What Should Health Departments Do with HIV Sequence Data?
Abstract
:1. Introduction
2. Genetic Tracking of HIV
3. Risks and Concerns of HIV Genetic Tracking
3.1. Minimal Analysis
3.1.1. Arguments in Favor of Minimal Analysis
3.1.2. Arguments Against Minimal Analysis
3.2. Transmission Dynamics Analysis
3.2.1. Arguments for Transmission Dynamic Analysis
3.2.2. Arguments against Transmission Dynamic Analysis
3.3. Documenting Historical Epidemiology
3.3.1. Arguments for Documenting Historical Epidemiology
3.3.2. Arguments against Documenting Historical Epidemiology
4. An Image of a Phylogeny-Based HIV Surveillance System
5. Ethical Aspects of Genetic Tracking of HIV Transmissions
6. Conclusions and Recommendations
Author Contributions
Funding
Conflicts of Interest
References
- CDC. Detecting and Responding to HIV Transmission Clusters—A guide for Health Departments; (ver. 2.0 draft); CDC: Atlanta, GA, USA, 2018. [Google Scholar]
- Advancing HIV Prevention Through Cluster Detection and Response. Available online: https://www.cdc.gov/hiv/pdf/programresources/guidance/cluster-outbreak/cdc-hiv-advancing-HIV-prevention-through-cluster-detection.pdf (accessed on 5 September 2020).
- Volz, E.M.; Ionides, E.; Romero-Severson, E.O.; Brandt, M.G.; Mokotoff, E.; Koopman, J.S. HIV-1 Transmission during early infection in men who have sex with men: A phylodynamic analysis. PLoS Med. 2013, 10, 1–12. [Google Scholar] [CrossRef]
- Ragonnet-Cronin, M.; Hu, Y.W.; Morris, S.R.; Sheng, Z.; Poortinga, K.; Wertheim, J.O. HIV transmission networks among transgender women in Los Angeles County, CA, USA: A phylogenetic analysis of surveillance data. Lancet HIV 2019, 6, e164–e172. [Google Scholar] [CrossRef]
- Coltart, C.E.M.; Hoppe, A.; Parker, M.; Dawson, L.; Amon, J.J.; Simwinga, M.; Geller, G.; Henderson, G.; Laeyendecker, O.; Tucker, J.D.; et al. Ethical considerations in global HIV phylogenetic research. Lancet HIV 2018, 5, e656–e666. [Google Scholar] [CrossRef]
- Dawson, L.; Benbow, N.; Fletcher, F.E.; Kassaye, S.; Killelea, A.; Latham, S.R.; Lee, L.M.; Leitner, T.; Little, S.J.; Mehta, S.R.; et al. Addressing Ethical Challenges in US-Based HIV Phylogenetic Research. J. Infect. Dis. 2020. [Google Scholar] [CrossRef] [PubMed]
- Dailey, A.F.; Hoots, B.E.; Hall, H.I.; Song, R.; Hayes, D.; Fulton, P.; Prejean, J.; Hernandez, A.L.; Koenig, L.J.; Valleroy, L.A. Vital signs: Human immunodeficiency virus testing and diagnosis delays—United States. Morb. Mortal. Wkly. Rep. 2017, 66, 1300–1306. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Shankarappa, R.; Margolick, J.B.; Gange, S.J.; Rodrigo, A.G.; Upchurch, D.; Farzadegan, H.; Gupta, P.; Rinaldo, C.R.; Learn, G.H.; He, X.; et al. Consistent viral evolutionary changes associated with the progression of human immunodeficiency virus type 1 infection. J. Virol. 1999, 73, 10489–10502. [Google Scholar] [CrossRef] [Green Version]
- McNearney, T.; Hornickova, Z.; Markham, R.; Birdwell, A.; Arens, M.; Saah, A.; Ratner, L. Relationship of human immunodeficiency virus type 1 sequence heterogeneity to stage of disease. Proc. Natl. Acad. Sci. USA 1992, 89, 10247–10251. [Google Scholar] [CrossRef] [Green Version]
- Leitner, T.; Halapi, E.; Scarlatti, G.; Rossi, P.; Albert, J.; Fenyo, E.M.; Uhlen, M. Analysis of heterogeneous viral populations by direct DNA sequencing. Biotechniques 1993, 15, 120–127. [Google Scholar]
- Romero-Severson, E.O.; Bulla, I.; Leitner, T. Phylogenetically resolving epidemiologic linkage. Proc. Natl. Acad. Sci. USA 2016, 113, 2690–2695. [Google Scholar] [CrossRef] [Green Version]
- Kosakovsky Pond, S.L.; Weaver, S.; Leigh Brown, A.J.; Wertheim, J.O. HIV-TRACE (TRAnsmission Cluster Engine): A Tool for Large Scale Molecular Epidemiology of HIV-1 and Other Rapidly Evolving Pathogens. Mol. Biol. Evol. 2018, 35, 1812–1819. [Google Scholar] [CrossRef] [Green Version]
- Oster, A.M.; Wertheim, J.O.; Hernandez, A.L.; Ocfemia, M.C.B.; Saduvala, N.; Hall, H.I. Using molecular HIV surveillance data to understand transmission between subpopulations in the United States. J. Acquir. Immune Defic. Syndr. 2015, 70, 444–451. [Google Scholar] [CrossRef] [Green Version]
