Collection Of Information Research Articles

Movement Recognition and Injury Risk Assessment of Wushu Athletes Based on Computer Vision

This paper aims to study a method of movement recognition and injury risk assessment for Wushu athletes based on computer vision. Studying the optimization of Wushu athletes’ movement trajectory can effectively improve the athletes’ movement quality. Based on a hybrid real-time synchronization algorithm, the arm motion trajectory model of martial arts athletes is studied. A dynamic and static arm recognition algorithm is proposed, and the motion feature extraction method in Wushu movement is studied. Dynamic arm recognition typically relies on the collection of video or image sequences. These sequences contain the position, shape, and motion trajectory of the arm at different time points. Static arm recognition mainly relies on the acquisition of a single image or image frame. The dynamic arm recognition algorithm captures the motion trajectory and changes of the arm by processing video or image sequences, while the static arm recognition algorithm only processes individual images or image frames. On this basis, the design of the computer software architecture of the digital site system is completed. The real-time collection, analysis, display and storage of motion information and assembly configuration are realized. The simulation results show that the method has high accuracy and provides a powerful scientific basis for improving athletes’ movement injuries. To predict the risk of injury an athlete may suffer during training or competition.

SoyOD: An Integrated Soybean Multi-omics Database for Mining Genes and Biological Research

Abstract Soybean is a globally important crop for food, feed, oil, and nitrogen fixation. A variety of multi-omics studies has been carried out, generating datasets ranging from genotype to phenotype. In order to efficiently utilize these data for basic and applied research, a soybean multi-omics database with extensive data coverage and comprehensive data analysis tools was established. The Soybean Omics Database (SoyOD) integrates important new datasets with existing public datasets to form the most comprehensive collection of soybean multi-omics information. Compared to existing soybean databases, SoyOD incorporates an extensive collection of novel data derived from the deep-sequencing of 984 germplasms, 162 novel transcriptome datasets from seeds at different developmental stages, 53 phenotypic datasets, and more than 2500 phenotypic images. In addition, SoyOD integrates existing data resources, including 59 assembled genomes, genetic variation data from 3904 soybean accessions, 225 sets of phenotypic data, and 1097 transcriptomic sequences covering 507 different tissues and treatment conditions. Moreover, SoyOD can be used to mine candidate genes for important agronomic traits, as shown in a case study on plant height. Additionally, powerful analytical and easy-to-use toolkits enable users to easily access the available multi-omics datasets, and to rapidly search genotypic and phenotypic data in a particular germplasm. The novelty, comprehensiveness, and user-friendly features of SoyOD make it a valuable resource for soybean molecular breeding and biological research. SoyOD is publicly accessible at https://bis.zju.edu.cn/soyod.

EMPIRICAL INSIGHTS INTO CENTRALIZED PUBLIC PROCUREMENT: A CASE STUDY

This study case analyzes the implementation of the centralized model of public procurement by the Executive Branch of the Brazilian State of Amapa. Therefore, there is following research question: did the implementation of the centralized model result in improvements in the public procurement process in Amapa? In addition, the adopted methodology is based on a case study, as well as on the collection of information in official systems, added bibliographical and documentary research, questionnaires and semi-structured interviews. As a result, it was found that, from a general perspective, the centralized model works well in the State, however adjustments and improvements are necessary in areas of the centralized model that still require investments, such as planning, procedural agility and articulation with some bodies and entities of State. The findings provide insights into centralized public purchases in a Brazilian state and allow rise up hypothesis about similar experiences in another places (countries, states, municipalities). The compreension about Purchase Centrals it is a relevant tool into test how governments establishment suas procurement strategies and how to maximize the public spend getting economy and celerity.

