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Impact Modeling

IAVI and the Futures Institute, with support from the U.S. Agency for International Development (USAID), have developed a model that predicts the impact that preventive AIDS vaccines could have on HIV epidemics at both national and global levels. Such projections can assist policymakers, vaccine developers, advocates and funders make informed decisions and effective resource allocations. 

The model shows that a vaccine could avert millions of new HIV infections and play a crucial role in ending the AIDS pandemic, even if current targets for access to HIV prevention, treatment and care are reached before a vaccine is introduced.

IAVI’s new suite of modeling publications explores an AIDS vaccine’s potential impact in low- and middle-income countries in terms of infections averted, the specific impact on women and girls, and the potential cost-savings a vaccine could provide by reducing the number of people in need of life-saving antiretroviral treatment. IAVI and the Futures Institute also have collaborated with researchers and policymakers on country-level in Kenya, Uganda, Brazil and China.

To learn more about IAVI and the Futures Institute’s impact modeling work, visit IAVI’s policy studies database

Interactive Impact Modeling Tool
Explore the interaction of future potential preventive AIDS vaccines with existing HIV-prevention tools within an HIV epidemic representative of one of five regions. 

Click to learn about each section of the tool (click again to hide section):

1 Select region  |   2 Select baseline scenario  |   3 Select vaccine scenario 
4 Chart results  |   5 See the numbers  |   References

 

1. Select a region.

We have aggregated HIV data for countries in five global regions heavily impacted by HIV/AIDS and scaled those data to five sample “countries” of 50 million people to make the regions more comparable.

  • Southern Africa (hyper-epidemic) – Rates of HIV prevalence are very high and not limited to specific demographics
  • Eastern Africa (generalized epidemic) – Rates of HIV prevalence are high and not limited to specific demographics
  • Asia (concentrated epidemic) – HIV prevalence is high in at-risk populations
  • Latin America (generalized epidemic) - Rates of HIV prevalence are high and not limited to specific demographics
  • Eastern Europe (concentrated epidemic) HIV prevalence is high in at-risk populations

IAVI has worked with partners in Uganda, Kenya, Brazil, and China to explore the potential impact of AIDS vaccines in those specific countries. More information on those studies can be found here (link to Modeling site). 

2. Select baseline scenario for access and prevention.  

Four scenarios of HIV programming uptake were based on available current coverage data as well as projected scale-up to levels described by the UNAIDS Investment Framework (link to Lancet paper). The baseline projections for each included intervention are described in the following table.

Users also have the option of scaling up access to antiretroviral treatment (ART) to individuals whose CD4 cell count is below 500 cells per cubic millimeter of blood, in line with research showing that earlier access to ART can significantly lower the risk of HIV transmission. For more information on HIV treatment as prevention, see AVAC’s website (http://www.avac.org/ht/d/sp/i/421/pid/421)

 

Hyper-epidemic

Generalized

Concentrated

General Population

     

Mass media

80%

80%

20%

Community mobilization

70%

70%

0%

Counseling and testing

3%

3%

1%

Condoms

60%

60%

60%

Vulnerable Populations

     

Youth in school

100%

100%

30%

Youth out of school

0%

0%

0%

FSW outreach

60%

60%

60%

MSM

60%

60%

60%

IDU: Outreach

60%

60%

60%

Workplace

50%

50%

0%

Medical Services

     

Male circumcision

60%

60%

0%

ART

80%

80%

80%

PrEP program. This variable encompasses all forms of pre-exposure prophylaxis (PrEP) against HIV infection currently in development: oral, gels (microbicides), injectable PrEP and rings. For more information on PrEP and the strategies being explored for its delivery, see AVAC’s website: http://www.avac.org/ht/d/sp/i/266/pid/266

Start year is the year in which PrEP would begin to be rolled out, with the specified Coverage being achieved five years after introduction. Efficacy describes the proportion of infections PrEP would avert in a given population

3. Select a vaccine scenario.

These standardized scenarios are similar to those used by IAVI in other iterations of the model. For more information on those studies and IAVI impact model, see our Modeling page. (link)

Start year is the year in which distribution of vaccines would begin, with the specified Coverage being achieved five years after introduction. Efficacy describes the proportion of infections a vaccine would avert in a given population.  Users can also explore the results of Prioritized Vaccination and see how that targeting populations at higher risk can have a significant impact on the number of vaccinations needed to avert an infection. (See #5 below)

4. Chart the results.

This interface shows the additive impact of scaled-up HIV interventions and vaccines as opposed to current trends on three graphs that can be toggled by clicking the appropriate button: New Infections, Aids-Related Deaths, and Total Life-Years on Antiretroviral Treatment. 

5. See the numbers.

This interface shows the statistical results of the modeling based on the selections in Sections 1, 2, and 3, along with a brief analysis of the number of vaccinations needed to avert one HIV infection, one AIDS-related death, and one person-year of antiretroviral treatment. 

Data sources/References

• The Impact of an AIDS Vaccine in Developing Countries: A New Model and Preliminary Results. IAVI Policy Research Working Paper, October 2006

• Stover et al 2007. “The Impact of an AIDS Vaccine in Developing Countries: A New Model and Initial Results.” Health Affairs. Volume 26, Number 4, p. 1147.

• Schwartländer et al. 2011. “Towards an improved investment approach for an effective response to HIV/AIDS.” The Lancet. June 2011.

• Country data for this website came from demographics and health surveys (DHS), UNAIDS data, and program sources.