David Wilson

Cost-effectiveness of HIV financing

Global HIV resourcing

Resulted in tremendous health and economic savings

• E.g. Avahan achieved scale and coverage– HIV prevalence declined significantly– 19.6% to 16.4% among FSWs (aOR=0.81, p=0.04)

Source: Ramesh BM. IBBA two rounds analysis with FSWs in Karnataka, 5 districts. STI 2010; 86 (Suppl 1): i17; http://www.aidstar-one.com/sites/default/files/technical_consultations/mixed_epidemics/day_2/Avahan_program_Gina_Dallabetta.pdf

But not enough money to do everything

• 2.3 (1.9-2.7) million newly infected in 2012• 35.3 (29.1-35.3) million PLHIV and growing

Source: UNAIDS 2013 global report

Much money has been wasted

• Administrative and ‘other management’ costs• Programs have not operated most efficiently• Programs have not achieved scale and

coverage• Available money has not been

allocated to programs which have the largest impact– Proven effective and feasible programs

of the greatest cost-effectiveness– Many implemented programs have

not been cost-effective (Craig et al JIAS 2014)

Epidemiology of HIV in Asia-Pacific

• 86% of all 5 million PLHIV in Asia-Pacific are in 5 countries (India, China, Thailand, Indonesia, Vietnam)– 97% in 10 countries

• 70% of new infections in the KAPs

Source: Kirby Institute estimates based on UNAIDS HIV and AIDS data hub for Asia Pacific

Inefficient allocations• HIV prevention funding in Asia poorly targeted

Source: UNAIDS The Gap Report (2014): UNAIDS HIV and AIDS data hub for Asia Pacific based on AIDSinfo Online Database; Craig et al JIAS (2014) 17:18822

• 27/77 provinces in Thailand account for 70% of new HIV infections

• 43% of Philippines epidemicin Manila MSM

• 73% in just 3 cities

Need to focus limited resources by geography and population group

• Deciding HIV budget allocations / GF concept sheets / operational plans

• Know your epidemic, know your program costs, know your program impact, know your desired outcome

• Allocate based on all this knowledge to have the best possible (i.e. optimal) impact

Investing for the biggest impact: optimization / allocative efficiency

Allocations should be based on objectives

• Minimize incidence• Minimize deaths• Minimize DALYs• Minimize money to

achieve multiple targets in a national strategy

Different objectives

Different allocations

• Determine the allocation of resources or spending required that best meets the objective

Mathematical optimization• Formal mathematical approach, with epidemiological model,

taken to find the precise “best” / “optimal” solution to meet the objective according to the known epidemiology, costs and outcomes of programs

Allocation minimizing outcome

Current allocation

programme 1 programme 2

UNSW- World Bank allocative efficiency tool

E.g. An African country (specific country not disclosed)

Packages include condoms,HTC,SBCC

$5.6 million per year

Expected new infections, 2013-2020

Infe

ction

s (‘0

00s)

Same money, but avert 15% incidence

Minimize incidence: different budget amountsAn example from an Asian country

Large amounts of money on indirect or other management costs

Large indirect costs: ~50%

$5.6 million per year

• Program efficiency can free up this money for direct program efforts for greater impact– E.g. Efficiency study in Ukraine (UNSW, WB, UNAIDS)

• NSP costs can reduce by 18% • OST costs can reduce by at least half (stand alone); 43% for

integrated sites• ART costs can reduce by 28% (1st line) and 41% (2nd line)

Great need to invest smarter: focussed and efficient investments

“I simply wish that in a matter which so closely concerns the wellbeing of the human race, no decision shall be made without all the knowledge which a little analysis and calculation can provide”.

- Daniel Bernoulli, 1760