Modernizando a Redação Policial: Protótipo de Aplicativo Android para a Elaboração de Relatos de Ocorrências

This article presents the development of an Android application prototype designed to assist Military Police officers with writing incident reports. The application leverages Google's Gemini AI API to provide real-time grammar correction and intelligent suggestions for writing improvement, acting as an experienced officer reviewing and enhancing the text. The app's architecture, based on the MVVM (Model-View-ViewModel) pattern, and the user interface design, focused on simplicity and usability, are detailed. The implementation of the Gemini AI API, including the system prompt that defines the AI's role and behavior, is explored, along with cost analysis and comparison with other popular natural language processing APIs like OpenAI and Anthropic. Test results using real incident reports demonstrate the app's ability to improve text clarity, conciseness, and professionalism, as well as provide relevant suggestions for police practice, such as missing information, legal procedures, and evidence collection. The article discusses the impacts and benefits of the application for the PMPR, the limitations of the technology, and suggestions for future work, including integration with other platforms and expansion of AI functionalities.

Capturing uncertainty intuition in road maintenance decision‐making using an evidential neural network

AbstractDecision‐making of project‐level road maintenance is the process of mapping road information into a maintenance plan. Even though benefitting from deep learning, the decision‐making still faces the problem of maintenance data uncertainty. The data uncertainty derives from imperfect road information collection and arbitrary selection of maintenance plans. Such uncertainty always leads to unreasonable maintenance decision‐making. This study proposes an evidential approach using information entropy (IE) and Dempster–Shafer theory (DST) to capture and handle uncertainty in the decision‐making of project‐level road maintenance. The approach first uses an IE‐based judgment method (IE‐based method) to capture and observe quantitative data uncertainty. The DST‐based method is then developed to handle maintenance data uncertainty through utilizing evidential neural network and set‐valued decision‐making. A numerical experiment is performed on the maintenance data with 280 km of semi‐rigid base highways in China. The results indicate that the IE‐based method can measure the data uncertainty in the information of road sections. The DST‐based method captures the cautious intuition on the selection of maintenance plans, thereby reducing the decision error rate by over 14% under specific conditions when facing data uncertainty.

Melampaui Antropocentrism: Ekoteologi dan Etika Lingkungan dalam Dialog, Sebuah Pendekatan Interdisipliner Untuk Keberlanjutan dan Keadilan Ekologis

The current ecological issue has become a global challenge, one of the triggers of the current ecological issue is the human understanding that considers itself superior and anthropocentric. Responding to these fundamental problems needs to be addressed for the future sustainability of the earth. Interdisciplinary theology is present as an approach that bridges one or more disciplines to direct global issues that are being wrestled with. This research uses descriptive qualitative methods, collection and development of information through literature studies to answer the problem formulation being studied. The description contains ecological problems and interdisciplinary dialogues between eco-theology and environmental ethics to direct anthropocentric attitudes as the root of ecological problems. This research aims to provide new breakthroughs towards sustainability and ecological justice. The results of the study show that interdisciplinary theology provides a relevant and profound foundation for facing ecological challenges and shifting the human paradigm as a ruler of nature towards a wise and sustainable attitude.

FORMATION OF A CONTROL SYSTEM IN AN AGRO-INDUSTRIAL ENTERPRISE

The article examines the importance of control in the management systems of agro-industrial enterprises, which is critical for ensuring their stability and effectiveness in a dynamic environment. The aim of the article is to analyze, systematize, generalize, and improve the theoretical and methodological foundations for the formation of a control system in an agro-industrial enterprise. It is determined that in the context of constant changes affecting agriculture, the control function becomes particularly significant as it helps adapt enterprises to new challenges and prevents negative consequences. The study presents the elements of the control system in agro-industrial enterprises, which include: planning (establishing goals, defining standards, and developing plans that serve as a basis for further monitoring and control), monitoring (constant collection and analysis of information on the execution of production processes), deviation analysis (evaluating performance results and comparing them with planned indicators), and feedback mechanisms (providing information on the effectiveness of production processes and their results, which is used to update plans and improve subsequent stages of control). Key control tools applicable at all stages of agro-industrial enterprises' activities are presented: planning and forecasting, result analysis and reporting, monitoring and information, auditing and inspections, quality control of products, budgeting, verification and compliance with environmental standards, personnel management, risk management, and technological control. It is found that timely application of control tools helps avoid losses and maintain high product quality. The purpose of control is justified as ensuring compliance of all production processes with established plans and standards to achieve economic efficiency, reduce costs, and improve product quality. The study allowed for the identification of the significance of integrating modern control methods and information technologies, which significantly enhance the effectiveness of management processes. It is noted that the application of modern technologies, such as ERP systems, IoT, and analytical platforms, significantly improves control over all stages of production and supply.

