HIV/AIDS Insuring the uninsurable. The future of human longevity: breaking the code Rüschlikon, 8. Nov 2011, Wayne Dam and Urs Widmer

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Transcription:

HIV/AIDS Insuring the uninsurable The future of human longevity: breaking the code Rüschlikon, 8. Nov 2011, Wayne Dam and Urs Widmer

Agenda 30 years AIDS and 15 years HAART biology of HIV (UW) HIV/AIDS and insurance (WD) 2

30 years AIDS and 15 years HAART Biology of HIV 1) Today's management of HIV infection 2) Can HIV Infection be cured in a late phase? 3) Can HIV Infection be cured in an early phase? 4) Lipodystrophy and premature aging 3

4

MLA style: "The Nobel Prize in Physiology or Medicine 2008". Nobelprize.org. 21 Sep 2011 http://www.nobelprize.org/nobel_prizes/medicine/laureates/2008/ 5

Virology RNA-Retrovirus HIV RNA-Virus DNA-Virus Influenza A Virus HPV Human papilloma virus 6

Virology: HIV entry HIV-1 Receptor: CD4 Co-receptor: CCR5 Mutant: CCR5 Delta 32 HIV CD4 CCR5 CD4+ cell Nature Reviews Drug Discovery 2, 581-587 (2003) 7

Natural history HIV infection 2 3 CDC A/B/C1-3 1 Host Virus Human CD4 (cells/mm3) HIV Viral load HIV RNA (copies/ml) 8

Natural history Variable CD4 progression 1000 Acute HIV Infection CD4 Cell Count 800 Long-term non-progressor Elite suppressor 600 400 Typical progressor 200 Rapid progressor 0 0 2 Year 1 4 6 8 10 12 Years 9 14

ARV therapy (ART, cart, HAART) HIV life cycle, point of action for drugs adult junior Triomune baby (Stavudine + Lamivudine + Nevirapine) 1984 1996 2010 ca 23 different drugs available (2010) Baylor College od Medicine www.bcm.edu Nature Reviews Drug Discovery 6, 951-952 (2007) 10

VL dynamics after interruption of ART ART drug holiday ART (continued) 18 Patients Davey RT et al. PNAS 96:15109-14 (1999) 11

ART increased life expectancy for HIVinfected individuals Life expectancy of individuals on combination antiretroviral therapy in highincome countries: a collaborative analysis of 14 cohort studies Antiretroviral Therapy Cohort Collaboration ART-CC The Lancet, Volume 372, Issue 9635, Pages 293-299, 26 July 2008 An HIV-infected 20-year-old appropriately treated with ART can expect to live to >69 years in high-income countries 12

Life expectancy 13

30 years AIDS and 15 years HAART Biology of HIV 1) Today's management of HIV infection 2) Can HIV Infection be cured in a late phase? 3) Can HIV Infection be cured in an early phase? 4) Lipodystrophy and premature aging The Berlin patient 2009 14

Can HIV infection be cured in late phase? Contra: 1. Integration (HIV provirus in host DNA) 2. Persistence in reservoir (sanctuary) 3. Recurrent viremia with cessation of HAART Pro: 15

M 40 HIV + (10 years) ART ( 4 years) Leukemia AML M4 VL Stem cell TPL Donor CCR5 Delta32/Delta 32 CD4 Hütter G. NEJM 360:692(2009)

30 years AIDS and 15 years HAART Biology of HIV 1) Today's management of HIV infection 2) Can HIV Infection be cured in a late phase? 3) Can HIV Infection be cured in an early phase??may be with a vaccine? 4) Lipodystrophy and premature aging 17

Comparative AIDS research Virus replication African Green Monkey Rhesus Macaque chronic, non-pathogenic infection high viral load pathogenic infection, AIDS high viral load HIV-1 Humans HIV-2 Humans HIV-1 Humans LTNP Science 13 April 2007 Vol 316, Issue 5822 Pathogenicity

Vaginal transmission, early phase Immune response: too little too late Nature 464, 217-223(11 March 2010) 19

Very early phase Blue symbols depict a Monte Carlo simulation of viral RNA sequence identity (%) after transmission. We constructed a mathematical model of HIV-1 replication and diversification assuming 1. HIV-1 generation time: 2 days 2. reproductive ratio (R0 = 6) 3. reverse transcriptase (RT) error rate (2.16 x 10-5) Note: Number of founder viruses varies by mode of transmission HSX (1) MSM (2-5) IDU (5) Keele BF, et al. Proc Natl Acad Sci U S A. 105(21):7552 (2008) 20

30 years AIDS and 15 years HAART Biology of HIV 1) Today's management of HIV infection 2) Can HIV Infection be cured in a late phase? 3) Can HIV Infection be cured in an early phase? 4) Lipodystrophy and premature aging 21

Effect of HIV infection and its treatment on inflammation and immunosenescence Annu Rev Med. 2011 Feb 18;62:141-55. 22

HIV/AIDS and insurance 23

Conditions for insurability The loss must be definite The loss must be significant The loss must occur by chance timing important in life insurance insured must not be able to influence outcome The rate of loss must be predictable The loss must not be catastrophic to the insurer The above are generally met for life insurance 24

How were these conditions changed by HIV/AIDS? The loss must be definite The loss must be significant The loss must occur by chance timing important in life insurance insured must not be able to influence outcome The rate of loss must be predictable The loss must not be catastrophic to the insurer What was once a well understood risk with a small margin for error became poorly understood 25

Reactions Prevent anti-selection/underwriting initially 'lifestyle' questions testing Exclusions largely a technique of the past difficult to manage still exists today Pricing adjustments underwriting and tests are not perfect downstream infection exclusions can be difficult to enforce 26

