CSBD), also known as sex addiction or hypersexuality. Here, we review the evidence for various mindfulness-based treatments as mindfulness-based cognitive-behavioral treatment or mindfulness-based relapse prevention for different problems related to sexuality to respond our question: "Are Mindfulness-Based Treatments (MBT) effective in reducing the symptomatology of sexuality-related disorders?". METHODS: Through a systematic search conducted following the PRISMA guidelines, we found 11 studies that met the inclusion criteria: (I) articles using MBT for sexuality-related problems, (II) clinical population, (III) no date range limits were applied, (IV) only empirical studies were included, (V) language and (VI) quality of studies. RESULTS: Evidence shows that mindfulness practice could be effective for some sexual disorders, such as female sexual arousal/desire disorder. However, due to scarcity of studies on other sexual problems such as situational erectile dysfunction, genitopelvic pain/penetration disorder, childhood sexual abuse or compulsive sexual behavior disorder, the findings cannot be generalized. CONCLUSIONS: Mindfulness-based therapies provides evidence to reduce the symptomatology associated with various sexual problems. However more studies are needed for these sexual problems. By last, future directions and implications are discussed.

HIV Knowledge, Risk Behaviors, and Testing Among Chinese-, Korean-, and Vietnamese-American Women.

The relationship between HIV knowledge and testing behavior is poorly understood among young Chinese-, Korean-, and Vietnamese-American women. This study assesses: (1) levels of HIV/AIDS knowledge, (2) lifetime and annual prevalence of HIV testing, and (3) whether higher levels of HIV knowledge were associated with increased likelihood of testing after controlling for HIV risk behaviors. Fifty-one percent reported lifetime HIV testing (n=117); among those tested, 53% were tested within the past year. A significant and positive association between scores on the HIV Knowledge Questionnaire (HIV KQ-45) and HIV testing was identified. This association was no longer statistically significant after controlling for sexual risk behaviors. Participants were most knowledgeable about HIV symptoms (88.6%) and least knowledgeable about treatment options (56.8%). Future studies should further characterize cultural factors affecting these women's sexual practices, as well develop culturally adapted HIV educational interventions to increase HIV knowledge and testing rates.

Performance evaluation of publish-subscribe systems in IoT using energy-efficient and context-aware secure messages.

BACKGROUND: The Internet of Things (IoT) enables the development of innovative applications in various domains such as healthcare, transportation, and Industry 4.0. Publish-subscribe systems enable IoT devices to communicate with the cloud platform. However, IoT applications need context-aware messages to translate the data into contextual information, allowing the applications to act cognitively. Besides, end-to-end security of publish-subscribe messages on both ends (devices and cloud) is essential. However, achieving security on constrained IoT devices with memory, payload, and energy restrictions is a challenge. CONTRIBUTION: Messages in IoT need to achieve both energy efficiency and secure delivery. Thus, the main contribution of this paper refers to a performance evaluation of a message structure that standardizes the publish-subscribe topic and payload used by the cloud platform and the IoT devices. We also propose a standardization for the topic and payload for publish-subscribe systems. CONCLUSION: The messages promote energy efficiency, enabling ultra-low-power and high-capacity devices and reducing the bytes transmitted in the IoT domain. The performance evaluation demonstrates that publish-subscribe systems (namely, AMQP, DDS, and MQTT) can use our proposed energy-efficient message structure on IoT. Additionally, the message system provides end-to-end confidentiality, integrity, and authenticity between IoT devices and the cloud platform.

Towards ubiquitous requirements engineering through recommendations based on context histories.

The growing technological advance is causing constant business changes. The continual uncertainties in project management make requirements engineering essential to ensure the success of projects. The usual exponential increase of stakeholders throughout the project suggests the application of intelligent tools to assist requirements engineers. Therefore, this article proposes Nhatos, a computational model for ubiquitous requirements management that analyses context histories of projects to recommend reusable requirements. The scientific contribution of this study is the use of the similarity analysis of projects through their context histories to generate the requirement recommendations. The implementation of a prototype allowed to evaluate the proposal through a case study based on real scenarios from the industry. One hundred fifty-three software projects from a large bank institution generated context histories used in the recommendations. The experiment demonstrated that the model achieved more than 70% stakeholder acceptance of the recommendations.

