Download CROI 2006

Current State of Infectious
Diseases in Southern Africa
Diana Dickinson
Overview
HIV epidemic) already dealt with, just a few personal
TB
) insights
Pneumococcus in detail
Other regional problems
– Malaria
– Hepatitis B
– Herpes Simplex
– Cervical cancer associated with HPV
– KS associated with HHSV8
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Challenges of coping with the increases
and changing pattern of disease
How modellers fit in at every stage
– Planning
– Changing policy.
– Evaluating…
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
A global view of HIV infection
38.6 million people [33.4‒46.0 million] living with HIV, 2005
HIV prevalence (%) in adults
2.4
People living with HIV……….38.6 million
– Children
2.3
New HIV infections in 2005… 4.1 million
– Children
.54
Deaths due to AIDS in 2005.. 2.8 million
– Children
.38
– NB 1/3 of all HIV deaths are in Southern
Africa
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Estimated number of people living with HIV and adult HIV prevalence
Global HIV epidemic, 1990‒2005*
Number of people
living with HIV (millions)
HIV epidemic in sub-Saharan Africa,
1985‒2005*
% HIV prevalence,
adult (15‒49)
50
5.0
40
4.0
30
3.0
20
Number of people
living with HIV (millions)
% HIV prevalence,
adult (15‒49)
30
15.0
25
12.5
20
10.0
15
7.5
10
5.0
5
2.5
0
0.0
2.0
10
1.0
0
0.0
1990
1995
2000
2005
1985
1990
Number of people living with HIV
% HIV prevalence, adult (15-49)
This bar indicates the range around the estimate
1995
2000
2005
*Even though the HIV prevalence rates have
stabilized in sub-Saharan Africa, the actual
number of people infected continues to grow
because of population growth. Applying the
same prevalence rate to a growing population
will result in increasing numbers of people living
with HIV.
2.2
Impact of AIDS on life expectancy in five African countries, 1970–2010
70
65
Botswana
60
55
South Africa
Life
50
expectancy
45
at birth
40
(years)
Swaziland
Zambia
35
30
Zimbabwe
25
20
1970–1975
1980–1985
1990–1995
2000–2005
1975–1980
1985–1990
1995–2000
2005–2010
Source: United Nations Population Division (2004). World Population Prospects: The 2004 Revision, database.
4.1
People in sub-Saharan Africa on antiretroviral treatment
as percentage of those in need, 2002–2005
2005
2002
2003
2004
Source: WHO/UNAIDS (2005). Progress on global access to HIV antiretroviral therapy: An update on “3 by 5.”
7.2
Age-specific prevalence of HIV in pregnant
women, Botswana Sentinel Survey 2005
2003
22.8
38.6
49.7
45.9
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
41.5
34.4
So what influenced Botswana to be the trend setters???
Obviously the foresight and wisdom of Botswana’s
leaders, but aided by…
Brian Gazzard, Lisbon IAS 1999
-projection of reduction of costs when HIV is treated
The Durban AIDS Conference with Jeffrey Sach’s
projection on how NO developing country could afford
NOT to treat HIV
Projected population graph with AIDS unchecked
Lifetime risk of acquiring HIV of a 15 year old boy
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Age in years
Projected population structure with and
without the AIDS epidemic, Botswana, 2020
80
75
70
65
60
55
50
45
40
35
30
25
20
15
10
5
0
Projected population
structure in 2020
Males
140 120 100 80
Females
60
40
20
0
20
40
60
80 100 120 140
Population (thousands)
Source: US Census Bureau, World Population Profile
2000
Deficits due to AIDS
Lifetime risk of AIDS death for 15-year-old boys,
assuming unchanged or halved risk of becoming
infected with HIV, selected countries
100%
Risk of dying of AIDS
90%
Botswana
80%
Zimbabwe
70%
60%
50%
Côte d’Ivoire
Cambodia
Burkina
20% Faso
10%
0%
Zimbabwe
South Africa
Zambia
Kenya
40%
30%
Botswana
South Africa
Zambia
0%
risk halved over next 15 years
current level of risk maintained
Kenya
Côte d’Ivoire
Cambodia
Burkina Faso
5%
10%
15%
20%
25%
30%
35%
Current adult HIV prevalence rate
Source: Zaba B, 2000 (unpublished data)
40%
TB (CROI 2006)
2003
9,000,000 new cases
4,000,000 smear positive
2,000,000 deaths
Global TB incidence growing at 1% per year
Risk of TB 5-15% per year HIV + (50x HIV-)