- Wertheim, J.O.; Leigh Brown, A.J.; Hepler, N.L.; Mehta, S.R.; Richman, D.D.; Smith, D.M.; Kosakovsky Pond, S.L. The Global Transmission Network of HIV-1. J. Infect. Dis. 2014, 209, 304–313. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Whiteside, Y.O.; Song, R.; Wertheim, J.O.; Oster, A.M. Molecular analysis allows inference into HIV transmission among young men who have sex with men in the United States. AIDS 2015, 29, 2522. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ragonnet-Cronin, M.; Jackson, C.; Bradley-Stewart, A.; Aitken, C.; McAuley, A.; Palmateer, N.; Gunson, R.; Goldberg, D.; Milosevic, C.; Brown, A.J.L. Recent and rapid transmission of hiv among people who inject drugs in scotland revealed through phylogenetic analysis. J. Infect. Dis. 2018, 217, 1875–1882. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mutenherwa, F.; Wassenaar, D.R.; De Oliveira, T. Ethical issues associated with HIV molecular epidemiology: A qualitative exploratory study using inductive analytic approaches. BMC Med. Ethics 2019, 20, 67. [Google Scholar] [CrossRef] [PubMed]
- Mehta, S.R.; Schairer, C.; Little, S. Ethical issues in HIV phylogenetics and molecular epidemiology. Curr. Opin. HIV AIDS 2019, 14, 221–226. [Google Scholar] [CrossRef] [PubMed]
- State-by-State: HIV Laws. Available online: https://projects.propublica.org/tables/penalties.html (accessed on 21 July 2020).
- Chung, C.; Khanna, N.; Cardell, B.; Spieldenner, A.; Strub, S.; McClelland, A.; French, M.; Gagnon, M.; Guta, A. Consent and criminalisation concerns over phylogenetic analysis of surveillance data. Lancet HIV 2019, 6, E420–E421. [Google Scholar] [CrossRef] [Green Version]
- Lehman, J.S.; Carr, M.H.; Nichol, A.J.; Ruisanchez, A.; Knight, D.W.; Langford, A.E.; Gray, S.C.; Mermin, J.H. Prevalence and public health implications of state laws that criminalize potential HIV exposure in the United States. AIDS Behav. 2014, 18, 997–1006. [Google Scholar] [CrossRef] [Green Version]
- Hoppe, T. From sickness to badness: The criminalization of HIV in Michigan. Soc. Sci. Med. 2014, 101, 139–147. [Google Scholar] [CrossRef]
- Lee, L.M.; Heilig, C.M.; White, A. Ethical justification for conducting public health surveillance without patient consent. Am. J. Public Health 2012, 102, 38–44. [Google Scholar] [CrossRef]
- Wertheim, J.O.; Morris, S.; Ragonnet-Cronin, M. Consent and criminalisation concerns over phylogenetic analysis of surveillance data—Authors’ reply. Lancet HIV 2019, 6, e420–e421. [Google Scholar] [CrossRef] [Green Version]
- Ratmann, O.; Hodcroft, E.B.; Pickles, M.; Cori, A.; Hall, M.; Lycett, S.; Colijn, C.; Dearlove, B.; Didelot, X.; Frost, S.; et al. Phylogenetic tools for generalized HIV-1 epidemics: Findings from the PANGEA-HIV methods comparison. Mol. Biol. Evol. 2017, 34, 185–203. [Google Scholar] [CrossRef] [Green Version]
- Grenfell, B.T.; Pybus, O.G.; Gog, J.R.; Wood, J.L.N.; Daly, J.M.; Mumford, J.A.; Holmes, E.C. Unifying the Epidemiological and Evolutionary Dynamics of Pathogens. Science 2004, 303, 327–332. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Volz, E.M.; Kosakovsky Pond, S.L.; Ward, M.J.; Leigh Brown, A.J.; Frost, S.D.W. Phylodynamics of infectious disease epidemics. Genetics 2009, 183, 1421–1430. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Volz, E.M. Complex population dynamics and the coalescent under neutrality. Genetics 2012, 190, 187–201. [Google Scholar] [CrossRef] [Green Version]
- Stadler, T.; Kühnert, D.; Bonhoeffer, S.; Drummond, A.J. Birth-death skyline plot reveals temporal changes of epidemic spread in HIV and hepatitis C virus (HCV). Proc. Natl. Acad. Sci. USA 2013, 110, 228–233. [Google Scholar] [CrossRef] [Green Version]
- Karlsson, A.; Björkman, P.; Bratt, G.; Ekvall, H.; Gisslén, M.; Sönnerborg, A.; Mild, M.; Albert, J. Low prevalence of transmitted drug resistance in patients newly diagnosed with HIV-1 infection in sweden 2003–2010. PLoS ONE 2012, 7, e33484. [Google Scholar] [CrossRef]
- De Maio, N.; Wu, C.-H.; Wilson, D.J. SCOTTI: Efficient Reconstruction of Transmission within Outbreaks with the Structured Coalescent. PLOS Comput. Biol. 2016, 12, e1005130. [Google Scholar] [CrossRef]
