Distribución geoespacial de los casos de tuberculosis resistente en Loreto periodo 2015-2024

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Objectives: To analyze the geospatial distribution of drug-resistant tuberculosis cases in Loreto during the period 2015–2024. Methodology: Observational study with a cross-sectional and retrospective design, which evaluated the geospatial distribution of 409 cases of drug-resistant tuberculosis in...

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Detalles Bibliográficos
Autor: Moreno Garcia, Alfredo Byron
Formato: tesis de grado
Fecha de Publicación:2025
Institución:Universidad Nacional De La Amazonía Peruana
Repositorio:UNAPIquitos-Institucional
Lenguaje:español
OAI Identifier:oai:repositorio.unapiquitos.edu.pe:20.500.12737/11901
Enlace del recurso:https://hdl.handle.net/20.500.12737/11901
Nivel de acceso:acceso abierto
Materia:Tuberculosis resistente a múltiples medicamentos
Datos geoespaciales
Factores sociodemográficos
Factores epidemiológicos
https://purl.org/pe-repo/ocde/ford#3.03.08
Descripción
Sumario:Objectives: To analyze the geospatial distribution of drug-resistant tuberculosis cases in Loreto during the period 2015–2024. Methodology: Observational study with a cross-sectional and retrospective design, which evaluated the geospatial distribution of 409 cases of drug-resistant tuberculosis in the Loreto region between 2015 and 2024, using QGIS software version 3.28.4 and Kernel density analysis. Results: Most cases were concentrated in the province of Maynas (88.3%), particularly in the districts of Iquitos, Belén, and San Juan Bautista. High-density geographic clusters were identified in urban areas, with a progressive shift toward peripheral zones starting in 2019. Multidrug-resistant tuberculosis (MDR-TB) accounted for 51.1% of cases, and the most frequent comorbidities were diabetes (23%), malnutrition (18.6%), and HIV (11.5%). Conclusion: A heterogeneous and focal geospatial distribution of drug-resistant tuberculosis was identified in Loreto, with urban predominance and recent peripheral expansion. Spatial analysis is a key tool for guiding targeted control and surveillance strategies in high-burden settings.
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