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International Health Care Management Part 2a Steffen Fleßa Institute of Health Care Management University of Greifswald 1 Structure 1 2 3 4 International Public Health Demand for Health Services Supply of Health Services Health Systems and Reforms 2 2 Demand for Health Services 2.1 Determinants of Demand 2.1.1 Health Economic Framework 2.1.2 History of Epidemiologic Concepts 2.1.3 Excursus: Measuring Quality of Life 2.2 Demographic and Epidemiologic Transition 2.3 Epidemiology of Infectious Diseases 3 2.1.1 Health Economic Framework 4 OBJECTIVE SCARCITY OF HEALTH 5 OBJECTIVE SCARCITY OF HEALTH SUBJECTIVE EXPERIENCE OF SCARCITY = NEED 6 OBJECTIVE SCARCITY OF HEALTH SUBJECTIVE EXPERIENCE OF SCARCITY = NEED WANT 7 OBJECTIVE SCARCITY OF HEALTH SUBJECTIVE EXPERIENCE OF SCARCITY = NEED WANT DEMAND 8 Demography Infectious Diseases Chronic Degenerative Diseases OBJECTIVE SCARCITY OF HEALTH SUBJECTIVE EXPERIENCE OF SCARCITY = NEED WANT DEMAND 9 Demography Infectious Diseases Chronic Degenerative Diseases Health Education OBJECTIVE SCARCITY OF HEALTH SUBJECTIVE EXPERIENCE OF SCARCITY = NEED WANT DEMAND 10 Demography Infectious Diseases Chronic Degenerative Diseases Health Education Affordability Health Budgets of Private Households Price Policy Health Insurance Loss of Distance Benefit Quality Measurement Safeguarding OBJECTIVE SCARCITY OF HEALTH SUBJECTIVE EXPERIENCE OF SCARCITY = NEED WANT DEMAND 11 2.1.2 History of Epidemiologic Concepts Age Causal Model Concepts of Health Health Indicators 1900 Single-Cause-Model Ecological-Model (Infectious (Agent-HostDiseases) Environment) 1920 Multiple-CauseModel (Infectious Diseases, Transition to Chronic Diseases) Social-EcologyModel (HostEnvironmentBehavior) Mortality Morbidity (Prevalence, Incidence) Work-Related Dimensions of Invalidity (Inability to Work, Disability) 12 Age Causal Model 1940 1970 Multiple-CauseModel Multiple-EffectModel (Chronic Diseases) Concepts of Health Health Indicators WHO-Model: Complete Physical, Mental, Social Wellbeing Risk-Factor-Model Holistic Model (Environment, Biology, Lifestyle, Health Care System) WHO-Model: „Health for all by 2000“ Dimensions of Risk Factors (Smoking, Alcohol, Cancer Registry,...) 13 Age Causal Model 1980 1990 Multiple-CauseMultiple-Effect Model (Social Transformation Disease Cycle) Concepts of Health Health Indicators Wellness-Model (Increasing Conditions of Wellness) WHO: Health Promotion Developing Healthy Policies Dimensions of Wellness, Quality of Life (QALY) Dimensions of Equity Dimensions for Social Index (cf. Dever 1991) 14 Example: Attention Deficit – Hyperactivity Syndrome (ADHS) • Symptoms: – Low attention span – Impulsiveness – Hyperactivity (partial); „Dreamer“ – Starts before the age of 6 • Occurrence: – 3-5% of the population; 1:3 female:male 15 ADHS • Causes (Risk Factors) – Genetic: Abnormality of the cerebral ability to process signals (fragile X-Syndrome) – Complications during pregnancy and birth – Low birth weight – Infection – Pollutants – Illness or injury of the central nervous system – Bad parenting, negligence • No direct correlation between cause and effect 16 2.1.3 Excursus: Measuring Quality of Life • Dimensions of Individual Quality of Life – Analogue model – Questionnaires • i.e. SF-12, SF-36 • Standardized Dimensions of Quality of Life – Rosser-Matrix – Quality Adjusted Life Years – Disability Adjusted Life Years 17 Analogue Model 100 0 18 Example: SF-36 3. Do you experience limitations in performing the following activities due to your state of health? If so, to what degree? 