1 / 22

Dr Anatole S Menon-Johansson Drs Jean McGuire & Harvey Makadon Harvard School of Public Health

Developing and testing models for the investigation of barriers to effective HIV / AIDS prevention in the USA. Dr Anatole S Menon-Johansson Drs Jean McGuire & Harvey Makadon Harvard School of Public Health Harkness / Health Foundation Fellow 2006 Orlando June, 2007. Outline.

varsha
Download Presentation

Dr Anatole S Menon-Johansson Drs Jean McGuire & Harvey Makadon Harvard School of Public Health

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Developing and testing models for the investigation of barriers to effective HIV / AIDS prevention in the USA Dr Anatole S Menon-Johansson Drs Jean McGuire & Harvey Makadon Harvard School of Public Health Harkness / Health Foundation Fellow 2006 Orlando June, 2007

  2. Outline • Measuring AIDS prevention performance • Describe how AIDS prevention differs between men & women • Highlight correlations with AIDS prevention • Predicting AIDS prevention performance • Policy implications

  3. HIV > AIDS > Death 1o P R E V E N T I O N Viral transmission 2-3 weeks Acute retroviral syndrome 2-3 weeks Recovery + seroconversion HIV+ 2-4 weeks Chronic HIV infection ~ 8 years Symptomatic HIV infection / AIDS AIDS 2/3o ~ 1.3 years HIV Rx Death

  4. HIV vs AIDS data • HIV data available from 28 states in 1995 and 36 in 2004 • ? HIV data reliability • HIV ≤ AIDS diagnoses for some states • Estimated 25% HIV+ persons do not know their ‘serostatus’ • AIDS = notifiable disease since late 1980’s and disease definition set in 1993

  5. Changes in AIDS cases over time Data: Center for Disease Control and Prevention (CDC) 1995-2004

  6. AIDS prevention by gender Data: CDC 1995-2004

  7. AIDS prevention in men (1995-2004)

  8. AIDS prevention in women (1995-2004)

  9. Relationships with known prevention strategies • How does AIDS prevention relate to: • Demographics • Economics • Prevention strategies • Primary • Secondary / Tertiary • Linear regression was used to compare AIDS prevention with the above variables

  10. Demographics Data: US Census Bureau 2004

  11. Income / Poverty & AIDS prevention Data: US Census Bureau 2004

  12. Primary prevention Data: Kaiser Family Foundation, Office of Applied Studies, CDC

  13. Women’s Health Data: American Cancer Society 2004, CDC 2004, NARAL Pro-choice America 2006

  14. The uninsured and state to state disparity in provision • KFF / NASTAD ADAP reports • 25% of HIV+ people on Rx use ADAP • ADAP formulary varies by state • Waiting lists are used for cost control • Variation in eligibility criterion • Kaiser Daily HIV / AIDS reports • August 29th, 2003 • “Three people with HIV / AIDS die while on West Virginia ADAP waiting list”

  15. Health care provision Data: US Census Bureau 2004

  16. Secondary / Tertiary prevention Data: KFF / NASTAD ADAP reports 1997-2004, AMA 2004, US Census Bureau 2004

  17. Impact of sodomy laws Data: CDC 1995-2003, US Supreme Court

  18. Impact of Syringe Exchange Program (SEP) authorization laws Data: Beasley School of Law, Temple University

  19. Summary • State AIDS prevention can be accurately evaluated using this model • Less effective state AIDS prevention is associated with : • Women (Reduced reproductive health) • Poverty (Black) • Poor STD control • History sodomy laws • No SEP authorization laws

  20. Prediction AIDS prevention success • Key variables: • Poverty • Gonorrhoea rate • Not having a SEP authorization law • Properties of predictive model: • Sensitivity 83% • Specificity 79%

  21. Policy implications AIDS prevention could be improved by: • Standardization of SEP authorization laws • Improving sexual and reproductive health • Poverty alleviation

  22. Acknowledgements • Commonwealth Fund • Health Foundation • Ellison-Cliffe Travelling Fellowship • Senta Foulkes Travelling Fellowship • Avni Patel (KFF) • Drs Sullivan and Campsmith (CDC) • Professors and students at HSPH

More Related