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Kupperman MD, Ke R, Leitner T. Identifying Impacts of Contact Tracing on Epidemiological Inference from Phylogenetic Data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.30.567148. [PMID: 38076930 PMCID: PMC10705478 DOI: 10.1101/2023.11.30.567148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
Robust sampling methods are foundational to inferences using phylogenies. Yet the impact of using contact tracing, a type of non-uniform sampling used in public health applications such as infectious disease outbreak investigations, has not been investigated in the molecular epidemiology field. To understand how contact tracing influences a recovered phylogeny, we developed a new simulation tool called SEEPS (Sequence Evolution and Epidemiological Process Simulator) that allows for the simulation of contact tracing and the resulting transmission tree, pathogen phylogeny, and corresponding virus genetic sequences. Importantly, SEEPS takes within-host evolution into account when generating pathogen phylogenies and sequences from transmission histories. Using SEEPS, we demonstrate that contact tracing can significantly impact the structure of the resulting tree, as described by popular tree statistics. Contact tracing generates phylogenies that are less balanced than the underlying transmission process, less representative of the larger epidemiological process, and affects the internal/external branch length ratios that characterize specific epidemiological scenarios. We also examined real data from a 2007-2008 Swedish HIV-1 outbreak and the broader 1998-2010 European HIV-1 epidemic to highlight the differences in contact tracing and expected phylogenies. Aided by SEEPS, we show that the data collection of the Swedish outbreak was strongly influenced by contact tracing even after downsampling, while the broader European Union epidemic showed little evidence of universal contact tracing, agreeing with the known epidemiological information about sampling and spread. Overall, our results highlight the importance of including possible non-uniform sampling schemes when examining phylogenetic trees. For that, SEEPS serves as a useful tool to evaluate such impacts, thereby facilitating better phylogenetic inferences of the characteristics of a disease outbreak. SEEPS is available at github.com/MolEvolEpid/SEEPS.
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Affiliation(s)
- Michael D. Kupperman
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, New Mexico, United States of America
- Department of Applied Mathematics, University of Washington, Washington, United States of America
| | - Ruian Ke
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, New Mexico, United States of America
| | - Thomas Leitner
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, New Mexico, United States of America
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Hall M, Golubchik T, Bonsall D, Abeler-Dörner L, Limbada M, Kosloff B, Schaap A, de Cesare M, MacIntyre-Cockett G, Otecko N, Probert W, Ratmann O, Bulas Cruz A, Piwowar-Manning E, Burns DN, Cohen MS, Donnell DJ, Eshleman SH, Simwinga M, Fidler S, Hayes R, Ayles H, Fraser C. Demographics of sources of HIV-1 transmission in Zambia: a molecular epidemiology analysis in the HPTN 071 PopART study. THE LANCET. MICROBE 2024; 5:e62-e71. [PMID: 38081203 PMCID: PMC10789608 DOI: 10.1016/s2666-5247(23)00220-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 07/07/2023] [Accepted: 07/14/2023] [Indexed: 01/19/2024]
Abstract
BACKGROUND In the last decade, universally available antiretroviral therapy (ART) has led to greatly improved health and survival of people living with HIV in sub-Saharan Africa, but new infections continue to appear. The design of effective prevention strategies requires the demographic characterisation of individuals acting as sources of infection, which is the aim of this study. METHODS Between 2014 and 2018, the HPTN 071 PopART study was conducted to quantify the public health benefits of ART. Viral samples from 7124 study participants in Zambia were deep-sequenced as part of HPTN 071-02 PopART Phylogenetics, an ancillary study. We used these sequences to identify likely transmission pairs. After demographic weighting of the recipients in these pairs to match the overall HIV-positive population, we analysed the demographic characteristics of the sources to better understand transmission in the general population. FINDINGS We identified a total of 300 likely transmission pairs. 178 (59·4%) were male to female, with 130 (95% CI 110-150; 43·3%) from males aged 25-40 years. Overall, men transmitted 2·09-fold (2·06-2·29) more infections per capita than women, a ratio peaking at 5·87 (2·78-15·8) in the 35-39 years source age group. 40 (26-57; 13·2%) transmissions linked individuals from different communities in the trial. Of 288 sources with recorded information on drug resistance mutations, 52 (38-69; 18·1%) carried viruses resistant to first-line ART. INTERPRETATION HIV-1 transmission in the HPTN 071 study communities comes from a wide range of age and sex groups, and there is no outsized contribution to new infections from importation or drug resistance mutations. Men aged 25-39 years, underserved by current treatment and prevention services, should be prioritised for HIV testing and ART. FUNDING National Institute of Allergy and Infectious Diseases, US President's Emergency Plan for AIDS Relief, International Initiative for Impact Evaluation, Bill & Melinda Gates Foundation, National Institute on Drug Abuse, and National Institute of Mental Health.