Anthony Harries Malawi, Ministry of
Health
Reported TB Case Rate Botswana, 1975–2004
and HIV Prevalence Antenatal Women, 1992-2005
45
40
600
HIV
35
500
30
400
25
TB
20
300
15
200
10
100
5
0
19
75
19
77
19
79
19
81
19
83
19
85
19
87
19
89
19
91
19
93
19
95
19
97
19
99
20
01
20
03
20
05
0
Year
09/2006 TB Unit Ministry of Health
Botswana
HIV seroprevalence (%)
TB Case Rate (per 100,000)
700
Malawi illustrates this-- note
increasing smear negative cases
30% treatment success and 60% mortality
30-40% of all HIV deaths in Africa are due to
TB usually diagnosed postmortem
Lucas 1993 Cote d’Ivoire
– 40% of HIV wasted patients who died had TB
Lewis 2005 Malawi
– 10% of HIV patients with severe anemia had
disseminated TB diagnosed by bone marrow
C/S
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Malawi- 1999
– 2979 Health workers died- 50% TB
- 40% AIDS
– 105 TB control officers died
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Outcomes of TB in Malawi
HIV +ve only 20% still alive 2 years after
diagnosis (No treatment for HIV then)
HIV neg 50% only still alive at 7 yrs
11-12% of TB notifications
recurrences/relapse- strong HIV
association
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Outcomes of Isoniazid Prophylaxis (IPT) on
Incidence of TB
IPT Reduces TB risk 40% (Wilkinson, BMJ 1998)
IPT Reduces risk of recurrence 50-80% (Churchyard
AIDS 2003, Fitzgerald Lancet 2000)
HAART reduces TB risk but NOT back to normal
If patient has NO HAART
9.7 risk of TB per 100 pt yrs
If patient on HAART
2.4 TB cases /100 pt yrs- Badri Lancet 2001
continues reducing to 1% by 5 yrs Lawn
AIDS 2005
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Deaths due to TB
60% of TB deaths in 1st 2 months
Early HAART after 2 weeks reduces
deaths
However Increased IRIS with possible
deaths with early HAART in first 3m
A balance has to be struck
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
What about other respiratory
diseases?
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Pneumococcal invasive illness has
escalated in our region…
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Changing Patterns of Pneumococcal
Infection in Southern Africa
Generally Increasing prevalence of invasive
pneumococcal illness in developing countries. In RSA it
seems to have replaced Haemophilus Influenza in LRTIs
– Now 74% vs 12.9% Hib- reverse ratio
Increased prevalence of Paediatric (invasive) serotypes
in HIV+ patients
Increased mortality-65% with meningitis Malawi
-20% with pneumonia
Increased symptoms and signs with HIV+ patients
– Pleurisy, haemoptysis, diarrhoea, meningitis,
Degree of risk CD4 driven
– average CD4 in patients who died was 110 vs 170 in survivors
Keith Klugman CROI 2006
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Pneumococcal pneumonia is a disease of the very young and very old giving a U
shaped curve in Western countries
Percentage of distribution of deaths by age in southern Africa,
1985–1990 and 2000–2005
40
35
30
25
Percentage
of total deaths 20
15
10
5
0
0–4
5–19
20–29
30–39
40–49
50–59
60+
Age-groups
:
1985-1990
2000-2005
Source: Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat (2005).
World Population Prospects: The 2004 Revision. Highlights. New York: United Nations.
4.2
Note, modellers!
Risks now have changed– HIV+ (Lost immunity to paediatric strains)
– Young women
– Small child in home
– Health worker
– Abuse of drugs,
– smoking or alcohol
Antibiotic resistance and severity of illness
increase with HIV
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Morbidity reduced with HAART
– Spain, rate of invasive pneumococcal disease
dropped from 24.1/1000 in 1985 to 2/1000
(We have yet to see those results in Southern
Africa)
– However still increased risk X 30 to 35x
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Pneumococcal vaccine
Normal paediatric pneumococcal vaccine
reduces prevalence of paediatric
serotypes and greatly reduces risk
However other less virulent strains replace
them
Note- NOT the 23 valent vaccine- seemed
to increase morbidity in Rakai- ? Due to
severe immunocompromisation?
