Modelling the risk of emerging infections for blood transfusion

Transcription

1 Modelling the risk of emerging infections for blood transfusion Welling Oei Transfusion Technology Assessment (TTA) Group UMC Utrecht / Sanquin Blood Supply Foundation NVB TRIP symposium Ede, 17 May 2017 Health Sciences and Primary Care

2 Why modelling? A number of transmission by blood transfusion (TT) of emerging infectious disease (EID) was documented. Evidence for the TT risk available late. Consequences of implementing additional measures. TT risk of some EID has been estimated using models. A generic model that can timely estimate the TT risk is desirable. Modelling (emerging) Infections in the Transfusion CHain (MITCH) to provide decision support models that quantify decision elements that play a role in the decision making with respect to blood safety measures to be taken in case of outbreaks of EID.

3 Achievements 1) A quantitative model for ranking/rating the risk of emerging infections with known or unknown disease characteristics 2) A quantitative model to estimate the number of transmissions by blood donors given an outbreak of an emerging infectious disease

4 Risk prioritisation of EID Literature review of emerging infectious diseases (EID) in transfusion medicine Development of a risk prioritization algorithm Invite experts to participate in disease ranking exercise: expert meeting and web-based ranking 99% Unknown Likely Very likely 75% 50% Possible 25% 1% Unlikely Very unlikely

5 Value of the risk prioritisation model The application can support a more transparent rational decision making process Provides an objective prioritisation of transmission risks based on the best possible ranking by a group of experts The risk model can be used to: rank known EIDs prioritise unknown EIDs (incorporating lack of available information) Health Sciences and Primary Care Oei et al. A consensus based tool for ranking the risk of blood transmissible infections. Transfusion Neslo et al. Insight into calculated risk: An application to the prioritization of emerging infectious diseases for blood transfusion safety. Risk Anal

6 The EUFRAT model European Up-Front Risk Assessment Tool (EUFRAT) a web-based calculator for estimating the crude risk of receiving contaminated blood donations for a range of communicable diseases in outbreak situations Oei et al. Modelling the transmission risk of emerging infectious diseases through blood transfusion. Transfusion Oei et al. Estimating the transfusion transmission risk of Q fever. Transfusion 2014.

7 Modelling the transfusion chain from donor population to blood products derived STEP 1: Disease and outbreak STEP 2: Donor screening and donation testing STEP 3: Blood component production STEP 4: Recipient population and disease outcome

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9 EUFRAT update: travellers risk Oei et al. Modelling the risk of transfusion transmission from travelling donors. BMC Inf Dis 2016.

10 Model validation: Dengue in Surinam and the Dutch Caribbean I EUFRAT risk estimate 1) infections in outbreak region 2) travellers exposure (number of travellers per year, duration of visit) 3) proportion of donors among travellers 4) calculate expected number of infected donors II Validation estimate 1) Dengue infections identified in Dutch laboratories 2) travel history to Surinam or Dutch Caribbean 3) proportion of donors among travellers 4) calculate expected number of infected donors III Compare estimates Health Sciences and Primary Care

11 Model validation: Dengue in Surinam and the Dutch Caribbean Description Suriname (95%CI) Cumulative number of infected travelling donors in estimated by EUFRAT model 1 ( ) Dutch Caribbean (95%CI) ( ) Cumulative number of infected travelling donors in inferred from infections in the general Dutch population (lab-based study) ( ) 28.5 ( ) Ratio of EUFRAT vs lab-based study estimates Oei et al. Estimating the risk of dengue transmission from Dutch blood donors travelling to Suriname and the Dutch Caribbean. Vox Sang Cleton et al. Using routine diagnostic data as a method of surveillance of arboviral infection in travellers. Travel.Med.Infect.Dis. 2014

12 Value of the EUFRAT model The EUFRAT risk model is an simple, easily accessible model, requiring a minimum of inputs It allows obtaining risk estimates with relatively little data Quantification of transfusion risks allows putting these risks into perspective Allows estimating future as well as past transmissions by donors which may guide intervention and communication and strategies More detailed assessments can be made if so desired using the same modelling approach EUFRAT s outcomes are in agreement with other studies

13 Why modelling? Answers Transparent Timely Rational decisions

14 Acknowledgements Sanquin Blood Supply Foundation European Centre for Disease Prevention and Control (ECDC) Mart Janssen ~ UMC Utrecht, Sanquin Prof. Mirjam Kretzschmar ~ UMC Utrecht, RIVM Prof. Hans Zaaijer ~ Sanquin, AMC Prof. Roel Coutinho ~ UMC Utrecht, RIVM Rabin Neslo ~ UMC Utrecht Ryanne Lieshout ~ Sanquin Tonderai Mapako ~ UMC Groningen Pieternel Pasker-de Jong ~ Sanquin Renee van Hulst ~ UMC Groningen Karin Habets ~ Sanquin Yaskara Halabi ~ Suriname Sybille Rehmet ~ ECDC Beatrix Jubithana ~ Suriname Jim van Steenbergen ~ RIVM Izzy Gerstenbluth ~ Dutch Caribbean Cees L. van der Poel ~ Sanquin E Maduro ~ Dutch Caribbean Daniel Lewandowski ~ UMC Utrecht Maribelle Tromp ~ Dutch Caribbean Health Sciences and Primary Care