Using Artificial Intelligence in Employment: Problems and Prospects of Legal Regulation

Objective: to identify the legal problems of using artificial intelligence in hiring employees and the main directions of solving them.Methods: formal-legal analysis, comparative-legal analysis, legal forecasting, legal modeling, synthesis, induction, deduction.Results: a number of legal problems arising from the use of artificial intelligence in hiring were identified, among which are: protection of the applicant’s personal data, obtained with the use of artificial intelligence; discrimination and unjustified refusal to hire due to the bias of artificial intelligence algorithms; legal responsibility for the decision made by a generative algorithm during hiring. The author believes that for the optimal solution of these problems, it is necessary to look at the best practices of foreign countries, first of all, those which have adopted special laws on the regulation of artificial intelligence for hiring and developed guidelines for employers using generative algorithms for similar purposes. Also, the European Union’s and USA’s legislative work in the area of managing risks arising from the use of artificial intelligence should be taken into account.Scientific novelty: the article contains a comprehensive study of legal problems arising from the use of artificial intelligence in hiring and foreign experience in solving these problems, which allowed the author to develop recommendations to improve Russian legislation in this area. As for the problem of applicants’ personal data protection when using artificial intelligence for hiring, the author proposes to solve it by supplementing the labor legislation with norms that enshrine the requirements for transparency and consistency in the collection, processing and storage of information when using generative algorithms. The list and scope of personal data allowed for collection should be reflected in a special state standard. The solution to the problem of discrimination due to biased algorithms is seen in the mandatory certification and annual monitoring of artificial intelligence software for hiring, as well as the prohibition of scoring tools for evaluating applicants. The author adheres to the position that artificial intelligence cannot “decide the fate” of a job seeker: the responsibility for the decisions made by the algorithm is solely on the employer, including in cases of involving third parties for the selection of employees.Practical significance: the obtained results can be used to accelerate the development and adoption of legal norms, rules, tools and standards in the field of using artificial intelligence for hiring. The lack of adequate legal regulation in this area creates significant risks both for human rights and for the development of industries that use generative algorithms to hire employees.

Managerial and organisational factors: Unravelling resource allocation choices in high-performing micro-firms

Resource allocation decisions are pivotal in shaping the strategic direction of organisations, particularly in micro-firms that operate with limited resources and dispersed information. This research delves into the intricate interplay between managerial and organisational factors related to information collection, processing and resource allocation in the context of high-performing micro-firms. By advancing our understanding of how the internal coordination of information needed in decision-making and resource allocation evolves within micro-firms, we reveal the mechanisms that stabilise the relationship between participants and problems. Additionally, we explore how the capabilities of managers and owners, who often centralise final decisions in micro-firms, can catalyse the emergence of such coordination. This holistic view of strategic resource allocation in micro-firm settings addresses the fundamental question of how micro-enterprises overcome structural limitations to achieve high levels of performance. Our findings provide valuable insights for scholars, managers and policymakers, contributing to the broader discourse on resource management in micro-firms.