Abusive language detection in youtube comments leveraging replies as conversational context.

Nowadays, social media experience an increase in hostility, which leads to many people suffering from online abusive behavior and harassment. We introduce a new publicly available annotated dataset for abusive language detection in short texts. The dataset includes comments from YouTube, along with contextual information: replies, video, video title, and the original description. The comments in the dataset are labeled as abusive or not and are classified by topic: politics, religion, and other. In particular, we discuss our refined annotation guidelines for such classification. We report a number of strong baselines on this dataset for the tasks of abusive language detection and topic classification, using a number of classifiers and text representations. We show that taking into account the conversational context, namely, replies, greatly improves the classification results as compared with using only linguistic features of the comments. We also study how the classification accuracy depends on the topic of the comment.

The assessment of leading traits in the taxonomy of the Bacillus cereus group.

Bacillus cereus sensu lato strains (B. cereus group) are widely distributed in nature and have received interest for decades due to their importance in insect pest management, food production and their positive and negative repercussions in human health. Consideration of practical uses such as virulence, physiology, morphology, or ill-defined features have been applied to describe and classify species of the group. However, current comparative studies have exposed inconsistencies between evolutionary relatedness and biological significance among genomospecies of the B. cereus group. Here, the combined analyses of core-based phylogeny and all versus all Average Nucleotide Identity values based on 2116 strains were conducted to update the genomospecies circumscriptions within B. cereus group. These analyses suggested the existence of 57 genomospecies, 37 of which are novel, thus indicating that the taxonomic identities of more than 39% of the analyzed strains should be revised or updated. In addition, we found that whole-genome in silico analyses were suitable to differentiate genomospecies such as B. anthracis, B. cereus and B. thuringiensis. The prevalence of toxin and virulence factors coding genes in each of the genomospecies of the B. cereus group was also examined, using phylogeny-aware methods at wide-genome scale. Remarkably, Cry and emetic toxins, commonly assumed to be associated with B. thuringiensis and emetic B. paranthracis, respectively, did not show a positive correlation with those genomospecies. On the other hand, anthrax-like toxin and capsule-biosynthesis coding genes were positively correlated with B. anthracis genomospecies, despite not being present in all strains, and with presumably non-pathogenic genomospecies. Hence, despite these features have been so far considered relevant for industrial or medical classification of related species of the B. cereus group, they were inappropriate for their circumscription. In this study, genomospecies of the group were accurately affiliated and representative strains defined, generating a rational framework that will allow comparative analysis in epidemiological or ecological studies. Based on this classification the role of specific markers such as Type VII secretion system, cytolysin, bacillolysin, and siderophores such as petrobactin were pointed out for further analysis.

Substandard Quality of the Antimicrobials Sold in the Street Markets in Haiti.

This pilot study was conducted to analyze the quality of the antimicrobials sold in the street markets in Port-au-Prince, Haiti. A total of 258 packs containing antimicrobials were bought in 28 street markets in Port-au-Prince (Haiti). Tablets and contents of capsules included in 196 packs were analyzed using a Raman handheld spectrometer (NanoRAM of BWTEK, Model: BWS456-785) during the first quarter of 2019. Three out of 11 antimicrobials (Amoxicillin, Metronidazole, and Cotrimoxazole) had a high spectral match with an HQI ≥ 90 to the respective authentic medicine for more than 95% of their tablets/capsules. For six antimicrobials (Tetracycline, Erythromycin, Cloxacillin, Azithromycin, Clarithromycin, and the combination Amoxicillin + Clavulanic Acid) none of their tablets/capsules showed a sufficient spectral match with the authentic medicine. This finding indicates that these products sold in the markets did not contain the labeled drug and/or contained a degraded drug. In addition to the fact that prescription antimicrobials can be purchased in street markets, the present field study found that for most of them (including "Watch" antimicrobials according to the AWaRe classification) were substandard, which contributes to the present antimicrobials resistance epidemic.

Patterns of Antibiotic Prescription in Colombia: Are There Differences between Capital Cities and Municipalities?

