Search results for: epidemiological surveillance system

Authors: E. Bennion, A. Acharya, S. Barnes, D. Ferrell, S. Luckett-Cole, G. Mower, J. Nelson, Y. Nguyen

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Objective: This study aimed to evaluate the validity of a firearm injury query in the Early Notification of Community-based Epidemics syndromic surveillance system. Syndromic surveillance data are used at the Utah Department of Health for early detection of and rapid response to unusually high rates of violence and injury, among other health outcomes. The query of interest was defined by the Centers for Disease Control and Prevention and used chief complaint and discharge diagnosis codes to capture initial emergency department encounters for firearm injury of all intents. Design: Two epidemiologists manually reviewed electronic health records of emergency department visits captured by the query from April-May 2020, compared results, and sent conflicting determinations to two arbiters. Results: Of the 85 unique records captured, 67 were deemed probable, 19 were ruled out, and two were undetermined, resulting in a positive predictive value of 75.3%. Common reasons for false positives included non-initial encounters and misleading keywords. Conclusion: Improving the validity of syndromic surveillance data would better inform outbreak response decisions made by state and local health departments. The firearm injury definition could be refined to exclude non-initial encounters by negating words such as “last month,” “last week,” and “aftercare”; and to exclude non-firearm injury by negating words such as “pellet gun,” “air gun,” “nail gun,” “bullet bike,” and “exit wound” when a firearm is not mentioned.

Keywords: evaluation, health information system, firearm injury, syndromic surveillance

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Authors: Devi Srinivas, K. Sindhuja

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This paper presents architecture to improve surveillance applications based on the usage of the service oriented paradigm, with smart phones as user terminals, allowing application dynamic composition and increasing the flexibility of the system. According to the result of moving object detection research on video sequences, the movement of the people is tracked using video surveillance. The moving object is identified using the image subtraction method. The background image is subtracted from the foreground image, from that the moving object is derived. So the Background subtraction algorithm and the threshold value is calculated to find the moving image by using background subtraction algorithm the moving frame is identified. Then, by the threshold value the movement of the frame is identified and tracked. Hence, the movement of the object is identified accurately. This paper deals with low-cost intelligent mobile phone-based wireless video surveillance solution using moving object recognition technology. The proposed solution can be useful in various security systems and environmental surveillance. The fundamental rule of moving object detecting is given in the paper, then, a self-adaptive background representation that can update automatically and timely to adapt to the slow and slight changes of normal surroundings is detailed. While the subtraction of the present captured image and the background reaches a certain threshold, a moving object is measured to be in the current view, and the mobile phone will automatically notify the central control unit or the user through SMS (Short Message System). The main advantage of this system is when an unknown image is captured by the system it will alert the user automatically by sending an SMS to user’s mobile.

Keywords: security, graphical password, persuasive cued click points

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Authors: Maryam Maleki, Esther Mead, Mohammad Arani, Nitin Agarwal

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The proliferation of social media platforms like Twitter has heightened the consequences of the spread of misinformation. To understand and model the spread of misinformation, in this paper, we leveraged the SEIZ (Susceptible, Exposed, Infected, Skeptics) epidemiological model to describe the underlying process that delineates the spread of misinformation on Twitter. Compared to the other epidemiological models, this model produces broader results because it includes the additional Skeptics (Z) compartment, wherein a user may be Exposed to an item of misinformation but not engage in any reaction to it, and the additional Exposed (E) compartment, wherein the user may need some time before deciding to spread a misinformation item. We analyzed misinformation regarding the unrest in Washington, D.C. in the month of March 2020, which was propagated by the use of the #DCblackout hashtag by different users across the U.S. on Twitter. Our analysis shows that misinformation can be modeled using the concept of epidemiology. To the best of our knowledge, this research is the first to attempt to apply the SEIZ epidemiological model to the spread of a specific item of misinformation, which is a category distinct from that of rumor and hoax on online social media platforms. Applying a mathematical model can help to understand the trends and dynamics of the spread of misinformation on Twitter and ultimately help to develop techniques to quickly identify and control it.

Keywords: Black Lives Matter, epidemiological model, mathematical modeling, misinformation, SEIZ model, Twitter

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Authors: Abe D. Desta

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This study suggests a deep learning-based method for identifying and following moving objects in surveillance video. The proposed method uses a fast regional convolution neural network (F-RCNN) trained on a substantial dataset of vehicle images to first detect vehicles. A Kalman filter and a data association technique based on a Hungarian algorithm are then used to monitor the observed vehicles throughout time. However, in general, F-RCNN algorithms have been shown to be effective in achieving high detection accuracy and robustness in this research study. For example, in one study The study has shown that the vehicle detection and tracking, the system was able to achieve an accuracy of 97.4%. In this study, the F-RCNN algorithm was compared to other popular object detection algorithms and was found to outperform them in terms of both detection accuracy and speed. The presented system, which has application potential in actual surveillance systems, shows the usefulness of deep learning approaches in vehicle detection and tracking.

