7.2 Supplemental tables
Age | Probability (95% CI) | PSA Distribution | Source |
0 – 18 | 0 | - | Assumption |
19 – 34 | 0.121 (0.104 – 0.137) | ß (182.5526, 1326.146) | Frenzen 2008 |
35 – 64 | 0.220 (0.208 – 0.232) | ß (999.9999 – 3545.454) | Frenzen 2008 |
65+ | 0.488 (.471 - .505) | ß (999.9999, 1049.18) | Frenzen 2008 |
Age | Sex | Probability (95% CI) | PSA Distribution | Source |
0 – 19 | Female | 0.57 (0.40 – 0.75) | ß (16.78068, 12.65911) | Hollmann 2013 |
0 – 19 | Male | 0.50 (0.30 – 0.70) | ß (11.25985, 11.25985) | Hollmann 2014 |
20 – 34 | Female | 0.58 (0.44 – 0.72) | ß (26.90024, 19.47948) | Hollmann 2015 |
20 – 34 | Male | 0.59 (0.40 – 0.77) | ß (15.15362, 10.53048) | Hollmann 2016 |
35 – 49 | Female | 0.63 (0.52 – 0.75) | ß (42.14228, 24.75023) | Hollmann 2017 |
35 – 49 | Male | 0.58 (0.44 – 0.71) | ß (28.88818, 20.91903) | Hollmann 2018 |
50 - 64 | Female | 0.61 (0.48 – 0.74) | ß (32.20624, 20.59088) | Hollmann 2019 |
50 - 64 | Male | 0.55 (0.41 – 0.68) | ß (27.8526, 22.78849) | Hollmann 2020 |
65+ | Female | 0.59 (0.37 – 0.81) | ß (10.51865, 7.30957) | Hollmann 2021 |
65+ | Male | 0.54 (0.37 – 0.71) | ß (17.04872, 14.52298) | Hollmann 2022 |
Parameter | Base-case value (95% credible range for Probabilistic Sensitivity Analyses) | Distribution | Source |
Probability of stillbirth given congenital Zika syndrome1 | 0.07 (0.054 - 0.084) | Tri(.054, .084) | Li 2017 and Cragen 2009 |
Probability of terminated pregnancy given congenital Zika syndrome | 0.28 (0.2 – 0.5) | Uniform | Li 2017 |
Cost of maternal Zika testing and monitoring | $467.6 (373.9 - 561.4) | Tri(373.9, 561.4) | Li 2017 and Grosse 2008 |
Cost of infant ZIKV testing | $224.8 (180.0 – 270.0) | Tri(180.0, 270.0) | Li 2017 |
Cost of a stillbirth | $6152.6 (4922 – 7382) | Tri(4922, 7382) | Li 2017 |
Cost of termination | $5354.8 (4283.2 – 6425.3) | Tri(4283.2, 6425.3) | Li 2017 |
Cost of livebirth without congenital Zika syndrome | $23,505.9 (18,803.0 - $28,205.6) | Tri(18,803, 28,205.6) | Li 2017 |
Cost of livebirth with congenital Zika syndrome | $24,196.1 (19,356.9 – 29,035.3) | Tri(19356.9, 29035.3) | Li 2017 |
Cost of testing fetus for congenital Zika syndrome | $351.5 (281.2 – 421.8) | Tri(281.2, 421.8) | Li 2017 |
Utility loss of congenital Zika syndrome | 79.8 | Not varied. | The World Bank |
1All stillbirths incurred costs equivalent to a lifetime productivity loss netted consumption, which came out to be $1.13 million in the 50 states and $576 thousand in Puerto Rico, discounted at 3%. We assumed infants born with congenital Zika syndrome would never be productive and thus incurred the same productivity loss. | |||