The use of antibiotics is the most important modifiable risk factor for the development of microorganism resistance. A cross-sectional study of outpatients receiving antibiotic prescriptions registered in a population database in Colombia was conducted. The characteristics of the consumption in capital cities and small municipalities was studied and the AWaRe classification was used. AWaRe classifies antibiotics into three stewardship groups: Access, Watch and Reserve, to emphasize the importance of their optimal use and potential harms of antimicrobial resistance. A total of 182,397 patients were prescribed an antibiotic; the most common were penicillins (38.6%), cephalosporins (30.2%) and fluoroquinolones (10.9%). 'Access' antibiotics (86.4%) were the most frequently prescribed, followed by 'Watch' antibiotics (17.0%). Being 18 or older, being male, living in a municipality, having one or more comorbidities and urinary, respiratory or gastrointestinal disorders increased the probability of receiving 'Watch' or 'Reserve' antibiotics. Penicillin and urinary antiseptic prescriptions predominated in cities, while cephalosporin and fluoroquinolone prescriptions predominated in municipalities. This analysis showed that the goal set by the WHO Access of mainly using Access antibiotics is being met, although the high use of Watch antibiotics in municipalities should be carefully studied to determine if it is necessary to design specific campaigns to improve antibiotics use.

FESTIval: A versatile framework for conducting experimental evaluations of spatial indices.

The use of a spatial index is a common strategy to improve the performance of spatial queries in spatial database systems and Geographic Information Systems. Choosing the right spatial index to be employed in a given context requires a quantitative method to analyze the performance of spatial indices. This is done through extensive experimental evaluations. However, conducting these evaluations is an expensive, error-prone, and challenging task because (i) spatial objects are complex data to manage, (ii) spatial indices can apply different parameter values and thus assume distinct configurations, and (iii) there are indices specifically developed for different storage systems, such as disks and flash memories. In this article, we propose FESTIval, a versatile framework for conducting experimental evaluations of spatial indices. FESTIval has the following main advantages: •the support for different types of disk-based and flash-aware spatial indices;•the specification and execution of user-defined workloads;•the use of a data schema that stores index configurations and statistical data of executed workloads. Because of its characteristics, FESTIval allows users to reproduce executed experiments. Further, FESTIval provides an extensible environment, where any spatial dataset can be handled by spatial indices. FESTIval has been used to validate new proposals of flash-aware spatial indices, such as eFIND-based indices.

A Cognitive-Inspired Event-Based Control for Power-Aware Human Mobility Analysis in IoT Devices.

Mobile Edge Computing (MEC) relates to the deployment of decision-making processes at the network edge or mobile devices rather than in a centralized network entity like the cloud. This paradigm shift is acknowledged as one key pillar to enable autonomous operation and self-awareness in mobile devices in IoT. Under this paradigm, we focus on mobility-based services (MBSs), where mobile devices are expected to perform energy-efficient GPS data acquisition while also providing location accuracy. We rely on a fully on-device Cognitive Dynamic Systems (CDS) platform to propose and evaluate a cognitive controller aimed at both tackling the presence of uncertainties and exploiting the mobility information learned by such CDS toward energy-efficient and accurate location tracking via mobility-aware sampling policies. We performed a set of experiments and validated that the proposed control strategy outperformed similar approaches in terms of energy savings and spatio-temporal accuracy in LBS and MBS for smartphone devices.

GaTO: An Ontological Model to Apply Gamification in Intelligent Tutoring Systems.

Intelligent Tutoring Systems (ITSs) are concerned with the use of artificial intelligence techniques for performing adaptive tutoring to learners' according to what they know about the domain. Researchers are increasingly interested in applying gamification in e-learning systems to engage students and to drive desired learning behaviors. However, little attention has been drawn to the effective application of gamification in ITS, and how to connect theories of both concepts in a standard and formal way. Moreover, gamified ITS should manipulate a huge amount of knowledge regarding several models, i.e., gamification, domain, student and pedagogical models. Formally connecting such theories as well as representing system's knowledge relies on the use of ontologies. In this paper, we present an ontological model that connects gamification and ITS concepts. Our model takes advantage of ontologies to allow automated reasoning (e.g., on the domain, student, pedagogical or gamification models), to enable interoperability, and create awareness about theories and good practices for the designers of gamified ITS. To evaluate our model, we use an ontology evaluation method based on five knowledge representation roles. We also illustrate how it could support the development of an intelligent authoring tool to design gamified ITS.

