Background: One Health is a collaborative, multisectoral, and transdisciplinary approach-working at the local, regional, national, and global levels-with the goal of achieving optimal health outcomes recognizing the interconnection between people, animals, plants, and their shared environment. Operationalization of the One Health approach is still unclear for various local health systems with their respective targets. In this scenario, the empirical study of intersectoral collaboration between the human and animal health systems provides an opportunity to investigate the appropriate strategies and their enabling factors at the local health system level. Thus, this study documented and validated the innovative strategy for intersectoral collaboration, focusing on effectual prevention and control of zoonotic diseases with its enabling factors for a city in western India, Ahmedabad.
Methods: This case study was conducted in three phases: phase I (qualitative data collection, i.e., vignette interview), phase II (quantitative data collection through modified policy Delphi), and phase III (participatory workshop). The vignette data were handled for content analysis, and the Delphi data, like other quantitative data, for descriptive statistics. The participatory workshop adapts the computerized Sensitivity Model developed by Vester to analyse the health system dynamics.
Result: Out of the possible 36 strategies, this study validated the top 15 essential (must-have) and five preferred (should-have) strategies for the study area. For operationalization of the One Health approach, the enabling factors that were identified through the systems approach are micro-level factors at the individual level (trust, leadership, motivation, knowledge), meso-level factors at the organizational level (human resource, capacity-building, shared vision, decision-making capacity, laboratory capacity, surveillance), macro-level factors at the system level (coordinated roles, relationships, common platform), and external factors outside of the system (guidelines/policies, community participation, a specific budget, political will, smart technology).
Discussion: This study reveals that the micro-level factors at the individual level are potential levers of the health system. More attention to these factors could be beneficial for the operationalization of the One Health approach. This study recommends a systems approach through a bottom-up exploration to understand the local health system and its enabling factors, which should be accounted for in formulating future One Health policies.
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http://dx.doi.org/10.1186/s12961-021-00727-9 | DOI Listing |
Harv Public Health Rev (Camb)
August 2024
Washington State University, School of Electrical Engineering and Computer Science in Pullman.
Health technologies featuring artificial intelligence (AI) are becoming more common. Some healthcare AIs are exhibiting bias towards underrepresented persons and populations. Although many computer scientists and healthcare professionals agree that eliminating or mitigating bias in healthcare AIs is needed, little information exists regarding how to operationalize bioethics principles like autonomy in product design and implementation.
View Article and Find Full Text PDFJ Racial Ethn Health Disparities
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Valleywise Health, Phoenix, AZ, USA.
Background: Missed clinic appointments disproportionately affect Medicaid-insured patients and residents of socioeconomically deprived neighborhoods. The role of the recent telemedicine expansion in reducing these disparities is unclear. We analyzed the relationship between census tract (CT) poverty level, residential segregation, missed appointments, and the role of telemedicine.
View Article and Find Full Text PDFSoc Sci Med
December 2024
Thomas Jefferson University College of Population Health, 130 S. 9th Street, Suite 100. Philadelphia, PA, 19107, USA.
In this paper, we apply a measurement science perspective to explore both the epidemiologic and psychometric frameworks for the conceptualization, operationalization and assessment of self-reported adverse childhood experiences (srACEs). The epidemiologic paradigm suggests that srACEs are 'exposures', while the psychometric paradigm views responses on srACEs instrumentation as 'indicators'. It is the central premise of this paper that srACEs cannot be both exposures and indicators of scales.
View Article and Find Full Text PDFEnviron Health Perspect
January 2025
Centre for Environment, Fisheries and Aquaculture Science (CEFAS), Weymouth, UK.
Background: Environmental change in coastal areas can drive marine bacteria and resulting infections, such as those caused by , with both foodborne and nonfoodborne exposure routes and high mortality. Although ecological drivers of in the environment have been well-characterized, fewer models have been able to apply this to human infection risk due to limited surveillance.
Objectives: The Cholera and Other Illness Surveillance (COVIS) system database has reported infections in the United States since 1988, offering a unique opportunity to both explore the forecasting capabilities machine learning could provide and to characterize complex environmental drivers of infections.
Gerontologist
January 2025
Department of Neurosciences, School of Medicine, University of California San Diego, San Diego, CA, USA.
Background And Objectives: While Hispanic/Latino populations in the U.S. are remarkably diverse in terms of birthplace and age at migration, we poorly understand how these factors are associated with cognitive aging.
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