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Secondary Data Usage
Osamah Hamouda, MD, MPH
Dept. for Infectious Disease Epidemiology
Robert Koch Institute, Berlin
DFG Roundtable Discussion
„Public Health Research in Germany“
January 20-21 2014, Bonn
Federal Health Agencies
Ministry of Health
Robert Koch Institut (RKI)
disease control and prevention
Paul Ehrlich Institut (PEI)
licensing of vaccines and immunological
medical products
Bundesamt für Arzneimittel und
Medizinprodukte (BfArM)
licensing of drugs and medical products
Bundeszentrale für gesundheitliche
Aufklärung (BZgA)
health promotion
Deutsches Institut für medizinische
Dokumentation und Information (DIMDI)
medical documentation and information
Ministry of Agriculture and Consumer Protection
Friedrich Loeffler Institut (FLI)
animal health
Bundesinstitut für Risikobewertung (BfR)
risk assessment for food and other
products
Ministry for the Environment, Nature Conservation and Nuclear Safety
Umweltbundesamt (UBA)
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environmental safety
Public Health Research in Germany
Objectives and mission
•
Health Monitoring
•
Surveillance of notifiable infectious disease
•
Sentinel surveillance
•
Epidemiological research projects
•
Guidance (recommendations)
•
Concepts for disease prevention
•
Training programme in infectious disease epidemiology
•
advisory committees
•
European and International networks (ECDC, WHO)
24 h / 7 d on-call duty service / assist in outbreak investigation
•
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Public Health Research in Germany
Data scources
Primary data
•
National Surveillance data on reportable infectious diseases
•
Sentinel surveillance
•
Epidemiological research projects
•
National Health Surveys
Secondary data
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•
Associations of Statutory Health Insurance Practitioners
(ASHIPs, KVen)
•
Morbi RSA
•
billing data from pharmacies
•
CoD Statistics
Public Health Research in Germany
Data on vaccination coverage and
incidence of vaccine-preventable diseases
Background
• annual school entry examinations at age 5-7 yrs are
only continuous and nationwide legally enforced source
for vaccination coverage data
• not all vaccine-preventable diseases notifiable
• underreporting exists in the national passive
surveillance system
• Evaluate the performance/impact of national
immunization program
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Public Health Research in Germany
Research project: vaccination monitoring
utilizing health insurance claims data
 Project partners: RKI and all 17 Associations of Statutory Health Insurance
Practitioners (ASHIPs; KVen) funding BMG (2014)
 Utilization of ASHIP routine data (billing data of practitioners)
 Data covers ~85% of German population
 Data transfer: 500 million anonymized data sets per year (ID, vaccination codes, ICD-10
diagnosis codes, physician contact dates, sex, age, etc.)
 ASHIP-generated IDs ensure data protection but allow for cohort analysis
(consolidation of vaccinations and diagnoses to single-patient level)
Vaccination
coverage
Practitioner
ASHIP
Statutory health
insured patients
85% pop.
Practitioner
RKI
Practitioner
ASHIP
Practitioner
Incidences and
disease burden
Vaccine
effectiveness
Measles vaccination coverage: estimates
from retrospective cohort study
Vaccination coverage [%]
Cross-sectional, nationwide
(Rieck et al. Human Vaccines & Immunotherapeutics 2014; 10:27- 26)
Birth cohorts
2004-2009;
Age:24 months /
36 months
Measles vaccination coverage: estimates
from retrospective cohort study
Regional, districts in Baden-Württemberg
Birth cohort 2008,
Age: 24 months
Vaccination coverage
2nd dose measles [%]
(Rieck et al. Human Vaccines & Immunotherapeutics 2014; 10:27- 26)
Measles vaccination coverage: estimates
from retrospective cohort study
Longitudinal, Schleswig-Holstein
1 dose
2 doses
Birth cohorts
2004-2009
(Rieck et al. Human Vaccines & Immunotherapeutics 2014; 10:27- 26)
Cattle density and STEC incidence
in Germany
Background
•
In Germany, ~1,000 human Shiga Toxin-producing E. coli (STEC) cases
notified annually
•
Large differences in STEC incidence by geographic region.
•
Cattle important reservoir für STEC O157
•
Spatial ecological studies:
geographic variation in disease risk and its association with
explanatory variables measured at spatial unit level (eg, districts).
Objective
Is there an association between cattle density and STEC incidence among
humans for
– all STEC serogroups combined?
– specific serogroups?
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Public Health Research in Germany
Cattle density and STEC incidence
in Germany
Methods
Data sources
• National surveillance data
– STEC cases 2001-2003, n = 2,280
– Incidences by district
•
Data on cattle density (National database)
(Herkunftssicherungs- und Informationssystem für Tiere, HIT)
– Heads of cattle per km2 by district
Statistical methods: Poisson regression
– Modelling of STEC incidence considering:
cattle density, district, age group, week of notification, seasonal variation
Frank C, Kapfhammer S, Werber D, Stark K, Held L. Cattle density and Shiga toxin-producing Escherichia
coli infection in Germany: increased risk for most but not all serogroups.
