Search results for: health data

Authors: Ghazi Bouaziz, Abderrahim Derouiche, Damien Brulin, Hélène Pigot, Eric Campo

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Automatic ADL classification is a crucial part of ambient assisted living technologies. It allows to monitor the daily life of the elderly and to detect any changes in their behavior that could be related to health problem. But detection of ADLs is a challenge, especially because each person has his/her own rhythm for performing them. Therefore, we used a correlation matrix to extract custom rules that enable to detect ADLs, including eating activity. Data collected from 3 different individuals between 35 and 105 days allows the extraction of personalized eating patterns. The comparison of the results of the process of eating activity extracted from the correlation matrices with the declarative data collected during the survey shows an accuracy of 90%.

Keywords: elderly monitoring, ADL identification, matrix correlation, meal-taking activity

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Authors: Dragana Calic

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The openness, availability and the sheer volume of big data have provided, what some regard as, an invaluable and rich dataset. Researchers, businesses, advertising agencies, medical institutions, to name only a few, collect, share, and analyze this data to enable their processes and decision making. However, there are important ethical considerations associated with the use of big data. The rapidly evolving nature of online technologies has overtaken the many legislative, privacy, and ethical frameworks and principles that exist. For example, should we obtain consent to use people’s online data, and under what circumstances can privacy considerations be overridden? Current guidance on how to appropriately and ethically handle big data is inconsistent. Consequently, this paper focuses on two quite distinct but related ethical considerations that are at the core of the use of big data for research purposes. They include empowering the producers of data and empowering researchers who want to study big data. The first consideration focuses on informed consent which is at the core of empowering producers of data. In this paper, we discuss some of the complexities associated with informed consent and consider studies of producers’ perceptions to inform research ethics guidelines and practice. The second consideration focuses on the researcher. Similarly, we explore studies that focus on researchers’ perceptions and experiences.

Keywords: big data, ethics, producers’ perceptions, researchers’ perceptions

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Authors: Roberto Rubem Silva-Brandao, Aurea Maria Zollner Ianni

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This article discusses the use and the incorporation of Pre-exposure Prophylaxis for HIV (PrEP) within a risk society context. Considering contemporary social theoreticians, we discuss implications of biotechnological uses for health enhancement. Firstly, we explore examples of biological manipulation and its consequences of use on given ecological dynamics, particularly taking into account other Sexually Transmitted Infections. In addition, we discuss how HIV resistance cases occurred with people on PrEP and its possible consequences on population-based interventions. Moreover, we present recent studies that analyze biological modifications on bodies of those who are on consistent use of PrEP, and how these body modifications are addressed on common practices of Public Health. Secondly, we present our theoretical references, which are intended to the analysis that situates our contemporary society in the reflexive stage of modernization. We discuss limits of biological use by individuals and how this can fabric feelings of freedom and autonomy within the individualization process and health. Finally, we argue that biotechnological uses on health, specifically on Public Health, tackling the risk aspects of its application, shows that another sanitary pact is needed.

Keywords: PrEP, public health, social sciences, risk society

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Authors: Zainal Abidin Akasah, Maizam Alias, Azuin Ramli

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The safety and health performances aspects of a building are the most challenging aspect of facility management. It requires a deep understanding by the building managers on the factors that contribute to health and safety performances. This study attempted to develop an explanatory architectural safety performance model for stratified low-cost housing in Malaysia. The proposed Building Safety and Health Performance (BSHP) model was tested empirically through a survey on 308 construction practitioners using Partial Least Squares (PLS) and Structural Equation Modelling (SEM) tool. Statistical analysis results supports the conclusion that architecture, building services, external environment, management approaches and maintenance management have positive influence on safety and health performance of stratified low-cost housing in Malaysia. The findings provide valuable insights for construction industry to introduce BSHP model in the future where the model could be used as a guideline for training purposes of managers and better planning and implementation of building management.

Keywords: building management, stratified low-cost housing, safety, health model

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Authors: Walid Cherif

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Data mining has, over recent years, seen big advances because of the spread of internet, which generates everyday a tremendous volume of data, and also the immense advances in technologies which facilitate the analysis of these data. In particular, classification techniques are a subdomain of Data Mining which determines in which group each data instance is related within a given dataset. It is used to classify data into different classes according to desired criteria. Generally, a classification technique is either statistical or machine learning. Each type of these techniques has its own limits. Nowadays, current data are becoming increasingly heterogeneous; consequently, current classification techniques are encountering many difficulties. This paper defines new measure functions to quantify the resemblance between instances and then combines them in a new approach which is different from actual algorithms by its reliability computations. Results of the proposed approach exceeded most common classification techniques with an f-measure exceeding 97% on the IRIS Dataset.

Keywords: data mining, knowledge discovery, machine learning, similarity measurement, supervised classification

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Authors: Seraphina Bakta

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In many societies in Africa, it is a taboo to speak, let alone to practice or in any way to engage in matters relating to sexual and reproductive health. For instance, girls using contraceptives may be labeled prostitutes, and married women using family planning methods may be divorced on account that they are disobedient to their husbands as they do not want to bear children. As such, sexual and reproductive health as a right is still very far from reality to many men and women. To a large extent, the objections are mainly backed up in culture, which is deeply rooted in many African traditions. While such culture have both the good and bad side, the African Charter on Human and Peoples Rights has identified the bad ones as’ harmful cultural practices. This paper argues that, while cultural norms may hinder the realization of human rights, adopting a human rights based approach to address harmful cultural practices is likely, the best approach to realizing women’s rights to sexual and reproductive health rights in Africa.