3.a strenuous activities, i.e. walking fast, lifting heavy objects, strenuous physical activity 3.b Moderate activities, i.e. moving a table, vacuuming, bowling, playing golf 3.c Lifting and carrying grocery bags 3.d Climbing several flights of stairs 3.e Climbing one flight of stairs Yes, severe limitations Yes, some limitations No, no limitations 1 2 3 19 SF-36 (http://www.bodytechniques.com/pdf/Health%20Survey.pdf) 20 Rosser Matrix Pain Impairment I. No impairment A: Painless B: Slight Pain C: Moderate D : Severe Pain Pain 1,000 0,995 0,990 0,967 II. Slight Social Impairment 0,990 0,986 0,973 0,932 III. More Severe Social Impairment 0,980 0,972 0,956 0,912 IV. More Severe I. of the Ability to Work 0,964 0,956 0,942 0,870 V. Inability to Work 0,946 0,935 0,900 0,700 VI. Inability to Move without Assistance 0,875 0,845 0,680 0 VII. Bedrest 0,677 0,564 0 -1,486 VIII. Coma -1,028 - - - 21 States of Health According to DALYs State of Health Rating of State of Health Limited capability of performing at least one activity in one of the following areas: relaxation, education, procreation, profession 0.096 Limited capability of performing most activities in one of the following areas: relaxation, education, procreation, profession 0.220 Limited capability of performing activities in two or three of the following areas: relaxation, education, procreation, profession 0.400 Limited capability of performing most activities in all four areas 0.600 Need for assistance in instrumental activities of daily life, i.e. preparing meals, grocery shopping, household chores 0.810 Need for assistance in activities of daily life, i.e. eating, personal hygiene, toilette 0.920 Death 1.000 22 DALYs (http://www.who.int/healthinfo/global_burden_disease/GBD2004_DisabilityWeights.pdf) 23 Disability Weight and Culture • Example: Vitiligo – chronic skin disease – Loss of pigment – European: low disability – African/Asian: strong disability • Frequently confused with leprosy • International disability weight is wrong! 24 Remaining Life Expectancy according to DALYs Age 0 1 5 10 15 20 25 30 35 Male 80.00 79.36 75.38 70.40 65.41 60.44 55.47 50.51 45.57 Female 82.50 81.84 77.95 72.99 68.02 63.08 58.17 53.27 48.38 25 Age 40 45 50 55 60 65 70 75 80 85 90 95 Male 40.64 35.77 30.99 26.32 21.81 17.50 13.58 10.17 7.45 5.24 3.54 2.31 Female 43.53 38.72 33.99 29.37 24.83 20.44 16.20 12.28 8.90 6.22 4.25 2.89 26 Relative Value of One Year of Life Value of One Year of Life in the Calculation of DALYs 2 1.5 1 0.5 0 0 20 40 60 80 100 Age 27 At a discounting rate of 3 % and the described age adjustment the loss of DALYs due to illness or disability can be described accordingly: D L a x Value of state of health according to the table Period of physical disability; respectively loss of years lived due to premature death Age of starting physical impairment; respectively year of death Age 28 Global Burden of Disease 2004 N <15 DALYs p. 1000 30-45 DALYs p. 1000 15-19 DALYs p. 1000 >45 DALYs p. 1000 20-29 DALYs p. 1000 No data Keine Angabe 29 2.2 Demographic and Epidemiologic Transition 30 Demographic and Epidemiologic Transition 31 32 33 34 Indicator / Country Tanzania Thailand Germany Japan 7 2 2 2 