Vector Borne Zoonotic Dis. 2008 Oct;8(5):635-43.
Distribution of STEC incidence and cattle
density in Germany
STEC incidence
Cattle density
Frank C, et al. Vector Borne Zoonotic Dis. 2008
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Public Health Research in Germany
Cattle density and STEC incidence
in Germany
Results and discussion
•
Living in districts with higher cattle density significantly increased the STEC
risk.
Risk increased by 68% per 100 cattle / km2
•
This applies to all serogroups analysed
(except for O91: different risk factors?).
•
The results are stable in different models.
•
Secondary data in combination with surveillance data are useful for modelling.
•
No conclusions possible regarding risk factors on the individual level.
•
However, important information about the impact of direct and indirect contact
to cattle in STEC transmission.
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Public Health Research in Germany
Hantavirus infections:
Background and Epidemiology
•
Hantaviruses are rodent borne hemorrhagic fever viruses with a world wide distribution.
Human infection through inhalation of virus particles.
•
High spatio-temporal variability of disease incidence due to fluctuations in abundance of
the reservoir animals.
Hantavirus infections
Ecological Regression of Hantavirus
Incidence, Germany 2002-2012*
Data sources
•
•
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Objective
dependent variable:
Hantavirus incidence
(RKI surveillance data)
independent variables:
– Tree species distribution - Federal
Forest Inventory data - Thünen
Institute
– Yearly tree fructification data - Forest
condition surveys – Thünen institue
– CORINE land cover raster data –
German Aerospace Centre (DLR)
– State and county borders - Federal
Agency for Cartography and Geodesy
(BKG)
•
quantify influence of
environmental factors on space
time distribution of HTV infections
to aid in outbreak prediction
Methods
•
•
Generalized additive model
containing a 2D-spline to smooth
point-samples to county values.
Ecological regression, Bayesian
model with spatial effects
(Schrödle and Held, 2011, 2010)
*Faber, Stark, Höhle (RKI), Hilbrig, Polley (Thünen Institute), unpublished
Public Health Research in Germany
Hantavirus infections
Ecological Regression of Hantavirus
Incidence, Germany 2002-2012*
Preliminary results and conclusions
•
Strong predictors of hantavirus incidence:
– proportion of county area covered by beech forest
– proportion of beech trees showing medium or strong fructification in the previous
year
•
Possible opportunity for:
– prediction of hantavirus outbreaks in space and time
– targeted recommendations to the public
– prevention
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Public Health Research in Germany
Secondary analysis of vital registration data
•
Vital registration statistics
–
–
•
•
(1) non-official part of the death certificate contains
cause of death (primary data use: stats about most
frequent cause of death by age, …)
(2) official part of the death certificate contains age, sex,
week of death. Primary data use: calculation and
forecasting of demographic indicators
(1) suitable for retrospective estimation of deaths
associated with influenza (e.g. through modeling of
all respiratory deaths)
(2) suitable for real-time monitoring of excess deaths,
relevant e.g. in the case of influenza pandemics or
bioterror attacks
(1)
(2)
Chlamydia trachomatis (CT) infection
•
Most frequent sexually transmitted infection
•
Often asymptomatic (up to 80% females and 50% males)
•
Serious long-term complications possible
– Pelvic inflammatory disease (PID) in 5-40%:
 tubal blockage
 infertility and ectopic pregnancies
– Epididymitis with infertility
•
Screening for women < 25 yrs introduced in 2008 G-BA
•
Not reportable (exept Sachsen)
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Public Health Research in Germany
Analysis of the
Chlamydia trachomatis laboratory sentinel
Background
Evaluation of representativeness of the Chlamydia trachomatis (CT)
laboratory sentinel using CT accounting data of the National Association
of Statutory Health Insurance Physicians (Kassenärztliche
Bundesvereinigung (KBV); NASHIP)
Approach
• Primary data: CT tests within the laboratory sentinel
• Secondary data: NASHIP data of accounted CT tests of patients with
statutory health insurance
Aim
• Calculate the percentages of all CT tests conducted in Germany
detected by the laboratory sentinel
• Determine coverage of CT Screening
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Public Health Research in Germany
Results of the secondary data analysis
SECONDARY
??? DATA
NASHIP Data:
Number
of
2,964,346 CT tests
CT oftests
= 85.9%
all CT tests
in Germany
in Germany
PRIMARY DATA
CT laboratory
sentinel data:
1,126,073 CT
tests
Data weighting:
Sentinel data * 0.859
/ NASHIP data
= 32.6% Coverage
 Regional coverage:
 Good coverage (over 20%) in most of the federal states (11 of 16)
 Poor coverage (under 10%) in only 1 federal state (Baden-Württemberg)
 Gender specific coverage: better coverage of women (42.9%) than of men (23.4%)
Results were used to develop a recruitment plan for further CT data collection.
