Forecasting Global Fund Grant Disbursements for Malaria Treatments
Author Information
Author(s): Justin M Cohen, Inder Singh, Megan E O'Brien
Primary Institution: Clinton Foundation HIV/AIDS Initiative
Hypothesis
The rate at which a grant is disbursed can be considered an indicator of grant progress.
Conclusion
The predictive regression models successfully forecasted disbursement patterns for Global Fund malaria grants, indicating their utility for demand forecasting of ACT.
Supporting Evidence
- Quarterly forecasts were correlated highly with actual smoothed disbursement rates (r = 0.987, p < 0.0001).
- Predicted ACT procurement was correlated strongly with actual procurement supported by Global Fund grants (r = 0.945, p < 0.0001).
- Disbursement slopes were positively associated with total agreed funding and negatively associated with phase two funding.
Takeaway
This study created a way to predict how much money the Global Fund will give to countries for malaria treatments, helping ensure that there are enough medicines available.
Methodology
Predictive regression models were derived using a repeated split-sample procedure to estimate disbursement rates from the Global Fund.
Potential Biases
The disbursement rate may not accurately reflect ACT procurement if other components of the grant underperform.
Limitations
Further validation using data from other countries in different regions and environments is necessary to confirm generalizability.
Participant Demographics
The study involved grants from 75 countries or multi-country cooperatives.
Statistical Information
P-Value
p<0.0001
Statistical Significance
p<0.0001
Digital Object Identifier (DOI)
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