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Cholette F, Lazarus L, Macharia P, Thompson LH, Githaiga S, Mathenge J, Walimbwa J, Kuria I, Okoth S, Wambua S, Albert H, Mwangi P, Adhiambo J, Kasiba R, Juma E, Battacharjee P, Kimani J, Sandstrom P, Meyers AFA, Joy JB, Thomann M, McLaren PJ, Shaw S, Mishra S, Becker ML, McKinnon L, Lorway R. Community Insights in Phylogenetic HIV Research: The CIPHR Project Protocol. Glob Public Health 2023; 18:2269435. [PMID: 37851872 DOI: 10.1080/17441692.2023.2269435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 10/04/2023] [Indexed: 10/20/2023]
Abstract
Inferring HIV transmission networks from HIV sequences is gaining popularity in the field of HIV molecular epidemiology. However, HIV sequences are often analyzed at distance from those affected by HIV epidemics, namely without the involvement of communities most affected by HIV. These remote analyses often mean that knowledge is generated in absence of lived experiences and socio-economic realities that could inform the ethical application of network-derived information in 'real world' programmes. Procedures to engage communities are noticeably absent from the HIV molecular epidemiology literature. Here we present our team's protocol for engaging community activists living in Nairobi, Kenya in a knowledge exchange process - The CIPHR Project (Community Insights in Phylogenetic HIV Research). Drawing upon a community-based participatory approach, our team will (1) explore the possibilities and limitations of HIV molecular epidemiology for key population programmes, (2) pilot a community-based HIV molecular study, and (3) co-develop policy guidelines on conducting ethically safe HIV molecular epidemiology. Critical dialogue with activist communities will offer insight into the potential uses and abuses of using such information to sharpen HIV prevention programmes. The outcome of this process holds importance to the development of policy frameworks that will guide the next generation of the global response.
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Affiliation(s)
- François Cholette
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Canada
- Sexually Transmitted and Blood-Borne Infections, National Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, Canada
| | - Lisa Lazarus
- Institute for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Canada
| | - Pascal Macharia
- Health Options for Young Men on HIV/AIDS and STIs (HOYMAS), Nairobi, Kenya
| | - Laura H Thompson
- Sexually Transmitted and Blood-Borne Infections Surveillance Division, Centre for Communicable Diseases and Infection Control, Public Health Agency of Canada, Ottawa, Canada
| | - Samuel Githaiga
- Health Options for Young Men on HIV/AIDS and STIs (HOYMAS), Nairobi, Kenya
| | - John Mathenge
- Health Options for Young Men on HIV/AIDS and STIs (HOYMAS), Nairobi, Kenya
| | | | - Irene Kuria
- Key Population Consortium of Kenya, Nairobi, Kenya
| | - Silvia Okoth
- Bar Hostess Empowerment and Support Programme, Nairobi, Kenya
| | | | - Harrison Albert
- Health Options for Young Men on HIV/AIDS and STIs (HOYMAS), Nairobi, Kenya
| | - Peninah Mwangi
- Bar Hostess Empowerment and Support Programme, Nairobi, Kenya
| | - Joyce Adhiambo
- Partners for Health Development in Africa (PHDA), Nairobi, Kenya
- Sex Worker Outreach Programme (SWOP), Nairobi, Kenya
| | | | - Esther Juma
- Sex Worker Outreach Programme (SWOP), Nairobi, Kenya
| | | | - Joshua Kimani
- Sex Worker Outreach Programme (SWOP), Nairobi, Kenya
- Department of Medical Microbiology, University of Nairobi, Nairobi, Kenya
| | - Paul Sandstrom
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Canada
- Sexually Transmitted and Blood-Borne Infections, National Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, Canada
| | - Adrienne F A Meyers
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Canada
- Sexually Transmitted and Blood-Borne Infections, National Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, Canada
| | - Jeffrey B Joy
- British Columbia Centre for Excellence in HIV/AIDS (BCCfE), St. Paul's Hospital, Vancouver, Canada
- Division of Infectious Diseases, Department of Medicine, University of British Columbia, Vancouver, Canada
- Bioinformatics Programme, University of British Columbia, Vancouver, Canada
| | - Matthew Thomann
- Department of Anthropology, University of Maryland, College Park, MD, USA
| | - Paul J McLaren
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Canada
- Sexually Transmitted and Blood-Borne Infections, National Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, Canada
| | - Souradet Shaw
- Institute for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Canada
| | - Sharmistha Mishra
- MAP Centre for Urban Health Solutions, St. Michael's Hospital, Toronto, Canada
- Department of Medicine, University of Toronto, Toronto, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
| | - Marissa L Becker
- Institute for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Canada
| | - Lyle McKinnon
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Canada
- Department of Medical Microbiology, University of Nairobi, Nairobi, Kenya
- Centre for the AIDS Programme of Research in South Africa, Durban, South Africa
| | - Robert Lorway
- Institute for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Canada
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Stockdale JE, Liu P, Colijn C. The potential of genomics for infectious disease forecasting. Nat Microbiol 2022; 7:1736-1743. [PMID: 36266338 DOI: 10.1038/s41564-022-01233-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 08/18/2022] [Indexed: 11/09/2022]
Abstract
Genomic technologies have led to tremendous gains in understanding how pathogens function, evolve and interact. Pathogen diversity is now measurable at high precision and resolution, in part because over the past decade, sequencing technologies have increased in speed and capacity, at decreased cost. Alongside this, the use of models that can forecast emergence and size of infectious disease outbreaks has risen, highlighted by the coronavirus disease 2019 pandemic but also due to modelling advances that allow for rapid estimates in emerging outbreaks to inform monitoring, coordination and resource deployment. However, genomics studies have remained largely retrospective. While they contain high-resolution views of pathogen diversification and evolution in the context of selection, they are often not aligned with designing interventions. This is a missed opportunity because pathogen diversification is at the core of the most pressing infectious public health challenges, and interventions need to take the mechanisms of virulence and understanding of pathogen diversification into account. In this Perspective, we assess these converging fields, discuss current challenges facing both surveillance specialists and modellers who want to harness genomic data, and propose next steps for integrating longitudinally sampled genomic data with statistical learning and interpretable modelling to make reliable predictions into the future.
