Search results for: public health surveillance

Authors: Taurai T. Chikotie, Bruce W. Watson

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The manifestation of ‘new’ infectious diseases and the re-emergence of ‘old’ infectious diseases now present global problems and Southern Africa has not been spared from such calamity. Although having an organized public health system, countries in this region have failed to leverage on the proliferation in use of Information and Communication Technologies to promote effective disease surveillance. Objective: The objective of this study was to critically review and analyse the crucial variables to consider in the development and implementation of electronic disease surveillance systems in public health within the context of Southern Africa. Methodology: A critical review of literature published in English using, Google Scholar, EBSCOHOST, Science Direct, databases from the Centre for Disease Control (CDC and articles from the World Health Organisation (WHO) was undertaken. Manual reference and grey literature searches were also conducted. Results: Little has been done towards harnessing the potential of information technologies towards disease surveillance and this has been due to several challenges that include, lack of funding, lack of health informatics experts, poor supporting infrastructure, an unstable socio-political and socio-economic ecosystem in the region and archaic policies towards integration of information technologies in public health governance. Conclusion: The Southern African region stands to achieve better health outcomes if they adopt the use of e-disease surveillance systems in public health. However, the dynamics and complexities of the socio-economic, socio-political and technical variables would need addressing to ensure the successful development and implementation of e-disease surveillance systems in the region.

Keywords: critical review, disease surveillance, public health informatics, Southern Africa

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Authors: Chawarat Rotejanaprasert, Andrew Lawson

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Early detection of unusual health events depends on the ability to detect rapidly any substantial changes in disease, thus facilitating timely public health interventions. To assist public health practitioners to make decisions, statistical methods are adopted to assess unusual events in real time. We introduce a surveillance Kullback-Leibler (SKL) measure for timely detection of disease outbreaks for small area health data. The detection methods are compared with the surveillance conditional predictive ordinate (SCPO) within the framework of Bayesian hierarchical Poisson modeling and applied to a case study of a group of respiratory system diseases observed weekly in South Carolina counties. Properties of the proposed surveillance techniques including timeliness and detection precision are investigated using a simulation study.

Keywords: Bayesian, spatial, temporal, surveillance, prospective

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Authors: Stephen L. Roberts

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This article offers a critical analysis of the rise of syndromic surveillance systems for the advanced detection of pandemic threats within contemporary global health security frameworks. The article traces the iterative evolution and ascendancy of three such novel syndromic surveillance systems for the strengthening of health security initiatives over the past two decades: 1) The Program for Monitoring Emerging Diseases (ProMED-mail); 2) The Global Public Health Intelligence Network (GPHIN); and 3) HealthMap. This article demonstrates how each newly introduced syndromic surveillance system has become increasingly oriented towards the integration of digital algorithms into core surveillance capacities to continually harness and forecast upon infinitely generating sets of digital, open-source data, potentially indicative of forthcoming pandemic threats. This article argues that the increased centrality of the algorithm within these next-generation syndromic surveillance systems produces a new and distinct form of infectious disease surveillance for the governing of emergent pathogenic contingencies. Conceptually, the article also shows how the rise of this algorithmic mode of infectious disease surveillance produces divergences in the governmental rationalities of global health security, leading to the rise of an algorithmic governmentality within contemporary contexts of Big Data and these surveillance systems. Empirically, this article demonstrates how this new form of algorithmic infectious disease surveillance has been rapidly integrated into diplomatic, legal, and political frameworks to strengthen the practice of global health security – producing subtle, yet distinct shifts in the outbreak notification and reporting transparency of states, increasingly scrutinized by the algorithmic gaze of syndromic surveillance.

