The Last Mile: Use of Innovative Technologies to Attain the UNAIDS 90-90-90 Target

Thesis (Ph.D.)--University of Washington, 2019Introduction Multiple interventions and concerted efforts have led to an overall decline in the incidence of HIV. Despite these gains, new challenges emerge in sustaining the momentum of the fight against HIV. These challenges all call for creative approaches in enhancing implementation of the HIV care cascade to sustain the momentum and safeguard the gains made thus far. Linkage to care following HIV testing and counselling is a critical initial step in the HIV care cascade. However, lack of a unique patient identifier within HIV care services limits utilization of routine programme data due to inaccuracies associated with patient misidentification. e.g. use of testing data to obtain HIV incidence. Attainment and maintenance of viral suppression is the goal of the HIV care cascade. Type 2 diabetes (T2D), as a co-morbidity could affect viral suppression by reduced medication and clinical appointment adherence. With a high prevalence of HIV and an excess risk of T2D in PLHIV, prediabetes is an important target for screening and primary prevention in Sub-Saharan Africa. Methods In the first study, we evaluated feasibility and acceptance of an iris scan biometric system for unique patient identification integrated within the routine HIV care clinics in 4 centres in Kenya. All patients were offered the iris scanning and chose to opt-out. They would then proceed with their routine clinic services. In the second study, we evaluated the prevalence and risk factors for T2D and prediabetes in 2 centres in Central Kenya, using point of care HbA1c and 2nd confirmatory test as per ADA guidelines. We also conducted a budget impact analysis on the cost and affordability of integrating this screening within routine HIV care services. For this, we compared universal screening vs risk-based screening, targeting people with hypertension and obesity. Results For unique identification, we offered biometric scanning to 8,794 unique people and a total of 14,942 scans issued an ID. About 1% of people approached refused to have their iris scanned, often due to privacy and confidentiality concerns. The system sensitivity was 94.7%. The system’s limitation to issuing an ID was lack of internet connectivity. Time taken for the scanning and demographic profiling process was 3.5 min and this improved with time. For HbA1c, among 600 participants, we observed an overall prevalence of 5% and newly diagnosed prevalence of 3.4% for T2D. The prevalence of prediabetes was 14.2%. Risk factors for hyperglycemia were age, familial history, hypertension, central adiposity and combination of Tenofovir/Efavirenz. The unit cost of screening using HbA1c was 2018 USD ($) 42, and a confirmatory test was$6. Risk-based screening was slightly cost-efficient: the unit cost of identifying and confirming T2D per person was $892, needing to screen 21 people to identify one person with T2D, compared to universal screening at$ 1,705 and screening 25 people. Main drivers for unit costs were personnel and reagent costs. Conclusion Iris biometrics scanning is a feasible and highly acceptable among newly tested positive and PLHIV already engaged in care as a unique identifier and can be integrated with existing EMR systems for program implementation and scale-up. Screening for diabetes and prediabetes using POC HbA1c was feasible and showed a high prevalence of prediabetes, a modifiable risk factor for T2D and other cardiovascular conditions. It is also affordable if it were to be integrated within the HIV care program in Central Kenya, more so if it were risk-based. Innovative technologies (iris biometric scanning, point of care HbA1c devices) can therefore be integrated within routine service delivery among PLHIV to improve the HIV care cascade, bring us closer to the end of the epidemic

Characterization of long COVID temporal sub-phenotypes by distributed representation learning from electronic health record data: a cohort studyResearch in Context

Summary: Background: Characterizing Post-Acute Sequelae of COVID (SARS-CoV-2 Infection), or PASC has been challenging due to the multitude of sub-phenotypes, temporal attributes, and definitions. Scalable characterization of PASC sub-phenotypes can enhance screening capacities, disease management, and treatment planning. Methods: We conducted a retrospective multi-centre observational cohort study, leveraging longitudinal electronic health record (EHR) data of 30,422 patients from three healthcare systems in the Consortium for the Clinical Characterization of COVID-19 by EHR (4CE). From the total cohort, we applied a deductive approach on 12,424 individuals with follow-up data and developed a distributed representation learning process for providing augmented definitions for PASC sub-phenotypes. Findings: Our framework characterized seven PASC sub-phenotypes. We estimated that on average 15.7% of the hospitalized COVID-19 patients were likely to suffer from at least one PASC symptom and almost 5.98%, on average, had multiple symptoms. Joint pain and dyspnea had the highest prevalence, with an average prevalence of 5.45% and 4.53%, respectively. Interpretation: We provided a scalable framework to every participating healthcare system for estimating PASC sub-phenotypes prevalence and temporal attributes, thus developing a unified model that characterizes augmented sub-phenotypes across the different systems. Funding: Authors are supported by National Institute of Allergy and Infectious Diseases, National Institute on Aging, National Center for Advancing Translational Sciences, National Medical Research Council, National Institute of Neurological Disorders and Stroke, European Union, National Institutes of Health, National Center for Advancing Translational Sciences

Clinical phenotypes and outcomes in children with multisystem inflammatory syndrome across SARS-CoV-2 variant eras: a multinational study from the 4CE consortiumResearch in context

Summary: Background: Multisystem inflammatory syndrome in children (MIS-C) is a severe complication of SARS-CoV-2 infection. It remains unclear how MIS-C phenotypes vary across SARS-CoV-2 variants. We aimed to investigate clinical characteristics and outcomes of MIS-C across SARS-CoV-2 eras. Methods: We performed a multicentre observational retrospective study including seven paediatric hospitals in four countries (France, Spain, U.K., and U.S.). All consecutive confirmed patients with MIS-C hospitalised between February 1st, 2020, and May 31st, 2022, were included. Electronic Health Records (EHR) data were used to calculate pooled risk differences (RD) and effect sizes (ES) at site level, using Alpha as reference. Meta-analysis was used to pool data across sites. Findings: Of 598 patients with MIS-C (61% male, 39% female; mean age 9.7 years [SD 4.5]), 383 (64%) were admitted in the Alpha era, 111 (19%) in the Delta era, and 104 (17%) in the Omicron era. Compared with patients admitted in the Alpha era, those admitted in the Delta era were younger (ES −1.18 years [95% CI −2.05, −0.32]), had fewer respiratory symptoms (RD −0.15 [95% CI −0.33, −0.04]), less frequent non-cardiogenic shock or systemic inflammatory response syndrome (SIRS) (RD −0.35 [95% CI −0.64, −0.07]), lower lymphocyte count (ES −0.16 × 109/uL [95% CI −0.30, −0.01]), lower C-reactive protein (ES −28.5 mg/L [95% CI −46.3, −10.7]), and lower troponin (ES −0.14 ng/mL [95% CI −0.26, −0.03]). Patients admitted in the Omicron versus Alpha eras were younger (ES −1.6 years [95% CI −2.5, −0.8]), had less frequent SIRS (RD −0.18 [95% CI −0.30, −0.05]), lower lymphocyte count (ES −0.39 × 109/uL [95% CI −0.52, −0.25]), lower troponin (ES −0.16 ng/mL [95% CI −0.30, −0.01]) and less frequently received anticoagulation therapy (RD −0.19 [95% CI −0.37, −0.04]). Length of hospitalization was shorter in the Delta versus Alpha eras (−1.3 days [95% CI −2.3, −0.4]). Interpretation: Our study suggested that MIS-C clinical phenotypes varied across SARS-CoV-2 eras, with patients in Delta and Omicron eras being younger and less sick. EHR data can be effectively leveraged to identify rare complications of pandemic diseases and their variation over time. Funding: None