Keywords: rights, culture, health, women

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Authors: Ankur Mundhra, Shubhadeep Chakraborty, Y. R. Singh, Vishal Das

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Seismic data scaling affects the dynamic range of a data and with present day lower costs of storage and higher reliability of Hard Disk data, scaling is not suggested. However, in dealing with data of different vintages, which perhaps were processed in 16 bits or even 8 bits and are need to be processed with 32 bit available data, scaling is performed. Also, scaling amplifies low amplitude events in deeper region which disappear due to high amplitude shallow events that saturate amplitude scale. We have focused on significance of scaling data to aid interpretation. This study elucidates a proper seismic loading procedure in workstations without using default preset parameters as available in most software suites. Differences and distribution of amplitude values at different depth for seismic data are probed in this exercise. Proper loading parameters are identified and associated steps are explained that needs to be taken care of while loading data. Finally, the exercise interprets the un-certainties which might arise when correlating scaled and unscaled versions of seismic data with synthetics. As, seismic well tie correlates the seismic reflection events with well markers, for our study it is used to identify regions which are enhanced and/or affected by scaling parameter(s).

Keywords: clipping, compression, resolution, seismic scaling

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Authors: Ngabilas Salama

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Background: Indonesia has the 2nd highest number of incidents of tuberculosis (TB). It accounts for 1.020.000 new cases per year, only 30% of which has been reported. To find the lost 70%, a massive active case discovery was conducted through two programs: Ketuk Pintu Layani Dengan Hati (KPLDH) and Kader Juru Pemantau Batuk (Jumantuk cadres), who also plays a role in child TB screening. Methods: Data was collected and analyzed through Tuberculosis Integrated Online System from 2014 to 2017 involving 129 DOTS facility with 86 primary health centers in East Jakarta. Results: East Jakarta consists of 2.900.722 people. KPLDH program started in February 2016 consisting of 84 teams (310 people). Jumantuk cadres was formed 4 months later (218 orang). The number of new TB cases in East Jakarta (primary health center) from 2014 to June 2017 respectively is as follows: 6.499 (2.637), 7.438 (2.651), 8.948 (3.211), 5.701 (1.830). Meanwhile, the percentage of child TB case discovery in primary health center was 8,5%, 9,8%, 12,1% from 2014 to 2016 respectively. In 2017, child TB case discovery was 13,1% for the first 3 months and 16,5% for the next 3 months. Discussion: Increased TB incidence rate from 2014 to 2017 was 14,4%, 20,3%, and 27,4% respectively in East Jakarta, and 0,5%, 21,1%, and 14% in primary health center. This reveals the positive role of KPLDH and Jumantuk in TB detection and reporting. Likewise, these programs were responsible for the increase in child TB case discovery, especially in the first 3 months of 2017 (Ketuk Pintu TB Day program) and the next 3 months (active TB screening). Conclusion: KPLDH dan Jumantuk are actively involved in increasing TB case discovery in both adults and children.

Keywords: tuberculosis, case discovery program, primary health center, cadre

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Authors: Iva Trako, Maris Micaela Sviatschi, Guadalupe Kavanaugh

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Domestic violence is a major concern in developing countries, with important social, economic and health consequences. However, institutions do not usually address the problems facing women or ethnic and religious minorities. For example, the police do very little to stop domestic violence in rural areas of developing countries. This paper exploits the introduction of women’s justice centers (WJCs) in Peru to provide causal estimates on the effects of improving access to justice for women and children. These centers offer a new integrated public service model for women by including medical, psychological and legal support in cases of violence against women. Our empirical approach uses a difference in difference estimation exploiting variation over time and space in the opening of WJC together with province-by-year fixed effects. Exploiting administrative data from health providers and district attorney offices, we find that after the opening of these centers, there are important improvements on women's welfare: a large reduction in femicides and female hospitalizations for assault. Moreover, using geo-coded household surveys we find evidence that the existence of these services reduces domestic violence, improves women's health, increases women's threat points and, therefore, lead to household decisions that are more aligned with their interests. Using administrative data on the universe of schools, we find large gains on human capital for their children: affected children are more likely to enroll, attend school and have better grades in national exams, instead of working for the family. In sum, the evidence in this paper shows that providing access to justice for women can be a powerful tool to reduce domestic violence and increase education of children, suggesting a positive inter-generational benefit.

Keywords: access to justice, domestic violence, education, household bargaining

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Authors: Quinn Au, Amedeo Carmine, Tauheed Khan Mohd

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The Internet of Things (IoT) is emerging as a new development in information technology in recent years, with the potential to improve convenience and efficiency in life. Following the rise of IoT, the Social Internet of Things (SIoT) is another new development in which the benefits of connectivity and user-friendliness from social network services (SNS) are its main features. With the introduction of IoT, the world will be much more modernized, convenient, and industrialized. This paper will discuss the applications of IoT in different sectors such as healthcare services, education, and lifestyle. The privacy challenges that IoT still poses to user data will also be discussed. Finally, an empirical study to evaluate the number of active installed IoT connections in recent years demonstrates the increase in usage of IoT regardless of the privacy challenges. The study also examines some types of IoT devices that are being preferred in the market and predictions from researchers about IoT in the upcoming years.