Keywords: artificial intelligence, computer vision, deep learning, fast-regional convolutional neural networks, feature extraction, vehicle tracking

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Authors: Mera Ababneh, Sayer Al-Azzam, Karem Alzoubi, Abeer Rababa'h

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Background: Medication errors are among the most common medical errors. Their occurrences result in patient’s mortality, morbidity, and additional healthcare costs. Continuous monitoring and detection is required. Objectives: The aim of this study was to compare medication errors in outpatient’s prescriptions in two different hospitals (paper system vs. electronic system). Methods: This was a cross sectional observational study conducted in two major hospitals; King Abdullah University Hospital (KAUH) and Princess Bassma Teaching Hospital (PBTH) over three months period. Data collection was conducted by two trained pharmacists at each site. During the study period, medication prescriptions and dispensing procedures were screened for medication errors in both participating centers by two trained pharmacist. Results: In the electronic prescription hospital, 2500 prescriptions were screened in which 631 medication errors were detected. Prescription errors were 231 (36.6%), and dispensing errors were 400 (63.4%) of all errors. On the other side, analysis of 2500 prescriptions in paper-based hospital revealed 3714 medication errors, of which 288 (7.8%) were prescription errors, and 3426 (92.2%) were dispensing errors. A significant number of 2496 (67.2%) were inadequately and/or inappropriately labeled. Conclusion: This study provides insight for healthcare policy makers, professionals, and administrators to invest in advanced technology systems, education, and epidemiological surveillance programs to minimize medication errors.

Keywords: medication errors, prescription errors, dispensing errors, electronic prescription, handwritten prescription

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Authors: Berger Saintius, Edna Ariste, Djeamsly Salomon

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Background: Maternal mortality is a preventable global health problem that affects developed, developing, and underdeveloped countries alike. Globally, maternal mortality rates have declined since 1990, but 830 women die every day from pregnancy and childbirth-related causes that are often preventable. Haiti, with a number of 529 maternal deaths per 100,000 live births, is one of the countries with the highest maternal mortality rate in the Caribbean. This study consists of analyzing maternal death surveillance data in Haiti from 2017-2020. Method : A descriptive study was conducted; data were extracted from the National Epidemiological Surveillance Network of maternal deaths from 2017 to 2020. Sociodemographic variables were analyzed. Excel and Epi Info 7.2 were used for data analysis. Frequency and proportion measurements were calculated. Results: 756 deaths were recorded for the study period: 42 (6%) in 2017, 168 (22%) in 2018, 265 (35%) in 2019, and 281 (37%) in 2020. The North Department recorded the highest number of deaths, 167 (22%). 83(11%) in Les Cayes. 96% of these deaths are people aged between 15 and 49. Conclusion. Maternal mortality is a major health problem in Haiti. Mobilization, participation, and involvement of communities, increase in obstetric care coverage and promotion of Family Planning are among the strategies to fight this problem.

Keywords: epidemiology, maternal death, hospital, Haiti

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Authors: Magdalena Barbara Kaziuk

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Introduction: In December 2019, the first case of an acute infectious disease of the respiratory system caused by the SARS-CoV-2 virus was recorded in Wuhan in Central China. On March 11, 2020, the World Health Organization restrictions, among others, in the travel industry. Aim: The aim of the study was the assessment of the preparedness of European cultural institutions and catering establishments within the sanitary and epidemiological dimension during the COVID-19 pandemic by Polish tourists and their sense of safety in selected destinations. Material and methods: The study involved 300 Polish tourists (125 females, 175 males, age 46.5+/-12.9 years) who traveled during the COVID-19 pandemic to Southern European countries. 5 most popular travel destinations were selected: Italy, Austria, Greece, Croatia, and Mediterranean islands. The tourists assessed cultural institutions and catering establishments with the use of a proprietary questionnaire which concerned the preparedness regarding the sanitary and epidemiological requirements and the tourists' sense of safety. The number of respondents was deliberate - 60 persons per each country. Results: The more stringent sanitary regimes, the higher the sense of safety in the study group of females aged 45-50 (p<0.005), while the more stringent sanitary and epidemiological issues are implemented, the shorter the stay (p<0.001). Less stringent restrictions resulted in increased sense of freedom and mental rest in the group of studied males (p<0.005). Conclusions: The respondents' opinions revealed that the highest level of safety with regard to sanitary and epidemiological requirements (masks covering mouth and nose worn by both personnel and society, the necessity to present the COVID passport, the possibility to disinfect hands) was observed in Austria and Italy, while shorter length of the stay in these countries resulted from high prices, particularly in catering establishments. According to the respondents, less stringent restrictions, among others lack of the necessity to own the COVID passport, were linked to Croatia and Mediterranean islands. The sense of safety was satisfying, while the sense of freedom and mental rest was high. declared a string of COVID-19 cases a pandemic. Most countries implemented numerous sanitary and epidemiological

Keywords: sanitary and epidemiological regimes, tourist facilities, COVID-19 pandemic, sense of safety

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Authors: Muhammad Asim Nazir

