Personalized public health: An implementation research agenda for the HIV response and beyond
Autoři:
Elvin H. Geng aff001; Charles B. Holmes aff002; Mosa Moshabela aff004; Izukanji Sikazwe aff005; Maya L. Petersen aff006
Působiště autorů:
Division of Infectious Diseases, Department of Medicine and Center for Dissemination and Implementation, Institute for Public Health, Washington University in St. Louis, St. Louis, Missouri, United States of America
aff001; Center for Global Health and Quality, Georgetown University Department of Medicine, Washington, DC
aff002; Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
aff003; School of Nursing and Public Health, University of KwaZulu Natal, Republic of South Africa
aff004; Center for Infectious Diseases Research in Zambia, Lusaka, Zambia
aff005; Division of Biostatistics, School of Public Health, University of California Berkeley, Berkeley, California, United States of America
aff006
Vyšlo v časopise:
Personalized public health: An implementation research agenda for the HIV response and beyond. PLoS Med 16(12): e32767. doi:10.1371/journal.pmed.1003020
Kategorie:
Editorial
doi:
https://doi.org/10.1371/journal.pmed.1003020
Zdroje
1. Ghys PD, Williams BG, Over M, Hallett TB, Godfrey-Faussett P. Epidemiological metrics and benchmarks for a transition in the HIV epidemic. PLoS Med. 2018;15(10):e1002678. doi: 10.1371/journal.pmed.1002678 30359372
2. Haakenstad A, Moses MW, Tao T, Tsakalos G, Zlavog B, Kates J, et al. Potential for additional government spending on HIV/AIDS in 137 low-income and middle-income countries: an economic modelling study. Lancet HIV. 2019;6(6):e382–e95. doi: 10.1016/S2352-3018(19)30038-4 31036482
3. Nguyen N, Powers KA, Miller WC, Howard AG, Halpern CT, Hughes JP, et al. Sexual partner types and incident HIV infection among rural South African adolescent girls and young women enrolled in HPTN 068: a latent class analysis. J Acquir Immune Defic Syndr. 2019;82(1):24–33. doi: 10.1097/QAI.0000000000002096 31169772
4. Kagaayi J, Chang LW, Ssempijja V, Grabowski MK, Ssekubugu R, Nakigozi G, et al. Impact of combination HIV interventions on HIV incidence in hyperendemic fishing communities in Uganda: a prospective cohort study. Lancet HIV. 2019;6(10):e680–e7. doi: 10.1016/S2352-3018(19)30190-0 31533894
5. Cuadros DF, Graf T, de Oliveira T, Bärnighausen T, Tanser F. Assessing the role of geographical HIV hot-spots in the spread of the epidemic. InProc. Conference on Retroviruses and Opportunistic Infections 2018 Mar. Abstract 43.
6. Holmes CB, Sikazwe I, Sikombe K, Eshun-Wilson I, Czaicki N, Beres LK, et al. Estimated mortality on HIV treatment among active patients and patients lost to follow-up in 4 provinces of Zambia: Findings from a multistage sampling-based survey. PLoS Med. 2018;15(1):e1002489. doi: 10.1371/journal.pmed.1002489 29329301
7. Sikazwe I, Eshun-Wilson I, Sikombe K, Czaicki N, Somwe P, Mody A, et al. Retention and viral suppression in a cohort of HIV patients on antiretroviral therapy in Zambia: Regionally representative estimates using a multistage-sampling-based approach. PLoS Med. 2019;16(5):e1002811. doi: 10.1371/journal.pmed.1002811 31150380
8. Hayes RJ, Donnell D, Floyd S, Mandla N, Bwalya J, Sabapathy K, et al. Effect of universal testing and treatment on HIV incidence—HPTN 071 (PopART). N Engl J Med. 2019;381(3):207–18. doi: 10.1056/NEJMoa1814556 31314965
9. Anderson SJ, Cherutich P, Kilonzo N, Cremin I, Fecht D, Kimanga D, et al. Maximising the effect of combination HIV prevention through prioritisation of the people and places in greatest need: a modelling study. Lancet. 2014 Jul 19;384(9939):249–56. doi: 10.1016/S0140-6736(14)61053-9 25042235
10. Chambers DA, Glasgow RE, Stange KC. The dynamic sustainability framework: addressing the paradox of sustainment amid ongoing change. Implement Sci. 2013;8(1):117.