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Public Health Research in Germany
Opportunistic CT-screening
by age-group and time*
*data
as of 27.11.2012, for 2012
quartal 1 and 2
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Public Health Research in Germany
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Positivity rate by age-group
and test reason
12%
Opportunistic screening (n= 230,829)
Positivity rate
10%
Screening in pregnancy (n=432,604)
Diagnostic test (n=286,748)
8%
6%
4%
2%
0%
< 15
15<20
20<26
26<30
Age-group
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Public Health Research in Germany
30<35
35<40
40+
Coverage of opportunistic
CT-screening
Opportunistic
screening
(n=231,568)
19.3%
Diagnostic
(n=289,863)
24.1%
Screening
in pregnancy
(n=434,785)
36.2%
In general population*:
7 women 15-25 years old
per 1 pregnant women
CT sentinel data:
0.5 women 15-25 years old
(opportunistic screening)
per 1 pregnant women (screening in
pregnancy)
→ Opportunistic screening
coverage 8%
* 4,500,000 women 15-25 years old (2011), 665,000
Pregnant women (2011)
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Public Health Research in Germany
Estimating HIV Prevalence and
number of PLWHA under ART
Background
• Measuring HIV incidence and prevalence is difficult
• Important for guiding public Health decision making
• Targeting prevention and health services
Approach
• Estimate HIV incidence, prevalence and number of PLWHA under
ART using
– surveillance data
– mortality statistics data
– antiretroviral therapy billing data from pharmacies
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Public Health Research in Germany
Geschätzte Gesamtzahl der HIV-Neuinfektionen in
Deutschland nach Infektionsjahr und
Transmissionsrisiko
6000
HIV-NeuInfektionen bei MSM
5000
HIV-NeuInfektionen bei IVD
HIV-NeuInfektionen bei Hetero (Inland)
Anzahl
4000
3000
2000
1000
0
Jahr der Infektion
Estimating the number of death with HIV
using causes of death statistics
Death with HIV from
causes of death statistics
stratified by sex and 5-years
age group
Death with HIV from
AIDS case register
stratified by sex, 5-years age
group and transmission group
Maximum number
in each stratum of
sex and 5-year age group
Estimated number of
death with HIV
stratified by sex, 5-years age group and
transmission group (imputed with
multiple imputation)
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Public Health Research in Germany
Estimated number of people living with
HIV/AIDS in Germany
100.000
Anzahl
80.000
HIV-Prävalenz
HIV-Prävalenz - Gesamt (untere Schranke)
HIV-Prävalenz - Gesamt (obere Schranke)
60.000
40.000
20.000
0
(ohne Hämophile/ Transfusionsempfänger und perinatal
infizierte Kinder)
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Jahr
Public Health Research in Germany
Determine the number of persons receiving
antiretroviral therapy (ART) in Germany
using information on
therapy regimes from
ClinSurv data *
Antiretroviral prescription data (APD)
by pharmacy billing centres
Number of persons
receiving ART in
Germany
 covering >99% of prescriptions of
persons with statutory health insurance
(SHI)
* Additional adjustment for exotic ART regimes and ART interruptions necessary
(Assumption: ClinSurv is representative)
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Public Health Research in Germany
Determine the number of persons receiving
antiretroviral therapy (ART) in Germany
60000
100%
90%
50000
40000
80%
70%
60%
30000
50%
SHI (TCM) 90 days
SHI (TCM) 30 days
Treated patients (seasonal adjusted)
40%
20000
10000
30%
SHI (TCM) seasonal adjusted
SHI (TCM)
20%
10%
0
•
•
•
•
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0%
Number of persons with statutory health insurance (SHI) receiving ART SHI (TCM)
Due to seasonal fluctuations in prescriptions SHI (TCM) were seasonal adjusted
All persons receiving ART in Germany (including non-TCM, interruptions and non-SHI)
Prescribed formulations changed over time, packages for 90 days increased
Public Health Research in Germany
Number of people living with HIV/AIDS in Germany
and proportion diagnosed and under ART, 2001 - 2012
Anzahl
Anteil
80.000
100%
80%
60.000
Unter Therapie
Diagnostiziert, ohne
Therapie
Nicht Diagnostiziert
60%
40.000
40%
20.000
20%
0
0%
Jahr
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Public Health Research in Germany
Anteil unter Therapie
bezogen auf alle
Diagnostizierten
Anteil unter Therapie
bezogen auf alle
Infizierten
Thanks for your
attention
Vielen Dank für Ihr
Interesse
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