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Advisor(s)
Abstract(s)
HIV/AIDS epidemic is an important public health problem. The burden of the epidemic is estimated from surveillance systems data. The collected information is incomplete, making the estimation a challenging task and the reported trends often biased. The most common incomplete-data problems, in this kind of data, are due to under-diagnosis and reporting delays, mainly in the most recent years. This is a classical problem for imputation methodologies. In this paper we study the distribution of AIDS reporting delays through a mix approach, combining longitudinal K-means with the generalized least squares method. While the former identifies homogeneous delay patterns, the latter estimated longitudinal regression curves. We found that a 2-cluster structure is appropriated to accommodate the heterogeneity in reporting delay on HIV/AIDS data and that the corresponding estimated delay curves are almost stationary over time.
Description
Keywords
HIV/AIDS Reporting delay Incomplete data Imputation method KML GLS
Citation
Oliveira, A., Rita Gaio, A., da Costa, J. P., & Reis, L. P. (2016). An aproach for assessing the distribution of reporting delay in portuguese AIDS data. Em Á. Rocha, A. M. Correia, H. Adeli, L. P. Reis, & M. Mendonça Teixeira (Eds.), New Advances in Information Systems and Technologies (pp. 641–649). Springer International Publishing. https://doi.org/10.1007/978-3-319-31307-8_66
Publisher
Springer