Adapting Lot Quality Assurance Sampling to accommodate imperfect diagnostic tests: application to COVID-19 serosurveillance in Haiti
Abstract 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 s...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-11-01
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| Series: | BMC Public Health |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12889-022-14206-5 |
| _version_ | 1811310790830981120 |
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| author | Isabel R. Fulcher Mary Clisbee Wesler Lambert Fernet Renand Leandre Bethany Hedt-Gauthier |
| author_facet | Isabel R. Fulcher Mary Clisbee Wesler Lambert Fernet Renand Leandre Bethany Hedt-Gauthier |
| author_sort | Isabel R. Fulcher |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-04-13T10:06:13Z |
| format | Article |
| id | doaj.art-4bff116d64a54106b3442acc7b65ed73 |
| institution | Directory Open Access Journal |
| issn | 1471-2458 |
| language | English |
| last_indexed | 2024-04-13T10:06:13Z |
| publishDate | 2022-11-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Public Health |
| spelling | doaj.art-4bff116d64a54106b3442acc7b65ed732022-12-22T02:51:05ZengBMCBMC Public Health1471-24582022-11-012211810.1186/s12889-022-14206-5Adapting Lot Quality Assurance Sampling to accommodate imperfect diagnostic tests: application to COVID-19 serosurveillance in HaitiIsabel R. Fulcher0Mary Clisbee1Wesler Lambert2Fernet Renand Leandre3Bethany Hedt-Gauthier4Department of Global Health and Social Medicine, Harvard Medical SchoolDepartment of Research, Zanmi LasanteDepartment of Research, Education and Strategic InformationDepartment of Global Health and Social Medicine, Harvard Medical SchoolDepartment of Global Health and Social Medicine, Harvard Medical SchoolAbstract 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.https://doi.org/10.1186/s12889-022-14206-5Lot Quality Assurance SamplingSerosurveysDiagnostic testingCOVID-19 |
| spellingShingle | Isabel R. Fulcher Mary Clisbee Wesler Lambert Fernet Renand Leandre Bethany Hedt-Gauthier Adapting Lot Quality Assurance Sampling to accommodate imperfect diagnostic tests: application to COVID-19 serosurveillance in Haiti BMC Public Health Lot Quality Assurance Sampling Serosurveys Diagnostic testing COVID-19 |
| title | Adapting Lot Quality Assurance Sampling to accommodate imperfect diagnostic tests: application to COVID-19 serosurveillance in Haiti |
| title_full | Adapting Lot Quality Assurance Sampling to accommodate imperfect diagnostic tests: application to COVID-19 serosurveillance in Haiti |
| title_fullStr | Adapting Lot Quality Assurance Sampling to accommodate imperfect diagnostic tests: application to COVID-19 serosurveillance in Haiti |
| title_full_unstemmed | Adapting Lot Quality Assurance Sampling to accommodate imperfect diagnostic tests: application to COVID-19 serosurveillance in Haiti |
| title_short | Adapting Lot Quality Assurance Sampling to accommodate imperfect diagnostic tests: application to COVID-19 serosurveillance in Haiti |
| title_sort | adapting lot quality assurance sampling to accommodate imperfect diagnostic tests application to covid 19 serosurveillance in haiti |
| topic | Lot Quality Assurance Sampling Serosurveys Diagnostic testing COVID-19 |
| url | https://doi.org/10.1186/s12889-022-14206-5 |
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