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The investigations reported in this manuscript were carried on the screening of one hundred and seventy-eight chickpea germplasm lines/cultivars against wilt disease, caused by Fusarium oxysporum f. sp. ciceris. The screening was conducted in vivo (field) conditions. The field screening was accompanied with the study of some epidemiological factors affecting the occurrence and severity of the disease. Among the epidemiological factors maximum temperature range (28-40°C), minimum temperature range (12-24°C), relative humidity (19-44%), soil temperature (26-41°C) and soil moisture range (19-34°C) was studied for affecting the disease incidence/severity. The results revealed that air temperature was positively correlated with diseases. Soil temperature data revealed that in all cultivars disease incidence was maximum as 39°C. Most of the plants show 40-50% disease incidence. Disease incidence decreased at 33.5°C. The result of correlation of relative humidity of air and wilt incidence revealed that all cultivars/lines were negatively correlated with relative humidity. With increasing relative humidity wilt incidence decreased and vice versa.

Keywords: chickpea, epidemiological, screening, disease

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Authors: Eddy K. Mukadi

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This work is a documentary and descriptive study devoted to the epidemiological, clinical, histopathological and therapeutic profile of breast cancer deals with the department of gynecology and obstetrics of the university clinics of Kinshasa during the period from 1 January 2014 to 31 December 2014. We have identified 56 cases of breast cancer. These cancers accounted for 45.2% of gynecological mammary cancers. The youngest in our series was 18 years old while the oldest was 74 years old; And the mean age of these patients was 43.4 years and mostly multiparous (35.7%). Brides (60.7%) and bachelors (26.8%) were the most affected by breast cancer. The reasons for consultation were dominated by nodules in the breast (48.2%) followed by pain (35.7%) and nipple discharge (14.3%). In 89.2% of the cases, it was the advanced clinical stage (stage 3 and 4) and the infiltrating ductal carcinoma was the most frequent histological type (75%) The malignant tumor was mainly in the left breast (55.3%), and chemotherapy with hormone therapy and patey was the most convenient treatment (42.8%), while patey mastectomy was performed in 12.5% of patients. Because of the high incidence of breast cancer identified in our study, some preventive measures must be taken into account to address this public health problem, including breast autopalpation once a month, Early detection system development of a national breast cancer policy and the implementation of a national breast cancer control program.

Keywords: breast cancer, histopathological profile, epidemiological profile, Kinshasa

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Authors: Woldegerima G. Medhin, Tadele Araya

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Background: Rabies is acute viral encephalitis affecting mainly carnivores and insectivorous but can affect any mammal. Case fatality rate is 100% once clinical signs appear. Rabies has a worldwide distribution in continental regions of Asia and Africa. Globally, rabies is responsible for more than 61000 human deaths annually. An estimation of human mortality rabies in Asia and Africa annually exceed 35172 and 21476 respectively. Ethiopia approximately 2900 people were estimated to die of rabies annually, Tigary region approximately 98 people were estimated to die annually. The aim of this study is to analyze trends, describe, and evaluate the ten years rabies data in Tigray, Ethiopia. Methods: We conducted descriptive epidemiological study from 15-30 February, 2023 of rabies exposure and death in humans by reviewing the health management information system report from Tigray Regional Health Bureau and vaccination coverage of dog population from 2013 to 2022. We used case definition, suspected cases are those bitten by the dogs displaying clinical signs consistent with rabies and confirmed cases were deaths from rabies at time of the exposure. Results: A total 21031 dog bites and 375 deaths report of rabies and 18222 post exposure treatments for humans in Tigray region were used. A suspected rabies patients had shown an increasing trend from 2013 to 2015 and 2018 to 2019. Overall mortality rate was 19/1000 in Tigray. Majority of suspected patients (45%) were age <15 years old. An estimated by Agriculture Bureau of Tigray Region about 12000 owned and 2500 stray dogs are available in the region, but yearly dog vaccination remains low (50%). Conclusion: Rabies is a public health problem in Tigray region. It is highly recommended to vaccinate individually owned dogs and concerned sectors should eliminate stray dogs. Surveillance system should strengthen for estimating the real magnitude, launch preventive and control measures.

Keywords: rabies, Virus, transmision, prevalence

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Authors: Jinsiang Shaw, Pik-Hoe Chen

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This paper aims to integrate human recognition, motion recognition, and object tracking technologies without requiring a pre-training database model for motion recognition or the unknown object itself. Furthermore, it can simultaneously track multiple users and multiple objects. Unlike other existing human motion recognition methods, our approach employs a rule-based condition method to determine if a user hand is approaching or departing an object. It uses a background subtraction method to separate the human and object from the background, and employs behavior features to effectively interpret human object-grabbing actions. With an object’s histogram characteristics, we are able to isolate and track it using back projection. Hence, a moving object trajectory can be recorded and the object itself can be located. This particular technique can be used in a camera surveillance system in a shopping area to perform real-time intelligent surveillance, thus preventing theft. Experimental results verify the validity of the developed surveillance algorithm with an accuracy of 83% for shoplifting detection.

