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Epidemiological Patterns and Geospatial Mapping of Cleft Lip/Palate in a Comprehensive Cleft Center in Northwestern Nigeria: Estimating Distribution Using Geographical Information Systems.
Cleft Palate Craniofac J
January 2025
Department of Oral Pathology, Radiology and Medicine, Dows Institute for Dental Research, College of Dentistry, University of Iowa, Iowa City, IA, USA.
Objective: This study aims to estimate the geospatial distribution of cleft lip/palate (CL/P) cases in northwestern Nigeria and to estimate the prevalence and patterns of CL/P across wards.
Design: This retrospective study utilized information from health records for inpatients with CL/P. These data were analyzed via descriptive statistics.
Assessing the use of geospatial data for immunization program implementation and associated effects on coverage and equity in the Democratic Republic of Congo.
BMC Public Health
January 2025
Gavi, The Vaccine Alliance, Geneva, Switzerland.
Background: The National Expanded Program on Immunization in the Democratic Republic of the Congo implemented a program in 9 Provinces to generate georeferenced immunization microplans to strengthen the planning and implementation of vaccination services. The intervention aimed to improve identification and immunization of zero-dose children and overall immunization coverage.
Methods: This study applies a mixed-methods design including survey tools, in-depth interviews and direct observation to document the uptake, use, and acceptance of the immunization microplans developed with geospatial data in two intervention provinces and one control province from February to June 2023.
Mapping Drug-Resistant Tuberculosis Treatment Outcomes in Hunan Province, China.
Trop Med Infect Dis
December 2024
School of Population Health, Faculty of Health Sciences, Curtin University, Perth, WA 6102, Australia.
Background: Drug-resistant tuberculosis (DR-TB) remains a major public health challenge in China, with varying treatment outcomes across different regions. Understanding the spatial distribution of DR-TB treatment outcomes is crucial for targeted interventions to improve treatment success in high-burden areas such as Hunan Province. This study aimed to map the spatial distribution of DR-TB treatment outcomes at a local level and identify sociodemographic and environmental factors associated with poor treatment outcomes in Hunan Province, China.
View Article and Find Full Text PDFUnveiling predictive factors for household-level stunting in India: A machine learning approach using NFHS-5 and satellite-driven data.
Nutrition
December 2024
Central University of Jharkhand, Ranchi, Jharkland, India. Electronic address:
Objectives: Childhood stunting remains a significant public health issue in India, affecting approximately 35% of children under 5. Despite extensive research, existing prediction models often fail to incorporate diverse data sources and address the complex interplay of socioeconomic, demographic, and environmental factors. This study bridges this gap by employing machine learning methods to predict stunting at the household level, using data from the National Family Health Survey combined with satellite-driven datasets.
View Article and Find Full Text PDF'DeltaCAN - A new data set of Canadian Arctic and subarctic coastal deltas'.
Sci Data
January 2025
Department of Biology, McGill University, Montreal, Canada.
Arctic coasts constitute the critical interface between land and sea, and are subject to rapid changes caused by a warming climate. Current trends throughout the Arctic show increasing erosion trends, while other parts of the coast are experiencing prograding trends. Until now, a vast majority of our knowledge of Arctic coastal evolution is confined to site-specific studies with limited geospatial representation.
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