Betting on the fastest horse: Using computer simulation to design a combination HIV intervention for future projects in Maharashtra, India

Kelly V Ruggles, Anik R Patel, Stephen Schensul, Jean Schensul, Kimberly Nucifora, Qinlian Zhou, Kendall Bryant, R Scott Braithwaite, Kelly V Ruggles, Anik R Patel, Stephen Schensul, Jean Schensul, Kimberly Nucifora, Qinlian Zhou, Kendall Bryant, R Scott Braithwaite

Abstract

Objective: To inform the design of a combination intervention strategy targeting HIV-infected unhealthy alcohol users in Maharashtra, India, that could be tested in future randomized control trials.

Methods: Using probabilistic compartmental simulation modeling we compared intervention strategies targeting HIV-infected unhealthy alcohol users on antiretroviral therapy (ART) in Maharashtra, India. We tested interventions targeting four behaviors (unhealthy alcohol consumption, risky sexual behavior, depression and antiretroviral adherence), in three formats (individual, group based, community) and two durations (shorter versus longer). A total of 5,386 possible intervention combinations were tested across the population for a 20-year time horizon and intervention bundles were narrowed down based on incremental cost-effectiveness analysis using a two-step probabilistic uncertainty analysis approach.

Results: Taking into account uncertainty in transmission variables and intervention cost and effectiveness values, we were able to reduce the number of possible intervention combinations to be used in a randomized control trial from over 5,000 to less than 5. The most robust intervention bundle identified was a combination of three interventions: long individual alcohol counseling; weekly Short Message Service (SMS) adherence counseling; and brief sex risk group counseling.

Conclusions: In addition to guiding policy design, simulation modeling of HIV transmission can be used as a preparatory step to trial design, offering a method for intervention pre-selection at a reduced cost.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1. Analyses methodology.
Fig 1. Analyses methodology.
Pipeline workflow for intervention bundle prioritization. a, Creation of efficient frontier for all combinations of 15 interventions and filtering out 8 interventions that were never found on the frontier. b, For the remaining 7 interventions, completion of 100 probabilistic runs varying intervention costs and effects and filtering out intervention bundles that were never found on the frontier. c, Completion of a full probabilistic analyses (run N = 1000) varying intervention cost and effect as well as 96 input variables. All analysis was run for a 20-year simulation.
Fig 2. Efficient frontier for HIV interventions…
Fig 2. Efficient frontier for HIV interventions during a 20-year simulation of HIV epidemic in Maharashtra, India.
a, Graphical representation efficient frontier for all permutations of 12 interventions (4096 total combinations). Blue circles represent packages of interventions on the frontier, red represent packages off the frontier. b, focused graphical representation of efficient frontier for the lower end of discounted cost (0.888–0.898 Billion USD). c, Interventions contained within each efficient frontier package.
Fig 3. Final probabilistic analysis of top…
Fig 3. Final probabilistic analysis of top 32 intervention bundles.
a, Percentage of runs in which each bundle was identified on the efficient frontier across 1000 probabilistic runs using the 32 bundles identified in the previous analysis step. b, bundle ranking comparison between intervention-only probabilistic and the full probabilistic analysis. c, intervention bundle details corresponding to panel a. *Bundle 0 represents runs with no intervention.