A mixed methods study of student pharmacist perceptions of their confidence and competence in the provision of clinical assessment

Abstract Introduction Pharmacist involvement in clinical assessment or examination has recently come into the focus in the United Kingdom with the transition of the pharmacy workforce to prescribers. Clinical assessment starts with the collection of information on an individual’s past medical history and clinical presentation, and the interpretation of tests, observations, and physical assessments to inform a differential diagnosis.1 The range of clinical skills student pharmacists gain from placements during the MPharm is variable and shaped by local demands for pharmacy services. Therefore, there is a need for additional training on clinical assessment skills in classroom teaching.2-4 Aim To identify student pharmacist perceptions and beliefs on their competence in conducting clinical assessment. Methods Ethics approval for this research study was granted by the Strathclyde Institute of Pharmacy and Biomedical Sciences Ethics Committee and conducted between October-December 2023. A mixed-methods study was conducted using a survey and focus group discussions developed from the literature and validated through discussion to collect student pharmacist perceptions of the role of the pharmacist and current gaps/barriers to pharmacist provision of clinical assessments. Students from all years of the MPharm were invited by email to participate (n=615). Audio recordings captured from focus group discussions were thematically analysed to identify key themes. Results Four focus groups were held with a total of 30 students. There were 89 respondents to the online survey (119 in total). Across both approaches, five key themes were identified from the survey and four from the focus group interviews. These themes centred around student pharmacist perceived role of the pharmacist, time and technical resources available in the pharmacy workplace, and the current curriculum. Most students agreed that such clinics would be beneficial to their training. Discussion and Conclusions Student-led clinics are gaining popularity as a work-based approach to learning. We found varied perceptions of the pharmacist’s role by participant response, suggesting that the clinical nature of pharmacy as a profession must be highlighted to prospective students to ensure those entering the profession are aware of the responsibilities they may be required to undertake. A limitation of this study is that student perceptions reflect the views of a single institution. Careful design of future clinics is required to ensure their seamless integration in the existing MPharm curriculum, in a realistic setting reflecting the workplace, and sufficient support from practitioners to implement them. Future work in this area should focus on how clinical assessment skills should be learned and assessed in student populations.

Talk2Care: Facilitating Asynchronous Patient-Provider Communication with Large-Language-Model

Despite the plethora of telehealth applications to assist home-based older adults and healthcare providers, basic messaging and phone calls are still the most common communication methods, which suffer from limited availability, information loss, and process inefficiencies. One promising solution to facilitate patient-provider communication is to leverage large language models (LLMs) with their powerful natural conversation and summarization capability. However, there is a limited understanding of LLMs' role during the communication. We first conducted two interview studies with both older adults (N=10) and healthcare providers (N=9) to understand their needs and opportunities for LLMs in patient-provider asynchronous communication. Based on the insights, we built an LLM-powered communication system, Talk2Care, and designed interactive components for both groups: (1) For older adults, we leveraged the convenience and accessibility of voice assistants (VAs) and built an LLM-powered conversational interface for effective information collection. (2) For health providers, we built an LLM-based dashboard to summarize and present important health information based on older adults' conversations with the VA. We further conducted two user studies with older adults and providers to evaluate the usability of the system. The results showed that Talk2Care could facilitate the communication process, enrich the health information collected from older adults, and considerably save providers' efforts and time. We envision our work as an initial exploration of LLMs' capability in the intersection of healthcare and interpersonal communication.

Resource allocation design method based on WSN multi-dimension soil inspection

Abstract. With the industrialization of agriculture and the sharp rise of food prices, in order to promote the intensive development of natural resources and achieve economies of scale agriculture in production, people put forward the innovative strategy of "precision agriculture" to maintain the sustainable development of agriculture. To protect the environment and farmer communities and increase productivity. However, in the special context of precision agriculture, the problems related to energy consumption and electromagnetic wave propagation in complex environments have a significant impact on precision agriculture. In the case of no monitoring and harsh environment, wireless sensor networks (WSN) can complete the tasks of real-time monitoring and information collection. In the past, the understanding of WSN in agriculture was limited to unilateral detection, which led to the underutilization of the soil. This paper introduces an innovative solution for precision agriculture based on wireless sensor networks, which mainly focuses on the observation and impact assessment of soil water volume,PH value, temperature and pressure in agricultural production process. It aims to reduce the waste of natural resources and the use of fertilizer substances, while maintaining or improving the yield of farming, in order to better promote the development of WSN in the agricultural field.

