Surveillance of gastroenteritis using drug sales data in France Mathilde Pivette, PharmD, MPH Pr Avner Bar-Hen Dr Pascal Crépey.

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Presentation transcript:

Surveillance of gastroenteritis using drug sales data in France Mathilde Pivette, PharmD, MPH Pr Avner Bar-Hen Dr Pascal Crépey Dr Judith Mueller EHESP Young Researcher Forum, Brussels, 13 th November

Context Drug sales o Non-specific surveillance data o Outbreak detection o Infectious disease surveillance Gastroenteritis o High frequency disease o ~ 3 millions GP consultations o hospitalizations < 5 years old EHESP 2

Objective To assess the value of drug sales data as an early epidemic detection tool for gastroenteritis in France o By assessing correlation with reference data o By determining if drug data could provide an early signal of seasonal outbreak o By assessing prospective outbreak detection EHESP 3

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) EHESP 4

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 EHESP 5 Selection of 8 groups (256 products) Reference data Sentinel network of 1300 GP throughout France ( Acute diarrhea cases reported each week

EHESP 6 Sales of drugs for gastroenteritis and number of reported cases (Sentinel network), , France Results Prescribed drugs / cases Non prescribed drugs/ cases Coefficient correlation r 0,890,77 Time lag (week) 0 Cross-correlation

EHESP 7 Epidemics detection o Detection Method : Serfling method Epidemic periods Periodic baseline level Upper limit of the CI : threshold o Evaluation : Detection window : Start of epidemic from Sentinel network +/- 4 weeks Evaluation criteria: Sensitivity False alert rate Timeliness Selection of model parameters that optimize the 3 criteria

EHESP 8 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: weeks (min -3; median -2.5, max -1) Detection week (Drugs)

EHESP 9 The selected detection model for prescribed drugs allows the detection of seasonal outbreaks 0.2 weeks earlier 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) Drug sales

EHESP 10 Prospective detection during Detection of epidemic 3 weeks earlier than sentinel network in Non-prescribed Drug sales Threshold Detection week (Drugs) Training period

11 EHESP Example of the 2012/2013 seasonal epidemic. 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. Next step : regional analyses

EHESP Discussion 12 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

Limits o Selection of indicator drugs : specificity o Use of medications vary by demographic factors o Population source not precisely known : incidence ? EHESP 13 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 Advantages

Conclusion Useful and valid tool for real-time monitoring of GI Earlier indicator of gastroenteritis outbreak Other infectious diseases EHESP 14

Thank you QUESTIONS ? EHESP 15

EHESP 16

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 ANNEXES

EHESP 18 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: weeks (min - 3; median -2.5, max -1)

EHESP 19 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)