Keywords: algorithms, global health, pandemic, surveillance

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Authors: Bennasser Samira

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Meningitis, especially the meningococcal one, is a serious problem of public health. A system of vigilanceand surveillance is in place to allow effective actions to be taken on actual or potential health problems caused by all forms of meningitis. Objectives: 1. Describe the epidemiological surveillance system for meningitis in the province of Taza. 2. Evaluate the quality and responsiveness of the epidemiological surveillance system for meningitis in the province of Taza. 3. Propose measures to improve this system at the provincial level. Methods: This was a descriptive study with a purely quantitative approach by evaluating the quality and responsiveness of the system during 5 years between January 2016 and December 2020. We usedfor that the investigation files of meningitis cases and the provincial database of meningitis. We calculated some quality indicators of surveillance system already defined by the National Program for the Prevention and Control of Meningitis. Results: The notification is passive, the completeness of the data is quite good (94%), and the timeliness don’t exceed 71%. The quality of the data is acceptable (91% agreement). The systematic and rapid performance of lumbar punctures increases the diagnostic capabilities of the system. The local response actions are effected in 100%. Conclusion: The improvement of this surveillance system depends on strengthening the staff skills in diagnostic, reviewing surveillance tools, and encouraging judicious use of the data.

Keywords: evaluation, meningitis, system, taza, morocco

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Authors: Mike Dee

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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

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Authors: Jina K., Kittinan C. Athitaya J., Weerapat B., Amornrat T., Waraphan N.

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Working in the exploration and production of petroleum exposed workers to various health risks, including but not limited to physical and chemical risks. Although lots of barriers have been put in place, e.g., hazard monitoring in the workplace, appropriate training on health hazards, proper personal protective equipment (PPE), the health hazard may harm the workers if the barriers are not effectively implemented. To prove the effectiveness of these barriers, it is necessary to monitor exposure by putting in place the medical surveillance program via biological monitoring of chemical hazards and physical check-ups for physical hazards. Medical surveillance management is the systematic assessment and monitoring of employees exposed or potentially exposed to occupational hazards with the goal of reducing and ultimately preventing occupational illness and injury. The paper aims to demonstrate the effectiveness of medical surveillance management in mitigating health risks associated with physical and chemical hazards in the petroleum industry by focusing on implementing programs for biological monitoring and physical examinations, including defining procedures for biological monitoring, urine sample collection, physical examinations, and result management on offshore petroleum platforms. The implementation of medical surveillance management has proven effective in monitoring worker exposure to physical and chemical hazards, leading to reduced medical expenses and the risk associated with work-related diseases significantly.

Keywords: medical surveillance, petroleum industry, occupational hazards, medical surveillance process

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Authors: Djeamsly Salomon

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Background: Epidemiological surveillance is a dynamic national system used to observe all aspects of the evolution of priority health problems, through: collection, analysis, systematic interpretation of information, and dissemination of results with necessary recommendations. The study was conducted to assess the mandatory disease surveillance system in the Sud Department. Methods: A study was conducted from March to May 2021 with key players involved in surveillance at the level of health institutions in the department . The CDC's 2021 updated guideline was used to evaluate the system. We collected information about the operation, attributes, and usefulness of the surveillance system using interviewer-administered questionnaires. Epi-Info7.2 and Excel 2016 were used to generate the mean, frequencies and proportions. Results: Of 30 participants, 23 (77%) were women. The average age was 39 years[30-56]. 25 (83%) had training in epidemiological surveillance. (50%) of the forms checked were signed by the supervisor. Collection tools were available at (80%). Knowledge of at least 7 notifiable diseases was high (100%). Among the respondents, 29 declared that the collection tools were simple, 27 had already filled in a notification form. The maximum time taken to fill out a form was 10 minutes. The feedback between the different levels was done at (60%). Conclusion: The surveillance system is useful, simple, acceptable, representative, flexible, stable and responsive. The data generated was of high quality. However, it is threatened by the lack of supervision of sentinel sites, lack of investigation and weak feedback. This evaluation demonstrated the urgent need to improve supervision in the sites and to feedback information. Strengthen epidemiological surveillance.