Keywords: IoT, health care, robotics, social Internet of Things

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Authors: Abdelkadir Muzey Mohammed, Habtu Alemayehu Atsbaha, Yohannes Yirga Kefela, Woldegebriel Assefa Woldegerima, Kiros Tedla Gebrehiwot

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The circumstances of war and conflict have long been associated with concerns about heightening HIV infection due to the use of sexual violence and rape as a weapon of war and lack of health services access to the patients with HIV as well as sexual violence and rape victims. This paper examines the impact of war related mass rape on HIV incidence and prevalence in the war ravaged Tigray, Ethiopia. Risk equation model and uncertainty analyses with sampled ranges of parameters were employed using data from WHO, Ethiopian Public Health Institute and Ethiopian Central Statistical Agency was used. Our analysis indicated that the mass rape committed in Tigray could cause an increase of incidence and prevalence by a median of 63.01% and 1.14% respectively. The significant increase in HIV incidence and prevalence due to mass rape demands a special attention including region wide improved surveillance and tracing of rape survivors. Furthermore, HIV prevention and treatment strategies such as delivery of emergency health service, providing pre and post exposure treatments on the basis of human rights should priority of governmental and nongovernmental organizations in a conflict situation.

Keywords: conflict situation, mass rape, HIV, mathematical model, uncertainty analysis

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Authors: Rosemary Saunders, Courtney Glass, Karla Seaman, Karen Gullick, Julie Andrew, Anne Wilkinson, Ashwini Davray

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Current literature demonstrates that most Australians receive end-of-life care in a hospital setting, despite most hoping to die within their own home. The necessity for high quality end-of-life care has been emphasised by the Australian Commission on Safety and Quality in Health Care and the National Safety and Quality in Health Services Standards depict the requirement for comprehensive care at the end of life (Action 5.20), reinforcing the obligation for continual organisational assessment to determine if these standards are suitably achieved. Limited research exploring clinical staff perspectives of end-of-life care delivery has been conducted within an Australian private health context. This study aimed to investigate clinical staff member perceptions of end-of-life care delivery at a private hospital in Western Australia. The study comprised of a multi-faceted mixed-methods methodology, part of a larger study. Data was obtained from clinical staff utilising surveys and focus groups. A total of 133 questionnaires were completed by clinical staff, including registered nurses (61.4%), enrolled nurses (22.7%), allied health professionals (9.9%), non-palliative care consultants (3.8%) and junior doctors (2.2%). A total of 14.7% of respondents were palliative care ward staff members. Additionally, seven staff focus groups were conducted with physicians (n=3), nurses (n=26) and allied health professionals including social workers (n=1), dietitians (n=2), physiotherapists (n=5) and speech pathologists (n=3). Key findings from the surveys highlighted that the majority of staff agreed it was part of their role to talk to doctors about the care of patients who they thought may be dying, and recognised the importance of communication, appropriate training and support for clinical staff to provide quality end-of-life care. Thematic analysis of the qualitative data generated three key themes: creating the setting which highlighted the importance of adequate resourcing and conducive physical environments for end-of-life care and to support staff and families; planning and care delivery which emphasised the necessity for collaboration between staff, families and patients to develop care plans and treatment directives; and collaborating in end-of-life care, with effective communication and teamwork leading to achievable care delivery expectations. These findings contribute to health professionals better understanding of end-of-life care provision and the importance of collaborating with patients and families in care delivery. It is crucial that health care providers implement strategies to overcome gaps in care, so quality end-of-life care is provided. Findings from this study have been translated into practice, with the development and implementation of resources, training opportunities, support networks and guidelines for the delivery of quality end-of-life care.

Keywords: clinical staff, end-of-life care, mixed-methods, private hospital.

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Authors: Jan Muhammad, Saad Malik, Fadia W. Al-Azawi, Ali Imran

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In the era of climate variability, rising temperatures are the most significant aspect. In this study PRECIS model data and observed data are used for assessing the temperature change scenarios of Sindh province during the first half of present century. Observed data from various meteorological stations of Sindh are the primary source for temperature change detection. The current scenario (1961–1990) and the future one (2010-2050) are acted by the PRECIS Regional Climate Model at a spatial resolution of 25 * 25 km. Regional Climate Model (RCM) can yield reasonably suitable projections to be used for climate-scenario. The main objective of the study is to map the simulated temperature as obtained from climate model-PRECIS and their comparison with observed temperatures. The analysis is done on all the districts of Sindh in order to have a more precise picture of temperature change scenarios. According to results the temperature is likely to increases by 1.5 - 2.1°C by 2050, compared to the baseline temperature of 1961-1990. The model assesses more accurate values in northern districts of Sindh as compared to the coastal belt of Sindh. All the district of the Sindh province exhibit an increasing trend in the mean temperature scenarios and each decade seems to be warmer than the previous one. An understanding of the change in temperatures is very vital for various sectors such as weather forecasting, water, agriculture, and health, etc.