Setting | Testing Strategy | True positives interdicted | False positives interdicted | Positive predictive value |
Puerto Rico | No screening | 0 | 0 | NA |
½-MP | 240 | <0.0001 | >0.9999 | |
SI-ID | 23 | 0.19 | 0.9916 | |
½-ID | 257 | 1.17 | 0.9955 | |
MP | 259 | <0.0001 | >0.9999 | |
½-ID-MP | 276 | 1.17 | 0.9958 | |
SI-ID-MP | 261 | 0.19 | 0.9993 | |
ID | 277 | 2.34 | 0.9916 | |
50 U.S. States and DC | No screening | 0 | 0 | NA |
LA-MP | 28 | 0.003 | >0.9999 | |
LA-ID | 30 | 10.39 | 0.7447 | |
TA-MP | 46 | 0.001 | >0.9999 | |
TA-ID | 49 | 40.25 | 0.551 | |
SI-ID | 4 | 30.63 | 0.1162 | |
MP | 46 | 0.013 | 0.9997 | |
SI-ID-MP | 47 | 30.64 | 0.6033 | |
ID | 50 | 377.67 | 0.116 |
Input Parameters | BL1 | ID1 | MP1 | 1/2-ID1 | 1/2-MP1 | 1/2-ID-MP1 | SI-ID1 | SI-ID-MP |
Prob. CZS given maternal TTZ | 118,007 (p<.001) | 1,276 (p<.001) | 9,118 (p<.001) | 10,442 (p<.001) | 17,689 (p<.001) | 1,872 (p<.001) | 23,727 (p<.001) | 2,804 (p<.001) |
Cost ID-NAT | N.S. | 95,923 (p<.001) | N.S. | 48,150 (p<.001) | N.S. | 48,112 (p<.001) | 7,697 (p<.001) | 7,778 (p<.001) |
Cost MP-NAT | N.S. | N.S. | 95,759 (p<.001) | N.S. | 47,929 (p<.001) | 47,752 (p<.001) | N.S. | 88,003 (p<.001) |
Cost separate inventory | N.S. | N.S. | N.S. | N.S. | N.S. | N.S. | 55,021 (p<.001) | 55,077 (p<.001) |
Cost febrile illness, recipient | 22,612 (p<.001) | 236 (p<.001) | 1,719 (p<.001) | 1,986 (p<.001) | 3,357 (p<.001) | 347 (p<.001) | 20,988 (p<.001) | 1,623 (p<.001) |
Prob. recipient pregnant | 20,144 (p<.001) | 198 (p<.001) | 1,539 (p<.001) | 1,775 (p<.001) | 3,013 (p<.001) | 301 (p<.001) | N.S. | 188 (p<.001) |
Prob. Febrile illness | 13,653 (p<.001) | 128 (p<.001) | 1,044 (p<.001) | 1,162 (p<.001) | 2,008 (p<.001) | 198 (p<.001) | 12,521 (p<.001) | 966 (p<.001) |
Cost CZS, lifetime | 12,974 (p<.001) | 138 (p<.001) | 990 (p<.001) | 1,168 (p<.001) | 1,952 (p<.001) | 205 (p<.001) | 2,510 (p<.001) | 290 (p<.001) |
Transmissi-bility in RBC | 9,540 (p<.001) | 96 (p<.001) | 761 (p<.001) | 800 (p<.001) | 1,417 (p<.001) | 144 (p<.001) | 5,700 (p<.001) | 487 (p<.001) |
ZIKV+ rate, high season | 7,877 (p<.001) | 1,701 (p<.001) | 2,052 (p<.001) | 1,631 (p<.001) | 1,990 (p<.001) | 1,693 (p<.001) | 4,214 (p<.001) | 1,820 (p<.001) |
Prob. Sexual transmission | 5,819 (p<.001) | 74 (p<.001) | 475 (p<.001) | 536 (p<.001) | 908 (p<.001) | 102 (p<.001) | 5,707 (p<.001) | 467 (p<.001) |
Transmissibility in FFP | 3,675 (p<.001) | 53 (p<.001) | 306 (p<.001) | 362 (p<.001) | 595 (p<.001) | 72 (p<.001) | 1,711 (p<.001) | 174 (p<.001) |
ZIKV+ rate, low season | 2,470 (p<.001) | 455 (p<.001) | 579 (p<.001) | 2,227 (p<.001) | 2,248 (p<.001) | 558 (p<.001) | 1,318 (p<.001) | 479 (p<.001) |
