1. TRACE INITIATIVE: Data Management

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3. BACKGROUND

4. Recency Data Collected
Data will be collected on forms, in registers, and, in some cases, on tablets or computers
Example data sources:
Recency HIV Infection Surveillance Register or Recent Infection Results Documentation Form
Collects lot number, expiry date, date of test, and result
Electronic data collection forms
Collects basic demographics and risk factor information
Laboratory Requisition Form
Collects client ID, date of test, date of transport, results, and viral load
Return of Results Log
Collects information required to return result if applicable
Laboratory Log Book
Collects information about testing done in laboratory including confirmation and viral load as well as final RITA result

5. Minimum Data Set
Strongly suggested variables to collect in order to accurately assess the epidemic and track progress
Included range of values for data quality checks

6. DATA PLATFORM

7. Data Platform Paper or electronic
Solution based on central server in secure data center
Access through web browser and optionally mobile tools

8. Example Solutions
ODK
Open source data collection software easily adaptable
Works on most tablets and backs up to a cloud server
Has offline capability in the case of poor internet
REDCap
Origins in research data management
Large global presence, including and growing in LMIC
Ease of use, standards support, privacy and confidentiality support
Common Properties
Web-based software with central server and browser based interface
End-user configurable (meta-data driven)
Rich feature sets for data capture/management
Off-line data capture possible with mobile device application

9. Common Approach Build the electronic report form
Based on DGHT HIV case-based surveillance initial CRF
With recent infection test & algorithm added
Data abstraction perspective
Workflow aligned with transcription from source documentation
Configure advanced data management features
Data quality controls
Single-field validation rules
Multi-field logical consistency controls
Branching logic
Data capture workflow and quality support
Program reports
Basic analytics for program quality assurance

10. Example Case Report Form

11. Example Case Report Form Continued
Client Rapid HIV Recent Infection Test Information
Rapid HIV recent infection testing
If the test was conducted or not
If the test was conducted, indicate the test name and test date
Rapid HIV recent infection test results
Can be “Recent” OR “Long-term” OR “Inconclusive”
Viral load confirmation for the HIV rapid recent infection test result
A viral load test can be conducted to confirm recent infection among clients that test “recent” on the rapid HIV infection test
If a viral load test was conducted, indicate the sample collection date, the test date and the results in copies/mL.
Final rapid HIV recent infection testing algorithm result
if viral load test conducted; recent is defined as tested recent on the recent HIV infection test and having HIV RNA >1,000 copies/mL
Long-term is defined as tested long-term on the recent HIV infection test OR tested recent on the recent HIV infection test and having HIV RNA of 1,000 copies or lower

12. DATA SECURITY

13. Data Security
Platform requires strong security support to store identified information on HIV status
Use VPN if possible
Use managed authentication system
Confidentiality requires configurable data access rules to ensure that PII is only accessible to those individuals who are authorized

14. Data Security
Data security is important at every stage: data collection, transfer, and storage
All electronic devices, if used, will be physically secured when not in use.
All electronic devices and databases will be encrypted, password protected and accessible only by appropriate staff.
The database will be backed up monthly on a secure, external system.
All staff with access to data will receive training in data security and confidentiality and must affirm that they will abide by data security and confidentiality principles and procedures.

15. Electronic Capture of Data
For paper-based forms
Data from all recency forms will be entered into a secured computer at the lab by data entry staff
All forms will be kept in a locked cabinet after they have been entered
Electronic data entry
Data will be entered into a tablet kept in a secure place at the facility
SOPs should be in place to ensure proper storage, charging of tablet and internet access (hotspots if wifi is not available at the facility)
Tablets should be connected to the server daily for data upload

16. DATA CLEANING

17. Data Cleaning
Data will be reviewed and cleaned by the data manager weekly
Periodically, the entire database will be checked for errors
Inconsistencies will be confirmed by reviewing the original source (data forms)
If the data form is incorrect, the supervisor for that site will be called to confirm
If all attempts to correct the error fail, the data will not be usable

18. Review All Forms Carefully Before Submission
The success of the program depends on everyone doing their job with pride
We owe it to the clients to handle their data with the utmost care
PLEASE REVIEW ALL FORMS CAREFULLY AND ENSURE THEY ARE PROPERLY FILLED OUT AND ENTERED