Keywords: PRECIS Model, real observed data, Arc GIS, interpolation techniques

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Authors: Fathonah Siti, Ardiana Irma

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Indonesia is currently on its track to achieve Universal Health Coverage (UHC) by 2019. The program aims to address issues on disintegration in the implementation and coverage of various health insurance schemes and fragmented fund pooling. Family planning service is covered as one of benefit packages under preventive care. However, little has been done to examine how family planning program are appropriately managed across levels of governments and how family planning services are delivered to the end user. The study is performed through focus group discussion to related policy makers and selected programmers at central and district levels. The study is also benefited from relevant studies on family planning in the UHC scheme and other supporting data. The study carefully investigates some programmatic implications when family planning is integrated in the UHC program encompassing the need to recalculate contraceptive logistics for beneficiaries (eligible couple); policy reformulation for contraceptive service provision including supply chain management; establishment of family planning standard of procedure; and a call to update Management Information System. The study confirms that there is a significant increase in the numbers of contraceptive commodities needs to be procured by the government. Holding an assumption that contraceptive prevalence rate and commodities cost will be as expected increasing at 0.5% annually, the government need to allocate almost IDR 5 billion by 2019, excluded fee for service. The government shifts its focus to maintain eligible health facilities under National Population and Family Planning Board networks. By 2019, the government has set strategies to anticipate the provision of family planning services to 45.340 health facilities distributed in 514 districts and 7 thousand sub districts. Clear division of authorities has been established among levels of governments. Three models of contraceptive supply planning have been developed and currently in the process of being institutionalized. Pre service training for family planning services has been piloted in 10 prominent universities. The position of private midwives has been appreciated as part of the system. To ensure the implementation of quality and health expenditure control, family planning standard has been established as a reference to determine set of services required to deliver to the clients properly and types of health facilities to conduct particular family planning services. Recognition to individual status of program participation has been acknowledged in the Family Enumeration since 2015. The data is precisely recorded by name by address for each family and its members. It supplies valuable information to 15.131 Family Planning Field Workers (FPFWs) to provide information and education related to family planning in an attempt to generate demand and maintain the participation of family planning acceptors who are program beneficiaries. Despite overwhelming efforts described above, some obstacles remain. The program experiences poor socialization and yet removes geographical barriers for those living in remote areas. Family planning services provided for this sub population conducted outside the scheme as a complement strategy. However, UHC program has brought remarkable improvement in access and quality of family planning services.

Keywords: beneficiary, family planning services, national population and family planning board, universal health coverage

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Authors: Diego Rodrigues, Marcelo Lisboa, Elismar Batista, Marcos Dias

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Based on data on child labor, this work arises questions about how to understand and locate the factors that make up the child labor rates, and which properties are important to analyze these cases. Using data mining techniques to discover valid patterns on Brazilian social databases were evaluated data of child labor in the State of Tocantins (located north of Brazil with a territory of 277000 km2 and comprises 139 counties). This work aims to detect factors that are deterministic for the practice of child labor and their relationships with financial indicators, educational, regional and social, generating information that is not explicit in the government database, thus enabling better monitoring and updating policies for this purpose.

Keywords: social data, government decision making, association of social data, data mining

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Authors: Yesoda Bhargava

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This work is an ongoing research on understanding the existence or the non-existence of infrastructure for fitness for physically challenged people in India. Through the extensive field visits, interviews with differently abled people and observation of the schools for differently abled children, there have been some common observations in the realm of paucity of appropriate machinery, exercise physiologists and infrastructure catering to the fitness needs of physically challenged people in India both for adults and children. Amidst the more tangibly seen health issues, this crucial change which can better the life of physically challenged people is not given the due consideration at the national scale. The results of this study can be used to influence the policy making and program making related to inclusive health in India. Health and fitness are inextricably linked to each other, and one cannot be served at the cost of other. One of the other objectives of this paper is to create a traction for the importance of exercise promotion for the physically challenged people.

Keywords: fitness, health, inclusive health, exercise physiologists

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Authors: Zhi Zhu, Boquan Zhang, Tian Jing, Jingjing Li, Tao Wang

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Data assimilation is a model and data hybrid-driven method that dynamically fuses new observation data with a numerical model to iteratively approach the real system state. It is widely used in state prediction and parameter inference of continuous systems. Because of the discrete event system’s non-linearity and non-Gaussianity, traditional Kalman Filter based on linear and Gaussian assumptions cannot perform data assimilation for such systems, so particle filter has gradually become a technical approach for discrete event simulation data assimilation. Hence, we proposed a particle filter-based discrete event simulation data assimilation method and took the unmanned aerial vehicle (UAV) maintenance service system as a proof of concept to conduct simulation experiments. The experimental results showed that the filtered state data is closer to the real state of the system, which verifies the effectiveness of the proposed method. This research can provide a reference framework for the data assimilation process of other complex nonlinear systems, such as discrete-time and agent simulation.