MP-NAT sensitivity | N.S. | N.S. | -2,078 (p<.001) | N.S. | -1,910 (p<.001) | -153 (p<.001) | N.S. | -894 (p<.001) |
Cost true positive | N.S. | 1,702 (p<.001) | 1,532 (p<.001) | 1,572 (p<.001) | 1,419 (p<.001) | 1,685 (p<.001) | N.S. | 1,573 (p<.001) |
Transmissi-bility in PLT | N.S. | N.S. | N.S. | N.S. | N.S. | N.S. | 678 (p<.001) | N.S. |
ID-NAT sensitivity | N.S. | -807 (p<.001) | N.S. | -778 (p<.001) | N.S. | -747 (p<.001) | -529 (p=0.002) | -470 (p<.001) |
Prob. GBS | N.S. | N.S. | N.S. | N.S. | N.S. | N.S. | 639 (p<.001) | N.S. |
1Each cell contains coefficients (ßj) and p-value. Coefficients can be interpreted as: “Holding all other parameters at their expected value, a one standard-deviation increase in the parameter will increase the outcome variable by ßj.” N.S. indicates that the coefficient was not statistically significant with the Benjamini-Yekuteils multiple comparison p-value adjustment applied. | ||||||||
Input Parameters | BL1 | ID1 | MP1 | LA-ID1 | TA-ID1 | LA-MP1 | TA-MP1 | SI-ID | SI-ID-MP |
Cost ID-NAT | N.S. | 15,436,768 (p<.001) | N.S. | 424,258 (p<.001) | 1,640,937 (p<.001) | N.S. | N.S. | 1,253,636 (p<.001) | 1,253,131 (p<.001) |
Cost MP-NAT | N.S. | N.S. | 15,398,668 (p<.001) | N.S. | N.S. | 423,418 (p<.001) | 1,638,679 (p<.001) | N.S. | 14,147,894 (p<.001) |
Cost separate inventory | N.S. | N.S. | N.S. | N.S. | N.S. | N.S. | N.S. | 8,967,630 (p<.001) | 8,968,396 (p<.001) |
Proportion of donors with travel | N.S. | N.S. | N.S. | N.S. | 822,014 (p<.001) | N.S. | 493,969 (p<.001) | N.S. | N.S. |
Prob. CZS given maternal TTZ | 28,247 (p<.001) | N.S. | 2,202 (p<.001) | 11,124 (p<.001) | N.S. | 12,234 (p<.001) | N.S. | N.S. | N.S. |
Duration of febrile illness, recipient | 15,939 (p<.001) | N.S. | N.S. | 6,402 (p<.001) | N.S. | 6,966 (p<.001) | N.S. | 16,351 (p<.001) | N.S. |
ID-NAT specificity | N.S. | -9,226 (p<.001) | N.S. | N.S. | N.S. | N.S. | N.S. | N.S. | N.S. |
Prob. Febrile illness | 7,269 (p<.001) | N.S. | N.S. | 3,037 (p<.001) | N.S. | 3,242 (p<.001) | N.S. | 6,557 (p<.001) | N.S. |
ZIKV-infectious rate, FL KLT | 4,813 (p<.001) | N.S. | N.S. | 604 (p=0.001) | N.S. | 832 (p<.001) | N.S. | N.S. | N.S. |
Prob. recipient pregnant | 4,731 (p<.001) | N.S. | N.S. | 1,848 (p<.001) | N.S. | 2,034 (p<.001) | N.S. | N.S. | N.S. |
Cost febrile illness, recipient | 4,443 (p<.001) | N.S. | N.S. | 1,743 (p<.001) | N.S. | 1,900 (p<.001) | N.S. | N.S. | N.S. |
ZIKV+ rate, other donors | 4,256 (p<.001) | N.S. | N.S. | 4,280 (p<.001) | N.S. | 4,247 (p<.001) | N.S. | N.S. | N.S. |
Transmissi-bility in RBC | 3,871 (p<.001) | N.S. | N.S. | 1,412 (p<.001) | N.S. | 1,617 (p<.001) | N.S. | N.S. | N.S. |
