Uncertainty in estimates of HIV/AIDS: the estimation and application of plausibility bounds

被引:52
作者
Grassly, NC
Morgan, M
Walker, N
Garnett, G
Stanecki, KA
Stover, J
Brown, T
Ghys, PD
机构
[1] UNAIDS, CH-1211 Geneva 27, Switzerland
[2] Univ London Imperial Coll Sci & Technol, Dept Infect Dis Epidemiol, London W2 1PG, England
[3] Ctr Dis Control & Prevent, Atlanta, GA 30333 USA
[4] UNICEF, New York, NY USA
[5] Futures Grp Inc, Glastonbury, CT USA
[6] East West Ctr, Honolulu, HI 96848 USA
关键词
D O I
10.1136/sti.2004.010637
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
Objectives: To establish the accuracy of the country specific estimates of HIV prevalence, incidence, and AIDS mortality published every 2 years by UNAIDS and WHO. Methods: We review sources of error in the data used to generate national HIV/AIDS and where possible estimate their statistical properties. We use numerical and approximate analytic methods to estimate the combined impact of these errors on HIV/AIDS estimates. Heuristic rules are then derived to produce plausible bounds about these estimates for countries with different types of epidemic and different qualities of surveillance system. Results: Although 95% confidence intervals (CIs) can be estimated for some sources of error, the sizes of other sources of error must be based on expert judgment. We therefore produce plausible bounds about HIV/AIDS estimates rather than statistical CIs. The magnitude of these bounds depends on the stage of the epidemic and the quality and coverage of the sentinel HIV surveillance system. The bounds for adult estimates are narrower than those for children, and those for prevalence are narrower than those for new infections. Conclusions: This paper presents a first attempt at a rigorous description of the errors associated with estimation of global statistics of an infectious disease. The proposed methods work well in countries with generalised epidemics (>1% adult HIV prevalence) where the quality of surveillance is good. Although methods have also been derived for countries with low level or concentrated epidemics, more data on the biases in the estimation process are required.
引用
收藏
页码:i31 / i38
页数:8
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