Cooperative UAV Scheme for Enhancing Video Transmission and Global Network Energy Efficiency.

Collaboration between multiple Unmanned Aerial Vehicles (UAVs) to set up a Flying Ad Hoc Network (FANET) is a growing trend since future applications claim for more autonomous and rapid deployable systems. The user experience on watching videos transmitted over FANETs should always be satisfactory even under influence of topology changes caused by the energy consumption of UAVs. In addition, the FANET must keep the UAVs cooperating as much as possible during a mission. However, one of the main challenges in FANET is how to mitigate the impact of limited energy resources of UAVs on the FANET operation in order to monitor the environment for a long period of time. In this sense, UAV replacement is required in order to avoid the premature death of nodes, network disconnections, route failures, void areas, and low-quality video transmissions. In addition, decision-making must take into account energy consumption associated with UAV movements, since they are generally quite energy-intensive. This article proposes a cooperative UAV scheme for enhancing video transmission and global energy efficiency called VOEI. The main goal of VOEI is to maintain the video with QoE support while supporting the nodes with a good connectivity quality level and flying for a long period of time. Based on an Software Defined Network (SDN) paradigm, the VOEI assumes the existence of a centrailized controller node to compute reliable and energy-efficiency routes, as well as detects the appropriate moment for UAV replacement by considering global FANET context information to provide energy-efficiency operations. Based on simulation results, we conclude that VOEI can effectively mitigate the energy challenges of FANET, since it provides energy-efficiency operations, avoiding network death, route failure, and void area, as well as network partitioning compared to state-of-the-art algorithm. In addition, VOEI delivers videos with suitable Quality of Experience (QoE) to end-users at any time, which is not achieved by the state-of-the-art algorithm.

A Proposal for IoT Dynamic Routes Selection Based on Contextual Information.

The Internet of Things (IoT) is based on interconnection of intelligent and addressable devices, allowing their autonomy and proactive behavior with Internet connectivity. Data dissemination in IoT usually depends on the application and requires context-aware routing protocols that must include auto-configuration features (which adapt the behavior of the network at runtime, based on context information). This paper proposes an approach for IoT route selection using fuzzy logic in order to attain the requirements of specific applications. In this case, fuzzy logic is used to translate in math terms the imprecise information expressed by a set of linguistic rules. For this purpose, four Objective Functions (OFs) are proposed for the Routing Protocol for Low Power and Loss Networks (RPL); such OFs are dynamically selected based on context information. The aforementioned OFs are generated from the fusion of the following metrics: Expected Transmission Count (ETX), Number of Hops (NH) and Energy Consumed (EC). The experiments performed through simulation, associated with the statistical data analysis, conclude that this proposal provides high reliability by successfully delivering nearly 100% of data packets, low delay for data delivery and increase in QoS. In addition, an 30% improvement is attained in the network life time when using one of proposed objective function, keeping the devices alive for longer duration.

Performance of and preference for oral rapid HIV testing in The Bahamas.

Initiatives to increase access to quality rapid HIV diagnostics have had relative success in the Caribbean in recent years, including use of oral rapid HIV testing. However, to date, there has not been any investigation into the performance or acceptability of oral fluids HIV testing in the region. In this cross-sectional study in The Bahamas, 252 persons of unknown serostatus were tested side-by-side with two oral rapid test brands, and the results were compared with the national fingerprick algorithm. In addition, an exit survey was administered to 234 study participants to assess user test preference. The most frequent survey response was to have no test preference (47.8%), but of those who expressed a test preference, most preferred oral (34.4%) versus fingerprick (17.8%) method. Both OraQuick and AWARE were 100% concordant with the gold standard. Therefore, our results show that oral fluids rapid testing is preferred over fingerprick testing by a subset of the potential target population and performs well in a population of undiagnosed persons attending screening clinic in The Bahamas.