Gross Birth Rate 4,8 % 2,1 % 1,1 % 1,1 % Gross Mortality Rate 1,5 % 0,6 % 1,1 % 0,7 % Gross Growth Rate 3,3 % 1,5 % 0% 0,4 % Population Density [people per km²] 31 112 227 332 12,6 % 3,3 % 0,7 % 0,6 % Children per Woman Child Mortality 35 Concept of Demographic Transition Rate Gross Birth Rate Gross Mortality Rate 5% 1% Phase I Phase II Phase III Phase IV Phase V Time 36 Determinants of Birth Rates Level of Education in Women Cultural and religious imprinting Agricultural System/ Water / Fuels Benefit Motive Work Force Motive Desire for Children in Women Old-Age Insurance Desire for Children in Men Security Motive Level of Education in Men Male Dominance A Couple’s Desire for Children 37 Determinants of Birth Rates Cost of Contraceptives Ability to Conceive / Fertility A Couple’s Desire for Children Acceptance of Contraceptives Use of Contraceptives Nutritional Situation Conception Abortion Rate Maternal Mortality Ability to Stay Pregnant Diseases BIRTHS 38 Epidemiologic Transition Transition of Mortality in North Carolina Rate/100.000 Cancer, Cardiac Diseases 300 200 100 Influenza, Pneumonia, TBC 1920 1930 1940 1950 1960 1970 1980 Time [years]39 Development of Morbidity in Vietnam 1976-2001 70 Proportion [%] 60 50 40 30 20 10 0 1976 1981 1986 1991 1996 2001 Time [years] Infectious Diseases Chronic-degenerative Diseases Accidents 40 Development of Morbidity in Vietnam 1976-2001 70 Proportion [%] 60 50 40 30 20 10 0 1976 1981 1986 1991 1996 2001 Time [years] Infectious Diseases Chronic-degenerative Diseases Accidents 41 Model of Susceptibility Susceptibility Birth 10 20 … 50 60 70 80 Time [years] Chronic-degenerative Diseases Infectious Diseases 42 Proportion of Population Incidence and Prevalence [%] 100 80 60 40 20 0 0 20 Healthy 40 60 Time[years] Infectious Diseases 80 100 120 Chronic-degenerative Diseases 43 Incidence and Prevalence [%] Prevalence and Incidence of Infectious and Chronic-Degenerative Diseases 100 80 60 40 20 0 0 20 Incidence, Infectious Diseases Prevalence, Infectious Diseases 40 60 Time [years] 80 100 120 Incidence, Chronic-degenerative Diseases Prevalence, Chronic-degenerative Diseases 44 2.3 Epidemiology of Infectious Diseases 2.3.1 Background • Paths of Transmission – Symbols: Human Animal Vector 45 Paths of Transmission 1. Direct Transmission from Human to Human, i.e. Influenza, AIDS 2. Directly Transmitted Zoonoses, Human as aberrant host, i.e. Brucellosis 3. Vector-borne Human Diseases, i.e. Malaria 4. Vector-borne Zoonoses, i.e. TBE 46 Paths of Transmission 5. Vector-borne AnthropoidZoonoses, i.e. Plague, Yellow Fever 1 2 6. Transmission via Intermediate Host, i.e. Bilharzia 47 Examples 1.Directly Transmitted Diseases from Human to Human AIDS, Leprosy, Cholera, Amoeba, TBC, Syphilis, Ebola, Marburg, Pocks, Measles, Hepatitis A,B,C 2.Directly Transmitted Diseases from Animal to Human • Brucellosis, BSE (possibly?) 48 Hosts Aberrant Host: A subject that can be infected but not a transmitter of a disease, that means the infection ends with that subject. The aberrant host can die of the infection after a short period which does not affect the cycle. Final Host: The final host is integrated in the agent’s maturing cycle since the agent reaches full maturity inside the host. The final host is not to die (or not to die fast) as a result of the infection otherwise the disease faces extinction. 