| Author | Salganik, Matthew J. | |
| Author | Fazito, Dimitri | |
| Author | Bertoni, Neilane | |
| Author | Abdo, Alexandre H. | |
| Author | Mello, Maeve Brito de | |
| Author | Bastos, Francisco Inácio Pinkusfeld Monteiro | |
| Access date | 2012-08-12T03:05:27Z | |
| Available date | 2012-08-12T03:05:27Z | |
| Document date | 2011 | |
| Citation | SALGANIK, Matthew J. et al. Assessing Network Scale-up Estimates for Groups Most at Risk of HIV/AIDS: evidence From a Multiple-Method Study of Heavy Drug Users in Curitiba, Brazil. American Journal of Epidemiology, Oxford, v. 174, n. 10, p. 1-7, 2011. | en_US |
| ISSN | 0002-9262 | |
| URI | https://www.arca.fiocruz.br/handle/icict/4271 | |
| Language | eng | en_US |
| Publisher | Oxford University Press | en_US |
| Rights | open access | en_US |
| Title | Assessing Network Scale-up Estimates for Groups Most at Risk of HIV/AIDS: Evidence From a Multiple-Method Study of Heavy Drug Users in Curitiba, Brazil | en_US |
| Type | Article | en_US |
| DOI | 10.1093/aje/kwr246 | |
| Abstract | One of the many challenges hindering the global response to the human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) epidemic is the difficulty of collecting reliable information about the populations most at risk for the disease. Thus, the authors empirically assessed a promising new method for estimating the sizes of most at-risk populations: the network scale-up method. Using 4 different data sources, 2 of which were from other researchers, the authors produced 5 estimates of the number of heavy drug users in Curitiba, Brazil. The authors found that the network scale-up and generalized network scale-up estimators produced estimates 5–10 times higher than estimates made using standard methods (the multiplier method and the direct estimation method using data from 2004 and 2010). Given that equally plausible methods produced such a wide range of results, the authors
recommend that additional studies be undertaken to compare estimates based on the scale-up method with those made using other methods. If scale-up-based methods routinely produce higher estimates, this would suggest that scale-up-based methods are inappropriate for populations most at risk of HIV/AIDS or that standard methods may tend to underestimate the sizes of these populations. | en_US |
| Affilliation | Princeton University. Department of Sociology and Office of Population Research. Princeton, New Jersey, EUA. | en_US |
| Affilliation | Universidade Federal de Minas Gerais. Belo Horizonte, MG, Brasil. | en_US |
| Affilliation | Fundação Oswaldo Cruz. Instituto de Comunicação e Informação Cientifica e Tecnológica em Saúde. Rio de Janeiro, RJ, Brasil. | en_US |
| Affilliation | Fundação Oswaldo Cruz. Instituto de Comunicação e Informação Cientifica e Tecnológica em Saúde. Rio de Janeiro, RJ, Brasil. | en_US |
| Affilliation | Fundação Oswaldo Cruz. Instituto de Comunicação e Informação Cientifica e Tecnológica em Saúde. Rio de Janeiro, RJ, Brasil. | en_US |
| Affilliation | Fundação Oswaldo Cruz. Rio de Janeiro, RJ, Brasil. | en_US |
| Subject | Acquired immunodeficiency syndrome | en_US |
| Subject | Epidemiologic methods | en_US |
| Subject | HIV | en_US |
| Subject | Network sampling | en_US |
| Subject | Population size estimation | en_US |
| Subject | Social networks | en_US |
| DeCS | Síndrome de Imunodeficiência Adquirida | en_US |
| DeCS | Métodos Epidemiológicos | en_US |
| DeCS | Densidade Demográfica | en_US |
| DeCS | Rede Social | en_US |
