BackgroundTo track the HIV epidemic and responses to it, the World Health Organization recommends 10 global indicators to collect information along the HIV care cascade. Patient diagnosis and medical record data, harnessed through case-based surveillance (CBS), can be used to measure 8 of these. While many high burden countries have well-established systems for monitoring patients on HIV treatment, few have formally adopted CBS.ObjectiveIn response to the need for improved strategic HIV information and to facilitate the development of CBS in resource-limited countries, we aimed to conduct situational assessments of existing data collection systems in Tanzania, South Africa, and Kenya.MethodsWe developed a standardized protocol and a modularized data collection tool to be adapted for the particular focus of the assessments within each country. The three countries were selected based on their stage of readiness for CBS. The assessment included three parts: a desk review of relevant materials on HIV surveillance and program monitoring, stakeholder meetings, and site visits.ResultsIn all three countries, routine HIV program monitoring is conducted, and information on new HIV diagnoses and persons accessing HIV care and treatment services is collected. Key findings from the assessments included substantial stakeholder support for the development of CBS, significant challenges in linking data within and between systems, data quality, the ability to obtain data from multiple sources, and information technology infrastructure. Viral load testing capacity varied by country, and vital registry data were not routinely linked to health systems to update medical records.ConclusionsOur findings support the development of CBS systems to systematically capture routinely collected health data to measure and monitor HIV epidemics and guide responses. Although there were wide variations in the systems examined, some of the current program and patient monitoring systems can be adapted to function effectively for CBS, especially if supported by an improved patient registration system with shared unique health identifiers.

Background Tanzania is a high HIV burden country in Sub-Saharan Africa with 1.5 million people infected. Unless monitored and responded to, low levels of retention in care may lead to poor HIV associated clinical outcomes and an increased likelihood of onward viral transmission. Using routine data, we assessed changes in retention in care and on treatment for HIV over time in Tanzanian facilities, using the national care and treatment programme (CTC) database. Methods Data were extracted from the CTC database and analysed using two approaches: a series of cross-sectional analyses for each calendar year between 2008 and 2016 to assess the changing characteristics of the population in care and on treatment, and, a longitudinal analysis using survival analysis methods for a series of cohorts representing i) all engaging in care and ii) all initiating treatment in each calendar year from 2008 to 2015. Multivariate analyses were carried out to explore the independent effect of calendar year when controlling for other factors. Results The total number of individuals enrolled in care increased from 160 268 in 2008 to 548 296 in 2016. The percentage of the in-care population enrolled for more than 3 years increased from 9.9% in 2008 to 54.5% in 2016. The overall rates of retention in care were 80.9%, 57.3% and 45.4% at 12, 24 and 36 months respectively. The rates of retention on antiretroviral therapy (ART) ART at 12, 24 and 36 months after treatment-initiation were 83.9%, 64.0% and 53.5%. There were small but statistically significant differences in the retention rates between cohorts and evidence for a significant decrease in the rates of retention in the most recent years analysed. Conclusions Data from Tanzania show that while the number of People Living with HIV (PLHIV) who were in care and monitored through the routine data system increased over time, the retention rates in care and treatment remained relatively stable. These rates were similar to other regional estimates. Systematic reviews of tracing studies indicate that mortality among those lost to follow up has decreased over time, partly underpinned by an increase in the numbers transferring between clinics. True retention rates may therefore be higher than we report here, and this underpins the need for data systems that can track patients between clinics.

BackgroundA universal health care identifier (UHID) facilitates the development of longitudinal medical records in health care settings where follow up and tracking of persons across health care sectors are needed. HIV case-based surveillance (CBS) entails longitudinal follow up of HIV cases from diagnosis, linkage to care and treatment, and is recommended for second generation HIV surveillance. In the absence of a UHID, records matching, linking, and deduplication may be done using score-based persons matching algorithms. We present a stepwise process of score-based persons matching algorithms based on demographic data to improve HIV CBS and other longitudinal data systems.ObjectiveThe aim of this study is to compare deterministic and score-based persons matching algorithms in records linkage and matching using demographic data in settings without a UHID.MethodsWe used HIV CBS pilot data from 124 facilities in 2 high HIV-burden counties (Siaya and Kisumu) in western Kenya. For efficient processing, data were grouped into 3 scenarios within (1) HIV testing services (HTS), (2) HTS-care, and (3) within care. In deterministic matching, we directly compared identifiers and pseudo-identifiers from medical records to determine matches. We used R stringdist package for Jaro, Jaro-Winkler score-based matching and Levenshtein, and Damerau-Levenshtein string edit distance calculation methods. For the Jaro-Winkler method, we used a penalty (р)=0.1 and applied 4 weights (ω) to Levenshtein and Damerau-Levenshtein: deletion ω=0.8, insertion ω=0.8, substitutions ω=1, and transposition ω=0.5.ResultsWe abstracted 12,157 cases of which 4073/12,157 (33.5%) were from HTS, 1091/12,157 (9.0%) from HTS-care, and 6993/12,157 (57.5%) within care. Using the deterministic process 435/12,157 (3.6%) duplicate records were identified, yielding 96.4% (11,722/12,157) unique cases. Overall, of the score-based methods, Jaro-Winkler yielded the most duplicate records (686/12,157, 5.6%) while Jaro yielded the least duplicates (546/12,157, 4.5%), and Levenshtein and Damerau-Levenshtein yielded 4.6% (563/12,157) duplicates. Specifically, duplicate records yielded by method were: (1) Jaro 5.7% (234/4073) within HTS, 0.4% (4/1091) in HTS-care, and 4.4% (308/6993) within care, (2) Jaro-Winkler 7.4% (302/4073) within HTS, 0.5% (6/1091) in HTS-care, and 5.4% (378/6993) within care, (3) Levenshtein 6.4% (262/4073) within HTS, 0.4% (4/1091) in HTS-care, and 4.2% (297/6993) within care, and (4) Damerau-Levenshtein 6.4% (262/4073) within HTS, 0.4% (4/1091) in HTS-care, and 4.2% (297/6993) within care.ConclusionsWithout deduplication, over reporting occurs across the care and treatment cascade. Jaro-Winkler score-based matching performed the best in identifying matches. A pragmatic estimate of duplicates in health care settings can provide a corrective factor for modeled estimates, for targeting and program planning. We propose that even without a UHID, standard national deduplication and persons-matching algorithm that utilizes demographic data would improve a...