Problems in interpreting HIV sentinel seroprevalence studies

Howard Strickler; Donald R. Hoover; Rebecca Dersimonian

doi:10.1016/1047-2797(95)00070-4

Problems in interpreting HIV sentinel seroprevalence studies

Howard Strickler, Donald R. Hoover, Rebecca Dersimonian

Research output: Contribution to journal › Article › peer-review

21 Scopus citations

Abstract

Estimating human immunodeficiency virus (HIV) prevalence from sentinel seroprevalence studies is difficult. We characterize these studies and show that most are investigations of incompletely defined (hypothetical) cohorts and are usually based on nonprobability samples. Prevalence in HIV sentinel serosurveys is also time-averaged and vulnerable to several time-dependent sources of bias (e.g., migration, deaths, and changes in incidence). Assumptions must be made that these time-dependent biases did not meaningfully affect the data, and this can be helped by reducing the period of investigation. Furthermore, we show that "reliability" can not be adequately measured by standard error, that "internal validity" is vulnerable to self-selection bias and laboratory problems, and that "generalizability" is limited. We propose that what is needed is a procedure (like formal metaanalysis methods) incorporating information from several separate HIV sentinel seroprevalence studies, in a manner that is reproducible and can take into consideration the differences between studies.

Original language	English (US)
Pages (from-to)	447-454
Number of pages	8
Journal	Annals of Epidemiology
Volume	5
Issue number	6
DOIs	https://doi.org/10.1016/1047-2797(95)00070-4
State	Published - Nov 1995
Externally published	Yes

All Science Journal Classification (ASJC) codes

Epidemiology

Keywords

Acquired immunodeficiency syndrome
epidemiology
human immunodeficiency virus type 1
seroprevalence
survey methods

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10.1016/1047-2797(95)00070-4

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title = "Problems in interpreting HIV sentinel seroprevalence studies",

abstract = "Estimating human immunodeficiency virus (HIV) prevalence from sentinel seroprevalence studies is difficult. We characterize these studies and show that most are investigations of incompletely defined (hypothetical) cohorts and are usually based on nonprobability samples. Prevalence in HIV sentinel serosurveys is also time-averaged and vulnerable to several time-dependent sources of bias (e.g., migration, deaths, and changes in incidence). Assumptions must be made that these time-dependent biases did not meaningfully affect the data, and this can be helped by reducing the period of investigation. Furthermore, we show that {"}reliability{"} can not be adequately measured by standard error, that {"}internal validity{"} is vulnerable to self-selection bias and laboratory problems, and that {"}generalizability{"} is limited. We propose that what is needed is a procedure (like formal metaanalysis methods) incorporating information from several separate HIV sentinel seroprevalence studies, in a manner that is reproducible and can take into consideration the differences between studies.",

keywords = "Acquired immunodeficiency syndrome, epidemiology, human immunodeficiency virus type 1, seroprevalence, survey methods",

author = "Howard Strickler and Hoover, {Donald R.} and Rebecca Dersimonian",

note = "Funding Information: From the Viral Epidemiology Branch, Division of Cancer Etiology, National Cancer Insrirute, National Institutes of Health (H.S.); Departments of Epidemmlogy and Biostatistics, School of Hygiene and Public Health, The Johns Hopkins University, Baltimore (D.R.H.); and Division of Epidemiology, Statistics and Prevention Research, National Institute of dhild Health, National Institutes of Health (R.D.), Bethesda, MD.",

year = "1995",

month = nov,

doi = "10.1016/1047-2797(95)00070-4",

language = "English (US)",

volume = "5",

pages = "447--454",

journal = "Annals of Epidemiology",

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T1 - Problems in interpreting HIV sentinel seroprevalence studies

AU - Strickler, Howard

AU - Hoover, Donald R.

AU - Dersimonian, Rebecca

N1 - Funding Information: From the Viral Epidemiology Branch, Division of Cancer Etiology, National Cancer Insrirute, National Institutes of Health (H.S.); Departments of Epidemmlogy and Biostatistics, School of Hygiene and Public Health, The Johns Hopkins University, Baltimore (D.R.H.); and Division of Epidemiology, Statistics and Prevention Research, National Institute of dhild Health, National Institutes of Health (R.D.), Bethesda, MD.

PY - 1995/11

Y1 - 1995/11

N2 - Estimating human immunodeficiency virus (HIV) prevalence from sentinel seroprevalence studies is difficult. We characterize these studies and show that most are investigations of incompletely defined (hypothetical) cohorts and are usually based on nonprobability samples. Prevalence in HIV sentinel serosurveys is also time-averaged and vulnerable to several time-dependent sources of bias (e.g., migration, deaths, and changes in incidence). Assumptions must be made that these time-dependent biases did not meaningfully affect the data, and this can be helped by reducing the period of investigation. Furthermore, we show that "reliability" can not be adequately measured by standard error, that "internal validity" is vulnerable to self-selection bias and laboratory problems, and that "generalizability" is limited. We propose that what is needed is a procedure (like formal metaanalysis methods) incorporating information from several separate HIV sentinel seroprevalence studies, in a manner that is reproducible and can take into consideration the differences between studies.

AB - Estimating human immunodeficiency virus (HIV) prevalence from sentinel seroprevalence studies is difficult. We characterize these studies and show that most are investigations of incompletely defined (hypothetical) cohorts and are usually based on nonprobability samples. Prevalence in HIV sentinel serosurveys is also time-averaged and vulnerable to several time-dependent sources of bias (e.g., migration, deaths, and changes in incidence). Assumptions must be made that these time-dependent biases did not meaningfully affect the data, and this can be helped by reducing the period of investigation. Furthermore, we show that "reliability" can not be adequately measured by standard error, that "internal validity" is vulnerable to self-selection bias and laboratory problems, and that "generalizability" is limited. We propose that what is needed is a procedure (like formal metaanalysis methods) incorporating information from several separate HIV sentinel seroprevalence studies, in a manner that is reproducible and can take into consideration the differences between studies.

KW - Acquired immunodeficiency syndrome

KW - epidemiology

KW - human immunodeficiency virus type 1

KW - seroprevalence

KW - survey methods

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Problems in interpreting HIV sentinel seroprevalence studies

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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