Mahdi et al CID 2005, 40,1511-18
Burden of disease in adults reduced by
vaccination of children (USA)
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Malaria
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Malaria
Clinical Manifestations vary depending if occurs in stable or unstable
transmission areas
– Unstable
acute febrile disease, cerebral malaria and death;
still birth and abortion in pregnant women
– Stable
Children chronic recurrent infections with anemia and growth retardation
Adults acquired immunity, asymptomatic,
Pregnant women, increased foetal growth retardation and increased infant
mortality
Severity in adults and children invariably aggravated by HIV,
especially in unstable areas; with increased risk of Intensive care
and death (Cohen CID 2005, Grimwald Ped Inf Disease 2003)
Infants in stable areas get more frequent and severe anaemia (van
Eijke,AJTMH,2002)
LaurenceSlutsker Kenya Med Res
Station, Kisumu CROI 2006
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Cotrimoxazole Prophylaxis
Ugandan cohort Lancet 2004 70% reduction of
morbidity rate of severe malaria
Mali 97% efficacy to prevent infection in
HIV neg children
Abidjan (Anglaret Lancet 1999) 5-6% reduction of
morbidity
W Kenya- decreases in level of
parasitaemia
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Effect of HIV on malaria
3 million excess cases
5% increase of malaria deaths(65,000)
Increases parasitaemia with increasing
immunosuppression, reduced clearance ability
Under 5 yrs of age, 1.7 fold increase in clinical
disease
Max impact in unstable transmission areas
– Botswana, Namibia, Zimbabwe. South Africa
– Incidence increased 28% (14-40.7%)
– Deaths increased 114% (37-188%)
–
Emergent Infectious Diseases 2005
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Effect of Malaria on HIV
Reversible increase viral load (2 fold in
pregnancy)
Malawi- increased neonatal mortality (AIDS
1999)
Possible reduction in CD4
No evidence of mother to child
transmission increase
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Hepatitis B
Worldwide huge burden
– 2 billion people infected
– 400 million chronic infection
– 500,000 to 1 million deaths annually
Chronic hepatitis
Cirrhosis
Hepatocellular carcinoma
Jean Nachega
Subsaharan Africa
Horizontal transmission (Infected older siblings)
Acquired mainly between 6 months and 5 yrs
Some sexual transmission
– Most exposed to HBV as children before HIV
exposure
Some perinatal transmission (+ or- HIV)
Coinfection with HIV may result in
– Reactivation of infection in silent chronic carriers
– New HBV infection as protective immunity lost with
HIV
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
HOWEVER
– Botswana our own stats show 40% incidence
of exposure but <1% hepB sAG positive
Increased risk of Haart related hepatotoxicity
Increased liver related mortality
IDCC no longer screens for this as numbers are so
small there is no impact on disease management
– South Africa 2 studies concur
41-43.3% evidence of previous or current infection
Liver International 2005;25:201-213
AIDS Read 2004;14(3):122-137
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Kaposi Sarcoma
HHSV8 associated
– Men more common in West
– Similar prevalence of HHSv8 in M and F in sub saharan Africa
Incidence risen in Zimbabwe from
– 2.3/100,000 in males and 0.3/100,000 in females pre HIV
– Now 48/100,000 and 18/100,000 in 2001
Incidence risen in Uganda by 20 or 30 times in the last 2
decades, 81% HIV+
Incidence increased in South Africa by 2 (??)
Women seem to have more aggressive and symptomatic
disease ?due to increased cytokines. Maybe biological
difference?
Meditz U Zimbabwe
Robert Newton Univ of York UK
Cervical Cancer
Associated with oncogenic Human Papilloma Virus
Increases in Africa across all age groups
– Uganda, increases predate HIV epidemic
An international Collaboration on HIV and Ca Cervix showed 1.88
increased incidence and no change with HAART
HIV-infected women more likely than HIV-negative women to be
coinfected with HPV 1
– (58% vs 24%; P < .01)
HIV infected women more likely to have multiple strains of HPV
(clearance of HPV affected)
HIV-infected women more likely to have high-risk HPV infection 1
– (23% vs 14%; P < .01)
1 Duerr A, Paramsothy P, Jamieson DJ, et al. Effect of HIV infection on atypical squamous cells of undetermined significance. Clin
Infect Dis. 2006;42:855-861.
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Genital Herpes
Herpes Simplex 2 responsible for
recurrent outbreaks of genital herpes
Increases HIV shedding in HIV+ patients
Increases infectiousness of HIV+ and the
likelihood of infection in HIV- patient
exposed to HIV (upregulates mucosal
immune activity)
HIV increases severity of lesions and
duration
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Other infectious diseases with
differences
Toxoplasmosis
– COMMON opportunistic Infection in the west
– <1% among our HIV patients
Cytomegalovirus
– Causes devastating disease in very immune
compromised people, may result in blindness
– 50-65% previous exposure in the west
– 99.5% Botswana
Cryptococcus
– Very common in our setting
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Diarrhoea in HIV+ patients
Cryptosporidium
Microsporidium
Isospora Belli
Salmonella, recurrent- not easily cleared
As well as all the usual causes of diarrhoea
Botswana has recently had a country wide epidemic of
Cryptosporidium and enteropathogenic E Coli
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Where does all this lead to?
Where do modellers come in??
We need to be able to INFLUENCE
POLICY- you can help us there
We need to be able to
– predict the changing faces of the different
diseases
– Evaluate different prevention strategies
– Evaluate different treatment interventions
– Prioritise
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
We need you for
Programme Planning
–
–
–
–
Costs of prevention and testing
Costs of treatment, both of HIV but other diseases
Costs of laboratory tests, diagnostic and monitoring
Human resource management, number of health
workers required in different situations
– Education of Health Care Workers, costs and
personnel needed
– Social programmes necessary
Orphan care, education
Feeding programmes
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
And for the fun things?
Modelling even paints fitness landscapes
of individual HIV viruses and enables
prediction of resistance mutation patterns
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
I don’t know what we could do without you!
We would be struggling at an individual
level to make an impact
You paint the bigger picture
With you we can crack this epidemic, you
have already shown the way!
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling
Thank You for listening
Thankyou also to Florence Doualla Bell
– Who enabled you not to sit through 90
minutes today!!
Sala Sintle
09/2006 Facing the Challenges of
Infectious Diseases in Africa- the Role
of Mathematical Modelling