49 Hosts (cont.) Intermediate Host: The intermediate host is included in the cycle. The agent reaches a premature state inside the host. The intermediate host is to survive for a longer period than the agent requires to reach prematurity. Transport Host: Transports the agent physically. 50 Hosts (cont.) Accumulating Host: Accumulate the agent without them changing in maturity. Reservoir: An animal population that “stores” the agent without developing symptoms. 51 Examples (cont.) 3. Vector-borne Human Diseases • Malaria, Onchocerciasis 4. Vector-borne Zoonoses, Human as Aberrant Host • Cestoda (Dogs, Pigs, Cows, Fox), TBE, Lyme Disease 5. Vector-borne Anthropoid-Zoonoses (Transmission from Animal Reservoir) • Plague, Yellow Fever, Narcolepsy 6. Transmission via Intermediate Host • Schistosomiasis (=Bilharzias) 52 Epidemiologic Course: Constant Virus Measles Masern 53 Time Zeit Mutating Virus: Kilbourne Model Cases Immunity Pandemic Epidemic Endemic Time Influenza A1 Influenza A2 Group Immunity 54 Influenza (2015) 5., 7. 9. Woche 2015 55 Influenza 2015 (RKI) Praxisindex = number of consultations for acute respiratory infects compared to annual average Week of year 56 Conditions for Pandemics • • • „New“ agent within a population that shows low immunity • Infiltration, i.e. Plague • New Agent, i.e. Influenza Rapid Spread Low Lethality • Mortality of a disease referring to the proportion of fatalities to total number of sick people • High lethality results in the extinction of a disease before it is able to spread 57 Infiltration, i.e. Plague Plague (1347-1352) – Possibly originating in Central Asia – Infiltration to Europe via salesmen and ships – Spread in whole of Europe – Estimated 25 million fatalities (1/3 of the European population) – Theory: various diseases at the same time: Ruhr, TBC, Typhus, Influenza, Pocks http://www.scilogs.de/blogs/gallery/25/Pestilence_spreading_13471351_europe.png 58 Loss in Population in Central Europe Caused by Plague (14th+15th century) Source: http://www.yersiniapestis.info/geschichte.html 59 Plague • Thirty Years War (1618-48) – Recurring plague – Reduction of the population by 1/3 due to plague and war – Pattern: weakened population (i.e. famine, war) is especially prone to disease • Today: • Worldwide spread almost completely preventable thanks to antibiotics • Extinction impossible due to reservoirs in animals 60 Infiltration • AIDS (since 1980) – – – – Possibly originating in Africa Infiltration through migration, tourism etc. (under debate!) Worldwide spread, >20 million fatalities At present no cure 61 http://www.mapsharing.org/MS-maps/map-pages-worldmap/7-world-map-aids.html Emergence of New Viruses • Simultaneous Infection of a Host With Two Virus Strains – Danger of recombination through exchange of genetic material – Emergence of new, highly pathogen virus 62 Spanish Influenza (1918-1920) • Influenza A H1N1 • 25-50 Mio. Fatalities National Museum of Health and Medicine, Armed Forces Institute of Pathology, Washington, D.C., http://www.planet-schule.de/sf/multimedia/animationen/schweinegrippe/html/media/bild_spanischegrippe.jpg 165-WW-269B-25-police- 63 Bird Flu Worldwide Wild Birds Poultry Humans Spread of Avian Influenza / Bird Flu (as of April 8th, 2006) 64 Main Routes of Bird Migration Wild Birds Poultry Humans Spread of Avian Influenza / Bird Flu (as of April 8th, 2006) http://going-to-korea.blogspot.com/ 65 Swine Flu Worldwide