Download Grundlagen der Gesundheitsökonomik

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Document related concepts

Sociality and disease transmission wikipedia, lookup

Neonatal infection wikipedia, lookup

Infection wikipedia, lookup

Germ theory of disease wikipedia, lookup

Eradication of infectious diseases wikipedia, lookup

Infection control wikipedia, lookup

Hygiene hypothesis wikipedia, lookup

Neglected tropical diseases wikipedia, lookup

Hospital-acquired infection wikipedia, lookup

Transmission (medicine) wikipedia, lookup

Globalization and disease wikipedia, lookup

Transcript
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