Population-Based HIV Impact Assessments Survey Methods, Response, and Quality in Zimbabwe, Malawi, and Zambia

Abstract

Background: The population-based HIV impact assessment (population-based HIV impact assessments) surveys are among the first to estimate national adult HIV incidence, subnational prevalence of viral load suppression, and pediatric HIV prevalence. We summarize the survey methods implemented in Zimbabwe, Malawi, and Zambia, as well as response rates and quality metrics.

Methods: Each cross-sectional, household-based survey used a 2-stage cluster design. Survey preparations included sample design, questionnaire development, tablet programming for informed consent and data collection, community mobilization, establishing a network of satellite laboratories, and fieldworker training. Interviewers collected demographic, behavioral, and clinical information using tablets. Blood was collected for home-based HIV testing and counseling (HBTC) and point-of-care CD4+ T-cell enumeration with results immediately returned. HIV-positive blood samples underwent laboratory-based confirmatory testing, HIV incidence testing, RNA polymerase chain reaction (viral load), DNA polymerase chain reaction (early infant diagnosis), and serum antiretroviral drug detection. Data were weighted for survey design, and chi square automatic interaction detection-based methods were used to adjust for nonresponse.

Results: Each survey recruited a nationally representative, household-based sample of children and adults over a 6-10-month period in 2015 and 2016. Most (84%-90%) of the 12,000-14,000 eligible households in each country participated in the survey, with 77%-81% of eligible adults completing an interview and providing blood for HIV testing. Among eligible children, 59%-73% completed HIV testing. Across the 3 surveys, 97.8% of interview data were complete and had no errors.

Conclusion: Conducting a national population-based HIV impact assessment with immediate return of HIV and other point-of-care test results was feasible, and data quality was high.

Figure 1:. Data Architecture, for Population-based HIV Impact Assessments in Zimbabwe, Malawi, and Zambia, 2015 – 2016

At completion of all study activities in the household, supervisors uploaded data from the tablets (1) to a secure cloud server via a Wi-Fi or 3G network connection using a pocket wireless router (2). CD4+ cell counts and their associated participant identification number (PTIDs) were uploaded from the CD4 PIMA analyzer via Wi-Fi or 3G network to a secure cloud server (3) and subsequently merged with the survey database. Both satellite and central laboratories used a Laboratory Data Management System (LDMS) (Frontier Science, Boston, Massachusetts) database to track specimen receipt, processing, freezing times, quantity, quality assurance testing data, storage location. and shipment details which were transmitted to Frontier Science using encrypted flash drives (4a, 4b) or directly (5). Central laboratory-based test results, including viral load, early infant diagnosis, and HIV recency were either pulled directly from the local laboratory information management system (LIMS) or sent in files extracted from the test instruments and uploaded to a secure FTP server and appended to the database (6, 7). Questionnaire data from the ODK server, CD4 data and LDMS quality assurance/quality control (QA/QC) data that went through intermediary servers were all linked with the overall database (8, 9, 10). The overall survey database was sent daily to an in-country server for local stakeholders to access and monitor (11). After completion of data cleaning, finalized data was also transferred to an in-country server (12).

Figure 2:. Among adults interviewed, blood draw response rates by self-reported HIV status

*Other includes the response categories refused, don’t know, and missing ** Zimbabwe Population-based HIV Impact Assessment (ZIMPHIA); Malawi Population-based HIV Impact Assessment (MPHIA); Zambia Population-based HIV Impact Assessment (ZAMPHIA)

Figure 3:. Households and participants by country for Population-based HIV Impact Assessments in Zimbabwe, Malawi, and Zambia, 2015 – 2016

*all percentages are weighted percentages

Figure 3:. Households and participants by country for Population-based HIV Impact Assessments in Zimbabwe, Malawi, and Zambia, 2015 – 2016

*all percentages are weighted percentages

Figure 3:. Households and participants by country for Population-based HIV Impact Assessments in Zimbabwe, Malawi, and Zambia, 2015 – 2016

*all percentages are weighted percentages