http://gamapserver.who.int/h1n1/cases-deaths/h1n1_casesdeaths.html 66 http://www.innovationsreport.de/html/berichte/medizin_gesundheit/bericht-34912.html Flight Routes: faster than ever… 67 In Comparison: Spread of the 7th Cholera Epidemic http://www.bertelsmannbkk.de/fileadmin/Redakteure/Bilder/gesundheitslexikon/5 06693.jpg 68 Ebola • officially: Ebola virus disease (EVD; Ebola hemorrhagic fever (EHF)) • Victims: humans and primates • Cause: Ebolavirus • Infection: body fluids (blood!) • Natural reservoir: fruit bats • Incubation period: 2-21 days • Symptoms: fever, sore throat, pain, vomiting, diarrhea, liver and kidney failure, internal and external bleeding 69 Cases of ebola fever in Africa from 1979 to 2008. 70 www.cdc.org West-Africa Outbreak 2014 71 Ebola 2014 72 Ebola 2014 73 Major problems • Dysfunctional health care system • Culture (e.g. burial rite) • Fear and rejection of population • … Primarily Ebola is not a medical problem! 74 http://www.ecdc.europa.eu/en/data-tools/Pages/home.aspx 75 Determinants of Epidemiology • • • • • • • Temperature Altitude Precipitation Waterways Migration (Animals) Relief Division of Labor Men/Women • • • • • • Geographical Mobility Clothing Buildings Settlements Marriage Belief in Predestination 76 Course of Disease: Latency, Incubation, Convalescence Symptoms Period spent in Sickness Convalescence Latency Period Infection Seroconversion Incubation Period Time Outbreak 77 Vector Active Vector Infectivity Passive Vector Period spent in Sickness Latency Period Incubation Period Infection Seroconversion Outbreak Symptomless Time 78 2.3.2 Malaria • Background: – Agent: Plasmodium (single cell organism) – Disease: Malaria (parasitosis) – Vector: Anopheles – Under Risk: 36 % of worldwide population (> 2 billion people) 79 Case Figures 2010 • Incidence: 216 million (official) cases – Over-Reporting: Fever = Malaria? – Under-Reporting: not treated, not diagnosed, … – 174 million cases (81%) in Africa • Fatalities: – 655 000 – 91% in Africa – 86% of all fatalities are children under age 5 • Development 2000-2010 – Incidence: - 27% – Mortality: -26% World Malaria Report 201180 Temperature (°C) Malaria a „Intermittent Fever“ Day 91% of all cases and almost 100% of fatalities caused by Malaria Tropica (Plasmodium falciparum) 81 Worldwide Malaria Spread 3000 km N Not at Risk for Malaria Low Risk for Malaria High Risk for Malaria 82 Based on www.worldmalariareport.org/node/57 Cases of Malaria in Germany 1000 900 Cases of Malaria 800 700 600 500 400 300 200 100 0 1996 1998 2000 2002 2004 2006 2008 2010 2012 Time [Years] http://www.rki.de/DE/Content/Infekt/EpidBull/Archiv/2012/Ausgaben/43_12.pdf?__blob=publicationFile 83 Monthly Cases of Malaria in Mlowa Bwawani 1996 (own survey) Time [Months] Cases of Malaria 84 Precipitation, Anopheles and Malaria Cases of Malaria Anopheles-Population Precipitation 1 2 3 4 5 6 7 8 9 10 11 12 [Month] 85 Prevalence of Malaria in Tanzania 86 Malaria Prevalence in Tanzania (by Region) 2011/12 KENYA Simon (2013) based on National Burreau of Statistics, Dar-es-Salaam 87 http://www.giveapint.org/wp-content/uploads/2013/12/Cambodia.pdf Malaria Protective Recommendations Cambodia 88 Economic Significance of Malaria • Loss of 10 Man-Days per Case of Malaria • Strong Seasonal Fluctuation • Malaria Control Programs – Malaria Eradication Program – Roll-Back-Malaria (WHO) 89 Occupancy Rate Daily Occupancy