Keywords: evaluation, notifiable diseases, surveillance, system

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Authors: Walid Abdallah, Noureddine Boudriga

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Wireless sensor networks have shown their effectiveness in the deployment of many critical applications especially in the military domain. Border surveillance is one of these applications where a set of wireless sensors are deployed along a country border line to detect illegal intrusion attempts to the national territory and report this to a control center to undergo the necessary measures. Regarding its nature, this wireless sensor network can be the target of many security attacks trying to compromise its normal operation. Particularly, in this application the deployment and location of sensor nodes are of great importance for detecting and tracking intruders. This paper proposes a location-based authentication and key distribution mechanism to secure wireless sensor networks intended for border surveillance where the key establishment is performed using elliptic curve cryptography and identity-based public key scheme. In this scheme, the public key of each sensor node will be authenticated by keys that depend on its position in the monitored area. Before establishing a pairwise key between two nodes, each one of them must verify the neighborhood location of the other node using a message authentication code (MAC) calculated on the corresponding public key and keys derived from encrypted beacon messages broadcast by anchor nodes. We show that our proposed public key authentication and key distribution scheme is more resilient to node capture and node replication attacks than currently available schemes. Also, the achievement of the key distribution between nodes in our scheme generates less communication overhead and hence increases network performances.

Keywords: wireless sensor networks, border surveillance, security, key distribution, location-based

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Authors: Dina A. Amu, Fifi N. Afifah, Catur Rosidati, Tirton Nefianto

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Indonesia was shaken up by the avian influenza cases that had caused the country suffered losses of millions of dollars. The avian influenza case had even been suspected as a bioterrorism attack since it was an uncommon case in epidemiology. Furthermore, this avian influenza virus is a high pathogenic one and Indonesia has the highest case of fatality rate in the world. Bioterrorism threats or epidemic potential disease outbreaks currently does not exist in Tanjung Priok port yet. However, the surveillance system enhancement on epidemic potential diseases should be taken as a prevention, especially because Indonesia is currently facing the ASEAN Economic Society (AES). Therefore, this research evaluates the health surveillance system which is organized by Control, Quarantine and Surveillance Department, Health Office of Tanjung Priok Port. This study uses qualitative-evaluative method which utilizes Urgency Seriousness Growth (USG) method to determine priority issues and Root Cause analysis to determine the cause of prior problem. The result of this research shows that the implementation of epidemic potential disease surveillance in Tanjung Priok port has not done in the best possible way. It is because the lack of time allocation and the succinctness of the check list of ship's environmental health inspection. Therefore, Health Ministry of Indonesia should recruit more employees at the health office of Tanjung Priok port, hold a simulation of ship's inspection and simplify the list for ship's environmental health inspection.

Keywords: surveillance, epidemic potential disease, port health, bioterrorism

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Authors: Orathai Srithongtham, Ploypailin Mekathepakorn, Tossaphong Buraman, Pontida Moonpradap, Rungrueng Kitpati, Chulapon Kratet, Worayuth Nak-ai, Suwaree Charoenmukkayanan, Peeranuch Keawkanya

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The COVID-19 pandemic was effect to the health security of the Thai people. The PHEM principle was essential to the surveillance, prevention, and control of COVID-19. This study aimed to present the process of prevention and control of COVID-19 from February 29, 2021- April 30, 2022, and the factors and conditions influent the successful outcome. The study areas were three provinces. The target group was 37 people, composed of public health personnel. The data was collected in-depth, and group interviews followed the non-structure interview guide and were analyzed by content analysis. The components of COVID-19 prevention and control were found in the process of PHEM as follows; 1) Emergency Operation Center (EOC) with an incidence command system (ICS) from the district to provincial level and to propose the provincial measure, 2) Provincial Communicable Disease Committee (PCDC) to decide the provincial measure 3) The measure for surveillance, prevention, control, and treatment of COVID-19, and 4) outcomes and best practices for surveillance and control of COVID-19. The success factors of 4S and EC were as follows; Space: prepare the quarantine (HQ, LQ), Cohort Ward (CW), field hospital, and community isolation and home isolation to face with the patient and risky group, Staff network from various organization and group cover the community leader and Health Volunteer (HV), Stuff the management and sharing of the medical and non-medical equipment, System of Covid-19 respond were EOC, ICS, Joint Investigation Team (JIT) and Communicable Disease Control Unit (CDCU) for monitoring the real-time of surveillance and control of COVID-19 output, Environment management in hospital and the community with Infections Control (IC) principle, and Culture in term of social capital on “the relationship of Isan people” supported the patient provide the good care and support. The structure of PHEM, Isan’s Culture, and good preparation was a significant factor in the three provinces.

