CHOLHUA , March 2015 Jean-Marc Fix, FSA, MAAA, VP, R&D HIV? CHOLHUA , March 2015 Jean-Marc Fix, FSA, MAAA, VP, R&D

Why not? The End

Is a segment of the HIV-infected population insurable? CHOLHUA , March 2015 Jean-Marc Fix, FSA, MAAA, VP, R&D

Agenda What is HIV infection? Evolution of HIV infection mortality Evolution of HIV infection treatment Segmentation of HIV-infected population Mortality of the better segments Underwriting skills Unknowns and risk mitigation strategies

Face of a killer

Face of a killer

Face of a killer

Face of a killer

Face of a killer

A Close-up

Video- Infection https://www.youtube.com/watch?v=RO8MP3wMvqg 4’08”

Infectious pathway Men having sex with men Heterosexual Intravenous drug user Blood product (transfusion, hemophilia) Occupational

Infectious pathway -Men Source: HIV AIDS Surveillance vol 19 CDC

Infectious pathway -Women Source: HIV AIDS Surveillance vol 19 CDC

Source: Gill et al, Clin Infect Dis 2010 What kills? Depletion of CD4+ T helper cells Loss of immune protection AIDS defining diseases ~50% (1) Liver disease (hepatitis co-infection) Infection (non AIDS defining) Cancer (non AIDS defining) Cardiovascular Drug overdose, accident, suicide Source: Gill et al, Clin Infect Dis 2010

Together in Life and Death What we remember 1985 AIDS Is Top Cause of Death for Young Adults in U.S. Disturbing report by federal agency San Francisco Chronicle 2/1/95 Together in Life and Death San Ramon pair die of AIDS 2 days apart… Ray, 58, and Peggy, 54, of San Ramon, died earlier this month after battling the disease for five years. They were buried Monday in the same grave. SFC 2/1/95 2001 1992 Hunting for the Hidden Killers: AIDS Time Magazine 7/4/83

Total: 33,4 millones (31,1 – 35,8 millones) Número estimado de adultos y niños que vivían con el VIH en 2008 Europa oriental y Asia central 1,5 millones [1,4 – 1,7 millones] Europa occidental y central 850 000 [710 000 – 970 000] América del Norte 1,4 millones [1,2 – 1,6 millones] Asia oriental 850 000 [700 000 – 1,0 millones] África del Norte y Oriente Medio 310 000 [250 000 – 380 000] Caribe 240 000 [220 000 – 260 000] Asia meridional y sudoriental 3,8 millones [3,4 – 4,3 millones] África subsahariana 22,4 millones [20,8 – 24,1 millones] América Latina 2,0 millones [1,8 – 2,2 millones] Oceanía 59 000 [51 000 – 68 000] Total: 33,4 millones (31,1 – 35,8 millones)

HIV mortality

HIV deaths

What we should be hearing Managing HIV as a Chronic Disease South Afr j of HIV Med 2004 When AIDS became a chronic disease West J Med 2000 HIV: Now a Manageable Chronic Disease Pharmacy Times 2007 Comprehensive Clinical Care: Managing HIV as a Chronic Illness AIDS Clinical Care Journalwatch retrieved July 2010

HIV mortality

Trends in Annual Age-Adjusted Trends in Annual Age-Adjusted* Rate of Death Due to HIV Infection, United States, 1987−2010 Note: For comparison with data for 1999 and later years, data for 1987−1998 were modified to account for ICD-10 rules instead of ICD-9 rules. *Standard: age distribution of 2000 US population

Source: Pallella et al, J Acq Immune Def Syndr 2006 Advances in treatment Source: Pallella et al, J Acq Immune Def Syndr 2006

HAART Highly Active Antiretroviral Treatment Latest is triple cocktail, for ART naïve patients: NNRTI + 2 NRTI: Atripla and Complera Ritonavir boosted PI + 2 NRTI INSTI + 2 NRTI NRTI = nuclesos(t)ide reverse transcriptase inhibitor NNRTI = non-nucleoside reverse trans. inhib. PI = protease inhib. INSTI = integrase strand transfer inhib. Source: Guidelines for the use of antiretroviral agents in HIV-1 infected adults and adolescents DHHS as of 3/15

