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1.
J Avian Med Surg ; 31(3): 262-282, 2017 09.
Artículo en Inglés | MEDLINE | ID: mdl-28891690

RESUMEN

Psittacosis, also known as parrot fever and ornithosis, is a bacterial infection that can cause severe pneumonia and other serious health problems in humans. It is caused by Chlamydia psittaci. Reclassification of the order Chlamydiales in 1999 into 2 genera (Chlamydia and Chlamydophila) was not wholly accepted or adopted. This resulted in a reversion to the single, original genus Chlamydia, which now encompasses all 9 species including Chlamydia psittaci. During 2003-2014, 112 human cases of psittacosis were reported to the Centers for Disease Control and Prevention through the Nationally Notifiable Diseases Surveillance System. While many types of birds can be infected by C psittaci, in general, the literature suggests that human cases can most often occur after exposure to infected parrot-type birds kept as pets, especially cockatiels, parakeets, and conures. In birds, C psittaci infection is referred to as avian chlamydiosis. Infected birds shed the bacteria through feces and nasal discharges, and humans become infected from exposure to these materials. This compendium provides information about psittacosis and avian chlamydiosis to public health officials, physicians, veterinarians, the pet bird industry, and others concerned with controlling these diseases and protecting public health. The recommendations in this compendium provide standardized procedures to control C psittaci infections. This document will be reviewed and revised as necessary, and the most current version replaces all previous versions. This document was last revised in 2010. Major changes in this version include a recommendation for a shorter treatment time for birds with avian chlamydiosis, additional information about diagnostic testing, including genotyping, clearer language associated with personal protective equipment recommended for those caring for confirmed or exposed birds, and incorporating a grading scale with recommendations generally based on the United States Preventive Services Task Force's methods.


Asunto(s)
Enfermedades de las Aves/microbiología , Enfermedades de las Aves/prevención & control , Chlamydophila psittaci , Mascotas , Psitacosis/prevención & control , Psitacosis/veterinaria , Crianza de Animales Domésticos , Animales , Enfermedades de las Aves/diagnóstico , Enfermedades de las Aves/transmisión , Aves , Humanos , Psitacosis/diagnóstico , Psitacosis/transmisión , Zoonosis
2.
Am J Epidemiol ; 173(10): 1121-30, 2011 May 15.
Artículo en Inglés | MEDLINE | ID: mdl-21427173

RESUMEN

Mathematical and computer models can provide guidance to public health officials by projecting the course of an epidemic and evaluating control measures. The authors built upon an existing collaboration between an academic research group and the Los Angeles County, California, Department of Public Health to plan for and respond to the first and subsequent years of pandemic influenza A (H1N1) circulation. The use of models allowed the authors to 1) project the timing and magnitude of the epidemic in Los Angeles County and the continental United States; 2) predict the effect of the influenza mass vaccination campaign that began in October 2009 on the spread of pandemic H1N1 in Los Angeles County and the continental United States; and 3) predict that a third wave of pandemic influenza in the winter or spring of 2010 was unlikely to occur. The close collaboration between modelers and public health officials during pandemic H1N1 spread in the fall of 2009 helped Los Angeles County officials develop a measured and appropriate response to the unfolding pandemic and establish reasonable goals for mitigation of pandemic H1N1.


Asunto(s)
Planificación en Salud , Subtipo H1N1 del Virus de la Influenza A , Gripe Humana/prevención & control , Pandemias/prevención & control , Adulto , Niño , Humanos , Vacunas contra la Influenza/provisión & distribución , Vacunas contra la Influenza/uso terapéutico , Los Angeles/epidemiología , Vacunación Masiva/estadística & datos numéricos , Modelos Estadísticos , Procesos Estocásticos , Estados Unidos/epidemiología
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