References

    1. Kessler J, Myers JE, Nucifora KA, Mensah N, Kowalski A, Sweeney M, et al. Averting HIV Infections in New York City: A Modeling Approach Estimating the Future Impact of Additional Behavioral and Biomedical HIV Prevention Strategies. PLOS ONE. 2013;8: e73269 doi:
    1. Braithwaite RS, Nucifora KA, Kessler J, Toohey C, Mentor SM, Uhler LM, et al. Impact of Interventions Targeting Unhealthy Alcohol Use in Kenya on HIV Transmission and AIDS-Related Deaths. Alcohol Clin Exp Res. 2014;38: 1059–1067. doi:
    1. Yu W, Li C, Fu X, Cui Z, Liu X, Fan L, et al. The cost-effectiveness of different feeding patterns combined with prompt treatments for preventing mother-to-child HIV transmission in South Africa: estimates from simulation modeling. PloS One. 2014;9: e102872 doi:
    1. Desai K, Sansom SL, Ackers ML, Stewart SR, Hall HI, Hu DJ, et al. Modeling the impact of HIV chemoprophylaxis strategies among men who have sex with men in the United States: HIV infections prevented and cost-effectiveness. AIDS Lond Engl. 2008;22: 1829–1839. doi:
    1. Kessler J, Braithwaite RS. Modeling the cost-effectiveness of HIV treatment: how to buy the most “health” when resources are limited. Curr Opin HIV AIDS. 2013;8: 544–549. doi:
    1. Abuelezam NN, McCormick AW, Fussell T, Afriyie AN, Wood R, DeGruttola V, et al. Can the Heterosexual HIV Epidemic be Eliminated in South Africa Using Combination Prevention? A Modeling Analysis. Am J Epidemiol. 2016;184: 239–248. doi:
    1. Weiss HA, Wasserheit JN, Barnabas RV, Hayes RJ, Abu-Raddad LJ. Persisting with prevention: the importance of adherence for HIV prevention. Emerg Themes Epidemiol. 2008;5: 8 doi:
    1. Kagaayi J, Serwadda D. The History of the HIV/AIDS Epidemic in Africa. Curr HIV/AIDS Rep. 2016;13: 187–193. doi:
    1. Brown JL, Sales JM, DiClemente RJ. Combination HIV prevention interventions: the potential of integrated behavioral and biomedical approaches. Curr HIV/AIDS Rep. 2014;11: 363–375. doi:
    1. Braithwaite RS, Roberts MS, Justice AC. Incorporating Quality of Evidence into Decision Analytic Modeling. Ann Intern Med. 2007;146: 133–141.
    1. Doubilet P, Begg CB, Weinstein MC, Braun P, McNeil BJ. Probabilistic sensitivity analysis using Monte Carlo simulation. A practical approach. Med Decis Mak Int J Soc Med Decis Mak. 1985;5: 157–177.
    1. Padian NS, McCoy SI, Balkus JE, Wasserheit JN. Weighing the gold in the gold standard: challenges in HIV prevention research. AIDS Lond Engl. 2010;24: 621–635. doi:
    1. Cuadros DF, Abu-Raddad LJ, Awad SF, García-Ramos G. Use of agent-based simulations to design and interpret HIV clinical trials. Comput Biol Med. 2014;50: 1–8. doi:
    1. Holford NHG, Kimko HC, Monteleone JPR, Peck CC. Simulation of Clinical Trials. Annu Rev Pharmacol Toxicol. 2000;40: 209–234. doi:
    1. Huang X, Lin J, Demner-Fushman D. Evaluation of PICO as a Knowledge Representation for Clinical Questions. AMIA Annu Symp Proc. 2006;2006: 359–363.
    1. Smith PC, Schmidt SM, Allensworth-Davies D, Saitz R. Primary Care Validation of a Single-Question Alcohol Screening Test. J Gen Intern Med. 2009;24: 783–788. doi:
    1. Braithwaite RS, Justice AC, Chang C-CH, Fusco JS, Raffanti SR, Wong JB, et al. Estimating the proportion of patients infected with HIV who will die of comorbid diseases. Am J Med. 2005;118: 890–898. doi:
    1. Braithwaite RS, Shechter S, Roberts MS, Schaefer A, Bangsberg DR, Harrigan PR, et al. Explaining variability in the relationship between antiretroviral adherence and HIV mutation accumulation. J Antimicrob Chemother. 2006;58: 1036–1043. doi:
    1. Marcus R, Culver DH, Bell DM, Srivastava PU, Mendelson MH, Zalenski RJ, et al. Risk of human immunodeficiency virus infection among emergency department workers. Am J Med. 1993;94: 363–370.
    1. Kroese DP, Chan JCC. Statistical Modeling and Computation. Springer Science & Business Media; 2013.
    1. Braithwaite RS, Nucifora KA, Yiannoutsos CT, Musick B, Kimaiyo S, Diero L, et al. Alternative antiretroviral monitoring strategies for HIV-infected patients in east Africa: opportunities to save more lives? J Int AIDS Soc. 2011;14: 38 doi:
    1. Garnett GP, Anderson RM. Factors controlling the spread of HIV in heterosexual communities in developing countries: patterns of mixing between different age and sexual activity classes. Philos Trans R Soc Lond B Biol Sci. 1993;342: 137–159. doi:
    1. Uthman OA, Magidson JF, Safren SA, Nachega JB. Depression and adherence to antiretroviral therapy in low-, middle- and high-income countries: a systematic review and meta-analysis. Curr HIV/AIDS Rep. 2014;11: 291–307. doi:
    1. Mills EJ, Lester R, Thorlund K, Lorenzi M, Muldoon K, Kanters S, et al. Interventions to promote adherence to antiretroviral therapy in Africa: a network meta-analysis. Lancet HIV. 2014;1: e104–111. doi:
    1. Scott-Sheldon LAJ, Huedo-Medina TB, Warren MR, Johnson BT, Carey MP. Efficacy of behavioral interventions to increase condom use and reduce sexually transmitted infections: a meta-analysis, 1991 to 2010. J Acquir Immune Defic Syndr 1999. 2011;58: 489–498. doi:
    1. Moreno R, Nababan HY, Ota E, Wariki WMV, Ezoe S, Gilmour S, et al. Structural and community-level interventions for increasing condom use to prevent the transmission of HIV and other sexually transmitted infections. Cochrane Database Syst Rev. 2014; CD003363 doi:
    1. Foxcroft DR, Coombes L, Wood S, Allen D, Almeida Santimano NML. Motivational interviewing for alcohol misuse in young adults. Cochrane Database Syst Rev. 2014; CD007025 doi:
    1. Spies G, Asmal L, Seedat S. Cognitive-behavioural interventions for mood and anxiety disorders in HIV: a systematic review. J Affect Disord. 2013;150: 171–180. doi:
    1. Foxcroft DR, Coombes L, Wood S, Allen D, Almeida Santimano NML, Moreira MT. Motivational interviewing for the prevention of alcohol misuse in young adults. Cochrane Database Syst Rev. 2016;7: CD007025 doi:
    1. National AIDS Control Organization (NACO), Ministry of Health and Family Welfare, Government of India. NACO, Ministry of Health and Family Welfare, Government of Indi; 2009.
    1. National AIDS Control Organization (NACO), Ministry of Health and Family Welfare, Government of India. New Delhi, India: NACO, Ministry of Health and Family Welfare, Government of Indi; 2006.
    1. NACO. India: Annual Report 2012–2013. 2013.
    1. NACO. India: Annual Report 2013–2014. 2014.
    1. Nag M. Sexual behaviour in India with risk of HIV/AIDS transmission. Health Transit Rev. 1995;5: 293–305.
    1. Mehendale SM, Bollinger RC, Kulkarni SS, Stallings RY, Brookmeyer RS, Kulkarni SV, et al. Rapid disease progression in human immunodeficiency virus type 1-infected seroconverters in India. AIDS Res Hum Retroviruses. 2002;18: 1175–1179. doi:
    1. Kessler J, Ruggles K, Patel A, Nucifora K, Li L, Roberts MS, et al. Targeting an alcohol intervention cost-effectively to persons living with HIV/AIDS in East Africa. Alcohol Clin Exp Res. 2015;39: 2179–2188. doi:
    1. Kessler J, Myers JE, Nucifora KA, Mensah N, Toohey C, Khademi A, et al. Evaluating the impact of prioritization of antiretroviral pre-exposure prophylaxis in New York. AIDS Lond Engl. 2014;28: 2683–2691. doi:
    1. Weiser SD, Leiter K, Heisler M, McFarland W, Percy-de Korte F, DeMonner SM, et al. A population-based study on alcohol and high-risk sexual behaviors in Botswana. PLoS Med. 2006;3: e392 doi:
    1. Weiser SD, Leiter K, Bangsberg DR, Butler LM, Percy-de Korte F, Hlanze Z, et al. Food insufficiency is associated with high-risk sexual behavior among women in Botswana and Swaziland. PLoS Med. 2007;4: 1589–1597; discussion 1598. doi:
    1. Byakika-Tusiime J, Crane J, Oyugi JH, Ragland K, Kawuma A, Musoke P, et al. Longitudinal antiretroviral adherence in HIV+ Ugandan parents and their children initiating HAART in the MTCT-Plus family treatment model: role of depression in declining adherence over time. AIDS Behav. 2009;13 Suppl 1: 82–91. doi:
    1. Nakimuli-Mpungu E, Bass JK, Alexandre P, Mills EJ, Musisi S, Ram M, et al. Depression, alcohol use and adherence to antiretroviral therapy in sub-Saharan Africa: a systematic review. AIDS Behav. 2012;16: 2101–2118. doi:
    1. Nduna M, Jewkes RK, Dunkle KL, Shai NPJ, Colman I. Associations between depressive symptoms, sexual behaviour and relationship characteristics: a prospective cohort study of young women and men in the Eastern Cape, South Africa. J Int AIDS Soc. 2010;13: 44 doi:
    1. Tadios Y, Davey G. Antiretroviral treatment adherence and its correlates in Addis Ababa, Ethiopia. Ethiop Med J. 2006;44: 237–244.
    1. Chersich MF, Luchters SMF, Malonza IM, Mwarogo P, King’ola N, Temmerman M. Heavy episodic drinking among Kenyan female sex workers is associated with unsafe sex, sexual violence and sexually transmitted infections. Int J STD AIDS. 2007;18: 764–769. doi:
    1. Fisher JC, Cook PA, Sam NE, Kapiga SH. Patterns of alcohol use, problem drinking, and HIV infection among high-risk African women. Sex Transm Dis. 2008;35: 537–544. doi:
    1. Epidemiology publications | UNAIDS [Internet]. [cited 15 Jun 2016]. Available:
    1. Markowitz H. Portfolio Selection*. J Finance. 1952;7: 77–91. doi:
    1. Gold M, Siegel J, Russell L, Weinstein M. Cost-Effectiveness in Health and Medicine. New York, NY: Oxford University Press; 2006.
    1. Walensky RP, Ross EL, Kumarasamy N, Wood R, Noubary F, Paltiel AD, et al. Cost-effectiveness of HIV treatment as prevention in serodiscordant couples. N Engl J Med. 2013;369: 1715–1725. doi:
    1. Venkatesh KK, Becker JE, Kumarasamy N, Nakamura YM, Mayer KH, Losina E, et al. Clinical impact and cost-effectiveness of expanded voluntary HIV testing in India. PloS One. 2013;8: e64604 doi:
    1. Freedberg KA, Kumarasamy N, Losina E, Cecelia AJ, Scott CA, Divi N, et al. Clinical impact and cost-effectiveness of antiretroviral therapy in India: starting criteria and second-line therapy. AIDS Lond Engl. 2007;21 Suppl 4: S117–128. doi:
    1. Nagy L, Heikkinen T, Sackeyfio A, Pitman R. The Clinical Impact and Cost Effectiveness of Quadrivalent Versus Trivalent Influenza Vaccination in Finland. Pharmacoeconomics. 2016;34: 939–951. doi:
    1. Pitman R, Fisman D, Zaric GS, Postma M, Kretzschmar M, Edmunds J, et al. Dynamic Transmission Modeling A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force Working Group–5. Med Decis Making. 2012;32: 712–721. doi:
    1. Gibson E, Begum N, Martinón-Torres F, Safadi MA, Sackeyfio A, Hackett J, et al. Cost-effectiveness analysis of the direct and indirect impact of intranasal live attenuated influenza vaccination strategies in children: alternative country profiles. J Mark Access Health Policy. 2016;4 doi:
    1. WHO. Global Status report on alcohol and health [Internet]. 2014. Available:
    1. The World Factbook [Internet]. USA Central Intelligence Agency; 2017. Available:
    1. Briggs AH, Weinstein MC, Fenwick EAL, Karnon J, Sculpher MJ, Paltiel AD. Model Parameter Estimation and Uncertainty Analysis A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force Working Group–6. Med Decis Making. 2012;32: 722–732. doi:
    1. Ades AE, Lu G, Claxton K. Expected value of sample information calculations in medical decision modeling. Med Decis Mak Int J Soc Med Decis Mak. 2004;24: 207–227. doi:
    1. Volle J, Letatsi T, Tan A. A baseline survey of multiple and concurrent sexual partnerships among Basotho men in Lesotho. 2009;Washington, DC: C-Change/AED.
    1. Garnett GP, Anderson RM. Balancing sexual partnerships in an age and activity stratified model of HIV transmission in heterosexual populations. IMA J Math Appl Med Biol. 1994;11: 161–192.
    1. Obot SI, Room R. Alcohol, Gender and Drinking Problems. World Health Organ Dep Ment Health Subst Abuse; Geneva: 2005;
    1. Allam RR, Murhekar MV, Bhatnagar T, Uthappa CK, Chava N, Rewari BB, et al. Survival probability and predictors of mortality and retention in care among patients enrolled for first-line antiretroviral therapy, Andhra Pradesh, India, 2008–2011. Trans R Soc Trop Med Hyg. 2014;108: 198–205. doi:
    1. World Health Organization. Global Prevalence and Incidence of Selected Curable Sexually Transmitted Infections Overview and Estimates. 2001;
    1. Boily M-C, Baggaley RF, Wang L, Masse B, White RG, Hayes RJ, et al. Heterosexual risk of HIV-1 infection per sexual act: systematic review and meta-analysis of observational studies. Lancet Infect Dis. 2009;9: 118–129. doi:
    1. Cardo DM, Culver DH, Ciesielski CA, Srivastava PU, Marcus R, Abiteboul D, et al. A case-control study of HIV seroconversion in health care workers after percutaneous exposure. Centers for Disease Control and Prevention Needlestick Surveillance Group. N Engl J Med. 1997;337: 1485–1490. doi:
    1. Attia S, Egger M, Müller M, Zwahlen M, Low N. Sexual transmission of HIV according to viral load and antiretroviral therapy: systematic review and meta-analysis. AIDS Lond Engl. 2009;23: 1397–1404. doi:
    1. Mahanta J, Medhi GK, Paranjape RS, Roy N, Kohli A, Akoijam BS, et al. Injecting and sexual risk behaviours, sexually transmitted infections and HIV prevalence in injecting drug users in three states in India. AIDS Lond Engl. 2008;22 Suppl 5: S59–68. doi:
    1. Freedberg KA, Scharfstein JA, Seage GR, Losina E, Weinstein MC, Craven DE, et al. The cost-effectiveness of preventing AIDS-related opportunistic infections. JAMA. 1998;279: 130–136.

Source: PubMed

赞助者和合作者

医疗条件

药物干预

3
订阅