Keywords: public health, emergency management, covid-19, pandemic

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Authors: K. Mellou, G. Anastopoulos, T. Zakinthinos, C. Botsi, A. Terzidis

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‘PHILOS – Emergency health response to refugee crisis’ is a programme of the Greek Ministry of Health, implemented by the Hellenic Center for Disease Control and Prevention (HCDCP). The programme is funded by the Asylum, Migration and Integration Fund (AMIF) of EU’s DG Migration and Home Affairs. With the EU Member States accepting, the last period, accelerating migration flows, Greece inevitably occupies a prominent position in the migratory map due to this geographical location. The main objectives of the programme are a) reinforcement of the capacity of the public health system and enhancement of the epidemiological surveillance in order to cover refugees/migrant population, b) provision of on-site primary health care and psychological support services, and c) strengthening of national health care system task-force. The basic methods for achieving the aforementioned goals are: a) implementation of syndromic surveillance system at camps and enhancement of public health response with the use of mobile medical units (Sub-action A), b) enhancement of health care services inside the camps via increasing human resources and implementing standard operating procedures (Sub-action B), and c) reinforcement of the national health care system (primary healthcare units, hospitals, and emergency care spots) of affected regions with personnel (Sub-action C). As a result, 58 health professionals were recruited under sub-action 2 and 10 mobile unit teams (one or two at each health region) were formed. The main actions taken so far by the mobile units are the evaluation, of syndromic surveillance, of living conditions at camps and medical services. Also, vaccination coverage of children population was assessed, and more than 600 catch-up vaccinations were performed by the end of June 2017. Mobile units supported transportation of refugees/migrants from camps to medical services reducing the load of the National Center for Emergency Care (more than 350 transportations performed). The total number of health professionals (MD, nurses, etc.) placed at camps was 104. Common practices were implemented in the recording and collection of psychological and medical history forms at the camps. Protocols regarding maternity care, gender based violence and handling of violent incidents were produced and distributed at personnel working at camps. Finally, 290 health care professionals were placed at primary healthcare units, public hospitals and the National Center for Emergency Care at affected regions. The program has, also, supported training activities inside the camps and resulted to better coordination of offered services on site.

Keywords: migrants, refugees, public health, syndromic surveillance, national health care system, primary care, emergency health response

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Authors: Mobarok Hossain Bhuyain

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Video surveillance processing has attracted various security fields transforming it into one of the leading research fields. Today's demand for detection and tracking of human mobility for security is very useful for human security, such as in crowded areas. Accordingly, video surveillance technology has seen a rapid advancement in recent years, with algorithms analyzing the behavior of people under surveillance automatically. The main motivation of this research focuses on the detection and tracking of the elderly and socially vulnerable people in crowded areas. Degenerate people are a major health concern, especially for elderly people and socially vulnerable people. One major disadvantage of video surveillance is the need for continuous monitoring, especially in crowded areas. To assist the security monitoring live surveillance video, image processing, and artificial intelligence methods can be used to automatically send warning signals to the monitoring officers about elderly people and socially vulnerable people.

Keywords: human detection, target tracking, neural network, particle filter

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Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

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Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

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Authors: Sophonie Sarielle Jean Jacques Bertrand

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Background: Acute flaccid paralysis (PFA) is the sudden weakness or paralysis of muscles seen in children under 15 years of age. According to the WHO, PFA remains a real public health problem. For Haiti, the PFA represents a national priority. This study aims to describe the epidemiological profile of cases of Acute Flaccid Paralysis (PFA) in Haiti from 2018-2020. Methods: A descriptive cross-sectional study covering the period of 2018-2021 was carried out. epidemiological surveillance data PFA exported to Integrated Monitoring Evaluation Surveillance (MESI) were used. Sociodemographic variables were studied. Prevalence and clinical mortality rate were calculated. Epi Info 7.2 and Excel 2016 were used for data analysis. Results: 76 AFP cases were recorded for the period, or 13 (17%) in 2018, 23 (30%) in 2019, 8 (11%) in 2020 32 (42%) in 2021. Children aged 5-14 years accounted for 36% of cases (n= 26). The M/F sex ratio was 0.52, with a predominance of the female sex. The clinical mortality rate was 2.6%. The prevalence was 1.77/100,000 people. Conclusion: From 2018-2021, 76 cases of PFA cases were recorded in the 10 departments of the country, of which the West department was the most affected. Maintaining high vaccination coverage and a standard acute flaccid paralysis surveillance system are essential for the eradication of this condition. Strengthen epidemiological surveillance of PFA.