Research on path planning in UAV-assisted emergency communication

The rapid development of UAV communication technology makes it have application potential in wireless systems. However, for the optimization problem of UAV base station providing communication for ground personnel in the disaster area under special natural disasters, traditional deep reinforcement learning is used. Algorithms cannot solve such problems well. This article proposes the AD3QN algorithm combined with the attention mechanism, which can communicate with disaster victims on the ground better and more quickly, providing better information collection for rescue missions and completing the task of communication optimization. In the mission simulation environment, in order to make the environment more realistic, we innovatively designed the ground user distribution model, air-to-ground communication model, and electromagnetic interference model. Finally, the effect of the proposed algorithm is evaluated by comparing different deep reinforcement learning algorithms. The results show that the algorithm we proposed can provide communication services faster and has higher practicability in terms of algorithm.

Quality of medical care for patients with arterial hypertension and type 2 diabetes mellitus in outpatient medical organizations

BACKGROUND: The course of arterial hypertension and diabetes mellitus depends on the medical care quality since its poor provision increases the risk of unfavorable outcomes. Identifying and analysing defects in the management of such patients is an urgent task. AIM: To assess the medical care quality provided to patients with hypertension and type 2 diabetes mellitus on an outpatient medical organizations. MATERIALS AND METHODS: The assessment of the medical care for patients with hypertension and type 2 diabetes mellitus in outpatient medical organizations in St. Petersburg and the Leningrad region was carried out by analyzing primary medical records for 175 cases. RESULTS: The quality of medical care is recognized as appropriate only in 25% of the cases. The errors in collecting information were the most common (95% of the cases of poor quality medical care): in cases of hypertension and type 2 diabetes mellitus no information about the course of the disease, previous treatment, risk factors, anthropometry, ophthalmoscopy or referral to an ophthalmologist; neurological examination and assessing cognitive functions - in the patients with hypertension; foot examination – in the patients with diabetes. The most common defects of the examination included the absence of lipidogram, uric measurement and electrolyte levels in hypertension, determination of albuminuria in diabetes mellitus, electrocardiography and echocardiography. Diagnosis errors were detected in 7–15% of the cases, treatment defects — in 33–53%. The information collection error is the most common defect in case of the patients with hypertension and type 2 diabetes mellitus, which is comparable with the previously published data. Treatment errors mainly consisted in the absence of lifestyle modification recommendations necessary for the treatment of hypertension and type 2 diabetes mellitus since these measures reduce the risk of complications and improve the prognosis.The revealed defects in medication therapy were comparable to the previous data and consisted in the appointment of insufficient doses of medications and in the use of monotherapy in the presence of indications for combination therapy. CONCLUSIONS: The assessment of the medical care revealed an insufficiently high level of outpatient medical care for the patients with hypertension and type 2 diabetes mellitus, which requires a detailed analysis of the causes for future prevention.

HANZE v2.1: an improved database of flood impacts in Europe from 1870 to 2020

Abstract. Assessing long-term trends in flood losses and attributing them to climatic and socioeconomic changes requires comprehensive and systematic collection of historical information. Here, we present flood impact data for Europe that are part of the HANZE (Historical Analysis of Natural HaZards) database. The dataset covers riverine, pluvial, coastal, and compound floods that have occurred in 42 European countries between 1870 and 2020. The data were obtained by extensive data collection from more than 800 sources ranging from news reports through government databases to scientific papers. The dataset includes 2521 events characterized by at least one impact statistic: area inundated, fatalities, persons affected. or economic loss. Economic losses are presented both in the original currencies and price levels and with the inflation and exchange rate adjusted to the 2020 value of the euro. The spatial footprint of affected areas is consistently recorded using more than 1400 subnational units corresponding, with minor exceptions, to the European Union's Nomenclature of Territorial Units for Statistics (NUTS) level 3. Daily start and end dates, information on causes of the events, notes on data quality issues or associated non-flood impacts, and full bibliography of each record supplement the dataset. Apart from the possibility of downloading the data (https://doi.org/10.5281/zenodo.8410025; Paprotny, 2023a), the database can be viewed, filtered, and visualized online at https://naturalhazards.eu (last access: 4 November 2024). The dataset is designed to be complementary to HANZE-Exposure, a high-resolution model of historical exposure changes (such as population and asset values) and be easily usable in statistical and spatial analyses, including multi-hazard studies.