Rate of Karatu Hospital 1995 Time [Days] 90 Plasmodium Life Cycle 91 Chloroquine-Resistence 92 Prognosis of Dynamic Systems • Concepts: – Biometric Models – Analytic Models – Markov-Models – System Dynamics Models 93 Bio / Econometric Models y ui y (xi,yi) x x 94 Analytic Models, i.e. Ross-McDonald-Model m a b1 b2 e R0 r 2 • • • • • • • R0 m a b1 b2 r • • • • • • • t basic reproductive rate number of mosquitos number of bites infection risk of humans infection risk of mosquito recovery rate of humans mortality of mosquito 95 Markov-Models a 12 a a w2 21 a a w1 a a 32 41 w4 23 31 a a 42 14 a a 24 34 13 w3 a43 96 Markov-Model w t 1 w t A w1 w t ... ; w n a11 a12 a 21 a 22 A an1 an 2 w t w 0 A ... a1n ... a 2 n ... ann w t 1 w t A t 97 System Dynamics Model Imaginary Source Growth in t 98 System Dynamics of Anopheles Imaginary Source Growth in t Population 99 System Dynamics of Anopheles Imaginary Source Rate Growth in t Population 100 System Dynamics of a Population Bt t Bt Bt Bt 0,05 * Bt Year Population (Bt) 0 Bo=100.000 1 105.000 2 110.250 3 115.763 4 121.551 5 127.628 6 134.010 7 140.710 8 147.746 9 155.133 10 162.889 101 System Dynamics of Anopheles Imaginary source Eggs in t, t+1 102 System Dynamics of Anopheles Imaginary source Eggs in t, t+1 Larvae in t 103 System Dynamics of Anopheles Imaginary source Eggs in t, t+1 Larvae in t Anopheles in t 104 System Dynamics of Anopheles Imaginary source fertility Eggs in t, t+1 Larvae in t Anopheles in t 105 Variance Seasonal Influences on the Population of Anopheles Time [Months] Anoph. Region 1 Temperature Anoph. Region 2 Precipitation 106 Incidence Prevalence Prevalence and Incidence (in % of Population) Time [Days] Incidence Prevalence 107 Anopheles Population and Malaria Prevalence Mosquitoes Time [Months] Anopheles Malaria 108 Infections Infections and In-door-Spraying Time [Years] 109 Infections Sustainability of In-door-Spraying, Infections Time [Years] B=25 years B=5 years 110 Bed Net Programs Simon (2013) based on National Burreau of Statistics, Dar-es-Salaam 111 Infections Infections and Bed Net Programs Time [Years] 25 years 5 years 112 Infections Fatalities and Bed Net Programs, Region 2 Time [Years] 25 years 5 years 113 Anopheles Anopheles Population at Rising Temperatures Time [Years] Rise, R1 Rise, R2 114 Infections Infections at Rising Temperatures Time [Years] Rise, R1 Rise, R2 115 Infections Infections and El-Nino Time [Years] 116 Infections Infections and Resettlement Programs Time [Years] 117 Fatalities and Resettlement Programs Time [Years] 118 2.3.3 AIDS Cases of HIV and AIDS in Germany Estimated HIV/AIDS Incidence, Prevalence and Fatalities in Germany, by the end of 2010 (Model) HIV Prevalence (r) HIV Incidence (I) AIDS Incidence (I) HIV/AIDS Fatalities (I) Year Source: Robert Koch Institut 2009 119 newly diagnosed HIV infections 2008: 2.806 2007: 2.774 MSM: Men sex with Men IVDA: Intravenous Drug Abusers Hetero: Heterosexual Relationship HPL: High Prevalence Countries n.d. 120 Source: http://www.rki.de/DE/Content/InfAZ/H/HIVAIDS/Epidemiologie/Daten__und__Berichte/HIV-AIDS-Folien,templateId=raw,property=publicationFile.pdf/HIV-AIDS-Folien.pdf HIV Prevalence (RKI 2010) 121 HIV Prevalence Worldwide [in % of total population] 122 Aids Pandemic (WHO 2014) North America Western and Central Europe Eastern Europe and Central Asia Caribean Latin America Oceania East Asia South and