Keywords: epidemiology, PFA, Haïti, MESI

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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: Sarah Mhae Diaz, Erika Anna De Leon, Jacklin Alwil Cartagena, Geordan Caruncong, Micah Riezl Gonzales

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This study examined the intervention of threat and surveillance on the obedience of 100 preschool children through a task variable experiment replicated from the previous studies of Higbee (1979), and Chua, J., Chua, M., & Pico (1983). Nowadays, obedience among Filipino children to authority is disregarded since they are more outspoken and rebel due to social influences. With this, aside from corporal punishment, threat and surveillance became a mean of inducing obedience. Threat, according to the Dissonance Theory, can give attitudinal change. On the other hand, surveillance, according to the Theory of Social Facilitation, can either contribute to the completion or failure to do a task. Through a 2x2 factorial design, results show; (1) threat (F(1,96) = 12.487, p < 0.05) and (2) surveillance (F(1,96)=9.942, p<.05) had a significant main effect on obedience, suggesting that the Dissonance Theory and Theory of Social Facilitation is respectively true in the study. On the other hand, (3) no interaction (F(1,96)=1.303, p > .05) was seen since threat and surveillance both have a main effect that could be positive or negative, or could be because of their complementary property as supported by the post-hoc results. Also, (4) most effective commanding style is threat and surveillance setting (M = 30.04, SD = 7.971) due to the significant main effect of the two variables. With this, in the Filipino Setting, threat and surveillance has proven to be a very effective strategy to discipline and induce obedience from a child.

Keywords: experimental study, obedience, preschool children, surveillance, threat

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Authors: Ernest Tambo, Ghislaine Madjou, Jeanne Y. Ngogang, Shenglan Tang, Zhou XiaoNong

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Implementing national to community-based 'One Health' surveillance approach for human, animal and environmental consequences mitigation offers great opportunities and value-added in sustainable development and wellbeing. 'One Health' surveillance approach global partnerships, policy commitment and financial investment are much needed in addressing the evolving threats and epidemics crises mitigation in African countries. The paper provides insights onto how China-Africa health development cooperation in promoting “One Health” surveillance approach in response advocacy and mitigation. China-Africa health development initiatives provide new prospects in guiding and moving forward appropriate and evidence-based advocacy and mitigation management approaches and strategies in attaining Universal Health Coverage (UHC) and Sustainable Development Goals (SDGs). Early and continuous quality and timely surveillance data collection and coordinated information sharing practices in malaria and other diseases are demonstrated in Comoros, Zanzibar, Ghana and Cameroon. Improvements of variety of access to contextual sources and network of data sharing platforms are needed in guiding evidence-based and tailored detection and response to unusual hazardous events. Moreover, understanding threats and diseases trends, frontline or point of care response delivery is crucial to promote integrated and sustainable targeted local, national “One Health” surveillance and response approach needs implementation. Importantly, operational guidelines are vital in increasing coherent financing and national workforce capacity development mechanisms. Strengthening participatory partnerships, collaboration and monitoring strategies in achieving global health agenda effectiveness in Africa. At the same enhancing surveillance data information streams reporting and dissemination usefulness in informing policies decisions, health systems programming and financial mobilization and prioritized allocation pre, during and post threats and epidemics crises programs strengths and weaknesses. Thus, capitalizing on “One Health” surveillance and response approach advocacy and mitigation implementation is timely in consolidating Africa Union 2063 agenda and Africa renaissance capabilities and expectations.