Keywords: Automatic Tracking, Back Projection, Motion Recognition, Shoplifting

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Authors: Benoit Jauniaux, Azzam Ismail

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Objectives: The aims were to identify all incident adult cases of idiopathic inflammatory myopathies (IIMs) in the City of Leeds, UK, and to estimate the risk of cancer in IIMs as compared with the general population. Methods: Cases of IIMs were ascertained by review of all muscle biopsy reports from the Neuropathology Laboratory. A review of medical records was undertaken for each case to review the clinical diagnosis and collect epidemiological data such as age, ethnicity, sex, and comorbidities, including cancer. Leeds denominator population numbers were publicly obtainable. Results: Two hundred and six biopsy reports were identified, and after review, 50 incident cases were included in the study between June 2010 and January 2021. Out of the 50 cases, 27 were male, and 23 were female. The mean incidence rate of IIMs in Leeds throughout the study period was 7.42/1 000 000 person years. The proportion of IIMs cases with a confirmed malignancy was 22%. Compared to the general population, the relative risk of cancer was significantly greater in the IIMs population(31.56, P < 0.01). Conclusions: The incidence rate of IIMs in Leeds was consistent with data from previous literature, however, disagreement exists between different methods of IIMs case inclusion due to varying clinical criteria and definitions. IIMs are associated with increased risk of cancer however, the pathogenesis of this relationship still requires investigating. This study supports the practice of malignancy screening and long-term surveillance in patients with IIMs.

Keywords: idiopathic inflammatory myopathies, myositis, polymyositis, dermatomyositis, malignancy, epidemiology, incidence rate, relative risk

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Authors: Sisay Tiroro Salato

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Background: Ethiopia has been implementing the maternal death surveillance and response system to provide real-time actionable information, including causes of death and contributing factors. Analysis of maternal mortality surveillance data was conducted to identify the causes and underlying factors in Addis Ababa, Ethiopia. Methods: We carried out a retrospective surveillance data analysis of 324 maternal deaths reported in Addis Ababa, Ethiopia, from 2017 to 2021. The data were extracted from the national maternal death surveillance and response database, including information from case investigation, verbal autopsy, and facility extraction forms. The data were analyzed by computing frequency and presented in numbers, proportions, and ratios. Results: Of 324 maternal deaths, 92% died in the health facilities, 6.2% in transit, and 1.5% at home. The mean age at death was 28 years, ranging from 17 to 45. The maternal mortality ratio per 100,000 live births was 77for the five years, ranging from 126 in 2017 to 21 in 2021. The direct and indirect causes of death were responsible for 87% and 13%, respectively. The direct causes included obstetric haemorrhage, hypertensive disorders in pregnancy, puerperal sepsis, embolism, obstructed labour, and abortion. The third delay (delay in receiving care after reaching health facilities) accounted for 57% of deaths, while the first delay (delay in deciding to seek health care) and the second delay (delay in reaching health facilities) and accounted for 34% and 24%, respectively. Late arrival to the referral facility, delayed management after admission, andnon-recognition of danger signs were underlying factors. Conclusion: Over 86% of maternal deaths were attributed by avoidable direct causes. The majority of women do try to reach health services when an emergency occurs, but the third delays present a major problem. Improving the quality of care at the healthcare facility level will help to reduce maternal death.

Keywords: maternal death, surveillance, delays, factors

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Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

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Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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Authors: M. A. Alavianmehr, A. Tashk, A. Sodagaran

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Modeling background and moving objects are significant techniques for video surveillance and other video processing applications. This paper presents a foreground detection algorithm that is robust against illumination changes and noise based on adaptive mixture Gaussian model (GMM), and provides a novel and practical choice for intelligent video surveillance systems using static cameras. In the previous methods, the image of still objects (background image) is not significant. On the contrary, this method is based on forming a meticulous background image and exploiting it for separating moving objects from their background. The background image is specified either manually, by taking an image without vehicles, or is detected in real-time by forming a mathematical or exponential average of successive images. The proposed scheme can offer low image degradation. The simulation results demonstrate high degree of performance for the proposed method.

Keywords: image processing, background models, video surveillance, foreground detection, Gaussian mixture model

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Authors: Maryam Maleki, Esther Mead, Mohammad Arani, Nitin Agarwal

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This study is conducted to examine how opposing viewpoints related to COVID-19 were diffused on Twitter. To accomplish this, six datasets using two epidemiological models, SIR (Susceptible, Infected, Recovered) and SEIZ (Susceptible, Exposed, Infected, Skeptics), were analyzed. The six datasets were chosen because they represent opposing viewpoints on the COVID-19 pandemic. Three of the datasets contain anti-subject hashtags, while the other three contain pro-subject hashtags. The time frame for all datasets is three years, starting from January 2020 to December 2022. The findings revealed that while both models were effective in evaluating the propagation trends of these polarizing viewpoints, the SEIZ model was more accurate with a relatively lower error rate (6.7%) compared to the SIR model (17.3%). Additionally, the relative error for both models was lower for anti-subject hashtags compared to pro-subject hashtags. By leveraging epidemiological models, insights into the propagation trends of polarizing viewpoints on Twitter were gained. This study paves the way for the development of methods to prevent the spread of ideas that lack scientific evidence while promoting the dissemination of scientifically backed ideas.