- Didelot, X.; Fraser, C.; Gardy, J.; Colijn, C.; Malik, H. Genomic infectious disease epidemiology in partially sampled and ongoing outbreaks. Mol. Biol. Evol. 2017, 34, 997–1007. [Google Scholar] [CrossRef] [Green Version]
- Hall, M.; Woolhouse, M.; Rambaut, A. Epidemic reconstruction in a phylogenetics framework: Transmission trees as partitions of the node set. PLoS Comput. Biol. 2015, 11, 1004613. [Google Scholar] [CrossRef] [Green Version]
- Campbell, F.; Didelot, X.; Fitzjohn, R.; Ferguson, N.; Cori, A.; Jombart, T. outbreaker2: A modular platform for outbreak reconstruction. BMC Bioinformatics 2018, 19, 363. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Klinkenberg, D.; Backer, J.A.; Didelot, X.; Colijn, C.; Wallinga, J. Simultaneous inference of phylogenetic and transmission trees in infectious disease outbreaks. PLOS Comput. Biol. 2017, 13, e1005495. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Firestone, S.M.; Hayama, Y.; Bradhurst, R.; Yamamoto, T.; Tsutsui, T.; Stevenson, M.A. Reconstructing foot-and-mouth disease outbreaks: A methods comparison of transmission network models. Sci. Rep. 2019, 9, 4809. [Google Scholar] [CrossRef] [PubMed]
- Poon, A.F.Y.; Gustafson, R.; Daly, P.; Zerr, L.; Demlow, S.E.; Wong, J.; Woods, C.K.; Hogg, R.S.; Krajden, M.; Moore, D.; et al. Near real-time monitoring of HIV transmission hotspots from routine HIV genotyping: An implementation case study. Lancet HIV 2016, 3, e231–e238. [Google Scholar] [CrossRef] [Green Version]
- Leitner, T.; Romero-Severson, E. Phylogenetic patterns recover known HIV epidemiological relationships and reveal common transmission of multiple variants. Nat. Microbiol. 2018, 3, 983–988. [Google Scholar] [CrossRef] [PubMed]
- Leitner, T. Phylogenetics in HIV transmission: Taking within-host diversity into account. Curr. Opin. HIV AIDS 2019, 14, 181–187. [Google Scholar] [CrossRef]
- Romero-Severson, E.; Skar, H.; Bulla, I.; Albert, J.; Leitner, T. Timing and order of transmission events is not directly reflected in a pathogen phylogeny. Mol. Biol. Evol. 2014, 31, 2472–2482. [Google Scholar] [CrossRef]
- Posada, D.; Crandall, K.A. MODELTEST: Testing the model of DNA substitution. Bioinformatics 1998, 14, 817–818. [Google Scholar] [CrossRef] [Green Version]
- Bouckaert, R.; Vaughan, T.G.; Barido-Sottani, J.; Duchêne, S.; Fourment, M.; Gavryushkina, A.; Heled, J.; Jones, G.; Kühnert, D.; De Maio, N.; et al. BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis. PLOS Comput. Biol. 2019, 15, e1006650. [Google Scholar] [CrossRef] [Green Version]
- Zhang, Y.; Leitner, T.; Albert, J.; Britton, T. Inferring transmission heterogeneity using virus genealogies: Estimation and targeted prevention. PLOS Comput. Biol. 2020, 16, e1008122. [Google Scholar] [CrossRef]
Options | Benefits | Limitations |
---|---|---|
Minimal analysis | Less complex Simple interpretation Minimizes use of individual data | Underuse of resources Limited actionable information Limited resolution |
Transmission dynamic analysis | Macroscopic view of HIV transmission in sub-populations Little or no risk of identifying transmission pairs | Limited understanding of how sub-epidemics may communicate with each other Less applicable to individual transmission clusters Limited “ready to use” software options |
Documenting Historical Epidemiology | Maximum use of local HIV sequence collections Identify missing or undiagnosed persons Identify transmission risk factors Yield actionable insights | More complex, less certain Can identify direction or directness of transmission Misuse can discourage enrollment into HIV care and stigmatize populations May require computing resources beyond basic desktop computers |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Romero-Severson, E.; Nasir, A.; Leitner, T. What Should Health Departments Do with HIV Sequence Data? Viruses 2020, 12, 1018. https://doi.org/10.3390/v12091018
Romero-Severson E, Nasir A, Leitner T. What Should Health Departments Do with HIV Sequence Data? Viruses. 2020; 12(9):1018. https://doi.org/10.3390/v12091018
Chicago/Turabian StyleRomero-Severson, Ethan, Arshan Nasir, and Thomas Leitner. 2020. "What Should Health Departments Do with HIV Sequence Data?" Viruses 12, no. 9: 1018. https://doi.org/10.3390/v12091018