Becker N G, Chao X
Department of Statistics, La Trobe University, Bundoora VIC, Australia.
Stat Med. 1994;13(19-20):1945-58. doi: 10.1002/sim.4780131907.
Techniques for reconstructing plausible HIV incidence curves from AIDS incidence data are called methods of back-projection, or back-calculation. Approaches to back-projection tend to make the simplifying assumption that the quarterly HIV incidences are independent, which is not even approximately true. Here we investigate whether smoothed non-parametric back-projection based on this simplifying assumption gives sensible back-projections and appropriate measures of precision for these reconstructed HIV incidence curves. Simple models for HIV transmission are shown to have much greater variation than the corresponding non-homogeneous Poisson process arising from the independence assumption. Nevertheless, bearing in mind that the objective is to reconstruct the HIV epidemic curve for the current epidemic, it is argued that such back-projection does give sensible HIV curves. This conclusion is supported by a simulation study, which also finds that confidence intervals for the HIV incidences are wider for transmission data than those determined from independent Poisson data.
从艾滋病发病率数据重建合理的艾滋病毒发病率曲线的技术被称为反向投影法或反向计算法。反向投影法往往做出季度艾滋病毒发病率相互独立的简化假设，而这甚至都不完全正确。在此，我们研究基于这一简化假设的平滑非参数反向投影法是否能给出合理的反向投影以及这些重建的艾滋病毒发病率曲线的适当精度度量。结果表明，艾滋病毒传播的简单模型比由独立性假设产生的相应非齐次泊松过程具有更大的变异性。然而，考虑到目标是重建当前疫情的艾滋病毒流行曲线，有人认为这种反向投影法确实能给出合理的艾滋病毒曲线。这一结论得到了一项模拟研究的支持，该研究还发现，与根据独立泊松数据确定的置信区间相比，传播数据的艾滋病毒发病率置信区间更宽。