Video-Treatment https://www.youtube.com/watch?v=RO8MP3wMvqg 4’09”

Advances in treatment

Action path of treatment

Action path of treatment

(1): Marsden and Zack J Antimicrob Chemo 2009 HIV reservoirs CD4+ memory T-cell Can stay inactive and virus dormant for many years Under current therapy: 60+ years to clear the virus (1) (1): Marsden and Zack J Antimicrob Chemo 2009

Variables for mortality Age Gender Smoking Income CD4+ cell count Viral load Time since infection Response to treatment Quality of follow-up Infection source

Source: Pallella et al NEJM 1998 Mortality by therapy When: 1994-1997 Where: 8 cities in US Who:12% IDU, 12% Females, MSM decreasing to 65% Severity: All had CD4+ cell counts below 100/mm3 Significant treatment change in 1996 Source: Pallella et al NEJM 1998

Mortality by therapy RR death or morbidity None vs. Monotherapy 1.5 None vs. combo 2.9 None vs. combo with protease inhibitor 4.5 Source: Pallella et al NEJM 1998

Source: Bashkaran et al, JAMA 2008 Mortality evolution When: 1981-2006 Where: 23 cohorts in Europe, Australia, Canada Who:18% IDU, 22% Females, MSM 57% Severity: Since seroconversion Follow-up: median 6.3 (range 1 day to 23.8 years) Source: Bashkaran et al, JAMA 2008

Source: Bashkaran et al, JAMA 2008 Mortality evolution Deaths Pre 1996 1996-97 1998-99 2000-01 2002-03 2004-06 Expected 56 28 33 39 41 37 Observed 1332 481 231 212 188 127 Obs/Exp 24 17 7.0 5.5 4.6 3.4 Source: Bashkaran et al, JAMA 2008

Source: Bashkaran et al, JAMA 2008 Mortality evolution Source: Bashkaran et al, JAMA 2008

Source: Bashkaran et al, JAMA 2008 Mortality evolution Source: Bashkaran et al, JAMA 2008

Source: adapted from Table 4, Bashkaran et al, JAMA 2008 Mortality by age Ratio observed to expected mortality by age, 15 year after seroconversion Age at seroconversion 1996-1997 2004-2006 15-24 3720% 736% 25-34 2225% 375% 35-44 3728% 150% 45+ na 192% Source: adapted from Table 4, Bashkaran et al, JAMA 2008

Source: Lewden et al, J Acq Immune Def Syndr 2007 Mortality by segment 7 year post cART France, first treated with PI 1997-99 Overall: SMR 7.0 Men 4.8 Women 13.0 HCV status Positive: 13.9 Negative: 4.4 HIV transmission IV drugs 16.3 Other 5.5 Source: Lewden et al, J Acq Immune Def Syndr 2007

Source: Lewden et al, J Acq Immune Def Syndr 2007 Mortality by segment CD4+ count cells/mm3 SMR 500+ 2.5 350-499 3.5 200-349 5.6 <200 30.3 Source: Lewden et al, J Acq Immune Def Syndr 2007

Source: Lewden et al, J Acq Immune Def Syndr 2007 Mortality by segment Source: Lewden et al, J Acq Immune Def Syndr 2007

Mortality by age, CD4+ count and viral load Monte Carlo simulation model Includes HIV resistance evolution with treatment Calibrated from a US cohort (CHORUS, less IDU, less non-white) Validated against VA study (more IDU, more non-white) Source: Braithwaite et al, Am J of Med 2005

Source: Braithwaite et al, Am J of Med 2005 Modeling flowchart Source: Braithwaite et al, Am J of Med 2005

