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Kahariri S, Thumbi SM, Bett B, Mureithi MW, Nyaga N, Ogendo A, Muturi M, Thomas LF. The evolution of Kenya's animal health surveillance system and its potential for efficient detection of zoonoses. Front Vet Sci 2024; 11:1379907. [PMID: 38966562 PMCID: PMC11223174 DOI: 10.3389/fvets.2024.1379907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 05/22/2024] [Indexed: 07/06/2024] Open
Abstract
Introduction Animal health surveillance systems in Kenya have undergone significant changes and faced various challenges throughout the years. Methods In this article, we present a comprehensive overview of the Kenya animal health surveillance system (1944 to 2024), based on a review of archived documents, a scoping literature review, and an examination of past surveillance assessments and evaluation reports. Results The review of archived documents revealed key historical events that have shaped the surveillance system. These include the establishment of the Directorate of Veterinary Services in 1895, advancements in livestock farming, the implementation of mandatory disease control interventions in 1944, the growth of veterinary services from a section to a ministry in 1954, the disruption caused by the Mau Mau insurrection from 1952 to 1954, which led to the temporary halt of agriculture in certain regions until 1955, the transition of veterinary clinical services from public to private, and the progressive privatization plan for veterinary services starting in 1976. Additionally, we highlight the development of electronic surveillance from 2003 to 2024. The scoping literature review, assessments and evaluation reports uncovered several strengths and weaknesses of the surveillance system. Among the strengths are a robust legislative framework, the adoption of technology in surveillance practices, the existence of a formal intersectoral coordination platform, the implementation of syndromic, sentinel, and community-based surveillance methods, and the presence of a feedback mechanism. On the other hand, the system's weaknesses include the inadequate implementation of strategies and enforcement of laws, the lack of standard case definitions for priority diseases, underutilization of laboratory services, the absence of formal mechanisms for data sharing across sectors, insufficient resources for surveillance and response, limited integration of surveillance and laboratory systems, inadequate involvement of private actors and communities in disease surveillance, and the absence of a direct supervisory role between the national and county veterinary services. Discussion and recommendations To establish an effective early warning system, we propose the integration of surveillance systems and the establishment of formal data sharing mechanisms. Furthermore, we recommend enhancing technological advancements and adopting artificial intelligence in surveillance practices, as well as implementing risk-based surveillance to optimize the allocation of surveillance resources.
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Affiliation(s)
- Samuel Kahariri
- Directorate of Veterinary Services, Nairobi, Kenya
- International Livestock Research Institute, Nairobi, Kenya
- Department of Medical Microbiology and Immunology, Faculty of Health Sciences, University of Nairobi, Nairobi, Kenya
- Centre for Epidemiological Modelling and Analysis, Institute of Tropical and Infectious Diseases, University of Nairobi, Nairobi, Kenya
| | - S. M. Thumbi
- Centre for Epidemiological Modelling and Analysis, Institute of Tropical and Infectious Diseases, University of Nairobi, Nairobi, Kenya
- Institute of Immunology and Infection Research, University of Edinburgh, Edinburgh, United Kingdom
- Paul G. Allen School for Global Health, Washington State University, Pullman, WA, United States
| | - Bernard Bett
- International Livestock Research Institute, Nairobi, Kenya
| | - Marianne W. Mureithi
- Department of Medical Microbiology and Immunology, Faculty of Health Sciences, University of Nairobi, Nairobi, Kenya
| | - Nazaria Nyaga
- County Directorate of Veterinary Services, Kajiado, Kenya
| | - Allan Ogendo
- County Directorate of Veterinary Services, Busia, Kenya
| | - Mathew Muturi
- Directorate of Veterinary Services, Nairobi, Kenya
- International Livestock Research Institute, Nairobi, Kenya
- Centre for Epidemiological Modelling and Analysis, Institute of Tropical and Infectious Diseases, University of Nairobi, Nairobi, Kenya
| | - Lian Francesca Thomas
- International Livestock Research Institute, Nairobi, Kenya
- Institute of Infection Veterinary and Ecological Sciences, University of Liverpool, Neston, United Kingdom
