INVESTIGADORES
DE ANGELO Carlos Daniel
congresos y reuniones científicas
Título:
Environmental and sociodemographic risk factors of soil-transmitted helminths and intestinal protozoa infections in a tri-border area of South-America
Autor/es:
RIVERO, MARÍA ROMINA; DE ANGELO, CARLOS; SALAS, MARTÍN M.; NÚÑEZ, PABLO; SALOMON, OSCAR D.; LIANG, SONG
Lugar:
Gainesville
Reunión:
Workshop; Graduate Student Research Day; 2015
Institución organizadora:
Office of Research University of Florida
Resumen:
Intestinal parasitic infections are among the most common infections in tropical and subtropical regions of developing countries and the diseases they cause are in the group of neglected tropical diseases. Puerto Iguazú is a tri-border touristic city of South-America located in the north of Argentina, bordering with Brazil and Paraguay. Although the region?s socioeconomic and physical environments are speculated in favor of prevalence of human intestinal parasites, information is very limited. The study aims to assess the current status of major soil-transmitted helminth and zoonotic enteroparasitic infections in humans and their associated risk factors in Puerto Iguazú city. A cross-sectional study was conducted in urban-periurban, rural and forest areas in proximity to the town from July 2013 to January 2015. 744 soil samples, 530 canine?s feces and 380 human stool samples were collected and examined for soil-transmitted helminths (e.g. Ascaris lumbricoides, hookworms and whipworms) and intestinal protozoan parasites (e.g. Giardia lamblia, Cryptosporidium parvum). Generalized linear models were employed to assess presence/absence of the parasites and infection intensities vs. risk factors including multiple local and landscape variables (e.g. land cover, topography, sociodemographic conditions) Geographical Information Systems were utilized to extract relevant spatial information and for model building and to construct risk maps. The results suggested that environmental contamination in urban-periurban area was the most significant risk factor for parasitic infections. Based on maps and models analysis we are able to select the most vulnerable zones for short and long-term integrated interventions.