Keywords: mathematical modeling, epidemiological model, seiz model, sir model, covid-19, twitter, social network analysis, social contagion

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Authors: Maram Shahad Dana Anfal

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This research paper presents the design of a surveillance drone with computer-aided durability and model analyses that provides a cost-effective and efficient solution for various applications. The quadcopter's design is based on a lightweight and strong structure made of materials such as aluminum and titanium, which provide a durable structure for the quadcopter. The structure of this product and the computer-aided durability system are both designed to ensure frequent repairs or replacements, which will save time and money in the long run. Moreover, the study discusses the drone's ability to track, investigate, and deliver objects more quickly than traditional methods, makes it a highly efficient and cost-effective technology. In this paper, a comprehensive analysis of the quadcopter's operation dynamics and limitations is presented. In both simulation and experimental data, the computer-aided durability system and the drone's design demonstrate their effectiveness, highlighting the potential for a variety of applications, such as search and rescue missions, infrastructure monitoring, and agricultural operations. Also, the findings provide insights into possible areas for improvement in the design and operation of the drone. Ultimately, this paper presents a reliable and cost-effective solution for surveillance applications by designing a drone with computer-aided durability and modeling. With its potential to save time and money, increase reliability, and enhance safety, it is a promising technology for the future of surveillance drones. operation dynamic equations have been evaluated successfully for different flight conditions of a quadcopter. Also, CAE modeling techniques have been applied for the modal risk assessment at operating conditions.Stress analysis have been performed under the loadings of the worst-case combined motion flight conditions.

Keywords: drone, material, solidwork, hypermesh

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Authors: Muhammad Tahir Riaz, Khalid Mehmood, Ahmad Waseem Akhtar, Tariq Abbas, Sadaqat Ali, Muhammad Altaf

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Livestock sector contributes around 55.9 and 11.8% to agriculture and GDP respectively, according to economic survey of Pakistan 2013-2014. The goats population has been estimated about 66.6 million (M). Parasitic infestation is a major health problem in goats causing loss in body weight, poor body condition, low birth weights, and difficulty in kidding. Keeping in view the utilization of these animals in the country, a pilot epidemiological survey was conducted to find out the major parasitic problems of goats in and around Derawar fort area, Cholistan. Data regarding 662 fecal samples of goats was collected from 25 tobas of Cholistan during June 2012 to June 2013. All the fecal samples were examined through Direct Smear Method and Salt Flotation Technique for the presence of helminth eggs. External parasites were taken from the various components of the carcass of goat and were conserved in 70% alcohol in hygienic, properly enclosed glass jars that were tagged thoroughly. The collected date was analyzed statistically by Chi-square test to find out the prevalence in goats. Out of 662 goats, 261 (39.42%) were found positive for parasites. 233 (35.20%) goats were found positive for gastrointestinal parasites while 28 (4.23%) were positive for external parasites including ticks 20 (3.02%) and mange 8 (1.21%). The higher prevalence of parasites in the study area may be due to pasture grazing, poor management and lack of extension work. In this regards proper management and control measures should be adopted to minimize the Parasitic Problems.

Keywords: Cholistan, goats, parasite, surveillance

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Authors: Sukhvinder Kaur, Ashok Agarwal

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Background: For the first time in 2009, India was able to generate estimates of HIV incidence (the number of new HIV infections per year). Analysis of epidemic projections helped in revealing that the number of new annual HIV infections in India had declined by more than 50% during the last decade (GOI Ministry of Health and Family Welfare, 2010). Then, National AIDS Control Organisation (NACO) planned to scale up its efforts in generating projections through epidemiological analysis and modelling by taking recent available sources of evidence such as HIV Sentinel Surveillance (HSS), India Census data and other critical data sets. Recently, NACO generated current round of HIV estimates-2012 through globally recommended tool “Spectrum Software” and came out with the estimates for adult HIV prevalence, annual new infections, number of people living with HIV, AIDS-related deaths and treatment needs. State level prevalence and incidence projections produced were used to project consequences of the epidemic in spectrum. In presence of HIV estimates generated at state level in India by NACO, USIAD funded PIPPSE project under the leadership of NACO undertook the estimations and projections to district level using same Spectrum software. In 2011, adult HIV prevalence in one of the high prevalent States, Maharashtra was 0.42% ahead of the national average of 0.27%. Considering the heterogeneity of HIV epidemic between districts, two districts of Maharashtra – Thane and Mumbai were selected to estimate and project the number of People-Living-with-HIV/AIDS (PLHIV), HIV-prevalence among adults and annual new HIV infections till 2017. Methodology: Inputs in spectrum included demographic data from Census of India since 1980 and sample registration system, programmatic data on ‘Alive and on ART (adult and children)’,‘Mother-Baby pairs under PPTCT’ and ‘High Risk Group (HRG)-size mapping estimates’, surveillance data from various rounds of HSS, National Family Health Survey–III, Integrated Biological and Behavioural Assessment and Behavioural Sentinel Surveillance. Major Findings: Assuming current programmatic interventions in these districts, an estimated decrease of 12% points in Thane and 31% points in Mumbai among new infections in HRGs and migrants is observed from 2011 by 2017. Conclusions: Project also validated decrease in HIV new infection among one of the high risk groups-FSWs using program cohort data since 2012 to 2016. Though there is a decrease in HIV prevalence and new infections in Thane and Mumbai, further decrease is possible if appropriate programme response, strategies and interventions are envisaged for specific target groups based on this evidence. Moreover, evidence need to be validated by other estimation/modelling techniques; and evidence can be generated for other districts of the state, where HIV prevalence is high and reliable data sources are available, to understand the epidemic within the local context.