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Bouyer F, Thiongane O, Hobeika A, Arsevska E, Binot A, Corrèges D, Dub T, Mäkelä H, van Kleef E, Jori F, Lancelot R, Mercier A, Fagandini F, Valentin S, Van Bortel W, Ruault C. Epidemic intelligence in Europe: a user needs perspective to foster innovation in digital health surveillance. BMC Public Health 2024; 24:973. [PMID: 38582850 PMCID: PMC10999084 DOI: 10.1186/s12889-024-18466-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 03/27/2024] [Indexed: 04/08/2024] Open
Abstract
BACKGROUND European epidemic intelligence (EI) systems receive vast amounts of information and data on disease outbreaks and potential health threats. The quantity and variety of available data sources for EI, as well as the available methods to manage and analyse these data sources, are constantly increasing. Our aim was to identify the difficulties encountered in this context and which innovations, according to EI practitioners, could improve the detection, monitoring and analysis of disease outbreaks and the emergence of new pathogens. METHODS We conducted a qualitative study to identify the need for innovation expressed by 33 EI practitioners of national public health and animal health agencies in five European countries and at the European Centre for Disease Prevention and Control (ECDC). We adopted a stepwise approach to identify the EI stakeholders, to understand the problems they faced concerning their EI activities, and to validate and further define with practitioners the problems to address and the most adapted solutions to their work conditions. We characterized their EI activities, professional logics, and desired changes in their activities using NvivoⓇ software. RESULTS Our analysis highlights that EI practitioners wished to collectively review their EI strategy to enhance their preparedness for emerging infectious diseases, adapt their routines to manage an increasing amount of data and have methodological support for cross-sectoral analysis. Practitioners were in demand of timely, validated and standardized data acquisition processes by text mining of various sources; better validated dataflows respecting the data protection rules; and more interoperable data with homogeneous quality levels and standardized covariate sets for epidemiological assessments of national EI. The set of solutions identified to facilitate risk detection and risk assessment included visualization, text mining, and predefined analytical tools combined with methodological guidance. Practitioners also highlighted their preference for partial rather than full automation of analyses to maintain control over the data and inputs and to adapt parameters to versatile objectives and characteristics. CONCLUSIONS The study showed that the set of solutions needed by practitioners had to be based on holistic and integrated approaches for monitoring zoonosis and antimicrobial resistance and on harmonization between agencies and sectors while maintaining flexibility in the choice of tools and methods. The technical requirements should be defined in detail by iterative exchanges with EI practitioners and decision-makers.
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Affiliation(s)
- Fanny Bouyer
- Groupe d'Expérimentation et de Recherche: Développement et Actions Locales (GERDAL), Angers, France.
| | - Oumy Thiongane
- Joint Research Unit Animal, Health, Territories, Risks, Ecosystems (UMR ASTRE), French Agricultural Research Centre for International Development (CIRAD), National Research Institute for Agriculture, Food and Environment (INRAE), Montpellier, France
| | - Alexandre Hobeika
- UMR MOISA, French Agricultural Research Centre for International Development (CIRAD), 34398, Montpellier, France
- MOISA, University Montpellier, CIHEAM-IAMM, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - Elena Arsevska
- Joint Research Unit Animal, Health, Territories, Risks, Ecosystems (UMR ASTRE), French Agricultural Research Centre for International Development (CIRAD), National Research Institute for Agriculture, Food and Environment (INRAE), Montpellier, France
| | - Aurélie Binot
- Joint Research Unit Animal, Health, Territories, Risks, Ecosystems (UMR ASTRE), French Agricultural Research Centre for International Development (CIRAD), National Research Institute for Agriculture, Food and Environment (INRAE), Montpellier, France
| | - Déborah Corrèges
- Joint Research Unit EPIdemiological On Animal and Zoonotic Diseases (UMR EPIA), National School of Veterinary Services (VetAgro Sup), National Research Institute for Agriculture, Food and Environment (INRAE), Marcy L'Etoile, France
| | - Timothée Dub
- Department of Health Security, Finish Institute for Health and Welfare, Helsinki, Finland
| | - Henna Mäkelä
- Department of Health Security, Finish Institute for Health and Welfare, Helsinki, Finland