Source: from Braithwaite et al, Am J of Med 2005 Mortality Age 30 Age CD4+ (cells/mm^3) Viral load /ml Median survival Mort Mult (men) 30 800 10,000 31.30 400% 100,000 23.70 x 1,000,000 17.20 500 26.80 21.20 14.60 200 21.90 18.10 12.20 Source: from Braithwaite et al, Am J of Med 2005

Source: from Braithwaite et al, Am J of Med 2005 Mortality Age 40 Age CD4+ (cells/mm^3) Viral load /ml Median survival Mort Mult (men) 40 800 10,000 28.00 250% 100,000 22.60 425% 1,000,000 15.20 x 500 24.40 350% 18.90 14.00 200 19.70 15.50 10.90 Source: from Braithwaite et al, Am J of Med 2005

Source: from Braithwaite et al, Am J of Med 2005 Mortality Age 50 Age CD4+ (cells/mm^3) Viral load /ml Median survival Mort Mult (men) 50 800 10,000 22.30 200% 100,000 20.30 250% 1,000,000 14.30 x 500 21.10 225% 17.70 325% 12.90 200 16.50 375% 14.60 500% 10.20 Source: from Braithwaite et al, Am J of Med 2005

HAART treatment consequences Dyslipidemia Insulin resistance/diabetes Endothelial dysfunction Altered fat distribution More AMI in HIV + Source: Triant et al, J Clin Endocrinol Metab 2007

HAART treatment consequences HIV + HIV - Ratio Heart Attack Rates per 1000 PY 18-34 4.65 0.88 528% 35-44 10.13 3.34 303% 45-54 18.74 7.56 248% 55-64 33.39 14.78 226% 65-74 77.68 24.47 317% 75-84 43.63 36.47 120% Source: Triant et al, J Clin Endocrinol Metab 2007

Data limitations- the bad news Atherosclerotic cardiovascular conditions take a long time to manifest themselves

Underwriting skill-the good news Cardiovascular risk: our best skill set and treating physician are now well aware of the risk Hepatitis co-infection (Hep. B &C) IDU We CAN identify the best risks

Coronary heart disease risk in HIV % increase in risk HIV+ 1 HIV+ 2 HIV – (7) Age - per year 9% 6% 6-9% Sex – M vs F N/A 110% 110-160% Diabetes – Yes vs No 260% 90% 140-252% Smoking – Yes vs No 140% 290% 70-290% Hypertension –Yes vs No 30% 80% 80-90% Tot Chol - per 1mmol/L 26% 25-33% HDL chol. - per 1mmol/L -28% -52% Source: Schambelan et al, Circulation 2008

The best Age: older is better Behavior: no drugs, how HIV acquired Income: higher is better HIV characteristics: CD4+ cell count and viral load Treatment: timing, quality, response, follow-up, adherence Documentation: available and plentiful

Unknowns and risk mitigation strategies Full underwriting Shorter term or shorter term equivalent coverage? Limit the face amount Reinsure

Potential Treatment Venues Don’t get infected Kill the virus Prevent entry of the virus in the cell Prevent normal virus intracellular processes Prevent viability of cell produced virus Kill infected active cells Kill infected latent cells Prevent CD4+ cell depletion

Kill the Virus Immune response boosters: cytokines, interferon, monoclonal antibodies, vaccine, gene therapy

Prevent Virus Entry Prevent entry of the virus Block access on T cell CD4 CCR5 CXCR4 Block connectors from virus Block fusion Cleave connectors: abzyme

Prevent Normal Virus Process Viral decay accelerator Innate antiretroviral factor

Prevent viability of cell produced virus Maturation inhibitors Env targeted cytotoxin (Berger 6/10) Gag cleavage (Adamson, 8/09) CA-CA interaction (ibid.) Zinc finger inhibitors

Maybe one day Kill infected active cells Kill infected latent cells Prevent CD4+ cell depletion Gene therapy Vaccine

Updates Better understanding of CD4 cell death due to HIV infection of nearby cells and drug blocking that death and an existing drug blocking that effect (Doitsh, Nature 2013) In monkeys, gene therapy ups the natural defenses against HIV (Gardner, Nature 2015)

Questions?