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Affiliation(s)
- Matthew Hall
- Pandemic Sciences Institute and Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Tanya Golubchik
- Pandemic Sciences Institute and Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK; Sydney Infectious Diseases Institute, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - David Bonsall
- Pandemic Sciences Institute and Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Lucie Abeler-Dörner
- Pandemic Sciences Institute and Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | | | - Barry Kosloff
- Zambart, University of Zambia, Lusaka, Zambia; Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK
| | - Ab Schaap
- Zambart, University of Zambia, Lusaka, Zambia
| | - Mariateresa de Cesare
- Pandemic Sciences Institute and Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - George MacIntyre-Cockett
- Pandemic Sciences Institute and Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Newton Otecko
- Pandemic Sciences Institute and Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - William Probert
- Pandemic Sciences Institute and Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Oliver Ratmann
- Department of Mathematics, Imperial College London, London, UK
| | - Ana Bulas Cruz
- Pandemic Sciences Institute and Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | | | - David N Burns
- Division of AIDS, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD, USA
| | - Myron S Cohen
- Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - Susan H Eshleman
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | | | - Sarah Fidler
- Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Richard Hayes
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Helen Ayles
- Zambart, University of Zambia, Lusaka, Zambia; Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK
| | - Christophe Fraser
- Pandemic Sciences Institute and Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
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Pickles M, Gregson S, Moorhouse L, Dadirai T, Dzamatira F, Mandizvidza P, Maswera R, Museka T, Schaefer R, Skovdal M, Thomas R, Tsenesa B, Mugurungi O, Nyamukapa C, Hallett TB. Strengthening the HIV prevention cascade to maximise epidemiological impact in eastern Zimbabwe: a modelling study. Lancet Glob Health 2023; 11:e1105-e1113. [PMID: 37349036 DOI: 10.1016/s2214-109x(23)00206-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 04/19/2023] [Accepted: 04/19/2023] [Indexed: 06/24/2023]
Abstract
BACKGROUND HIV prevention cascades provide a systematic understanding of barriers to prevention. In this study we used mathematical modelling to understand the consequences of these barriers and how the cascade could be strengthened to maximise epidemiological impact, providing potentially important insights for programmes. METHODS We used an individual-based model of HIV transmission (PopART-IBM), calibrated to data from the Manicaland cohort from eastern Zimbabwe. HIV prevention cascade estimates from this cohort were used as probabilities for indicators in the model representing an individual's motivation, access, and capacity to effectively use pre-exposure prophylaxis, voluntary male medical circumcision, and condoms. We examined how current barriers affect the number and distribution of HIV infections compared with a no-barrier scenario. Using assumptions about how interventions could strengthen the HIV prevention cascade, we estimated the reduction in HIV infections over a 10-year period through addressing different elements of the cascade. FINDINGS 21 200 new potentially avertable HIV infections will occur over the next 10 years due to existing HIV prevention cascade barriers, 74·2% of the 28 500 new infections that would occur with existing barriers in a population of approximately 1·2 million adults. Removing these barriers would reduce HIV incidence below the benchmarks for epidemic elimination. Addressing all cascade steps in one priority population is substantially more effective than addressing one step across all populations. INTERPRETATION Interventions exist in eastern Zimbabwe to reduce HIV towards elimination, but barriers of motivation, access, and effective use prevent their full effect being realised. Interventions need to be multilayered and address all steps along the HIV prevention cascade. Models incorporating the HIV prevention cascade can help to identify the main barriers to greater effectiveness. FUNDING National Institutes of Mental Health, Bill & Melinda Gates Foundation, and Medical Research Council Centre for Global Infectious Disease Analysis funding from the UK Medical Research Council and UK Foreign, Commonwealth & Development Office (FCDO).
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Affiliation(s)
- Michael Pickles
- Medical Research Council Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK.
| | - Simon Gregson
- Medical Research Council Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK; Biomedical and Research Training Institute, Harare, Zimbabwe
| | - Louisa Moorhouse
- Medical Research Council Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
| | - Tawanda Dadirai
- Biomedical and Research Training Institute, Harare, Zimbabwe
| | | | | | | | - Tafadzwa Museka
- Biomedical and Research Training Institute, Harare, Zimbabwe
| | - Robin Schaefer
- Medical Research Council Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
| | - Morten Skovdal
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Ranjeeta Thomas
- Department of Health Policy, London School of Economics and Political Science, London, UK
| | | | | | - Constance Nyamukapa
- Medical Research Council Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK; Biomedical and Research Training Institute, Harare, Zimbabwe
| | - Timothy B Hallett
- Medical Research Council Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