Cost true positive | N.S. | 2,864 (p=0.022) | N.S. | N.S. | N.S. | N.S. | N.S. | N.S. | N.S. |
Cost CZS, lifetime | 2,562 (p<.001) | N.S. | N.S. | 971 (p<.001) | N.S. | 1,101 (p<.001) | N.S. | N.S. | N.S. |
ZIKV-infectious rate, TX KLT | 2,271 (p<.001) | N.S. | N.S. | N.S. | N.S. | 480 (p<.001) | N.S. | N.S. | N.S. |
MP-NAT sensitivity | N.S. | N.S. | N.S. | N.S. | N.S. | -398 (p=0.002) | N.S. | N.S. | N.S. |
Transmissi-bility in FFP | 1,079 (p<.001) | N.S. | N.S. | N.S. | N.S. | 472 (p<.001) | N.S. | N.S. | N.S. |
Prob. Sexual transmission | 1,351 (p<.001) | N.S. | N.S. | 537 (p=0.009) | N.S. | 577 (p<.001) | N.S. | N.S. | N.S. |
1Each cell contains coefficients (ßj) and p-value. Coefficients can be interpreted as: “Holding all other parameters at their expected value, a one standard-deviation increase in the parameter will increase the outcome variable by ßj.” N.S. indicates that the coefficient was not statistically significant with the Benjamini-Yekuteils multiple comparison p-value adjustment applied. | |||||||||
Input Parameters | BL1 | ID1 | MP1 | 1/2-ID1 | 1/2-MP1 | 1/2-ID-MP1 | SI-ID1 | SI-ID-MP |
Prob. CZS given maternal TTZ | -0.944 (p<.001) | -0.010 (p<.001) | -0.073 (p<.001) | -0.083 (p<.001) | -0.142 (p<.001) | -0.015 (p<.001) | -0.188 (p<.001) | -0.022 (p<.001) |
Duration of febrile illness, recipient | -0.784 (p<.001) | -0.008 (p<.001) | -0.061 (p<.001) | -0.068 (p<.001) | -0.116 (p<.001) | -0.012 (p<.001) | -0.721 (p<.001) | -0.056 (p<.001) |
Prob. Febrile illness | -0.236 (p<.001) | -0.002 (p<.001) | -0.018 (p<.001) | -0.020 (p<.001) | -0.035 (p<.001) | -0.003 (p<.001) | -0.217 (p<.001) | -0.017 (p<.001) |
Prob. recipient pregnant | -0.160 (p<.001) | -0.002 (p<.001) | -0.012 (p<.001) | -0.014 (p<.001) | -0.024 (p<.001) | -0.002 (p<.001) | N.S. | -0.002 (p<.001) |
Transmissi-bility in RBC | -0.125 (p<.001) | -0.001 (p<.001) | -0.010 (p<.001) | -0.011 (p<.001) | -0.019 (p<.001) | -0.002 (p<.001) | -0.092 (p<.001) | -0.007 (p<.001) |
ZIKV+ rate, high season | -0.099 (p<.001) | -0.001 (p<.001) | -0.008 (p<.001) | N.S. | -0.007 (p<.001) | -0.001 (p<.001) | -0.065 (p<.001) | -0.006 (p<.001) |
Prob. Sexual transmission | -0.058 (p<.001) | -0.001 (p<.001) | -0.005 (p<.001) | -0.005 (p<.001) | -0.009 (p<.001) | -0.001 (p<.001) | -0.057 (p<.001) | -0.005 (p<.001) |
Util. febrile illness, M 65+ recipient | 0.058 (p<.001) | 0.001 (p<.001) | 0.005 (p<.001) | 0.005 (p<.001) | 0.009 (p<.001) | 0.001 (p<.001) | 0.058 (p<.001) | 0.005 (p<.001) |
Util. febrile illness, F 65+ recipient | 0.050 (p<.001) | 0.000 (p<.001) | 0.004 (p<.001) | 0.005 (p<.001) | 0.007 (p<.001) | 0.001 (p<.001) | 0.053 (p<.001) | 0.004 (p<.001) |