Best practice today No exclusions Risk priced for HAART was the big step change Life insurance Group life Individual Management via compulsion high take-up Guaranteed acceptance Underwritten low sums insured underwriting Low sums insured Tested testing Negative Positive 27

Global view of HIV prevalence in 2010 Source: UNAIDS 28

Life insurance penetration Swiss Re Sigma World Insurance - Insurance density life 2010 Premiums written per capita 29

South African AIDS timeline: the first two decades Global HIV timeline AIDS modelling in South Africa 1980 HIV-AIDS first identified in the US 80's Rapid spread of the epidemic 1981 1982 1983 By 1987: Estimated 5-10 million infected with HIV 150 000 cases of AIDS First ARV drug to treat HIV approved 1984 1985 1986 1987 1988 1989 Metropolitan Life/Doyle model 1990 1991 1992 90's 1993 Estimate 240 000 new infections in South Africa 1994 1995 HAART introduced for the first time 1996 ASSA500 model 1997 Immediate and substantial drop in AIDS deaths South Africa National Adult prevalence reaches 10% 1998 1999 ASSA600 model 30

AIDS timeline: 2000 onwards The epidemic deepens Global HIV timeline AIDS modelling in South Africa 2000 ASSA2000 2001 2002 00's 2003 2004 ASSA2002 2005 ASSA2003 ARV treatment included in PMB's Estimated accumulated AIDS deaths in South Africa exceed 1 million 2006 10's 2007 ARV protocols revised CD4 200 2008 Estimated accumulated AIDS deaths in South Africa exceed 2 million 2009 ARV protocols revised Pregnant women CD4 350+ 2010 NSP target to cover 80% of people who need to be on ARVs 2011 ASSA2008 model released 2012 2013 2014 Millennium development goals target 2015 31

10.9% population prevalence 5.5 million HIV+ 1 million on ART 32

Ante Natal Clinic Data is a key input into the model How have our prevalence estimates changed? Ante-natal prevalence largely unchanged for 2010, but lower for 2025 35% 30% 25% 20% 15% 10% 5% 0% 1985 1990 1995 ANC survey 2000 2005 ASSA2000 2010 2015 ASSA2003 2020 ASSA2008 33 2025

What were our mortality estimates a decade ago? Adult mortality (45q15) has dropped significantly in each model update 90% 80% 70% 60% 50% 40% Interventions 30% 20% 10% 0% 1985 1990 1995 2000 ASSA2000 2005 ASSA2003 2010 2015 ASSA2008 34 2020 2025

Life expectancy increased dramatically for 2010 35

Swiss Re HIV Testing Survey Key differentiators in HIV prevalence in SA Overall HIV Prevalence 2.43% Monthly salary <~USD2k Monthly salary >~USD2k 4.18% Married/Divorced 2.68% 1.01% Single/Widowed 6.22% Married/Divorced 0.67% Single/Widowed 2.16% Salary indicator of socio-economic class Marital Status proxy for sexual activity: intuitive link between HIV prevalence rates and behaviour 36

Life insurance and HIV/AIDS in South Africa Covered in group policies no questions, no tests, no exclusions HIV/AIDS claims are commonplace (can see in disability) cover is compulsory pricing is managed via epidemiological models Individual policies testing for larger sums insured (varies but can be as high as USD100k) pricing via select models for later infection no exclusions, whole of life guarantees HIV positive offered via specialist providers managed product (regular follow up) with reviewable rates 37

What is the goal and where are we? Ideally offer exactly the same product as the rest of the market ratings in a similar format to other diseases or impairments similar guarantees whole of life ideal but longer term e.g. 20 years OK to back mortgages Where we are whole of life but with reviewable rates and 6 monthly follow up standard product but with quite high loadings and only 10 year term (admittedly only in some markets) Getting there slowly 38

Recall - Landmark publication (Lancet 2003) We measured mortality rates in the Swiss HIV Cohort Study (SHCS) from 1997 to 2001 and compared them with those of the Swiss reference population. In patients who were successfully treated with highly active anti-retroviral therapy (HAART), and who were not also infected with the hepatitis C virus, excess death rates were below five per thousand per year. Patients with successfully treated cancer have much the same excess death rates but are not excluded from life insurance policies. (Extracted from abstract) Lancet 2003; 362: 877 78 39

Expansion of the Jaggy et al. study Original cohort Switzerland original study 1997-2001 ±25 'insurable' deaths Expanded study Italy 5% Canada UK 5% 2% Spain 8% Switzerland 9% France 41% Netherlands 12% based on the ART-CC database USA 18% 17 cohorts in 8 countries longer period of analysis 1997-2008 over 55 000 patients with known CD4+ count and viral load count at 6 months after starting ART ±600 'insurable' deaths (roughly 45% of the data) generalized linear model (GLM) analysis relative to insured population 40

Underwriting issues Assessment of future compliance past compliance opinion of specialist physician Assessment of quality of medical care Co-morbidities some more obvious than others drug interactions Accelerated aging future mortality due to 'normal' causes but at an earlier age 41

Pricing issues We have just over 10 years data how do we extrapolate another 10? With guaranteed rates no room for future adjustments as we learn Policyholder behaviour is likely to be completely different normal pricing relies on a fair amount of lapses HIV+ lives likely to have considerably different behaviour New products/rates in the future anti-selective lapsing forced to follow good experience but can't adjust for poor experience 42

Insuring HIV+ Available in many forms already. Treatment as a normal rateable impairment within sight. 43

Thank you

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