Keywords: HIV sentinel surveillance, high risk groups, projections, new infections

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Authors: Julian Iliev

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The recent release of The Matrix Resurrections persuaded many film scholars that The Matrix trilogy had lost its appeal and its concepts were largely outdated. This study examines the human pods and growing fields in the trilogy. Their functionality is compared to Michel Foucault’s concept of docile bodies: linking fictional and contemporary worlds. This paradigm is scrutinized through surveillance literature. The analogy brings to light common elements of hidden surveillance practices in technologies. The comparison illustrates the effects of body manipulation portrayed in the movies and their relevance with contemporary surveillance practices. Many scholars have utilized a close reading methodology in film studies (J.Bizzocchi, J.Tanenbaum, P.Larsen, S. Herbrechter, and Deacon et al.). The use of a particular lens through which media text is examined is an indispensable factor that needs to be incorporated into the methodology. The study spotlights both scenes from the trilogy depicting the human pods and growing fields. The functionality of the pods and the fields compare directly with Foucault’s concept of docile bodies. By utilizing Foucault’s study as a lens, the research will unearth hidden components and insights into the films. Foucault recognizes three disciplines that produce docile bodies: 1) manipulation and the interchangeability of individual bodies, 2) elimination of unnecessary movements and management of time, and 3) command system guaranteeing constant supervision and continuity protection. These disciplines can be found in the pods and growing fields. Each body occupies a single pod aiding easier manipulation and fast interchangeability. The movement of the bodies in the pods is reduced to the absolute minimum. Thus, the body is transformed into the ultimate object of control – minimum movement correlates to maximum energy generation. Supervision is exercised by wiring the body with numerous types of cables. This ultimate supervision of body activity reduces the body’s purpose to mere functioning. If a body does not function as an energy source, then it’s unplugged, ejected, and liquefied. The command system secures the constant supervision and continuity of the process. To Foucault, the disciplines are distinctly different from slavery because they stop short of a total takeover of the bodies. This is a clear difference from the slave system implemented in the films. Even though their system might lack sophistication, it makes up for it in the elevation of functionality. Further, surveillance literature illustrates the connection between the generation of body energy in The Matrix trilogy to the generation of individual data in contemporary society. This study found that the three disciplines producing docile bodies were present in the portrayal of the pods and fields in The Matrix trilogy. The above comparison combined with surveillance literature yields insights into analogous processes and contemporary surveillance practices. Thus, the constant generation of energy in The Matrix trilogy can be equated to the consistent data generation in contemporary society. This essay shows the relevance of the body manipulation concept in the Matrix films with contemporary surveillance practices.

Keywords: docile bodies, film trilogies, matrix movies, michel foucault, privacy loss, surveillance

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Authors: Özlem Canbolat, Sevgisun Kapucu

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The aim of this study was to determine the effect of a computer-assisted glycemic surveillance protocol on nursing workload in intensive care unit. The study is completed in an Education and Research Hospital in Ankara with the attendance of volunteered 19 nurse who had been worked in reanimation unit. Nurses used the written protocol and computer-assisted glycemic surveillance protocol for glycemic follow-up approach of the intensive care patients. Nurses used the written protocol first in the glycemic follow-up of the patient, then used the computer-assisted protocol. (Nurses used the written protocol first, then the computer-assisted protocol in the glycemic follow-up of the patient). Less time was spent in glycemic control with computerized protocol than written protocol and this difference is statistically significant (p < 0.001). It was determined that the computerized protocol application was completed in about 10 seconds (25% shorter) than the written protocol implementation. The computer-assisted glycemic surveillance protocol was found to be more easy and appropriate by nurses and the satisfaction level of the users was higher than with written protocol. While 79% of the nurses find it confusing to implement the written protocol, 79% were satisfied with the use of computerized protocol.

Keywords: computer-assisted protocol, glycemic control, insulin infusion protocol, intensive care, nursing workload

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Authors: Ali Ganoun, Wesam Algablawi, Wasim BenAnaif

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Video based traffic surveillance based on License Plate Recognition (LPR) system is an essential part for any intelligent traffic management system. The LPR system utilizes computer vision and pattern recognition technologies to obtain traffic and road information by detecting and recognizing vehicles based on their license plates. Generally, the video based LPR system is a challenging area of research due to the variety of environmental conditions. The LPR systems used in a wide range of commercial applications such as collision warning systems, finding stolen cars, controlling access to car parks and automatic congestion charge systems. This paper presents an automatic LPR system of Libyan license plate. The performance of the proposed system is evaluated with three video sequences.