South-East Asia Middle East and North Africa Sub-Saharan Africa 0 Aids in % of total population 5 10 15 20 People living with HIV ['000,000] 25 123 HIV Prevalence in Africa, 1982-97 [% of total population]* 0-0,5 % 1982 0,6-2,0 % 1987 2,1-8,0 % 8,1-16,0 % 1992 16,1-32 % 1997 Source: UNAIDS (1998a, S. 98036-E-12, 15.Juli 1998) *Inconsistencies in data may occur among the maps. 124 Age Distribution of Cases of AIDS 1400 25 1200 1000 20 Proportion Rate [Cases/100.000] 30 800 15 600 10 400 5 200 0 0 0 10 20 30 40 Age [Years] 50 60 Male, Cases Female, Cases Male, Rates Female, Rates 70 80 125 Distribution of Orphans http://www.mindfully.org/Reform/2003/AIDS-Orphans-Increase30jul03.htm 126 Non-Infected Gesundheitszustände Pre- and perinatal infection Infection via circumcision Infection via blood transfusion Infection via contaminated needles Infection via sexual intercourse HIV-Positive F(t) Incubation Period t AIDS F(u) Survival Period u Death 127 Population and AIDS Related Fatalities in Tanzania, Total 70.000.000 Population 60.000.000 50.000.000 40.000.000 30.000.000 20.000.000 10.000.000 0 1970 Population HIV-Infected Population w/o AIDS 1980 1990 2000 2010 2020 Time [Years] Healthy AIDS Fatalities, accumulated 128 Composition of Population 100% 60% 40% 20% Healthy 2016 2011 2006 2001 1996 1991 1986 1981 0% 1976 Proportion [%] 80% Time [Years] HIV Infected AIDS Patients 129 2500000 25000000 2000000 20000000 1500000 15000000 1000000 10000000 500000 5000000 0 1970 1980 1990 2000 2010 Accumulated Fatalitites Patients, Fatalities AIDS Patients and AIDS Related Fatalities 0 2020 Time [Years] AIDS Patients AIDS Fatalities AIDS Fatalities, accumulated 130 Proportion of Paths of Infection [%] Proportion of Paths of Infection 60 50 40 30 20 10 0 1980 1990 2000 2010 2020 Time [Years] Pra/perinatal Transfusion Once Partner 131 HIV Prevalence in the Compartments of 13-32 Year Olds HIV-Prevalence [%] 100 80 60 40 20 0 1980 1990 Male rural Female rural Professional Prostitutes 2000 Time [Years] 2010 2020 Male urban Female urban Occasional Prostitutes 132 States of Health of 250.000 HIV-positive Life Births 250.000 Population 200.000 150.000 100.000 50.000 0 0 2 4 6 8 10 12 Time [Years] HIV Infected AIDS Patients 133 HIV-Prevalence in the Compartments of 0-12 Year Olds 8 HIV-Prevalence [%] 7 6 5 4 3 2 1 0 1980 1985 1990 1995 2000 2005 2010 2015 2020 Time [Years] Boys rural Boys urban Girls rural Girls urban 134 120.000.000 6 100.000.000 5 80.000.000 4 60.000.000 3 40.000.000 2 20.000.000 1 0 1970 1980 1990 2000 2010 per Resident / per Healthy Person [US$] Direct Cost [US$] Direct Annual Cost of AIDS [US$] 0 2020 Time [Years] Direct Cost Direct Cost/Resident Direct Cost/Healthy Person 135 AIDS-Orphans in Tanzania 2500000 AIDS-Orphans 2000000 1500000 1000000 500000 0 1970 1980 1990 2000 2010 2020 Time [Years] Increase Amount 136 Consequences of Vaccination as of January 1st, 2001 60.000.000 7.000.000 50.000.000 6.000.000 40.000.000 5.000.000 30.000.000 4.000.000 3.000.000 20.000.000 2.000.000 10.000.000 1.000.000 0 1990 1995 HIV Infected 2000 2005 Time [Years] AIDS Patients 2010 2015 AIDS Fatalities 0 2020 Population 137 Population Infected, Patients, Fatalitites 8.000.000 AIDS-Patients AIDS Vaccination: Various Scenarios 2.000.000 1.800.000 1.600.000 1.400.000 1.200.000 1.000.000 800.000 600.000 400.000 200.000 0 1990 Standard 1995 2000 Vacc 2005 Time [Years] Half 