International Journal of Public Health

, Volume 60, Issue 4, pp 457–466 | Cite as

Evaluating HIV prevention strategies for populations in key affected groups: the example of Cabo Verde

  • João Filipe G. Monteiro
  • Sandro Galea
  • Timothy Flanigan
  • Maria de Lourdes Monteiro
  • Samuel R. Friedman
  • Brandon D. L. Marshall
Original Article

Abstract

Objectives

We used an individual-based model to evaluate the effects of hypothetical prevention interventions on HIV incidence trajectories in a concentrated, mixed epidemic setting from 2011 to 2021, and using Cabo Verde as an example.

Methods

Simulations were conducted to evaluate the extent to which early HIV treatment and optimization of care, HIV testing, condom distribution, and substance abuse treatment could eliminate new infections (i.e., reduce incidence to less than 10 cases per 10,000 person-years) among non-drug users, female sex workers (FSW), and people who use drugs (PWUD).

Results

Scaling up all four interventions resulted in the largest decreases in HIV, with estimates ranging from 1.4 (95 % CI 1.36–1.44) per 10,000 person-years among non-drug users to 8.2 (95 % CI 7.8–8.6) per 10,000 person-years among PWUD in 2021. Intervention scenarios prioritizing FWS and PWUD also resulted in HIV incidence estimates at or below 10 per 10,000 person-years by 2021 for all population sub-groups.

Conclusions

Our results suggest that scaling up multiple interventions among entire population is necessary to achieve elimination. However, prioritizing key populations with this combination prevention strategy may also result in a substantial decrease in total incidence.

Keywords

Individual-based model Condom use Female sex workers Monte Carlo simulation People who use drugs Substance use 

Notes

Acknowledgements

The authors would like to thank Dr. Celso Herminio Soares Ribeiro at the Cabo Verde National Statistic Institute (INE-CV), for providing the technical reports and HIV/AIDS data in Cabo Verde. The authors also acknowledge the staff and resources provided by the Brown University Center for Computation & Visualization. We would like to thank Dr. Magdalena Paczkowski for assisting with the ABM python code adaptation to the Cabo Verde population. This research was supported, in part, by a T32 training grant from the National Institute on Drug Abuse awarded to the Miriam Hospital (T32-DA13911). This project is funded in part by the National Institutes of Health (R01-DA013336) as part of the Community Vulnerability and Responses to Drug-User Related HIV/AIDS (CVAR) study, and was also funded in part by a 2012 developmental grant from the Lifespan/Tufts/Brown Center for AIDS Research (P30-AI042853). Dr. Filipe Monteiro is supported by a postdoctoral fellowship, T32 Training Program in HIV and Other Consequences of Substance Abuse (grant number T32-DA013911). Dr. Brandon Marshall is supported by a Salomon Faculty Research Award from Brown University.

Supplementary material

38_2015_676_MOESM1_ESM.pdf (2.6 mb)
Supplementary material 1 (PDF 2685 kb)

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Copyright information

© Swiss School of Public Health 2015

Authors and Affiliations

  • João Filipe G. Monteiro
    • 1
    • 2
  • Sandro Galea
    • 3
  • Timothy Flanigan
    • 2
  • Maria de Lourdes Monteiro
    • 4
  • Samuel R. Friedman
    • 5
  • Brandon D. L. Marshall
    • 1
  1. 1.Department of EpidemiologyBrown University School of Public HealthProvidenceUSA
  2. 2.Division of Infectious DiseasesThe Miriam HospitalProvidenceUSA
  3. 3.Department of EpidemiologyColumbia University Mailman School of Public HealthNew YorkUSA
  4. 4.Ministério da SaúdePalácio do Governo, PraiaIlha De SantiagoCabo Verde
  5. 5.Institute for Infectious Disease ResearchNational Development and Research Institutes Inc.New YorkUSA

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