19. DATA AGGREGATION & ANALYSIS

20. Data Aggregation
Data will be aggregated at the sub- national/national level
Data will be used to:
Monitor trends in the proportion testing recent among newly diagnosed PLHIV by select demographic and HIV risk indicators
Identify geographic locations associated with testing recent
Inform targeted interventions by demographic variables, risk indicators, and/or geography

21. Data Analysis
Implementing partner is responsible for ensuring analysis happens in conjunction with other stakeholders including the Ministry of Health
Data should be analyzed and reviewed quarterly for action

22. E.g. age, sex, risk behavior, access to health services
Objectives of Data Analysis
Monitor trends in the proportion testing recent among newly diagnosed PLHIV by select demographic and HIV risk indicators to inform targeted interventions
E.g. age, sex, risk behavior, access to health services
Identify geographic locations associated with testing recent to inform geographic prioritization of interventions
GIS software packages (ArcGIS, QGIS)
Maps (dot maps, shaded maps, heat maps, bubble maps) help visualize the location of recent and long-term HIV infections by health facility GIS location or client residence

23. Monitor those who chose not to test for recent infection
Objectives of Data Analysis
Monitor those who chose not to test for recent infection
Number and proportion of eligible clients who chose not to test for recent infection
Comparison of demographic and behavioral characteristics of persons who did not receive testing for recent infection compared to those who were tested

24. Data Analysis New PEPFAR MER indicator: HTS_RECENT
Percentage of persons aged ≥15 years newly diagnosed with HIV-1 infection who have a test for recent infection result of recent infection during the reporting period
Reporting:
Frequency: quarterly
Level: facility and community
Number of newly diagnosed HIV-positive persons aged ≥15 years with a test for recent infection result of recent infection during the past quarter
Numerator
Denominator
Number of newly diagnosed HIV-positive persons aged ≥15 years with a test for recent infection result during the past quarter

25. Relationship with HTS_TST
Facility or community where testing for recent infection is performed
Newly diagnosed and recent infection
HTS_RECENT
(numerator)
HTS_TST
Testing for recent infection
HTS_TST_POS (≥15 years)
NOTE: Only persons who are newly diagnosed HIV-positive should be tested for recent infection. Persons who have been diagnosed HIV positive and are retesting or persons who are on ART should not receive testing for recent infection. Each country may use different methods for determining who is truly newly diagnosed HIV positive (e.g., additional post-test counseling to discuss prior diagnosis or ART history, review of registers to check whether a client is a silent transfer, and viral load testing to help eliminate those who test recent and are on ART and virally suppressed).
Newly diagnosed HIV positive
HTS_RECENT
(denominator)
Newly diagnosed and long-term infection
Newly diagnosed HIV-positive persons aged ≥15 years who tested for recent infection and have a result
HIV negative

26. Data Analysis: Table Shells
Outcomes
Number and percentage of recent infections
Characteristics
Sex
Age
Marital status
Geography: testing site, residence, urban/rural, SNU
Education level
HTS point
Priority/key population type
Pregnancy status
Number of sexual partners in last 12 months
HIV testing history
Violence in last 12 months

27. Example Analyses for HIV Recency Testing

28. Testing Coverage and % Recent by Quarter

29. % Recent by Assay and RITA

30. % Recent by Facility and Quarter

31. Not Tested for Recent Infection

32. Index Partners by Recent Infection Status

33. Index Testing Yield Example
HIV yield among partners by index case recency status, Central America, January-August 2018, Guatemala, Nicaragua, and Honduras

34. Factors Associated with Recent Infection

35. Incidence Estimation

36. Recent Cases by Location
Source: Data collected by the Ministries of Health in Guatemala, Honduras, and Nicaragua and presented at the 2018 PEPFAR Annual Meeting by Northbrook S et al.

37. Recent and Long-Term Cases by Location
Source: A pragmatic approach to HIV hotspot mapping in a developing country available at

38. SaTScan Analysis
Source: Data collected by Nicaragua Ministry of Health and presented at the 2018 PEPFAR Annual Meeting by Northbrook S et al.

39. DATA REPORTING

40. Data Reporting
Implementing partners are responsible for MER reporting and any other reporting required by the Ministry of Health
MER reporting data will be made available
All data
Are the property of the country Ministry of Health
Will be monitored by the project investigators
Will be accessible to all investigators

41. Data Reporting
Periodically, results will be presented to a meeting of a group of stakeholders such as the government (MOH), civil society, non- governmental organizations, donors, and international technical experts.
Dissemination of results will take several forms, including reports for distribution and peer-reviewed publications.

42. Questions? Comments?

43. Thank You!