Keywords: Africa, one health approach, surveillance, response

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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: Margaret S. Wright

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Background/Significance: During many recent public health emergencies/disasters, public health nursing data has been missing or delayed, potentially impacting the decision-making and response. Data used as evidence for decision-making in response, planning, and mitigation has been erratic and slow, decreasing the ability to respond. Methodology: Applying best practices in data management and data use in public health settings, and guided by the concepts outlined in ‘Disaster Standards of Care’ models leads to the development of recommendations for a model of best practices in data management and use in public health disasters/emergencies by public health nurses. As the ‘patient’ in public health disasters/emergencies is the community (local, regional or national), guidelines for patient documentation are incorporated in the recommendations. Findings: Using model public health nurses could better plan how to prepare for, respond to, and mitigate disasters in their communities, and better participate in decision-making in all three phases bringing public health nursing data to the discussion as part of the evidence base for decision-making.

Keywords: data management, decision making, disaster planning documentation, public health nursing

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Authors: Samuel Munaf, Kevin Swingler, Franz Brülisauer, Anthony O’Hare, George Gunn, Aaron Reeves

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Web scraping and text mining are popular computer science methods deployed by public health researchers to augment traditional epidemiological surveillance. However, within veterinary disease surveillance, such techniques are still in the early stages of development and have not yet been fully utilised. This study presents an exploration into the utility of incorporating internet-based data to better understand the smallholder farming communities within Scotland by using online text extraction and the subsequent mining of this data. Web scraping of the livestock fora was conducted in conjunction with text mining of the data in search of common themes, words, and topics found within the text. Results from bi-grams and topic modelling uncover four main topics of interest within the data pertaining to aspects of livestock husbandry: feeding, breeding, slaughter, and disposal. These topics were found amongst both the poultry and pig sub-forums. Topic modeling appears to be a useful method of unsupervised classification regarding this form of data, as it has produced clusters that relate to biosecurity and animal welfare. Internet data can be a very effective tool in aiding traditional veterinary surveillance methods, but the requirement for human validation of said data is crucial. This opens avenues of research via the incorporation of other dynamic social media data, namely Twitter and Facebook/Meta, in addition to time series analysis to highlight temporal patterns.

Keywords: veterinary epidemiology, disease surveillance, infodemiology, infoveillance, smallholding, social media, web scraping, sentiment analysis, geolocation, text mining, NLP

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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: Khanh D.Do, Loi V.Nguyen, Thanh N.Nguyen, Thang M.Nguyen, Vu T.Tran

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Along with the development of Secondary surveillance radar (SSR) in air traffic surveillance systems, the Multipath phenomena has always been a noticeable problem. This following article discusses the geometrical aspect and power aspect of the Multipath interference caused by reflection in SSR and proposes a method to deal with these unwanted multipath targets (ghosts) by false-target position predicting and adaptive target suppressing. A field-experiment example is mentioned at the end of the article to demonstrate the efficiency of this measure.

Keywords: multipath, secondary surveillance radar, digital signal processing, reflection

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Authors: Vinesh Thiruchelvam, Umar Mumtaz Chowdry, Sathish Kumar Selvaperumal

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The prime purpose of the project is to provide a sophisticated system for surveillance specialized for the Port Authorities in the Maritime Industry. The current aerial surveillance does not have a wide dimensioning view. The channels of communication is shared and not exclusive allowing for communications errors or disturbance mainly due to traffic. The scope is to analyze the various aspects as real-time aerial and marine surveillance is one of the most important methods which could ensure the domain security of the sailors. The system will improve real time data as obtained for the controller base station. The key implementation will be based on camera speed, angle and adherence to a sustainable power utilization module.

