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 underdiagnosis 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.
CITATION STYLE
Oliveira, A., Gaio, A. R., da Costa, J. P., & Reis, L. P. (2016). An approach for assessing the distribution of reporting delay in Portuguese AIDS data. In Advances in Intelligent Systems and Computing (Vol. 445, pp. 641–649). Springer Verlag. https://doi.org/10.1007/978-3-319-31307-8_66
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