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Estimating HIV prevalence from surveys with low individual consent rates: annealing individual and pooled samples.

Hund L, Pagano M - Emerg Themes Epidemiol (2013)

Bottom Line: : Many HIV prevalence surveys are plagued by the problem that a sizeable number of surveyed individuals do not consent to contribute blood samples for testing.For those individuals, we suggest offering the option of being tested in a pool.We quantify improvements in a prevalence estimator based on this combined testing strategy, relative to an individual testing only approach and a pooled testing only approach.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Family and Community Medicine, University of New Mexico, 2400 Tucker NE, Albuquerque, NM 87106, USA. lhund@salud.unm.edu.

ABSTRACT
: Many HIV prevalence surveys are plagued by the problem that a sizeable number of surveyed individuals do not consent to contribute blood samples for testing. One can ignore this problem, as is often done, but the resultant bias can be of sufficient magnitude to invalidate the results of the survey, especially if the number of non-responders is high and the reason for refusing to participate is related to the individual's HIV status. One reason for refusing to participate may be for reasons of privacy. For those individuals, we suggest offering the option of being tested in a pool. This form of testing is less certain than individual testing, but, if it convinces more people to submit to testing, it should reduce the potential for bias and give a cleaner answer to the question of prevalence. This paper explores the logistics of implementing a combined individual and pooled testing approach and evaluates the analytical advantages to such a combined testing strategy. We quantify improvements in a prevalence estimator based on this combined testing strategy, relative to an individual testing only approach and a pooled testing only approach. Minimizing non-response is key for reducing bias, and, if pooled testing assuages privacy concerns, offering a pooled testing strategy has the potential to substantially improve HIV prevalence estimates.

No MeSH data available.


Comparing the asymptotic properties of the combined estimator to the pooling-only estimator. Ratio of the mse for the combined estimator to the ratio of the mse when everyone is offered pooled testing, as a function of pool size for the low, moderate, and high prevalence settings when pooled testers have a higher prevalence than individual testers. The combined estimator always has lower mse than the estimator where everyone is offered pooled testing in these settings.
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Figure 2: Comparing the asymptotic properties of the combined estimator to the pooling-only estimator. Ratio of the mse for the combined estimator to the ratio of the mse when everyone is offered pooled testing, as a function of pool size for the low, moderate, and high prevalence settings when pooled testers have a higher prevalence than individual testers. The combined estimator always has lower mse than the estimator where everyone is offered pooled testing in these settings.

Mentions: Testing using the combined estimator results in a smaller asymptotic mse than the estimator which only offers pooled testing (Figure 2), assuming the sample size is the same for both estimators. The mse for the combined estimator is 10% less than the mse for the pooled testing only estimator in the moderate and high prevalence settings, with less reduction in mse in the low prevalence setting. The combined estimator provides an improvement in mse because the variance of the pooled prevalence estimator always decreases as the pool size decreases; intuitively, individual test results provide more information than pooled test results on the same number of people, so providing an individual testing option is optimal. Further, if everyone is offered pooled testing, individual results are no longer available to those who are interested in learning their hiv status and thus may be unethical [30]. And lastly, the survey protocol we suggest gives individuals two opportunities to consent to testing (pooled or individual), rather than only asking individuals to test once as in the pooled-testing only design, which could help increase consent rates. Therefore, having both pooled and individual testing options is advantageous.


Estimating HIV prevalence from surveys with low individual consent rates: annealing individual and pooled samples.

Hund L, Pagano M - Emerg Themes Epidemiol (2013)

Comparing the asymptotic properties of the combined estimator to the pooling-only estimator. Ratio of the mse for the combined estimator to the ratio of the mse when everyone is offered pooled testing, as a function of pool size for the low, moderate, and high prevalence settings when pooled testers have a higher prevalence than individual testers. The combined estimator always has lower mse than the estimator where everyone is offered pooled testing in these settings.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3649931&req=5

Figure 2: Comparing the asymptotic properties of the combined estimator to the pooling-only estimator. Ratio of the mse for the combined estimator to the ratio of the mse when everyone is offered pooled testing, as a function of pool size for the low, moderate, and high prevalence settings when pooled testers have a higher prevalence than individual testers. The combined estimator always has lower mse than the estimator where everyone is offered pooled testing in these settings.
Mentions: Testing using the combined estimator results in a smaller asymptotic mse than the estimator which only offers pooled testing (Figure 2), assuming the sample size is the same for both estimators. The mse for the combined estimator is 10% less than the mse for the pooled testing only estimator in the moderate and high prevalence settings, with less reduction in mse in the low prevalence setting. The combined estimator provides an improvement in mse because the variance of the pooled prevalence estimator always decreases as the pool size decreases; intuitively, individual test results provide more information than pooled test results on the same number of people, so providing an individual testing option is optimal. Further, if everyone is offered pooled testing, individual results are no longer available to those who are interested in learning their hiv status and thus may be unethical [30]. And lastly, the survey protocol we suggest gives individuals two opportunities to consent to testing (pooled or individual), rather than only asking individuals to test once as in the pooled-testing only design, which could help increase consent rates. Therefore, having both pooled and individual testing options is advantageous.

Bottom Line: : Many HIV prevalence surveys are plagued by the problem that a sizeable number of surveyed individuals do not consent to contribute blood samples for testing.For those individuals, we suggest offering the option of being tested in a pool.We quantify improvements in a prevalence estimator based on this combined testing strategy, relative to an individual testing only approach and a pooled testing only approach.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Family and Community Medicine, University of New Mexico, 2400 Tucker NE, Albuquerque, NM 87106, USA. lhund@salud.unm.edu.

ABSTRACT
: Many HIV prevalence surveys are plagued by the problem that a sizeable number of surveyed individuals do not consent to contribute blood samples for testing. One can ignore this problem, as is often done, but the resultant bias can be of sufficient magnitude to invalidate the results of the survey, especially if the number of non-responders is high and the reason for refusing to participate is related to the individual's HIV status. One reason for refusing to participate may be for reasons of privacy. For those individuals, we suggest offering the option of being tested in a pool. This form of testing is less certain than individual testing, but, if it convinces more people to submit to testing, it should reduce the potential for bias and give a cleaner answer to the question of prevalence. This paper explores the logistics of implementing a combined individual and pooled testing approach and evaluates the analytical advantages to such a combined testing strategy. We quantify improvements in a prevalence estimator based on this combined testing strategy, relative to an individual testing only approach and a pooled testing only approach. Minimizing non-response is key for reducing bias, and, if pooled testing assuages privacy concerns, offering a pooled testing strategy has the potential to substantially improve HIV prevalence estimates.

No MeSH data available.