Keywords: SMS, real time, GUI, maritime industry

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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: Francesca Nardi, Kashish Aneja, Katherine Ginsbach

Abstract:

The COVID-19 pandemic has demonstrated both a need for evidence-based and rights-based public health policy and how challenging it can be to make effective decisions with limited information, evidence, and data. The O’Neill Institute, in conjunction with several partners, has been working since the beginning of the pandemic to collect, analyze, and distribute critical data on public health policies enacted in response to COVID-19 around the world in the COVID-19 Law Lab. Well-designed laws and policies can help build strong health systems, implement necessary measures to combat viral transmission, enforce actions that promote public health and safety for everyone, and on the individual level have a direct impact on health outcomes. Poorly designed laws and policies, on the other hand, can fail to achieve the intended results and/or obstruct the realization of fundamental human rights, further disease spread, or cause unintended collateral harms. When done properly, laws can provide the foundation that brings clarity to complexity, embrace nuance, and identifies gaps of uncertainty. However, laws can also shape the societal factors that make disease possible. Law is inseparable from the rest of society, and COVID-19 has exposed just how much laws and policies intersects all facets of society. In the COVID-19 context, evidence-based and well-informed law and policy decisions—made at the right time and in the right place—can and have meant the difference between life or death for many. Having a solid evidentiary base of legal information can promote the understanding of what works well and where, and it can drive resources and action to where they are needed most. We know that legal mechanisms can enable nations to reduce inequities and prepare for emerging threats, like novel pathogens that result in deadly disease outbreaks or antibiotic resistance. The collection and analysis of data on these legal mechanisms is a critical step towards ensuring that legal interventions and legal landscapes are effectively incorporated into more traditional kinds of health science data analyses. The COVID-19 Law Labs see a unique opportunity to collect and analyze this kind of non-traditional data to inform policy using laws and policies from across the globe and across diseases. This global view is critical to assessing the efficacy of policies in a wide range of cultural, economic, and demographic circumstances. The COVID-19 Law Lab is not just a collection of legal texts relating to COVID-19; it is a dataset of concise and actionable legal information that can be used by health researchers, social scientists, academics, human rights advocates, law and policymakers, government decision-makers, and others for cross-disciplinary quantitative and qualitative analysis to identify best practices from this outbreak, and previous ones, to be better prepared for potential future public health events.

Keywords: public health law, surveillance, policy, legal, data

Procedia PDF Downloads 141

Authors: Snigdha Sahai, Devaki Chikkavenkatappa Yellappa

Abstract:

This study outlines approaches for testing and validating stochastic models used in epidemiology, focusing on the integration and functional testing of simulation code. It details methods for combining simple functions into comprehensive simulations, distinguishing between deterministic and stochastic components, and applying tests to ensure robustness. Techniques include isolating stochastic elements, utilizing large sample sizes for validation, and handling special cases. Practical examples are provided using R code to demonstrate integration testing, handling of incorrect inputs, and special cases. The study emphasizes the importance of both functional and defensive programming to enhance code reliability and user-friendliness.

Keywords: computational epidemiology, epidemiology, public health, infectious disease modeling, statistical analysis, health data analysis, disease transmission dynamics, predictive modeling in health, population health modeling, quantitative public health, random sampling simulations, randomized numerical analysis, simulation-based analysis, variance-based simulations, algorithmic disease simulation, computational public health strategies, epidemiological surveillance, disease pattern analysis, epidemic risk assessment, population-based health strategies, preventive healthcare models, infection dynamics in populations, contagion spread prediction models, survival analysis techniques, epidemiological data mining, host-pathogen interaction models, risk assessment algorithms for disease spread, decision-support systems in epidemiology, macro-level health impact simulations, socioeconomic determinants in disease spread, data-driven decision making in public health, quantitative impact assessment of health policies, biostatistical methods in population health, probability-driven health outcome predictions

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Authors: Shishir Kumar, Chhaya Gangwal, Seema Raj

Abstract:

Public health informatics (PHI) which has seen successful implementation in the developed world, become the buzzword in the developing countries in providing improved healthcare with enhanced access. In rural areas especially, where a huge gap exists between demand and supply of healthcare facilities, PHI is being seen as a major solution. There are factors such as growing network infrastructure and the technological adoption by the health fraternity which provide support to these claims. Public health informatics has opportunities in healthcare by providing opportunities to diagnose patients, provide intra-operative assistance and consultation from a remote site. It also has certain barriers in the awareness, adaptation, network infrastructure, funding and policy related areas. There are certain medico-legal aspects involving all the stakeholders which need to be standardized to enable a working system. This paper aims to analyze the potential and challenges of public health informatics services in rural communities.

