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Impacts on knowledge and testing on HIV in waves of Mozambique surveys with Bayes estimates
BACKGROUND: It is well known that it is more reliable to investigate the effects of several covariates simultaneously rather than one at time. Similarly, it is more informative to model responses simultaneously, as more often than not, the multiple responses from the same subject are correlated. Thi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7771863/ https://www.ncbi.nlm.nih.gov/pubmed/33373426 http://dx.doi.org/10.1371/journal.pone.0244563 |
Sumario: | BACKGROUND: It is well known that it is more reliable to investigate the effects of several covariates simultaneously rather than one at time. Similarly, it is more informative to model responses simultaneously, as more often than not, the multiple responses from the same subject are correlated. This is particularly true in the analysis of Mozambique survey data from 2009 and 2018. METHOD: A multiple response predictive model for testing positive for HIV and having sufficient HIV knowledge is modeled to 2009 and 2018 survey data with the use of Bayes estimates. These data are obtained through a hierarchical data structure. The model allows one to address the change in the response to HIV, as it relates to morbidity and to HIV knowledge in Mozambique in the fight against the disease in the last decade. RESULTS: A more affluent resident is more likely to test positive, more likely to be more knowledgeable about the disease. Whereas, individuals practicing the Islam faith are less likely to test positive but also less likely to be knowledgeable about the disease. Education, while still a factor, has declined in its impact on testing positive for HIV or being knowledgeable about HIV. Females are more likely to test positive but more likely to be knowledgeable about the disease than men. The rate of impact of affluence on knowledge has increased in the past decade. Marital status (cohabitating or married) showed no impact on the knowledge of the disease. Age had no impact on knowledge suggesting that the message is getting to resident. CONCLUSIONS: A joint Bayes modeling of correlated binary (testing positive and knowledge about the disease) responses, while accounting for the hierarchy of the data collection, presents an opportunity to extract the extra variation before allocating the variation on the responses as the due of the covariates. The fight against HIV in Mozambique seems to be succeeding. Some knowledge is common among all ages, and Islam religion has a positive effect. While education still shows an influence on the binary responses, it has declined over the last decade. |
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