Remote Sensing-Derived Environmental Variables to Estimate Transmission Risk and Predict Malaria Cases in Argentina: A Pre-Certification Study (1986–2005)

• Autores: Cuellar, Ana; Coello Peralta, Roberto D.; Calle Atariguana, Davis; Palacios Macias, Martha; Duque Padilla, Paul Leonardo; Galindo, Liliana María; Zaidenberg, Mario; Dantur Juri, Maria Julia
• Año de publicación: 2025
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: Malaria; Predictive models; Satellite images; ARIMA temporal series
• Institución: Consejo Nacional de Investigaciones Científicas y Técnicas

Early warning systems rely on statistical prediction models, with environmental risks and remote sensing data serving as essential sources of information for their development. The present work is focused on the use of remote sensing for the estimation of transmission risk and the prediction of malaria cases in northwest Argentina. This study was conducted in the city of San Ramón de la Nueva Orán, where cases of the disease have been reported from 1986 to 2005. The relationship between reported malaria cases and climatic/environmental variables—including the normalized difference vegetation index (NDVI), normalized difference water index (NDWI), and land surface temperature (LST)—obtained from Landsat 5 and 7 satellite images was analyzed using multilevel Poisson regression analyses. An increased abundance of reported malaria cases was observed in summer. An ARIMA (autoregressive integrated moving average) temporal series model incorporating environmental variables was developed to forecast malaria cases in the year 2000. The analysis of the relationship between malaria cases and environmental and climatic factors showed that malaria cases were associated with increases in LST and mean temperature and a decrease in the NDVI. Early warning systems that provide information about spatial and temporal predictions of epidemics could help to control and prevent malaria outbreaks. Based on these findings, this study is expected to support the development of future prevention and control measures by health officials.
Fil: Cuellar, Ana. Technical University of Denmark; Dinamarca
Fil: Coello Peralta, Roberto D.. Universidad de Guayaquil; Ecuador
Fil: Calle Atariguana, Davis. Universidad de Guayaquil; Ecuador
Fil: Palacios Macias, Martha. Universidad de Guayaquil; Ecuador
Fil: Duque Padilla, Paul Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - Tucumán. Unidad Ejecutora Lillo; Argentina
Fil: Galindo, Liliana María. Universidad Nacional de Tucumán; Argentina
Fil: Zaidenberg, Mario. Ministerio de Salud. Dirección de Enfermedades Transmisibles por Vectores; Argentina
Fil: Dantur Juri, Maria Julia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - Tucumán. Unidad Ejecutora Lillo; Argentina. Fundacion Miguel Lillo. Direccion de Biologia Integrativa. Instituto de Genetica y Microbiologia;