Online estimation of the risk of blood contamination
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1 Online estimation of the risk of blood contamination Welling Oei Transfusion Technology Assessment (TTA) Group Julius Center for Health Sciences and Primary Care, UMC Utrecht, The Netherlands IPFA/PEI 19th International Workshop on Surveillance and Screening of Blood Borne Pathogens 23 May 2012 Health Sciences and Primary Care Julius Center.nl
2 Julius Center.nl MITCH and EUFRAT projects Modelling emerging Infections in the Transfusion CHain (MITCH) to provide a decision support model that quantifies decision elements that play a role in the decision making with respect to blood safety measures to be taken in case of outbreaks of EIDs. European Up-Front Risk Assessment Tool (EUFRAT) to develop a web-based calculator for estimating the crude risk of receiving contaminated blood donations for a range of communicable diseases in outbreak situations.
3 Julius Center.nl Methods Literature review of emerging infectious diseases (EIDs) in transfusion medicine Development of a risk prioritization algorithm (70 diseases) Development of a generic model to quantify the risks of transfusion transmission of EIDs Organized an expert meeting to test the model and select most relevant EIDs to include in the model Convert the model into a web-based tool (EUFRAT) Test/validate the model with EID examples
4 Julius Center.nl EUFRAT: risk model scheme (Donor) population infectivity Donations Released components End products Recipients Population Donors Infected γ 1 γ 2 γ 3 Whole blood Plasma pheresis Platelet pheresis RBC Plasma recovered Platelets pooled Plasma-pheresis Platelet-pheresis RBC: 1/1 FFP: 1/1 Platelets: 5/1 FFP: 1/2 Platelets: 1/1 R E C I P I E N T S DHQ Testing Blood processes and interventions Prevalence of infection in (donor) population STEP 1 Number of Number of infected Number of infected Risk of infection infected donations released components end products in recipients STEP 2 STEP 3 STEP 4 STEP 5
5 EUFRAT --STEP 1-- Estimating the prevalence of infection in the donor population Course of epidemic Exposed population (N p ) (I p ) Number of infections Cases reported (I p ) Proportion of undetected cases (υ) Assessment interval (d) time (t) Course of infection Infectivity level Acute Proportion of acute cases developing chronic infection (κ) Acute infectious period (t a ) Chronic infectious period (t c ) P= I p R d (min( t N a p, d) min ( t d (1 ) c, d )) Health Sciences and Primary Care Julius Center.nl
6 EUFRAT -- STEP 2 -- Estimating number of infected donations Donor health questionnaire Compliance(Qc) & effectiveness (Qe) Healthy Donors Recipients Healthy Symptomatically infected (Is) Symptoms manifest later Healthy Infected Asymptomatically infected Infected Infectivity level Symptomatically infected (Is) Symptom onset Acute Symptom onset Chronic (Tais) (Taia) (Tcis) (Tcia) Critical infectivity Health Sciences and Primary Care Julius Center.nl
7 Julius Center.nl EUFRAT -- STEP 3 -- Estimating number of infected components Input: existence of screening test Coverage (Tc) Effectiveness (Te) Components Released Donations (-) Testing (Tc & Te) (+) Discarded
8 Julius Center.nl EUFRAT-- STEP 4 -- Estimating number of infected end products Preparation units (u) Infectivity level No intervention Effective intervention Donations Whole blood Blood products Red blood cells Time Platelets Interventions: 1. Pathogen inactivation or removal 2. Blood processing: leukofiltration, washing, freezing, thawing, storage, others Plasma products
9 Julius Center.nl EUFRAT-- STEP 5 -- Estimating number of infected recipients Infection Immune (Ri)` Infected Acute severe (S)` Chronic (CR) Death (M) Input: Specific immunity in recipients (Ri) Disease severity distribution (S, CR, M)
10 Julius Center.nl Test the model with chikungunya outbreak example Parameters input: 247 cases reported from an area with population of 3,977,508 during fifteen weeks of outbreak. 85% infected develop symptoms, infectious period of 2 and 8 days for sympt. and asympt infection. Donors 2% of total population donate WB twice a year Assumptions: donated blood is fully infectious for recipients. Liumbruno et al. The chikungunya epidemic in Italy. Transfusion (4):
11 Julius Center.nl
12 Julius Center.nl
13 Julius Center.nl STEP1 STEP2 STEP3 STEP4 STEP5
14 Julius Center.nl EUFRAT: chikungunya outbreak example Alternative scenario: A donor donates 1 day after visiting the area for one week probability of being infectious is 0.49 (95%CI, ) per 100,000. If DHQ exists with compliance of 97.6% and effectiveness of 35%, he is at risk of giving infected donations of 0.26 (95%CI, ) per 100,000.