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Probert WJM, Sauter R, Pickles M, Cori A, Bell-Mandla NF, Bwalya J, Abeler-Dörner L, Bock P, Donnell DJ, Floyd S, Macleod D, Piwowar-Manning E, Skalland T, Shanaube K, Wilson E, Yang B, Ayles H, Fidler S, Hayes RJ, Fraser C. Projected outcomes of universal testing and treatment in a generalised HIV epidemic in Zambia and South Africa (the HPTN 071 [PopART] trial): a modelling study. Lancet HIV 2022; 9:e771-e780. [PMID: 36332654 PMCID: PMC9646978 DOI: 10.1016/s2352-3018(22)00259-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 09/06/2022] [Accepted: 09/07/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND The long-term impact of universal home-based testing and treatment as part of universal testing and treatment (UTT) on HIV incidence is unknown. We made projections using a detailed individual-based model of the effect of the intervention delivered in the HPTN 071 (PopART) cluster-randomised trial. METHODS In this modelling study, we fitted an individual-based model to the HIV epidemic and HIV care cascade in 21 high prevalence communities in Zambia and South Africa that were part of the PopART cluster-randomised trial (intervention period Nov 1, 2013, to Dec 31, 2017). The model represents coverage of home-based testing and counselling by age and sex, delivered as part of the trial, antiretroviral therapy (ART) uptake, and any changes in national guidelines on ART eligibility. In PopART, communities were randomly assigned to one of three arms: arm A received the full PopART intervention for all individuals who tested positive for HIV, arm B received the intervention with ART provided in accordance with national guidelines, and arm C received standard of care. We fitted the model to trial data twice using Approximate Bayesian Computation, once before data unblinding and then again after data unblinding. We compared projections of intervention impact with observed effects, and for four different scenarios of UTT up to Jan 1, 2030 in the study communities. FINDINGS Compared with standard of care, a 51% (95% credible interval 40-60) reduction in HIV incidence is projected if the trial intervention (arms A and B combined) is continued from 2020 to 2030, over and above a declining trend in HIV incidence under standard of care. INTERPRETATION A widespread and continued commitment to UTT via home-based testing and counselling can have a substantial effect on HIV incidence in high prevalence communities. FUNDING National Institute of Allergy and Infectious Diseases, US President's Emergency Plan for AIDS Relief, International Initiative for Impact Evaluation, Bill & Melinda Gates Foundation, National Institute on Drug Abuse, and National Institute of Mental Health.
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Affiliation(s)
- William J M Probert
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
| | - Rafael Sauter
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Michael Pickles
- Medical Research Council Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
| | - Anne Cori
- Medical Research Council Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
| | - Nomtha F Bell-Mandla
- Desmond Tutu TB Centre, Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | | | - Lucie Abeler-Dörner
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Peter Bock
- Desmond Tutu TB Centre, Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | | | - Sian Floyd
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - David Macleod
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | | | | | | | - Ethan Wilson
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Blia Yang
- Desmond Tutu TB Centre, Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Helen Ayles
- Zambart, University of Zambia, Lusaka, Zambia; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Sarah Fidler
- Department of Infectious Disease, Imperial College London, London, UK; NIHR Imperial Biomedical Research Centre, London, UK
| | - Richard J Hayes
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Christophe Fraser
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
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Nguyen A, Drabo EF, Garland WH, Moucheraud C, Holloway IW, Leibowitz A, Suen SC. Are Unequal Policies in Pre-Exposure Prophylaxis Uptake Needed to Improve Equality? An Examination Among Men Who Have Sex with Men in Los Angeles County. AIDS Patient Care STDS 2022; 36:300-312. [PMID: 35951446 PMCID: PMC9419964 DOI: 10.1089/apc.2022.0011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
Racial and ethnic minority men who have sex with men (MSM) are disproportionately affected by HIV/AIDS in Los Angeles County (LAC), an important epicenter in the battle to end HIV. We examine tradeoffs between effectiveness and equality of pre-exposure prophylaxis (PrEP) allocation strategies among different racial and ethnic groups of MSM in LAC and provide a framework for quantitatively evaluating disparities in HIV outcomes. To do this, we developed a microsimulation model of HIV among MSM in LAC using county epidemic surveillance and survey data to capture demographic trends and subgroup-specific partnership patterns, disease progression, patterns of PrEP use, and patterns for viral suppression. We limit analysis to MSM, who bear most of the burden of HIV/AIDS in LAC. We simulated interventions where 3000, 6000, or 9000 PrEP prescriptions are provided annually in addition to current levels, following different allocation scenarios to each racial/ethnic group (Black, Hispanic, or White). We estimated cumulative infections averted and measures of equality, after 15 years (2021-2035), relative to base case (no intervention). By comparing allocation strategies on the health equality impact plane, we find that, of the policies evaluated, targeting PrEP preferentially to Black individuals would result in the largest reductions in incidence and disparities across the equality measures we considered. This result was consistent over a range of PrEP coverage levels, demonstrating that there are "win-win" PrEP allocation strategies that do not require a tradeoff between equality and efficiency.
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Affiliation(s)
- Anthony Nguyen
- Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California Viterbi School of Engineering, Los Angeles, California, USA
| | - Emmanuel Fulgence Drabo
- Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Wendy H. Garland
- Division of HIV and STD Programs, Los Angeles County Department of Public Health, Los Angeles, California, USA
| | - Corrina Moucheraud
- Department of Health Policy and Management, University of California Los Angeles Fielding School of Public Health, Los Angeles, California, USA
| | - Ian W. Holloway
- Department of Social Welfare, University of California Los Angeles Luskin School of Public Affairs, Los Angeles, California, USA
| | - Arleen Leibowitz
- Department of Public Policy, University of California Los Angeles Luskin School of Public Affairs, Los Angeles, California, USA
| | - Sze-chuan Suen
- Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California Viterbi School of Engineering, Los Angeles, California, USA
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