Transmissi-bility in FFP | -0.038 (p<.001) | -0.001 (p<.001) | -0.003 (p<.001) | -0.004 (p<.001) | -0.006 (p<.001) | -0.001 (p<.001) | -0.023 (p<.001) | -0.002 (p<.001) |
MP-NAT sensitivity | N.S. | N.S. | 0.032 (p<.001) | N.S. | 0.030 (p<.001) | 0.002 (p<.001) | N.S. | 0.021 (p<.001) |
ZIKV+ rate, low season | -0.027 (p<.001) | N.S. | -0.002 (p<.001) | -0.027 (p<.001) | -0.028 (p<.001) | -0.002 (p<.001) | -0.018 (p<.001) | -0.002 (p<.001) |
Util. febrile illness, M 50-64 recipient | 0.019 (p<.001) | N.S. | 0.001 (p=0.006) | 0.001 (p=0.005) | 0.003 (p<.001) | N.S. | 0.022 (p<.001) | 0.002 (p<.001) |
Util. febrile illness, F 50-64 recipient | 0.013 (p=0.006) | N.S. | N.S. | N.S. | N.S. | N.S. | 0.013 (p<.001) | 0.001 (p=0.008) |
Util. febrile illness, M 35-49 recipient | 0.013 (p=0.006) | N.S. | N.S. | 0.001 (p=0.007) | 0.002 (p=0.009) | N.S. | 0.009 (p=0.001) | 0.001 (p=0.012) |
Prob. GBS | -0.013 (p=0.007) | N.S. | N.S. | -0.001 (p=0.016) | N.S. | N.S. | -0.011 (p<.001) | -0.001 (p=0.010) |
ID-NAT sensitivity | N.S. | 0.012 (p<.001) | N.S. | 0.011 (p<.001) | N.S. | 0.011 (p<.001) | N.S. | 0.004 (p<.001) |
Duration of febrile illness, partner | -0.011 (p=0.029) | N.S. | N.S. | -0.001 (p=0.015) | -0.002 (p=0.041) | N.S. | -0.009 (p<.001) | N.S. |
Transmissi-bility in PLT | -0.011 (p=0.030) | N.S. | N.S. | -0.001 (p=0.008) | N.S. | N.S. | -0.010 (p<.001) | N.S. |
Util. GBS, year 1 | -0.011 (p=0.033) | N.S. | N.S. | -0.001 (p=0.012) | N.S. | N.S. | -0.009 (p=0.003) | N.S. |
Util. febrile illness, M 20-34 recipient | N.S. | N.S. | N.S. | N.S. | N.S. | N.S. | 0.010 (p<.001) | 0.001 (p=0.027) |
Cost separate inventory | N.S. | N.S. | N.S. | -0.001 (p=0.026) | -0.002 (p=0.045) | N.S. | N.S. | N.S. |
1Each cell contains coefficients (ßj) and p-value. Coefficients can be interpreted as: “Holding all other parameters at their expected value, a one standard-deviation increase in the parameter will increase the outcome variable by ßj.” N.S. indicates that the coefficient was not statistically significant with the Benjamini-Yekuteils multiple comparison p-value adjustment applied. | ||||||||
Input Parameters | BL1 | ID1 | MP1 | LA-ID1 | TA-ID1 | LA-MP1 | TA-MP1 | SI-ID | SI-ID-MP |
Prob. CZS given maternal TTZ | -0.175 (p<.001) | -0.002 (p<.001) | -0.013 (p<.001) | -0.069 (p<.001) | -0.002 (p<.001) | -0.076 (p<.001) | -0.014 (p<.001) | -0.035 (p<.001) | -0.004 (p<.001) |
Duration of febrile illness, recipient | -0.145 (p<.001) | -0.001 (p<.001) | -0.011 (p<.001) | -0.058 (p<.001) | -0.002 (p<.001) | -0.063 (p<.001) | -0.011 (p<.001) | -0.133 (p<.001) | -0.010 (p<.001) |
