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1.
Artigo em Inglês | IMSEAR | ID: sea-137341

RESUMO

HIV diagnostic and follow up testing are usually done in laboratory settings. However, in developing countries there is a need to decentralize testing as the majority of the population lives in rural settings. In developing countries stringent quality assurance (QA) practices, which include appropriate training, development of standard operating procedures, maintenance of operator proficiency, routine use of quality control (QC) specimens, standardized data management, equipment calibration and maintenance, and biohazard safety with proper disinfection/disposal procedures are not routinely followed to ensure reliability of results and a safe work environment. The introduction of point-of-care testing technologies involving the use of non-laboratorians in routine testing has further increased the complexity of QA. Therefore, a careful approach towards improvement of laboratories that encourages best practices, coupled with incentives, and review of government policies in point-of-care testing is needed to improve quality of testing as decentralization takes place. Development of a functional laboratory tiered network that facilitates communication, referral, training and problem solving could further enhance confidence in laboratory testing. There is also a need for special considerations in implementing a stepwise approach towards quality improvement, strengthening of the supply chain management, human capacity development, infrastructure upgrade, and strong public private partnerships to ensure long term sustainability of these efforts.


Assuntos
Técnicas de Laboratório Clínico/métodos , Países em Desenvolvimento , Infecções por HIV/diagnóstico , Infecções por HIV/prevenção & controle , Humanos , Sistemas Automatizados de Assistência Junto ao Leito/normas , Prática de Saúde Pública , Parcerias Público-Privadas , Garantia da Qualidade dos Cuidados de Saúde/métodos
2.
Artigo em Inglês | IMSEAR | ID: sea-23290

RESUMO

Estimating HIV-1 incidence (rate of new HIV-1 infections) in various populations is important to understand the current status of transmission dynamics, identify high-risk populations, monitor prevention efforts and target resources on programmes that are most effective in reducing transmissions. Recent developments in our ability to detect and distinguish recent and longterm HIV-1 infections using laboratory tests have made the measurement of HIV-1 incidence realistic and practical. These approaches most commonly rely on the properties of early HIV-1 antibodies after seroconversion as characterized by their levels, antibody avidity/affinity or antibody classes/subclasses or epitope specificity. The sensitive/less-sensitive testing strategy provided simple laboratory tools to detect recent seroconversion in a cross-sectional population. These assays are based on differences in antibody titres in recent versus long-term infections and have been used for sometime for estimating population incidence. However, recent work demonstrated limitations of this approach which included subtype-dependent performance and significant variability of "window periods", precluding its use in many areas of the world. Recently an IgG-Capture BED-EIA was developed in our laboratory which detects the increasing HIV-IgG as proportion of total IgG following seroconversion and can be used to detect recent seroconversion. The format of the assay, which includes a multi-subtype derived antigen, allows high consistency and similar "window periods" in different subtypes. This assay is now available commercially and is made specifically for population estimates of HIV-1 incidence. Due to the presence of divergent HIV-1 subtypes and the rapidly expanding HIV epidemic, it is important that the method selected is robust, performs similarly in different subtypes and is widely applicable for meaningful incidence estimates, trend analysis and comparison between populations.


Assuntos
Sorodiagnóstico da AIDS/métodos , Infecções por HIV/diagnóstico , HIV-1/isolamento & purificação , Humanos , Incidência , Sensibilidade e Especificidade
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