Young Researcher Forum, Brussels, 13th November 2013
Surveillance of gastroenteritis
using drug sales data in
France
Mathilde Pivette, PharmD, MPH
mathilde.pivette@ehesp.fr
Pr Avner Bar-Hen
Dr Pascal Crépey
Dr Judith Mueller
1
EHESP
Context
Drug sales
o Non-specific surveillance data
o Outbreak detection
o Infectious disease surveillance
Gastroenteritis
o
o
o
High frequency disease
~ 3 millions GP consultations
50 000 hospitalizations < 5 years old
2
EHESP
Objective
To assess the value of drug sales data as an
early epidemic detection tool for gastroenteritis
in France
o
o
o
By assessing correlation with reference data
By determining if drug data could provide an early signal of
seasonal outbreak
By assessing prospective outbreak detection
3
EHESP
Data
Stratified sample of pharmacies
•
•
•
•
•
1647 in 2009 to 4627 pharmacies in 2013 (20%)
Number of boxes sold of all products
Prescribed/ Non-prescribed
Data obtained at D+1
Geographic location of the pharmacies (region)
4
EHESP
Indicator drug selection
Intestinal antiinfectives antidiarrhoeals (A07A)
Intestinal adsorbents antidiarrhoeals (A07B)
Antidiarrheal microorganisms (A07F)
Other antidiarrheals (A07X)
Motility inhibitors (A07H)
Antiemetics and antinauseants (A04A9)
Oral rehydration solutions
Dietetic products for diarrhea and vomiting
Selection of 8 groups (256 products)
Reference data
• Sentinel network of 1300 GP throughout France
(www.sentiweb.fr)
• Acute diarrhea cases reported each week
5
EHESP
Results Sales of drugs for gastroenteritis and number of reported cases
Incidence of cases / boxes sold
for 100000 inhabitants
(Sentinel network), 2009-2012, France
2000
Reported cases
1800
Non-prescribed drugs
1600
Prescribed drugs
1400
1200
1000
800
600
400
200
0
Jan-09
Jul-09
Jan-10
Jul-10
Jan-11
Jul-11
Jan-12
Jul-12
Jan-13
Weeks
Cross-correlation
Prescribed drugs /
cases
Non prescribed drugs/
cases
Coefficient correlation r
0,89
0,77
Time lag (week)
0
-1
6
EHESP
Epidemics detection
Number of boxes sold for
100000 inhabitants
o Detection Method : Serfling method
Epidemic periods
1600
1400
1200
Upper limit
of the CI :
threshold
Periodic
baseline
level
1000
800
600
400
200
0
Jan-09
Jul-09
Jan-10
Jul-10
Jan-11
Jul-11
Jan-12
Jul-12
Jan-13
Weeks
o Evaluation :
• Detection window : Start of epidemic from Sentinel network +/- 4 weeks
• Evaluation criteria:
• Sensitivity
Selection of model parameters that
• False alert rate
optimize the 3 criteria
• Timeliness
EHESP
7
The selected detection model for non-prescribed drugs
allows the detection of seasonal outbreaks 2.25 weeks earlier
Number of boxes sold for 100000
inhabitants
1400
Detection performance of the selected model (IC 95%, cut-off 30%)
Sensitivity : 100%
False alert rate : 0%
Mean timeliness: -2.25 weeks (min -3; median -2.5, max -1)
1200
1000
800
600
400
200
0
Jan-09
Jul-09
Jan-10
Jul-10
Jan-11
Jul-11
Jan-12
Jul-12
Jan-13
Weeks
Epidemic period (Sentinel)
EHESP
Drug sales
Detection week (Drugs)
8
The selected detection model for prescribed drugs allows the
detection of seasonal outbreaks 0.2 weeks earlier
Number of boxes sold for 100000
inhabitants
2500
Detection performance of the selected model (IC 99%, cut-off 30%)
Sensitivity : 100%
False alert rate : 0%
Mean timeliness: -0.2 weeks (min -2; median 0, max +1)
2000
1500
1000
500
0
January-09
January-10
January-11
January-12
January-13
Weeks
Epidemic period (Drug) Drug sales
EHESP
Detection week (Drugs)
9
Prospective detection during 2012-2013
Detection of epidemic 3
weeks earlier than sentinel
network in 2012-2013
Number of drug sales /100,000
inhabitants
1600
1400
1200
Training period
1000
800
600
400
200
0
January-09
January-10
January-11
January-12
January-13
Week
Non-prescribed Drug sales
EHESP
Threshold
Detection week (Drugs)
10
Next step : regional analyses
Example of the 2012/2013 seasonal epidemic.
EHESP
First epidemic week from drug sales
First epidemic week from Sentinel network
Detection from non-prescribed drugs 3 weeks earlier than
detection from reference data, with a beginning at the east
of France.
11
Discussion
Confirmation of the potential of drug sales analysis
for gastroenteritis surveillance
o Prescribed drugs: high correlation with reported cases / No
benefit for early detection
o Adequacy between the 2 sources
o Non prescribed drugs :Detection on average 2,25 weeks
earlier (daily analysis: 16.7 days earlier, detection after 7 epidemics
days)
o Purchase of drugs during the early phase of illness
o Reflects patient behaviors
12
EHESP
Limits
o
o
o
Selection of indicator drugs : specificity
Use of medications vary by demographic factors
Population source not precisely known : incidence ?
Advantages
o Relevant tool to determine dynamics and detect outbreaks
o Reporting lag of one day
o rapid assessment of Public Health situation
o prospective analyses
o Automatically collection of data
13
EHESP
Conclusion
Useful and valid tool for real-time monitoring of GI
Earlier indicator of gastroenteritis outbreak
Other infectious diseases
14
EHESP
Thank you
QUESTIONS ?
15
EHESP
16
EHESP
ANNEXES
Epidemics detection
o Detection Method (Serfling method) :
• Periodic regression models
• Key parameters :
• highest pruning percentile (varying from
15% to 40%)
• prediction interval (varying from
90%,95%,99%)
• Number of consecutive weeks to detect an
epidemic
17
The selected detection model for non-prescribed drugs
allows the detection of seasonal outbreaks 2.25 weeks earlier
Detection performance of the
selected model (IC 95%, cut-off 30%)
Sensitivity : 100%
False alert rate : 0%
Mean timeliness: -2.25 weeks (min 3; median -2.5, max -1)
18
EHESP
The selected detection model for prescribed drugs allows the
detection of seasonal outbreaks 0.6 weeks earlier
Detection performance of the
selected model (IC 99%, cut-off 30%)
Sensitivity : 100%
False alert rate : 0%
Mean timeliness: -0.6 weeks (min -2;
median 0, max +1)
19
EHESP