Studies of AIDS and HIV surveillance. Screening tests: can we get more by doing less?

Estimating the prevalence of the human immunodeficiency virus (HIV) in a group is challenging; this is especially so when the prevalence is small. One reason is that the presence of measurement errors resulting from the limited precision of tests makes estimation, using traditional methods, impossible in some screening situations. Measurement error is real, ignoring it leads to severe bias, and inference about the prevalence becomes unsatisfactory. Indeed, in a low prevalence situation the expected number of false positives is very high, often even higher than the number of true positives. The second reason is that in the low prevalence areas the large sample is needed in order to obtain non-zero estimate. This is usually a very costly, and often unrealistic, solution. This paper considers the advantages and disadvantages of pooled testing as an alternative solution to this problem. We show that by pooling sera samples we not only achieve a cost saving but also, which is counterintuitive, an increase in the estimation accuracy. We also discuss the statistical issues associated with the resulting estimator.

[1]  T. Quinn,et al.  Successful use of pooled sera to determine HIV-1 seroprevalence in Zaire with development of cost-efficiency models. , 1990, AIDS.

[2]  S G Pauker,et al.  Screening for HIV: can we afford the false positive rate? , 1987, The New England journal of medicine.

[3]  J. Allan,et al.  Antigens of human T-lymphotropic virus type III/lymphadenopathy-associated virus. , 1985, Annals of internal medicine.

[4]  D. Berns,et al.  Newborn seroprevalence study: methods and results. , 1991, American journal of public health.

[5]  S. Lohr Statistics (2nd Ed.) , 1994 .

[6]  R. Dorfman The Detection of Defective Members of Large Populations , 1943 .

[7]  J. Fleiss Statistical methods for rates and proportions , 1974 .

[8]  P. Bickel,et al.  Mathematical Statistics: Basic Ideas and Selected Topics , 1977 .

[9]  X M Tu,et al.  Issues in human immunodeficiency virus (HIV) screening programs. , 1992, American journal of epidemiology.

[10]  Thomas A. Louis,et al.  Confidence Intervals for a Binomial Parameter after Observing No Successes , 1981 .

[11]  Marcello Pagano,et al.  On the informativeness and accuracy of pooled testing in estimating prevalence of a rare disease: Application to HIV screening , 1995 .

[12]  J. Gaudino,et al.  Sensitivity and specificity of pooled versus individual sera in a human immunodeficiency virus antibody prevalence study , 1989, Journal of clinical microbiology.

[13]  M. Sobel,et al.  Group testing to eliminate efficiently all defectives in a binomial sample , 1959 .

[14]  Eamonn Mullins,et al.  Probability and Statistics. 2nd edn. , 1988 .

[15]  S Zeger,et al.  Evaluation of human immunodeficiency virus seroprevalence in population surveys using pooled sera , 1989, Journal of clinical microbiology.

[16]  M. Bassett,et al.  Pooling of sera for human immunodeficiency virus (HIV) testing: an economical method for use in developing countries. , 1988, Journal of clinical pathology.

[17]  Joseph L. Gastwirth,et al.  Estimation of the prevalence of a rare disease, preserving the anonymity of the subjects by group testing: application to estimating the prevalence of aids antibodies in blood donors , 1989 .

[18]  P. Hall The Bootstrap and Edgeworth Expansion , 1992 .

[19]  Marcello Pagano,et al.  Screening for the Presence of a Disease by Pooling Sera Samples , 1994 .