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Affiliation(s)
- Jessica E Stockdale
- Department of Mathematics, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Pengyu Liu
- Department of Mathematics, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Caroline Colijn
- Department of Mathematics, Simon Fraser University, Burnaby, British Columbia, Canada.
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Young C, Meng S, Moshiri N. An Evaluation of Phylogenetic Workflows in Viral Molecular Epidemiology. Viruses 2022; 14:v14040774. [PMID: 35458504 PMCID: PMC9032411 DOI: 10.3390/v14040774] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 04/04/2022] [Accepted: 04/06/2022] [Indexed: 01/25/2023] Open
Abstract
The use of viral sequence data to inform public health intervention has become increasingly common in the realm of epidemiology. Such methods typically utilize multiple sequence alignments and phylogenies estimated from the sequence data. Like all estimation techniques, they are error prone, yet the impacts of such imperfections on downstream epidemiological inferences are poorly understood. To address this, we executed multiple commonly used viral phylogenetic analysis workflows on simulated viral sequence data, modeling Human Immunodeficiency Virus (HIV), Hepatitis C Virus (HCV), and Ebolavirus, and we computed multiple methods of accuracy, motivated by transmission-clustering techniques. For multiple sequence alignment, MAFFT consistently outperformed MUSCLE and Clustal Omega, in both accuracy and runtime. For phylogenetic inference, FastTree 2, IQ-TREE, RAxML-NG, and PhyML had similar topological accuracies, but branch lengths and pairwise distances were consistently most accurate in phylogenies inferred by RAxML-NG. However, FastTree 2 was the fastest, by orders of magnitude, and when the other tools were used to optimize branch lengths along a fixed FastTree 2 topology, the resulting phylogenies had accuracies that were indistinguishable from their original counterparts, but with a fraction of the runtime.
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Miller RL, McLaughlin A, Liang RH, Harding J, Wong J, Le AQ, Brumme CJ, Montaner JSG, Joy JB. Phylogenetic prioritization of HIV-1 transmission clusters with viral lineage-level diversification rates. Evol Med Public Health 2022; 10:305-315. [PMID: 35899097 PMCID: PMC9311310 DOI: 10.1093/emph/eoac026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 07/07/2022] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background and objectives
Public health officials faced with a large number of transmission clusters require a rapid, scalable and unbiased way to prioritize distribution of limited resources to maximize benefits. We hypothesize that transmission cluster prioritization based on phylogenetically derived lineage-level diversification rates will perform as well as or better than commonly used growth-based prioritization measures, without need for historical data or subjective interpretation.
Methodology
9822 HIV pol sequences collected during routine drug resistance genotyping were used alongside simulated sequence data to infer sets of phylogenetic transmission clusters via patristic distance threshold. Prioritized clusters inferred from empirical data were compared to those prioritized by the current public health protocols. Prioritization of simulated clusters was evaluated based on correlation of a given prioritization measure with future cluster growth, as well as the number of direct downstream transmissions from cluster members.
Results
Empirical data suggest diversification rate-based measures perform comparably to growth-based measures in recreating public heath prioritization choices. However, unbiased simulated data reveals phylogenetic diversification rate-based measures perform better in predicting future cluster growth relative to growth-based measures, particularly long-term growth. Diversification rate-based measures also display advantages over growth-based measures in highlighting groups with greater future transmission events compared to random groups of the same size. Furthermore, diversification rate measures were notably more robust to effects of decreased sampling proportion.
Conclusions and implications
Our findings indicate diversification rate-based measures frequently outperform growth-based measures in predicting future cluster growth and offer several additional advantages beneficial to optimizing the public health prioritization process.
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Affiliation(s)
- Rachel L Miller
- Molecular Epidemiology and Evolutionary Genetics, British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada
- Bioinformatics Program, University of British Columbia, Vancouver, Canada
| | - Angela McLaughlin
- Molecular Epidemiology and Evolutionary Genetics, British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada
- Bioinformatics Program, University of British Columbia, Vancouver, Canada
| | - Richard H Liang
- Laboratory Program, British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada
| | | | - Jason Wong
- Clinical Prevention Services, British Columbia Centre for Disease Control, Vancouver, Canada
| | - Anh Q Le
- Laboratory Program, British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada
| | - Chanson J Brumme
- Laboratory Program, British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada
- Department of Medicine, University of British Columbia, Vancouver, Canada
| | - Julio S G Montaner
- Department of Medicine, University of British Columbia, Vancouver, Canada
- British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada
| | - Jeffrey B Joy
- Corresponding author. Molecular Epidemiology and Evolutionary Genetics, BC Centre for Excellence in HIV/AIDS, 615-1033 Davie St, Vancouver, BC, V6E 1M5, Canada. Tel: +1-(604)-368-5569; E-mail:
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