Keywords: PHI, e-health, public health, health informatics

Procedia PDF Downloads 375

Authors: B. Baba Ahmed, P. Yanogo, B. Djibryl. N. Medas

Abstract:

Introduction: Polio is a highly contagious viral infection, with children under 5 years of age being the most affected. It is a public health emergency of international concern. Polio surveillance in Mauritania has been ongoing since 1998 and has achieved "polio free" status in 2007. our objective is to analyse a pidemiological surveillance database of poliomyélitis in Mauritania from 2012-2019. Method: A transversal descriptive analysis of poliomyélitis database was carried out in Mauritania from 2012-2019.An exhaustive sampling was done on all suspected polio cases recorded in the database from 2012 -2019. This study used EPI-INFO 7.4 for frequency calculation for qualitative variables, mean and standard deviation for quantitative variables. Results: We found 459 suspected cases of polio over the study period with an average rate of acute non-polio flaccid paralysis of 25.4 cases/100,000 children under 15 years of age. The age group 0-6 years represented 75.2%. Males constituted 50.2%. Females represented 49.78% with a ratio of M/F=1.Among the 422 observations, the average age is 4 years +/- 3.38. The four regions, TIRIS-ZEMMOUR, INCHIRI, TAGANT, NOUACHCHOTT OUEST recorded the lowest percentages of notifications, respectively (3.28%; 3.93%; 4.37%; 4.8%). 99.34% [98.09-99.78] of cases presented acute flaccid paralysis. And 56.77% [52.19-61.23], had limb asymmetry. We showed that 82.93% [79.21-86.10], had fever. we found that 89.5% of suspected polio cases were investigated before 48 hours. And 88.39% of suspected cases had two adequate samples taken 48 hours apart and within 14 days after the onset of symptoms. Only 30.95% of samples arrived at the referral laboratory before 72 hours. Conclusion: This study has shown that Mauritania has achieved the objectives in most of the quantitative performance indicators of polio surveillance. This study has shown a low notification of cases in the northern and central regions of the country. There is a problem with the transport of samples to the laboratory.

Keywords: analysis, data base, Epi-Info, polio

Procedia PDF Downloads 175

Authors: T. Ahilan, V. Aswin Adityan, S. Kailash

Abstract:

UAV’s are small remote operated or automated aerial surveillance systems without a human pilot aboard. UAV’s generally finds its use in military and special operation application, a recent growing trend in UAV’s finds its application in several civil and non military works such as inspection of power or pipelines. The objective of this paper is the augmentation of a UAV in order to replace the existing expensive sonar (sound navigation and ranging) based equipment amongst small scale fisherman, for whom access to sonar equipment are restricted due to limited economic resources. The surveillance equipment’s present in the UAV will relay data and GPS location onto a receiver on the fishing boat using RF signals, using which the location of the schools of fishes can be found. In addition to this, an emergency beacon system is present for rescue operations and drone recovery.

Keywords: UAV, Surveillance, RF signals, fishing, sonar, GPS, video stream, school of fish

Procedia PDF Downloads 457

Authors: K. M. G. T. R. Waidyarathna, S. M. Vidanagamachchi

Abstract:

Public Health System exists in Sri Lanka has a satisfactory complete information flow when compared to other systems in developing countries. The availability of a good health information system contributed immensely to achieve health indices that are in line with the developed countries like US and UK. The health information flow at the moment is completely paper based. In Sri Lanka, the fields like banking, accounting and engineering have incorporated information and communication technology to the same extent that can be observed in any other country. The field of medicine has behind those fields throughout the world mainly due to its complexity, issues like privacy, confidentially and lack of people with knowledge in both fields of Information Technology (IT) and Medicine. Sri Lanka’s situation is much worse and the gap is rapidly increasing with huge IT initiatives by private-public partnerships in all other countries. The major goal of the framework is to support minimizing the spreading diseases. To achieve that a web based framework should be implemented for this application domain with web mapping. The aim of this GIS based public health system is a secure, flexible, easy to maintain environment for creating and maintaining public health records and easy to interact with relevant parties.

Keywords: DHIS2, GIS, public health, Sri Lanka

Procedia PDF Downloads 563