Keywords: license plate recognition, localization, segmentation, recognition

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Authors: Joulié Aurélien, Isabelle Desjardins, Elsa Jourdain, Sophie Pradier, Dufour Philippe, Elodie Rousset, Agnès Leblond

Abstract:

Q fever is a worldwide zoonosis caused by the bacterium Coxiella burnetii. It may infect a broad range of host species, including horses. Although the role of horses in C. burnetii infections remains unknown, their use as sentinel species may be interesting to better assess the human risk exposure. Thus, we aimed to assess the C. burnetii horse exposition in a French endemic area by describing the antibody dynamics detected in serum; investigating the pathogen circulation in the horse environment, and exploring potential links with unexplained syndromes. Blood samples were collected in 2015 and 2016 on 338 and 294 horses, respectively and analyzed by ELISA. Ticks collected on horses were identified, and C. burnetii DNA detection was performed by qPCR targeting the IS1111 gene. Blood sample analyses revealed a significant increase of the seroprevalence in horses between both years, from 11% [7.67; 14.43] to 25% [20.06; 29.94]. On 36 seropositive horses in 2015 and 73 in 2016, 5 and four respectively showed clinical signs compatible with a C. burnetii infection (i.e., chronic fever or respiratory disorders, unfitness and unexplained weight loss). DNA was detected in almost 40% of ticks (n=59/148 in 2015 and n=103/305 in 2016) and exceptionally in dust samples (n=2/46 in 2015 and n=1/14 in 2016) every year. The C. burnetti detection in both the serum and the environment of horses confirm their exposure to the bacterium. Therefore, consideration should be given to target a relevant sentinel species to better assess the Q fever surveillance depending on the epidemiological context.

Keywords: ELISA, Q fever, qPCR, syndromic surveillance

Procedia PDF Downloads 234

Authors: Shourav Chowdhury, Subrata Barua, K. M. Naimuddin, Imam Hassan Sajib, Md. Hasan, Shudipta Banik, Muna Das

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Traffic accidents stand as a leading cause of fatalities worldwide, significantly impacting global mortality rates. Accurate classification of road accidents through advanced technological solutions presents a crucial opportunity to revolutionize accident prevention and emergency response strategies. This paper presents an advanced deep-learning methodology customized for the classification of road accidents using CCTV surveillance footage. This real-time dataset, comprising approximately 18,000 frames, has been amassed, which is pivotal for enabling comprehensive research in this field. This substantial dataset is the foundation for these investigative efforts, providing a rich and diverse source for conducting an in-depth analysis of the features. It has achieved a remarkable accuracy of 97% on this dataset through the strategic utilization of transfer learning in conjunction with LSTM (Long short-term memory) techniques. This accomplishment underscores the efficacy of our approach, combining the strengths of transfer learning and LSTM models, resulting in a highly accurate classification system for road accident events.

Keywords: accident, CCTV, footage, long short-term memory, surveillance

Procedia PDF Downloads 23

Authors: Mulugeta K. Tefera, Xiaolong Yang, Jian Liu

Abstract:

Detection and tracking of moving objects are very important in many application contexts such as detection and recognition of people, visual surveillance and automatic generation of video effect and so on. However, the task of detecting a real shape of an object in motion becomes tricky due to various challenges like dynamic scene changes, presence of shadow, and illumination variations due to light switch. For such systems, once the moving object is detected, tracking is also a crucial step for those applications that used in military defense, video surveillance, human computer interaction, and medical diagnostics as well as in commercial fields such as video games. In this paper, an object presents in dynamic background is detected using adaptive mixture of Gaussian based analysis of the video sequences. Then the detected moving object is tracked using the region based moving object tracking and inter-frame differential mechanisms to address the partial overlapping and occlusion problems. Firstly, the detection algorithm effectively detects and extracts the moving object target by enhancing and post processing morphological operations. Secondly, the extracted object uses region based moving object tracking and inter-frame difference to improve the tracking speed of real-time moving objects in different video frames. Finally, the plotting method was applied to detect the moving objects effectively and describes the object’s motion being tracked. The experiment has been performed on image sequences acquired both indoor and outdoor environments and one stationary and web camera has been used.

Keywords: background modeling, Gaussian mixture model, inter-frame difference, object detection and tracking, video surveillance

Procedia PDF Downloads 445

Authors: Ahmadu Girgiri, Lawan Gana Ali, Mamman M. Baba

Abstract:

Environmental security clearly articulates the perfections and developments of various communities around the world irrespective of the region, culture, religion or social inclination. Although, the present state of insecurity has become serious issue devastating the peace, unity, stability and progress of man and his physical environment particularly in developing countries. Recently, measure of security and it management in Nigeria has been a bottle-neck to the effectiveness and advancement of various sectors that include; business, education, social relations, politics and above all an economy. Several measures have been considered on mitigating environment insecurity such as surveillance, demarcation, security personnel empowerment and the likes, but still the issue remains disturbing. In this paper, we present the application of new technology that contributes to the improvement of security surveillance known as “Wireless Sensor Network (WSN)”. The system is new, smart and emerging technology that provides monitoring, detection and aggregation of information using sensor nodes and wireless network. WSN detects, monitors and stores information or activities in the deployed area such as schools, environment, business centers, public squares, industries, and outskirts and transmit to end users. This will reduce the cost of security funding and eases security surveillance depending on the nature and the requirement of the deployment.