AuNPs enhanced electrochemical and optical dual-mode fiber optic sensor for trace Hg2+ detection

Efficient and low-concentration detection of heavy metal ions is crucial for healthcare and environmental monitoring. Traditional fiber optic surface plasmon resonance (SPR) sensors face challenges in detecting trace heavy metal ions due to limited sensitivity and the need for complex specific modifications. To overcome these challenges, an innovative electrochemical and optical dual-mode fiber optic sensor for in situ, real-time detection of trace mercury ions is proposed in this paper. The sensor utilizes a reflection-type fiber optic probe coated with thin gold (Au)/indium tin oxide (ITO) film and gold nanoparticles (AuNPs), enabling simultaneous electrochemical and optical interrogation. The coupling effect between the SPR of thin film and the localized surface plasmon resonance (LSPR) of AuNPs significantly improves optical sensitivity, with AuNPs also offering additional active sites for the redox reaction of Hg2+. The ITO film not only facilitates the stripping of Hg2+, leading to sharper stripping peaks but also enhances the ability of the sensor to rapidly respond to anomalous potential changes. Experimental results show that the sensor has a wide dynamic detection range from 10−10 M to 10−5 M, with a limit of detection reaching the pM level. The dual-mode functionality allows the simultaneous collection of voltage, current, and optical information, enabling cross-validation of the detection results and improving the accuracy and reliability of detection.

АНАЛІЗ ЦІНОВИХ СТРАТЕГІЙ ТА СПОЖИВЧА ПОВЕДІНКА В КОНТЕКСТІ МАРКЕТИНГОВИХ ДОСЛІДЖЕНЬ

Abstract introduction. The article examines the views of scientists regarding the formation of price strategies. The main approaches to pricing are considered, with the help of which companies set optimal prices for their services and goods. Factors affecting the company's choice of pricing strategy and affecting consumer behavior are considered. It is conducted research in relation to behavior of consumers and built model of satisfaction of consumer necessities. The purpose of the article. Consideration of pricing strategies of companies and their impact on consumer behavior. Researching consumer behavior and building a model for satisfying consumer needs in goods or services. Methods. Carrying out research the methods of abstraction, analysis, logical, theoretical and historical generalization and comparison are used. For basis of research a dialectical method is taken. Results. The article examines the main approaches to pricing, with the help of which companies set optimal prices for their services and goods. The factors affecting the company's choice of price strategy are considered, and the factors influencing consumer behavior are highlighted. Conducted research on consumer behavior. The proposed model of meeting the needs of consumers in goods or services, which contains 8 sections: the consumer's awareness of the need for the need for a product or service; collection of information; selection of goods or services; decision-making; purchase (payment) of goods or services; evaluation of the choice made and enrichment of experience; the degree of satisfaction of the need for a product or service and consumption of the results. Conclusiоns. After researching and analyzing the available types of marketing price strategies, business entities choose their own price strategy, taking into account certain existing tools, taking into account: characteristics of the service or product, market segment, market competition, competitor analysis, level of market demand, marketing strategies, etc. .. The use of the correct price strategy and the concept of pricing contributes to the achievement of goals: ensuring the stable financial condition of the business entity, meeting the needs of consumers. The offered model in relation to satisfaction of necessities of consumers in commodities or services gives understanding to the process of making decision by consumers in relation to a purchase that is the basic factor of success of company in a competition environment. Companies, that is able to adapt oneself to the necessities of consumers and, to their requirements, that understand the customers, have more chances to retain and attract clients, promote a competitiveness and score a success at the market. The question of the method of determining prices for certain types of services and the behavioral reaction of consumers requires further research.

