Ivory Coast Government Rethinks HIV/AIDS Funds Allocation

The Issue You Tackled

Sub-Saharan Africa is home to 24.7 million people living with HIV, 70% of the world’s HIV infected population as of 2013. Cote d’Ivoire has the highest HIV prevalence in West Africa with 3.7% of its population infected in 2012. The high prevalence and incidence rates of HIV/ADS in Cote d’Ivoire offer an immense opportunity for effective HIV/AIDS policies developed by epidemiological models calibrated to country data. The current work aims to develop such policies to curb the progression of the HIV epidemic in Cote d’Ivoire. The accurate monitoring of the pattern in which a disease evolves is important for governments and donors as they decide how to allocate their scarce resources for health care.

The objective of this research is to actively support the quest for an AIDS-free generation in Côte d’Ivoire with a data-based approach that provides decision makers with a tool to identify priority areas, set a sustainable pace for the investment of limited resources, and develop realistic strategies that prioritize the allocation of resources among different HIV response programs.

What You Actually Did

This research developed a formal system dynamics model that shows the evolution of HIV/AIDS in Côte d’Ivoire over four decades, starting in 1990 and projecting prevalence through to 2040. It is the first system dynamics application to describe and map the evolution of the HIV/AIDS epidemic in Cote d’Ivoire. In addition, the modeling work provided the first opportunity of using HIV transmission data to replicate historical data and inform program design and re-alignment.

Findings included mapping the development of the HIV/AIDS epidemic over time and understanding the impact of evidence-based policies when implemented at different points in time. Historical data on prevalence and incidence rates were used to calibrate the model with country data from 1990 to 2012, then the model was verified with the collection and collation of other historical data from multiple public reports.

The main inputs and assumptions in the model were based on discussions with decision-makers from the Ministry of Health and the PEPFAR Management Team in Côte d’Ivoire, along with a review of the data available from relevant literature. The model was calibrated to ensure it accurately captured the progression of the epidemic in Cote d’Ivoire for the last 23 years, and then it projected HIV/AIDS dynamics going 27 years into the future. The model allowed us to simulate the implementation of different HIV/AIDs policies and evaluate their impact on the progression of the epidemic.

Policy analyses and reflection on their applicability informed our recommendations of how to optimally combine different policies given implementation constraints. Our analyses show that policies addressing single areas (e.g., a policy that controls infection rate alone) cannot significantly reduce the number of HIV/AIDs infected individuals in the long run. Rather, combining several policies can be much more effective in reducing HIV/AIDS. We found that the greatest impact can be achieved by concentrating on 3 areas:

1. Focusing on HIV- Prenatal Transmission
2. Reducing Infectivity among Adults
3. Increase in Enrolment Rate on ART

A policy that combines all three types of interventions at maximum rates would result in the greatest reduction in prevalence, however, this is prohibitive in terms of cost and other constraints. Instead, an effective policy would combine fractions of the proposed policies, such as (a) reducing HIV prenatal transmission by 50%; (b) decreasing infectivity among mature healthy by 20% and (c) increasing adult enrollment rate on ART by 10%.

The Results

The system dynamics model proved to be an effective tool in mapping the effects of HIV/AIDS policy shifts in Côte d’Ivoire, and enabled decision makers to experiment with different constraints to determine positive outcomes on an aggregate level. According to USAID/PEPFAR program officers in CIV, the model allowed better forecasting and better allocation of resources and could support decision-making and goal setting for HIV/AIDS policies. The USAID Office of Global AIDS suggested the model was “promising for PEPFAR use at global level.” These positive results motivated a change in the terms of reference of a USAID employee to include collection of specific data and further development of the model.

In addition, ministry of health officials secured funding and issued a call for proposals for further analysis, to include the economic impact of investment versus non-investment in AIDS response programs.

The extended model would capture costs associated with the process of selecting, testing, diagnosing, monitoring and treating HIV/AIDS patients, and explore other economic factors affected by the epidemic such as the cost of absenteeism and the economic burden of caring for infected family members. The follow-on project includes a training element that describes the process undertaken to bring scientific modeling of a highly complex issue to policymakers with an emphasis on the policy questions. We aim to provide an understanding of the analytical process to impart useful insights for others who seek to use system dynamics to enhance response policies in health care.

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