| | - Esther van Kleef
- Institute of Tropical Medicine, Department of Biomedical Sciences, Outbreak Research Team, Antwerp, Belgium
| | - Ferran Jori
- Joint Research Unit Animal, Health, Territories, Risks, Ecosystems (UMR ASTRE), French Agricultural Research Centre for International Development (CIRAD), National Research Institute for Agriculture, Food and Environment (INRAE), Montpellier, France
| | - Renaud Lancelot
- Joint Research Unit Animal, Health, Territories, Risks, Ecosystems (UMR ASTRE), French Agricultural Research Centre for International Development (CIRAD), National Research Institute for Agriculture, Food and Environment (INRAE), Montpellier, France
| | - Alize Mercier
- Joint Research Unit Animal, Health, Territories, Risks, Ecosystems (UMR ASTRE), French Agricultural Research Centre for International Development (CIRAD), National Research Institute for Agriculture, Food and Environment (INRAE), Montpellier, France
| | - Francesca Fagandini
- Joint Research Unit Land, Remote Sensing and Spatial Information (UMR TETIS), French Agricultural Research Centre for International Development (CIRAD), Montpellier, France
| | - Sarah Valentin
- Joint Research Unit Land, Remote Sensing and Spatial Information (UMR TETIS), French Agricultural Research Centre for International Development (CIRAD), Montpellier, France
| | - Wim Van Bortel
- Institute of Tropical Medicine, Department of Biomedical Sciences, Outbreak Research Team, Antwerp, Belgium
- Institute of Tropical Medicine, Department of Biomedical Sciences, Unit of Entomology, Antwerp, Belgium
| | - Claire Ruault
- Groupe d'Expérimentation et de Recherche: Développement et Actions Locales (GERDAL), Angers, France
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Son YS, Kwon KH. Utilization of smart devices and the evolution of customized healthcare services focusing on big data: a systematic review. Mhealth 2023; 10:7. [PMID: 38323151 PMCID: PMC10839508 DOI: 10.21037/mhealth-23-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Accepted: 10/24/2023] [Indexed: 02/08/2024] Open
Abstract
Background Currently, smart devices can prevent diseases by continuously collecting user information and providing health-related feedback. Smart devices big data provide personalized, faster, and more accurate health care. By examining existing studies, we suggest a new healthcare evolution and health promotion through information technology (IT) convergence. A big data systematic review examined the evolution of new health care and their potential for health promotion by monitoring physical activities, preventing diseases, and analyzing health data smart devices. Methods Therefore, this evaluates whether a new healthcare industry combining smart devices and big-data-based customized health care services can promote health. This study searched PubMed, Google Scholar, Scopus, and Research Information Sharing Service (RISS) for keywords related to big data, smart devices, healthcare, customized health services, health apps, and mobile health. This study comprised 43 of 453 publications from 2007 to 2023. Among them, a total of 43 articles were successfully completed in this study using the PRISMA flowchart in the final stage. Results Smart devices centered on big data enable personalized health care, and app technologies that promote well-being to prepare for aging society have many applications in clinical, prevention, public health, and rehabilitation settings. Smart devices and tailored healthcare services using big data to inform individuals about exercise, health status, diagnosis, and health information will expand into major sectors. By reviewing previous studies, the convergence of the IT technology field, which allows you to easily identify individual health and receive faster and more accurate medical services through customized health care services, has future-oriented values as, new health care services evolve. The systematic review of big data herein can monitor physical activity and prevent diseases using smart devices, thus promoting a healthy lifestyle. Conclusions Smart devices that analyze data to provide personal exercise and health conditions, checkups, and information, are making our lives easier. The information service using big data will continue to evolve into a personalized management service and provide basic healthcare data as it grows into an expected industry in the future.
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Affiliation(s)
- Youn Sun Son
- Division of Beauty Arts Care, Department of Practical Arts, Graduate School of Culture and Arts, Dongguk University, Seoul, Korea
| | - Ki Han Kwon
- College of General Education, Kookmin University, Seoul, Korea
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