2010 Short 2015 2020 Delayed 138 Behavioral Prevention: Various Scenarios 1.800.000 AIDS-Patients 1.600.000 1.400.000 1.200.000 1.000.000 800.000 600.000 2000 2005 2010 2015 2020 Time [Years] Standard Promis Teil Prost 139 2.500.000.000 140.000.000 120.000.000 2.000.000.000 100.000.000 1.500.000.000 80.000.000 1.000.000.000 60.000.000 40.000.000 500.000.000 0 2000 20.000.000 2005 2010 Condoms (Promis, Prost) Condoms (Maximum, Part) Annual Demand for Condoms in Tanzania 0 2020 2015 Time [Years] Maximum Teil Promis Prost 140 Cost Savings due to Use of Condoms (absolute) 40.000.000 30.000.000 Cost Difference 20.000.000 10.000.000 0 2000 -10.000.000 2005 2010 2015 2020 -20.000.000 -30.000.000 -40.000.000 Time [Years] Promis Part Prost 141 Quotient Cost Savings due to Use of Condoms (relative)* 15,0 14,0 13,0 12,0 11,0 10,0 9,0 8,0 7,0 6,0 5,0 4,0 3,0 2,0 1,0 0,0 2000 2005 2010 2015 2020 Time [Years] * Direct costs of treatment saved divided by costs of condoms. Promis Prost Part 142 AIDS Patients, Various Scenarios of Preor Perinatal Infection 1.800.000 AIDS-Patients 1.600.000 1.400.000 1.200.000 1.000.000 800.000 600.000 2000 2005 2010 2015 2020 Time [Years] Standard Half Three-Quarters Zero 143 Population, Various Scenarios of Pre- or Perinatal Infection 37.000.000 36.500.000 Population 36.000.000 35.500.000 35.000.000 34.500.000 34.000.000 33.500.000 33.000.000 2000 2005 Standard 2010 Time [Years] Half 2015 Three-Quarters 2020 Zero 144 Screening-Kits per Transfusion Screening Kits per Transfusion 3,2 3 2,8 2,6 2,4 2,2 2 1990 1995 2000 2005 2010 2015 2020 Time [Years] 145 Screening Costs [US$] 900000 Screening Costs [US$] 800000 700000 600000 500000 400000 300000 200000 100000 0 1990 1995 2000 2005 2010 2015 2020 Time [Years] 146 Antiretroviral Drugs: Curse or Blessing? • Application: – Prevention: Mother-to-Child Transmission – Cure • ART and HAART • Requirements (Availability, Nutrition, Black Market) • Risks – – – – Development of Resistance Compliance Sexual Behavior Opportunity Costs 147 ART: a Blessing … 148 … Which Still Does Not Reach Many! 149 Costs (source: Brot für die Welt) 150 HIV-neg. Pop Medical infectiveness + + infection rate + Health Care Budget Intended, Short-Term Effect of HAART + risk behaviour - resistance + HIV-pos. Pop HIV/AIDS-Budget direct costs of HAART + of HAART Efficiency + GNP HAART Cost-Efficiency - Resistance Monitoring incubation + - HAART•effectiveness Long Term??? Other diseases and infirmities FEAR + + + + indirect costs of AIDS + AIDS Pop + Other health care budget + Indirect Costs other diseases + + Direct Costs other diseases + survival + Intangible COI + Total COI+ + + direct costs of opportunistic infections Death 151 HIV-neg. Pop + Health Care Budget Medical infectiveness + + infection rate + risk behaviour - resistance + HIV-pos. Pop HIV/AIDS-Budget Resistance Monitoring HAART direct costs of HAART + + GNP - + Other health care budget incubation + - HAARTeffectiveness Other diseases and infirmities FEAR + + + + indirect costs of AIDS + AIDS Pop + Indirect Costs other diseases + + Direct Costs other diseases + survival + Intangible COI + Total COI+ + + direct costs of opportunistic infections Death 152 Ethics • Ethical Concepts – Consequential Ethics: Something that has good consequences in the long-term can be considered good? – Teleological Ethics: Something with a good intend can be considered good? 153