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Transfusion Transmitted Babesiosis Risk Assessment Mark Walderhaug Mikhail Menis David King Richard Forshee.

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Presentation on theme: "Transfusion Transmitted Babesiosis Risk Assessment Mark Walderhaug Mikhail Menis David King Richard Forshee."— Presentation transcript:

1 Transfusion Transmitted Babesiosis Risk Assessment Mark Walderhaug Mikhail Menis David King Richard Forshee

2 CDC Cases of TTB part 1 State of Donation TOTAL RI NY CT 33 6 NJ WI 44 MN 1 34 MA 134 IN CA 11 … Total

3 CDC Cases of TTB part 2 State of Donation TOTAL MD 1 1 PA 1 1 FL 11 TX 1 1 OH 1 1 NH 1 1 VA 1 1 ME 1 1 Not Known 11 2 Total

4 Babesiosis and TTB reporting limitations Not a nationally notifiable disease Reportable in few states Passive reporting Differing state hemovigilance –Unfamiliar illness, misdiagnosis –Not looked for, except in endemic areas Many mild cases go undiagnosed

5 Assumptions of the Model Asymptomatic carriers are responsible for TTB cases Asymptomatic prevalence is fixed ratio to symptomatic incidence Reported cases of babesiosis are a measure of a state’s potential for asymptomatic carriers Assuming uniform risk throughout a state One to one ratio of infected units to asymptomatic donors

6 Transfusion Transmitted Babesiosis Blood donors Asymp- tomatic Transfusion Transmitted Babesiosis Blood recipients Symp- tomatic Babesia carriers Unknown: fraction of Babesia carriers who are asymptomatic Unknown: infectivity of blood from asymptomatic Babesia carriers

7 Data sources for symptomatic Babesiosis CDC –Sparse, not nationally notifiable, includes TTB AHRQ Healthcare Cost and Utilization Project (HCUP) –Regional reporting but incomplete individual state reporting CMS –Elderly population (some younger disabled beneficiaries), national reporting, billing data

8 CMS Data Number of beneficiaries approximately 11% of state population Location of recording diagnosis –In-patient facility 6% –Physician recording diagnosis 81% –Out-patient facility 13% Babesiosis results courtesy of SafeRx Contract Year Case

9 CMS Reported Babesiosis Incidence State Average CT RI NY MA MD NJ VA VT***4.7 DC***4.4 NH** ME** DE***3.6 PA CA * Calculation based on less than 11 cases Rate per 100,000

10 Red Cell Calculation of Model State symptomatic Babesiosis rate × Asymptomatic/ Symptomatic ratio Adult population of state Fraction of donating population Number of asymptomatic units donated × × = × Average units donated by donor Predicted number of cases of TTB =?

11 Model Results: Predicted Cases of Babesiosis State Assumed Asymptomatic/Symptomatic Ratio 1.75%17.5% NY 4.94 (4.71, 5.18)† (47.1, 51.8) CT 1.87 (1.74, 2) (17.4, 20) MA 1.57 (1.45, 1.7) (14.5, 17) CA 1.07 (0.94, 1.21) (9.4, 12.1) NJ 1.05 (0.96, 1.15) (9.6, 11.5) MD 0.72 (0.63, 0.8) 7.15 (6.3, 8) VA 0.56 (0.49, 0.63) 5.58 (4.9, 6.3) FL 0.45 (0.39, 0.52) 4.50 (3.9, 5.2) PA 0.43 (0.37, 0.5) 4.32 (3.7, 5) RI 0.43 (0.36, 0.5) 4.30 (3.6, 5) TX 0.22 (0.17, 0.27) 2.15 (1.7, 2.7) MI 0.13 (0.1, 0.17) 1.35 (1, 1.7) MN 0.13 (0.1, 0.18) 1.34 (1, 1.8) † 90% confidence interval

12 States with 95% of TTB Cases CDC dataFDA model prediction RINY CT MA NJCA WINJ MNMD MAVA INFL CAPA MDRI PATX FLMI TXMN OHWI NHCO VANC MEAZ MO GA

13 FDA Model Predicted TTB Cases

14 Conclusions Model shows concordance (not identity) with observed data Model can be improved with more complete observational data, better understanding of infectivity, better asymptomatic to symptomatic ratio


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