Keywords: discrete event simulation, data assimilation, particle filter, model and data-driven

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Authors: Dhananjay W. Bansod, Santosh Phad

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Non-Communicable Diseases (NCD) are major contributing factors to the disease burden in the world as well as in India. With a growing proportion of older persons in India gives rise to several challenges. With the advancement of age, elderly is exposed to various kinds of health problems more specifically NCDs. Therefore, an effort has been made to examine the prevalence of NCDs among older persons and its treatment-seeking behaviour, also it is tried to explore the association between the NCDs and its effect on the overall wellbeing of older persons. Data used from “Building Knowledge Base of Population Ageing Survey” conducted in 2011 in seven states of India. Six chronic diseases used (non-communicable diseases) namely Arthritis, Hypertension, Cataract, Diabetes, Asthma and Heart diseases to understand the issues related to NCDs. Also seen the effect of NCDs on the wellbeing of the elderly, the subjective well-being consists of nine questions from which SUBI score generated for mental health status, which ranges from 9 to 27. This Index indicates that lower the score better is the mental health status. Further, this index modified and generated three categories of Better (9-15), Average (16-20) and Worse (21-27). The reliability analysis is carried out with the coefficient (Cronbach’s alpha) of the scale was 0.8884. The result shows that Orthopedic / musculoskeletal ailments involving arthritis, rheumatism and osteoarthritis are the most common type of ailment followed by hypertension. Two-thirds of the elderly reported suffering from at least one chronic ailment. Most chronic illness conditions received some form of treatment and mainly depend on public health facilities. Financial insecurity is the primary obstruction in seeking treatment for most of the chronic ailments which typically require a longer duration of medication and repeated medical consultations, both having significant economic implications. According to SUBI index, only 15 per cent of the elderly are in Better mental health status, and one-third of the elderly are with the worse score. Elderly with the ailments like Cataract, Asthma and Arthritis have worse mental health. It depicts that the burden of disease is more among the elderly and it is directly affecting the overall wellbeing of older persons.

Keywords: NCD, well-being, older person, India

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Authors: Jonathan Kissi, Baozhen Dai, Wisdom W. K. Pomegbe, Abdul-Basit Kassim

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Protecting patient’s digital information is a growing concern for healthcare institutions as people nowadays perpetually live their lives through telemedicine services. These telemedicine services have been confronted with several determinants that hinder their successful implementations, especially in developing countries. Identifying such determinants that influence the acceptance of telemedicine services is also a problem for healthcare professionals. Despite the tremendous increase in telemedicine services, its adoption, and use has been quite slow in some healthcare settings. Generally, it is accepted in today’s globalizing world that the success of telemedicine services relies on users’ satisfaction. Satisfying health professionals and patients are one of the crucial objectives of telemedicine success. This study seeks to investigate the determinants that influence health professionals’ intention to utilize telemedicine services in clinical activities in a sub-Saharan African country in West Africa (Ghana). A hybridized model comprising of health adoption models, including technology acceptance theory, diffusion of innovation theory, and protection of motivation theory, were used to investigate these quandaries. The study was carried out in four government health institutions that apply and regulate telemedicine services in their clinical activities. A structured questionnaire was developed and used for data collection. Purposive and convenience sampling methods were used in the selection of healthcare professionals from different medical fields for the study. The collected data were analyzed based on structural equation modeling (SEM) approach. All selected constructs showed a significant relationship with health professional’s behavioral intention in the direction expected from prior literature including perceived usefulness, perceived ease of use, management strategies, financial sustainability, communication channels, patients security threat, patients privacy risk, self efficacy, actual service use, user satisfaction, and telemedicine services systems securities threat. Surprisingly, user characteristics and response efficacy of health professionals were not significant in the hybridized model. The findings and insights from this research show that health professionals are pragmatic when making choices for technology applications and also their willingness to use telemedicine services. They are, however, anxious about its threats and coping appraisals. The identified significant constructs in the study may help to increase efficiency, quality of services, quality patient care delivery, and satisfactory user satisfaction among healthcare professionals. The implantation and effective utilization of telemedicine services in the selected hospitals will aid as a strategy to eradicate hardships in healthcare services delivery. The service will help attain universal health access coverage to all populace. This study contributes to empirical knowledge by identifying the vital factors influencing health professionals’ behavioral intentions to adopt telemedicine services. The study will also help stakeholders of healthcare to formulate better policies towards telemedicine service usage.

Keywords: telemedicine service, perceived usefulness, perceived ease of use, management strategies, security threats

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Authors: Adam Gushgari

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The SARS-CoV-2 pandemic has catalyzed the rapid adoption of wastewater-based epidemiology (WBE) methodologies both domestically and internationally. To support the rapid scale-up of pandemic-response wastewater surveillance systems, multiple federal agencies (i.e. US CDC), non-government organizations (i.e. Water Environment Federation), and private charities (i.e. Bill and Melinda Gates Foundation) have funded over $220 million USD supporting development and expanding equitable access of surveillance methods. Funds were primarily distributed directly to municipalities under the CARES Act (90.6%), followed by academic projects (7.6%), and initiatives developed by private companies (1.8%). In addition to federal funding for wastewater monitoring primarily conducted at wastewater treatment plants, state/local governments and private companies have leveraged wastewater sampling to obtain health and lifestyle data on student, prison inmate, and employee populations. We explore the viable paths for expansion of the WBE m1ethodology across a variety of analytical methods; the development of WBE-specific samplers and real-time wastewater sensors; and their application to various governments and private sector industries. Considerable investment in, and public acceptance of WBE suggests the methodology will be applied to other future notifiable diseases and health risks. Early research suggests that WBE methods can be applied to a host of additional “biological insults” including communicable diseases and pathogens, such as influenza, Cryptosporidium, Giardia, mycotoxin exposure, hepatitis, dengue, West Nile, Zika, and yellow fever. Interest in chemical insults is also likely, providing community health and lifestyle data on narcotics consumption, use of pharmaceutical and personal care products (PPCP), PFAS and hazardous chemical exposure, and microplastic exposure. Successful application of WBE to monitor analytes correlated with carcinogen exposure, community stress prevalence, and dietary indicators has also been shown. Additionally, technology developments of in situ wastewater sensors, WBE-specific wastewater samplers, and integration of artificial intelligence will drastically change the landscape of WBE through the development of “smart sewer” networks. The rapid expansion of the WBE field is creating significant business opportunities for professionals across the scientific, engineering, and technology industries ultimately focused on community health improvement.

