دورية أكاديمية

Adapting Lot Quality Assurance Sampling to accommodate imperfect diagnostic tests: application to COVID-19 serosurveillance in Haiti.

التفاصيل البيبلوغرافية
العنوان: Adapting Lot Quality Assurance Sampling to accommodate imperfect diagnostic tests: application to COVID-19 serosurveillance in Haiti.
المؤلفون: Fulcher IR; Department of Global Health and Social Medicine, Harvard Medical School, 641 Huntington Ave, Boston, MA, USA. isabel_fulcher@hms.harvard.edu., Clisbee M; Department of Research, Zanmi Lasante, Santo 18A, Croix-des-Bouquets, Haïti., Lambert W; Department of Research, Education and Strategic Information, Santo 18A, Croix-des-Bouquets, Haïti., Leandre FR; Department of Global Health and Social Medicine, Harvard Medical School, 641 Huntington Ave, Boston, MA, USA.; Division of Global Health Equity, Brigham and Women's Hospital, 800 Boylston Street Suite 300, Boston, USA., Hedt-Gauthier B; Department of Global Health and Social Medicine, Harvard Medical School, 641 Huntington Ave, Boston, MA, USA.; Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA.
المصدر: BMC public health [BMC Public Health] 2022 Nov 29; Vol. 22 (1), pp. 2221. Date of Electronic Publication: 2022 Nov 29.
نوع المنشور: Journal Article; Research Support, Non-U.S. Gov't
اللغة: English
بيانات الدورية: Publisher: BioMed Central Country of Publication: England NLM ID: 100968562 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2458 (Electronic) Linking ISSN: 14712458 NLM ISO Abbreviation: BMC Public Health Subsets: MEDLINE
أسماء مطبوعة: Original Publication: London : BioMed Central, [2001-
مواضيع طبية MeSH: COVID-19*/diagnosis , COVID-19*/epidemiology , Lot Quality Assurance Sampling*, Humans ; Antibodies, Viral ; Haiti/epidemiology ; SARS-CoV-2
مستخلص: Background: Lot Quality Assurance Sampling (LQAS), a tool used for monitoring health indicators in low resource settings resulting in "high" or "low" classifications, assumes that determination of the trait of interest is perfect. This is often not true for diagnostic tests, with imperfect sensitivity and specificity. Here, we develop Lot Quality Assurance Sampling for Imperfect Tests (LQAS-IMP) to address this issue and apply it to a COVID-19 serosurveillance study design in Haiti.
Methods: We first derive a modified procedure, LQAS-IMP, that accounts for the sensitivity and specificity of a diagnostic test to yield correct classification errors. We then apply the novel LQAS-IMP to design an LQAS system to classify prevalence of SARS-CoV-2 antibodies among healthcare workers at eleven Zanmia Lasante health facilities in Haiti. Finally, we show the performance of the LQAS-IMP procedure in a simulation study.
Results: We found that when an imperfect diagnostic test is used, the classification errors in the standard LQAS procedure are larger than specified. In the modified LQAS-IMP procedure, classification errors are consistent with the specified maximum classification error. We then utilized the LQAS-IMP procedure to define valid systems for sampling at eleven hospitals in Haiti.
Conclusion: The LQAS-IMP procedure accounts for imperfect sensitivity and specificity in system design; if the accuracy of a test is known, the use of LQAS-IMP extends LQAS to applications for indicators that are based on laboratory tests, such as SARS-CoV-2 antibodies.
(© 2022. The Author(s).)
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فهرسة مساهمة: Keywords: COVID-19; Diagnostic testing; Lot Quality Assurance Sampling; Serosurveys
المشرفين على المادة: 0 (Antibodies, Viral)
تواريخ الأحداث: Date Created: 20221129 Date Completed: 20221230 Latest Revision: 20221230
رمز التحديث: 20240628
مُعرف محوري في PubMed: PMC9707425
DOI: 10.1186/s12889-022-14206-5
PMID: 36447195
قاعدة البيانات: MEDLINE
الوصف
تدمد:1471-2458
DOI:10.1186/s12889-022-14206-5