Frontloading HIV financing maximizes the achievable impact of HIV prevention.
INTRODUCTION
Due to the nature of funding, national planners and international donors typically balance budgets over short time periods when designing HIV programmes (˜5-year funding cycles). We aim to explicitly quantify the cost of short-term funding arrangements on the success of future HIV prevention programmes.


METHODS
Using mathematical models of HIV transmission in Kenya, we compare the impact of optimized combination prevention strategies under different constraints on investment over time. Each scenario has the same total budget for the 30-year intervention period but the pattern of spending over time is allowed to vary. We look at the impact of programmes with decreasing, increasing or constant spending across 5-year funding cycles for a 30-year period. Interventions are optimized within each funding cycle such that strategies take a short-term view of the epidemic. We compare these with two strategies with no spending pattern constraints: one with static intervention choices and another flexible strategy with interventions changed in year ten.


RESULTS AND DISCUSSION
For the same total 30-year budget, greatest impact is achieved if larger initial prevention spending is offset by later treatment savings which leads to accumulating benefits in reduced infections. The impact under funding cycle constraints is determined by the extent to which greater initial spending is permitted. Short-term funding constraints and funds held back to later years may reduce impact by up to 18% relative to the flexible long-term strategy.


CONCLUSIONS
Ensuring that funding arrangements are in place to support long-term prevention strategies will make spending most impactful. Greater prevention spending now will bring considerable returns through reductions in new infections, greater population health and reductions in the burden on health services in the future.
['Anderson|Sarah-Jane|SJ|0000-0002-5945-2285', 'Ghys|Peter D|PD|', 'Ombam|Regina|R|', 'Hallett|Timothy B|TB|']
D000328:Adult D058872:Epidemics D015658:HIV Infections D006801:Humans D007630:Kenya D008297:Male D008962:Models, Theoretical
HIV Prevention mathematical modelling health policy healthcare financing programme planning