Keywords: wastewater surveillance, wastewater-based epidemiology, smart cities, public health, pandemic management, substance abuse

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Authors: Sadam Alwadi

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Outlier values become a problem that frequently occurs in the data observation or recording process. Thus, the need for data imputation has become an essential matter. In this work, it will make use of the methods described in the prior work to detect the outlier values based on a collection of stock market data. In order to implement the detection and find some solutions that maybe helpful for investors, real closed price data were obtained from the Amman Stock Exchange (ASE). Tukey and Maximum Overlapping Discrete Wavelet Transform (MODWT) methods will be used to impute the detect the outlier values.

Keywords: outlier values, imputation, stock market data, detecting, estimation

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Authors: Rubaiat S. Ahmed, Jemer Garrido, Sergey M. Motov

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Clinical informatics (CI) enables the transformation of data into a systematic organization that improves the quality of care and the generation of positive health outcomes.Innovative technology through informatics that compiles accurate data on analgesic utilization in the emergency department can enhance pain management in this important clinical setting. We aim to establish a simplified reporting system through CI to examine and assess the analgesic prescribing practices in the EDthrough executing a U.S. federal grant project on opioid reduction initiatives. Queried data points of interest from a level-one trauma ED’s electronic medical records were used to create data sets and develop informational/visual reporting dashboards (on Microsoft Excel and Google Sheets) concerning analgesic usage across several pre-defined parameters and performance metrics using CI. The data was then qualitatively analyzed to evaluate ED analgesic prescribing trends by departmental clinicians and leadership. During a 12-month reporting period (Dec. 1, 2020 – Nov. 30, 2021) for the ongoing project, about 41% of all ED patient visits (N = 91,747) were for pain conditions, of which 81.6% received analgesics in the ED and at discharge (D/C). Of those treated with analgesics, 24.3% received opioids compared to 75.7% receiving opioid alternatives in the ED and at D/C, including non-pharmacological modalities. Demographics showed among patients receiving analgesics, 56.7% were aged between 18-64, 51.8% were male, 51.7% were white, and 66.2% had government funded health insurance. Ninety-one percent of all opioids prescribed were in the ED, with intravenous (IV) morphine, IV fentanyl, and morphine sulfate immediate release (MSIR) tablets accounting for 88.0% of ED dispensed opioids. With 9.3% of all opioids prescribed at D/C, MSIR was dispensed 72.1% of the time. Hydrocodone, oxycodone, and tramadol usage to only 10-15% of the time, and hydromorphone at 0%. Of opioid alternatives, non-steroidal anti-inflammatory drugs were utilized 60.3% of the time, 23.5% with local anesthetics and ultrasound-guided nerve blocks, and 7.9% with acetaminophen as the primary non-opioid drug categories prescribed by ED providers. Non-pharmacological analgesia included virtual reality and other modalities. An average of 18.5 ED opioid orders and 1.9 opioid D/C prescriptions per 102.4 daily ED patient visits was observed for the period. Compared to other specialties within our institution, 2.0% of opioid D/C prescriptions are given by ED providers, compared to the national average of 4.8%. Opioid alternatives accounted for 69.7% and 30.3% usage, versus 90.7% and 9.3% for opioids in the ED and D/C, respectively.There is a pressing need for concise, relevant, and reliable clinical data on analgesic utilization for ED providers and leadership to evaluate prescribing practices and make data-driven decisions. Basic computer software can be used to create effective visual reporting dashboards with indicators that convey relevant and timely information in an easy-to-digest manner. We accurately examined our ED's analgesic prescribing practices using CI through dashboard reporting. Such reporting tools can quickly identify key performance indicators and prioritize data to enhance pain management and promote safe prescribing practices in the emergency setting.

Keywords: clinical informatics, dashboards, emergency department, health informatics, healthcare informatics, medical informatics, opioids, pain management, technology

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Authors: Sudha T., Naveen C.

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Dengue is a serious public health issue that causes significant annual economic and welfare burdens on nations. However, enhanced optimization techniques and quantitative modeling approaches can predict the incidence of dengue. By advocating for a data-driven approach, public health officials can make informed decisions, thereby improving the overall effectiveness of sudden disease outbreak control efforts. The National Oceanic and Atmospheric Administration and the Centers for Disease Control and Prevention are two of the U.S. Federal Government agencies from which this study uses environmental data. Based on environmental data that describe changes in temperature, precipitation, vegetation, and other factors known to affect dengue incidence, many predictive models are constructed that use different machine learning methods to estimate weekly dengue cases. The first step involves preparing the data, which includes handling outliers and missing values to make sure the data is prepared for subsequent processing and the creation of an accurate forecasting model. In the second phase, multiple feature selection procedures are applied using various machine learning models and optimization techniques. During the third phase of the research, machine learning models like the Huber Regressor, Support Vector Machine, Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR) are compared with several optimization techniques for feature selection, such as Harmony Search and Genetic Algorithm. In the fourth stage, the model's performance is evaluated using Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) as assistance. Selecting an optimization strategy with the least number of errors, lowest price, biggest productivity, or maximum potential results is the goal. In a variety of industries, including engineering, science, management, mathematics, finance, and medicine, optimization is widely employed. An effective optimization method based on harmony search and an integrated genetic algorithm is introduced for input feature selection, and it shows an important improvement in the model's predictive accuracy. The predictive models with Huber Regressor as the foundation perform the best for optimization and also prediction.