11. Chambers DA, Norton WE. The adaptome: advancing the science of intervention adaptation. Am J Prev Med. 2016;51(4):S124–S31.
12. Lei H, Nahum-Shani I, Lynch K, Oslin D, Murphy SA. A" SMART" design for building individualized treatment sequences. Annu Rev Clin Psychol. 2012;8:21–48. doi: 10.1146/annurev-clinpsy-032511-143152 22224838
13. Luedtke A, van der Laan MJ. Statistical inference for the mean outcome under a possibly non-unique optimal treatment strategy. The Annals of Statistics. 2016;44(2):713–42. doi: 10.1214/15-AOS1384 30662101
14. Luedtke A, van der Laan MJ. Super-learning of an optimal dynamic treatment rule. Int J Biostat. 2016;12(1):305–32. doi: 10.1515/ijb-2015-0052 27227726
15. van der Laan MJ, Luedtke A. Targeted learning of the mean outcome under an optimal dynamic treatment rule. J Causal Inference. 2015;3(1):61–95. doi: 10.1515/jci-2013-0022 26236571
16. Food and Drug Administration. Adaptive Designs for Clinical Trials of Drugs and Biologics: Guidance for Industry. U.S. Department of Health and Human Services. 2018.
17. Pallmann P, Bedding AW, Choodari-Oskooei B, Dimairo M, Flight L, Hampson LV, et al. Adaptive designs in clinical trials: why use them, and how to run and report them. BMC Med. 2018;16(1):29. doi: 10.1186/s12916-018-1017-7 29490655
18. Berry SM, Petzold EA, Dull P, Thielman NM, Cunningham CK, Corey GR, et al. A response adaptive randomization platform trial for efficient evaluation of Ebola virus treatments: A model for pandemic response. Clin Trials. 2016;13(1):22–30. doi: 10.1177/1740774515621721 26768569
19. Chambaz A, van der Laan MJ. Inference in targeted group-sequential covariate-adjusted randomized clinical trials. Scand J Stat. 2014;41(1):104–40.
20. Chambaz A, Zheng W, van der Laan MJ. Targeted sequential design for targeted learning inference of the optimal treatment rule and its mean reward. Ann Statist. 2017;45(6):2537–64.
21. Simon KC, Tideman S, Hillman L, Lai R, Jathar R, Ji Y, et al. Design and implementation of pragmatic clinical trials using the electronic medical record and an adaptive design. JAMIA Open. 2018;1(1):99–106. doi: 10.1093/jamiaopen/ooy017 30386852
22. Johnson FR, Lancsar E, Marshall D, Kilambi V, Mühlbacher A, Regier DA, et al. Constructing experimental designs for discrete-choice experiments: report of the ISPOR conjoint analysis experimental design good research practices task force. Value Health. 2013;16(1):3–13. doi: 10.1016/j.jval.2012.08.2223 23337210
23. Eshun-Wilson I, Mukumbwa-Mwenechanya M, Kim HY, Zannolini A, Mwamba CP, Dowdy D, et al. Differentiated Care Preferences of Stable Patients on Antiretroviral Therapy in Zambia: A Discrete Choice Experiment. J Acquir Immune Defic Syndr. 2019 Aug 15;81(5):540. doi: 10.1097/QAI.0000000000002070 31021988
24. Miners A, Nadarzynski T, Witzel C, Phillips AN, Cambiano V, Rodger AJ, et al. Preferences for HIV testing services among men who have sex with men in the UK: A discrete choice experiment. PLoS Med. 2016;16(4):e1002779. https://doi.org/10.1371/journal.pmed.1002779
25. Bazzano AN, Martin J, Hicks E, Faughnan M, Murphy L. Human-centred design in global health: A scoping review of applications and contexts. PLoS ONE. 2017;12(11):e0186744. doi: 10.1371/journal.pone.0186744 29091935
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