Keywords: application, environment, insecurity, sensor, wireless sensor network

Procedia PDF Downloads 217

Authors: Won-Ho Kim

Abstract:

In this paper, a design of H.263 based wireless video transceiver is presented for wireless camera system. It uses standard WIFI transceiver and the covering area is up to 100m. Furthermore the standard H.263 video encoding technique is used for video compression since wireless video transmitter is unable to transmit high capacity raw data in real time and the implemented system is capable of streaming at speed of less than 1Mbps using NTSC 720x480 video.

Keywords: wireless video transceiver, video surveillance camera, H.263 video encoding digital signal processing

Procedia PDF Downloads 340

Authors: Martynova Alina, Lyubov Buzoleva

Abstract:

Streptococcus pneumoniae is the causative agent of pneumonias and meningitids throught all the world. Having high genetic diversity, this microorganism can cause different clinical forms of pneumococcal infections and microbiologically it is really difficult diagnosed by routine methods. Also, epidemiological surveillance requires more developed methods of molecular typing because the recent method of serotyping doesn't allow to distinguish invasive and non-invasive isolates properly. Non-coding genome of bacteria seems to be the interesting source for seeking of highly distinguishable markers to discriminate the subspecies of such a variable bacteria as Streptococcus pneumoniae. Technically, we proposed scheme of discrimination of S.pneumoniae strains with amplification of non-coding region (SP_1932) with the following restriction with 2 types of enzymes of Alu1 and Mn1. Aim: This research aimed to compare different methods of typing and their application for molecular epidemiology purposes. Methods: we analyzed population of 100 strains of S.pneumoniae isolated from different patients by different molecular epidemiology methods such as pulse-field gel electophoresis (PFGE), restriction polymorphism analysis (RFLP) and multilolocus sequence typing (MLST), and all of them were compared with classic typing method as serotyping. The discriminative power was estimated with Simpson Index (SI). Results: We revealed that the most discriminative typing method is RFLP (SI=0,97, there were distinguished 42 genotypes).PFGE was slightly less discriminative (SI=0,95, we identified 35 genotypes). MLST is still the best reference method (SI=1.0). Classic method of serotyping showed quite weak discriminative power (SI=0,93, 24 genotypes). In addition, sensivity of RFLP was 100%, specificity was 97,09%. Conclusion: the most appropriate method for routine epidemiology surveillance is RFLP with non-coding region of Streptococcsu pneumoniae, then PFGE, though in some cases these results should be obligatory confirmed by MLST.

Keywords: molecular epidemiology typing, non-coding genome, Streptococcus pneumoniae, MLST

Procedia PDF Downloads 359

Authors: Muleya Nqobile, Winston Garira

Abstract:

We presented a compartmental deterministic multi-scale model which encompass internal plant defensive mechanism and pathogen interaction, then we consider nesting the model into the epidemiological model. The objective was to improve our understanding of the transmission dynamics of within host and between host of Guignardia citricapa Kiely. The inflow of infected class was scaled down to individual level while the outflow was scaled up to average population level. Conceptual model and mathematical model were constructed to display a theoretical framework which can be used for predicting or identify disease pattern.

Keywords: epidemiological model, mathematical modelling, multi-scale modelling, immunological model

Procedia PDF Downloads 424

Authors: Mike Dee

Abstract:

Urban public spaces are sutured with a range of surveillance and sensor technologies that claim to enable new forms of ‘data based citizen participation’, but also increase the tendency for ‘function-creep’, whereby vast amounts of data are gathered, stored and analysed in a broad application of urban surveillance. This kind of monitoring and capacity for surveillance connects with attempts by civic authorities to regulate, restrict, rebrand and reframe urban public spaces. A direct consequence of the increasingly security driven, policed, privatised and surveilled nature of public space is the exclusion or ‘unfavourable inclusion’ of those considered flawed and unwelcome in the ‘spectacular’ consumption spaces of many major urban centres. In the name of urban regeneration, programs of securitisation, ‘gentrification’ and ‘creative’ and ‘smart’ city initiatives refashion public space as sites of selective inclusion and exclusion. In this context of monitoring and control procedures, in particular, children and young people’s use of space in parks, neighbourhoods, shopping malls and streets is often viewed as a threat to the social order, requiring various forms of remedial action. This paper suggests that cities, places and spaces and those who seek to use them, can be resilient in working to maintain and extend democratic freedoms and processes enshrined in Marshall’s concept of citizenship, calling sensor and surveillance systems to account. Such accountability could better inform the implementation of public policy around the design, build and governance of public space and also understandings of urban citizenship in the sensor saturated urban environment.

Keywords: citizenship, public space, surveillance, young people

Procedia PDF Downloads 420