Reducing Emissions in the Maritime Sector: Offshore Wind Energy as a Key Factor

The maritime environment is the setting for a variety of economic activities, such as offshore wind energy, aquaculture, salt extraction, and oil and gas platforms. While some of these activities have a long-term presence, others require decarbonization as they head towards their demise. In this context, the aim of this study is to develop a methodology to replace the electrical energy from offshore high-emission industrial processes with clean electricity generated by offshore wind energy. The proposal is structured in three phases: initiation, which involves the collection of quantitative, technical, and geospatial information of the study area; indicators, where the main indicators are calculated, and the best alternative is selected using multi-criteria evaluation methods; and finally, short-, medium-, and long-term scenarios are proposed. The methodology is evaluated in Spain, and the best alternative, which has a nominal power of 225 MW, is capable of avoiding up to 1.44 MtCO2 by 2050.

PERSEPSI MASYARAKAT TERHADAP KEBERADAAN RUMAH WALET DI DESA WATUTAU KECAMATAN LORE PEORE KABUPATEN POSOSULAWESI TENGAH

This research aims to determine the public's perception of the existence of swallow houses in Watutau Village, Lore Peore District, Poso Regency, and the factors that influence people's perceptions of swallow houses. In this research, the population was taken from a community located at a radius of 250 meters, namely 31 heads of families, the number of samples taken was 31 respondents. This research is a qualitative descriptive research. The research method used by the survey method is one of the information collection techniques carried out by compiling a list of questions asked to respondents at the research location. The data analysis used is descriptive statistics using grouping, simplification and presentation of data such as frequency distribution tables and measurements using the likert and chi- square scales. Based on the results of the study, the perception of the community in Watutau Village, Lore Peore District, Poso Regency, is in the category of Disturbed / Disagreed with the exis tence of swallow houses and the most influential factors in the perception of the community in Watutau Village, Lore Peore District, Poso Regency are the distance of houses on sound and socio-cultural indicators on community perceptions.

Prevalence of Human Papillomavirus‐Associated Head and Neck Cancer in Rwanda: A 10‐Year Review

ABSTRACTIntroductionHead and neck cancer (HNC) is a significant global health burden, with late presentation leading to complex treatment. While human papillomavirus (HPV) infection has been implicated in HNC, data from low‐ and middle‐income countries (LMICs) are limited. In this study, we investigated the prevalence and role of HPV in head and neck cancers diagnosed in Rwanda.MethodsA retrospective cross‐sectional study was conducted using Rwanda Cancer Registry from January 2011 through December 2020. p16 immunohistochemistry as a surrogate for HPV was performed on a randomly selected case. p16‐positive cases were genotyped.ResultsA total of 1001 patients with HNC were identified; 82% (n = 819) had squamous cell carcinoma. The mean age at diagnosis was 51.1 years, with a majority being males (58%). Oral cavity and lip (27%) were the most common primary cancer sites. Stage was unknown in most cases (75%, n = 747). HIV status was known in 33% (n = 334) of patients with 10% (n = 33) HIV‐positive; 22% of 202 randomly selected cases were p16‐positive; 34% of the p16‐positive cases were oropharynx. PCR analysis of p16‐positive cases showed 19% HPV positivity, and HPV16 was the most common high‐risk HPV strain, and 55.5% were recorded HPV‐positive by PCR.ConclusionsHNC cases in Rwanda have been increasing from 2011 to 2020, with a significant portion being HPV‐positive. Strategies to implement routine testing for p16, especially in oropharynx cancer patients, improved preservation of tissue samples, collection of comprehensive information including cancer risk factors, staging, and treatment are needed in Rwanda.