15 Julius Center.nl EUFRAT: chikungunya outbreak example Estimated prevalence of infection in the donor population Estimated number of viraemic donations per 100, Epidemic week Fixed cumulative Random cumulative Fixed weekly Random weekly Epidemic week Fixed cumulative Random cumulative Fixed weekly Random weekly per 100, Epidemic week Liumbruno et al EUFRAT Epidemic week Liumbruno et al. The chikungunya epidemic in Italy. Transfusion (4):
16 Model validation using Q fever outbreak in NL 1. Notifications data: Q fever confirmed cases of 373 from high risk areas (1 June 2009 to 31 January 2010) with a population of 86, An independent donation screening study reveals three out of 1004 serum samples collected from 762 donors tested positive for C. burnetii DNA and by IFA for presence of IgG phase II (prevalence of per 100,000). EUFRAT estimates the prevalence of infection to be (95%CI, ) per 100,000. Health Sciences and Primary Care Julius Center.nl 1. van der Hoek et al. Relation between Q fever notifications and Coxiella burnetii infections. Euro Surveill. 2012; 17(3): pii: Hogema et al. Coxiella burnetii infection among blood donors during the 2009 Q fever outbreak in the Netherlands. Transfusion. 2012; 52: :
17 Julius Center.nl Q fever outbreak in NL Cumulative assessment Daily assessment Prevalence of infection (per 100,000) 1.5E E E E E E E+00 1/06/09 1/07/09 1/08/09 1/09/09 1/10/09 1/11/09 1/12/09 1/01/10 Date 1.5E E E E E E E+00 1/06/09 1/07/09 1/08/09 1/09/09 1/10/09 1/11/09 1/12/09 1/01/10 Date Infected donations /06/09 01/07/09 01/08/09 01/09/09 01/10/09 01/11/09 01/12/09 01/01/10 Date 0 01/06/09 01/07/09 01/08/09 01/09/09 01/10/09 01/11/09 01/12/09 01/01/10 Date
18 Q fever outbreak in NL Cumulative assessment Daily assessment Infected components /06/09 01/07/09 01/08/09 01/09/09 01/10/09 01/11/09 01/12/09 01/01/10 Date /06/09 01/07/09 01/08/09 01/09/09 01/10/09 01/11/09 01/12/09 01/01/10 Date Infected products Chronic infections in recipients 0 01/06/09 01/07/09 01/08/09 01/09/09 01/10/09 01/11/09 01/12/09 01/01/10 Date /06/09 01/07/09 01/08/09 01/09/09 01/10/09 01/11/09 01/12/09 01/01/10 Date Julius Center.nl 0 01/06/09 01/07/09 01/08/09 01/09/09 01/10/09 01/11/09 01/12/09 01/01/10 Health Sciences and Primary Care Date 0 01/06/09 01/07/09 01/08/09 01/09/09 01/10/09 01/11/09 01/12/09 01/01/10 Date
19 Julius Center.nl Conclusion The EUFRAT can be used: to quantify the risk of emerging infections to blood safety to analyse the impact of preventive measures on transfusion safety to support decision making by public health policy makers (and transfusion regulators) in future
20 Project team Dr. Mart P.Janssen ~ TTA, Sanquin Dr. Cees L. van der Poel ~ TTA, Sanquin Dr. Mirjam Kretzschmar ~ UCID, RIVM Dr. Daniel Lewandowski ~ TTA Dr. Sybille Rehmet ~ ECDC Dr. Ardine de Wit ~ MTA, RIVM Dr. Jim van Steenbergen ~ CIb, RIVM Prof. Hans Zaaijer ~ Sanquin, AMC Prof. Roel Coutinho ~ Julius Centre, RIVM Health Sciences and Primary Care Julius Center.nl
21 Questions and discussion Health Sciences and Primary Care Julius Center.nl
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