Keywords: deep learning model, dengue fever, prediction, optimization

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Authors: J. R. Wang, Y. Chiang, W. S. Hsu, S. H. Chen, J. H. Yang, S. W. Chen, C. Shih, Y. F. Chang, Y. H. Huang, B. R. Shen

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In this research, the RASCAL code was used to simulate and analyze the postulated UF₆ fire accident which may occur in the Institute of Nuclear Energy Research (INER). There are four main steps in this research. In the first step, the UF₆ data of INER were collected. In the second step, the RASCAL analysis methodology and model was established by using these data. Third, this RASCAL model was used to perform the simulation and analysis of the postulated UF₆ fire accident. Three cases were simulated and analyzed in this step. Finally, the analysis results of RASCAL were compared with the hazardous levels of the chemicals. According to the compared results of three cases, Case 3 has the maximum danger in human health.

Keywords: RASCAL, UF₆, safety, hydrogen fluoride

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Authors: P. Jayashree, S. Rajkumar

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With social networks and smart devices generating a multitude of data, effective data management is the need of the hour for networks and cloud applications. Some applications need effective storage while some other applications need effective communication over networks and data reduction comes as a handy solution to meet out both requirements. Most of the data compression techniques are based on data statistics and may result in either lossy or lossless data reductions. Though lossy reductions produce better compression ratios compared to lossless methods, many applications require data accuracy and miniature details to be preserved. A variety of data compression algorithms does exist in the literature for different forms of data like text, image, and multimedia data. In the proposed work, a generic progressive compression algorithm, based on probabilistic encoding, called PEINS is projected as an enhancement over irrational number stored coding technique to cater to storage issues of increasing data volumes as a cost effective solution, which also offers data security as a secondary outcome to some extent. The proposed work reveals cost effectiveness in terms of better compression ratio with no deterioration in compression time.

Keywords: compression ratio, generic compression, irrational number storage, probabilistic encoding

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Authors: Femi Elegbeleye, Omobayo Esan, Muienge Mbodila, Patrick Bowe

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This paper focused on cost effective storage architecture using fog and cloud data storage gateway and presented the design of the framework for the data privacy model and data analytics framework on a real-time analysis when using machine learning method. The paper began with the system analysis, system architecture and its component design, as well as the overall system operations. The several results obtained from this study on data privacy model shows that when two or more data privacy model is combined we tend to have a more stronger privacy to our data, and when fog storage gateway have several advantages over using the traditional cloud storage, from our result shows fog has reduced latency/delay, low bandwidth consumption, and energy usage when been compare with cloud storage, therefore, fog storage will help to lessen excessive cost. This paper dwelt more on the system descriptions, the researchers focused on the research design and framework design for the data privacy model, data storage, and real-time analytics. This paper also shows the major system components and their framework specification. And lastly, the overall research system architecture was shown, its structure, and its interrelationships.

Keywords: IoT, fog, cloud, data analysis, data privacy

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Authors: Chinyama Lukama, Million Phiri, Namuunda Mutombo

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Background: Improving access and utilization to high-quality sexual and reproductive health (SRH) information and services, including family planning (FP) commodities, is central to the global developmental agenda of sub-Saharan Africa (SSA). Despite the importance of family planning use in enhancing maternal health outcomes and fertility reduction, the prevalence of adolescents and young women using modern contraception is generally low in SSA. Zambia is one of the countries in Southern Africa with a high prevalence of teenage pregnancies and fertility rates. Despite many initiatives that have been implemented to improve access and demand for family planning commodities, utilization of FP, especially among adolescents and young women, has generally been low. The objective of this research agenda was to better understand the determinants of modern contraceptive use in adolescents and young women in Zambia. This analysis produced findings that will be critical for informing the strengthening of sexual and reproductive health policy strategies aimed at bolstering the provision and use of maternal health services in order to further improve maternal health outcomes in the country. Method: The study used the recent data from the Demographic and Health Survey of 2018. A sample of 3,513 adolescents and young women (ADYW) were included in the analysis. Multilevel logistic regression models were employed to examine the association of individual and contextual factors with modern contraceptive use among adolescents and young women. Results: The prevalence of modern contraception among sexually active ADYW in Zambia was 38.1% [95% CI, 35.9, 40.4]. ADYW who had secondary or higher level education [aOR = 2.16, 95% CI=1.35–3.47], those with exposure to listening to the radio or watching television [aOR = 1.26, 95% CI=1.01–1.57], and those who had decision-making power at household level [aOR = 2.18, 95% CI=1.71–2.77] were more likely to use modern contraceptives. Conversely, strong neighborhood desire for large family size among ADYW [aOR = 0.65 95% CI = 0.47–0.88] was associated with less likelihood to use modern contraceptives. Community access to family planning information through community health worker visits increased the likelihood [aOR = 1.48, 95% CI=1.16–1.91] of using modern contraception among ADYW. Conclusion: The study found that both individual and community factors were key in influencing modern contraceptive use among adolescents and young women in Zambia. Therefore, when designing family planning interventions, the Government of Zambia, through its policymakers and sexual reproductive health program implementers at the Ministry of Health, in collaboration with stakeholders, should consider the community context. There should also be deliberate actions to encourage family planning education through the media.

