ArticleJournal of acquired immune deficiency syndromes (1999)2014
Tracing of patients lost to follow-up and HIV transmission: mathematical modeling study based on 2 large ART programs in Malawi.
Article in Journal of acquired immune deficiency syndromes (1999), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Who does tracing work for? Characteristics of clients successfully re-engaged in ART care in sub-Saharan Africa after a tracing intervention: A systematic review.PLOS global public health · 2026Article
- How much does it cost to retain clients on antiretroviral treatment for one year in a large, public clinic? Routine financial costs of retention interventions at Lighthouse Trust in Lilongwe, Malawi.BMC research notes · 2025Article
- Centering healthcare workers in digital health design: Usability and acceptability of two-way texting to improve retention in antiretroviral therapy in a public HIV clinic in Lilongwe, Malawi.PLOS digital health · 2024Article
- How much does it cost to retain antiretroviral therapy (ART) clients in care? Routine financial costs of retention interventions at Lighthouse Trust's Martin Preuss Centre (MPC) in Lilongwe, Malawi.Research square · 2023Article
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- Centering healthcare workers in developing digital health interventions: usability and acceptability of a two-way texting retention intervention in a public HIV clinic in Lilongwe, Malawi.medRxiv : the preprint server for health sciences · 2023Article
- Incidence and predictors of loss to follow-up among adult HIV-infected patients taking antiretroviral therapy at North Shewa zone public Hospitals, Northeast Ethiopia: A retrospective follow-up study.African health sciences · 2022Article
- Time Until Loss to Follow-Up, Incidence, and Predictors Among Adults Taking ART at Public Hospitals in Southern Ethiopia.HIV/AIDS (Auckland, N.Z.) · 2021Article
- The role of HIV viral load in mathematical models of HIV transmission and treatment: a review.BMJ global health · 2020Review
- Economic and public health impact of decentralized HIV viral load testing: A modelling study in Kenya.PloS one · 2019Article
- Incidence and predictors of loss to follow up among HIV-infected adults at Pawi General Hospital, northwest Ethiopia: competing risk regression model.BMC research notes · 2018Article
- The Effect of Monitoring Viral Load and Tracing Patients Lost to Follow-up on the Course of the HIV Epidemic in Malawi: A Mathematical Model.Open forum infectious diseases · 2018Article
- Twelve-year mortality in adults initiating antiretroviral therapy in South Africa.Journal of the International AIDS Society · 2017Article
- The need for second-line antiretroviral therapy in adults in sub-Saharan Africa up to 2030: a mathematical modelling study.The lancet. HIV · 2016Article
- Predictors of dropout from care among HIV-infected patients initiating antiretroviral therapy at a public sector HIV treatment clinic in sub-Saharan Africa.BMC infectious diseases · 2016Article
- Prospects for HIV control in South Africa: a model-based analysis.Global health action · 2016Article
- Impact and Cost-Effectiveness of Hypothetical Strategies to Enhance Retention in Care within HIV Treatment Programs in East Africa.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2015Article
- gems: An R Package for Simulating from Disease Progression Models.Journal of statistical software · 2015Article
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Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
objectiveTreatment as prevention depends on retaining HIV-infected patients in care. We investigated the effect on HIV transmission of bringing patients lost to follow-up (LTFU) back into care.
designMathematical model.
methodsStochastic mathematical model of cohorts of 1000 HIV-infected patients on antiretroviral therapy, based on the data from 2 clinics in Lilongwe, Malawi. We calculated cohort viral load (sum of individual mean viral loads each year) and used a mathematical relationship between viral load and transmission probability to estimate the number of new HIV infections. We simulated 4 scenarios: "no LTFU" (all patients stay in care), "no tracing" (patients LTFU are not traced), "immediate tracing" (after missed clinic appointment), and "delayed tracing" (after 6 months).
resultsAbout 440 of 1000 patients were LTFU over 5 years. Cohort viral loads (million copies/mL per 1000 patients) were 3.7 [95% prediction interval (PrI), 2.9-4.9] for no LTFU, 8.6 (95% PrI, 7.3-10.0) for no tracing, 7.7 (95% PrI, 6.2-9.1) for immediate, and 8.0 (95% PrI, 6.7-9.5) for delayed tracing. Comparing no LTFU with no tracing, the number of new infections increased from 33 (95% PrI, 29-38) to 54 (95% PrI, 47-60) per 1000 patients. Immediate tracing prevented 3.6 (95% PrI, -3.3 to 12.8) and delayed tracing 2.5 (95% PrI, -5.8 to 11.1) new infections per 1000. Immediate tracing was more efficient than delayed tracing: to 116 and 142 tracing efforts, respectively, were needed prevent 1 new infection.
conclusionsTracing of patients LTFU enhances the preventive effect of antiretroviral therapy, but the number of transmissions prevented is small.
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