Keywords: adolescents, young women, modern contraception use, fertility, family planning

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Authors: Aiman Mazhar Qureshi, Ahmed Rachid

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Extreme heat events are emerging human environmental health concerns in dense urban areas due to anthropogenic activities. High spatial and temporal resolution heat maps are important for urban heat adaptation and mitigation, helping to indicate hotspots that are required for the attention of city planners. The Heat Vulnerability Index (HVI) is the important approach used by decision-makers and urban planners to identify heat-vulnerable communities and areas that require heat stress mitigation strategies. Amiens is a medium-sized French city, where the average temperature has been increasing since the year 2000 by +1°C. Extreme heat events are recorded in the month of July for the last three consecutive years, 2018, 2019 and 2020. Poor air quality, especially ground-level ozone, has been observed mainly during the same hot period. In this study, we evaluated the HVI in Amiens during extreme heat days recorded last three years (2018,2019,2020). The Principal Component Analysis (PCA) technique is used for fine-scale vulnerability mapping. The main data we considered for this study to develop the HVI model are (a) socio-economic and demographic data; (b) Air pollution; (c) Land use and cover; (d) Elderly heat-illness; (e) socially vulnerable; (f) Remote sensing data (Land surface temperature (LST), mean elevation, NDVI and NDWI). The output maps identified the hot zones through comprehensive GIS analysis. The resultant map shows that high HVI exists in three typical areas: (1) where the population density is quite high and the vegetation cover is small (2) the artificial surfaces (built-in areas) (3) industrial zones that release thermal energy and ground-level ozone while those with low HVI are located in natural landscapes such as rivers and grasslands. The study also illustrates the system theory with a causal diagram after data analysis where anthropogenic activities and air pollution appear in correspondence with extreme heat events in the city. Our suggested index can be a useful tool to guide urban planners and municipalities, decision-makers and public health professionals in targeting areas at high risk of extreme heat and air pollution for future interventions adaptation and mitigation measures.

Keywords: heat vulnerability index, heat mapping, heat health-illness, remote sensing, urban heat mitigation

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Authors: Nordila Ahmad, Thamer Mohammad, Bruce W. Melville, Zuliziana Suif

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Current methods for predicting local scour at wide bridge piers, were developed on the basis of laboratory studies and very limited scour prediction were tested with field data. Laboratory wide pier scour equation from previous findings with field data were presented. A wide range of field data were used and it consists of both live-bed and clear-water scour. A method for assessing the quality of the data was developed and applied to the data set. Three other wide pier-scour equations from the literature were used to compare the performance of each predictive method. The best-performing scour equation were analyzed using statistical analysis. Comparisons of computed and observed scour depths indicate that the equation from the previous publication produced the smallest discrepancy ratio and RMSE value when compared with the large amount of laboratory and field data.

Keywords: field data, local scour, scour equation, wide piers

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Authors: Mastewal Endeshaw Getnet

Abstract:

Imunization is one of the most cost-effective and extensively adopted public health strategies for preventing child disability and mortality. Expanded Program on Immunization (EPI) was launched in 1974 with the goal of providing life-saving vaccines to all children in all and building on the success of the global smallpox eradication program. According to World Health Organization report, by 2020, all countries should have achieved 90% vaccination coverage. Many developing countries still have not achieved the goal. Ethiopia is one of Africa's developing countries. The Ethiopian Ministry of health (MoH) launched the EPI program in 1980, with the goal of achieving 90% coverage among children under the age of 1 year by 1990. Among children aged 12-23 months, complete immunization coverage was 47% based on the Ethiopian Demographic and Health Survey (EDAS) 2019 report. The coverage varies depending on the administrative region, ranging from 21% in Afar region to 89% in Amhara region, Ethiopia. Therefore, identifying risk factors for incomplete immunization among children is a key challenge, particularly in Ethiopia, which has a large geographical diversity and a predicted with 119.96 million projected population size in the year 2022. Despite its critical and challenging issue, this issue is still open and has not yet been fully investigated. Recently, a few previous studies have been conducted on the assessment of incomplete children immunization determinants. However, the majority of the studies were cross-sectional surveys that assessed only EPI coverage. Motivated by the above investigation, this study focuses on investigating determinants associated with incomplete immunization among Ethiopian children to facilitate the rate of full immunization coverage. Moreover, we consider both individual immunization and service performance-related factors to investigate incomplete children's determinants. Consequently, we adopted an ecological model in this study. Individual and environmental factors are combined in the Ecological model, which provides multilevel framework for exploring different determinants related with health behaviors. The Ethiopian Demographic and Health Survey will be used as a source of data from 2021 to achieve the objective of this study. The findings of this study will be useful to the Ethiopian government and other public health institutes to improve the coverage score of childhood immunization based on the identified risk determinants.

Keywords: incomplete immunization, children, ethiopia, ecological model

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