Prob. Febrile illness | -0.043 (p<.001) | 0.000 (p<.001) | -0.003 (p<.001) | -0.017 (p<.001) | -0.001 (p<.001) | -0.019 (p<.001) | -0.003 (p<.001) | -0.039 (p<.001) | -0.003 (p<.001) |
ZIKV-infectious rate, FL KLT | -0.030 (p<.001) | 0.000 (p<.001) | -0.002 (p<.001) | N.S. | 0.000 (p<.001) | -0.002 (p<.001) | -0.002 (p<.001) | -0.020 (p<.001) | -0.002 (p<.001) |
Prob. recipient pregnant | -0.029 (p<.001) | 0.000 (p<.001) | -0.002 (p<.001) | -0.012 (p<.001) | 0.000 (p<.001) | -0.013 (p<.001) | -0.002 (p<.001) | N.S. | 0.000 (p<.001) |
ZIKV+ rate, other donors | -0.026 (p<.001) | 0.000 (p<.001) | -0.002 (p<.001) | -0.026 (p<.001) | -0.001 (p<.001) | -0.026 (p<.001) | -0.002 (p<.001) | -0.017 (p<.001) | -0.001 (p<.001) |
Transmissi-bility in RBC | -0.025 (p<.001) | 0.000 (p<.001) | -0.002 (p<.001) | -0.010 (p<.001) | 0.000 (p<.001) | -0.011 (p<.001) | -0.002 (p<.001) | -0.017 (p<.001) | -0.001 (p<.001) |
ZIKV-infectious rate, TX KLT | -0.014 (p<.001) | 0.000 (p<.001) | -0.001 (p<.001) | N.S. | 0.000 (p<.001) | -0.002 (p<.001) | -0.001 (p<.001) | -0.010 (p<.001) | -0.001 (p<.001) |
Util. febrile illness, M 65+ recipient | 0.010 (p<.001) | 0.000 (p<.001) | 0.001 (p<.001) | 0.004 (p<.001) | 0.000 (p<.001) | 0.005 (p<.001) | 0.001 (p<.001) | 0.011 (p<.001) | 0.001 (p<.001) |
Prob. Sexual transmission | -0.009 (p<.001) | 0.000 (p<.001) | -0.001 (p<.001) | -0.003 (p<.001) | 0.000 (p<.001) | -0.004 (p<.001) | -0.001 (p<.001) | -0.010 (p<.001) | -0.001 (p<.001) |
Util. febrile illness, F 65+ recipient | 0.009 (p<.001) | 0.000 (p=0.003) | 0.001 (p<.001) | 0.004 (p<.001) | 0.000 (p<.001) | 0.004 (p<.001) | 0.001 (p<.001) | 0.009 (p<.001) | 0.001 (p<.001) |
Transmissi-bility in FFP | -0.007 (p<.001) | N.S. | 0.000 (p<.001) | -0.002 (p<.001) | N.S. | -0.003 (p<.001) | -0.001 (p<.001) | -0.004 (p<.001) | 0.000 (p<.001) |
MP-NAT sensitivity | N.S. | N.S. | 0.006 (p<.001) | N.S. | N.S. | 0.003 (p<.001) | 0.006 (p<.001) | N.S. | 0.004 (p<.001) |
Util. febrile illness, M 50-64 recipient | 0.004 (p<.001) | N.S. | 0.000 (p=0.007) | 0.002 (p<.001) | 0.000 (p=0.050) | 0.002 (p<.001) | 0.000 (p=0.005) | 0.004 (p<.001) | 0.000 (p<.001) |
Prob. GBS | -0.003 (p=0.001) | N.S. | N.S. | N.S. | N.S. | -0.001 (p=0.047) | N.S. | -0.003 (p<.001) | 0.000 (p=0.002) |
Util. GBS, year 1 | -0.003 (p=0.003) | N.S. | N.S. | -0.001 (p=0.014) | N.S. | -0.001 (p=0.009) | N.S. | -0.003 (p<.001) | 0.000 (p=0.042) |
Util. febrile illness, M 35-49 recipient | N.S. | N.S. | N.S. | N.S. | N.S. | N.S. | N.S. | 0.003 (p<.001) | 0.000 (p=0.024) |
Util. febrile illness, F 50-64 recipient | 0.003 (p=0.035) | N.S. | 0.000 (p=0.017) | 0.001 (p=0.048) | N.S. | 0.001 (p=0.020) | 0.000 (p=0.014) | 0.002 (p=0.001) | 0.000 (p=0.002) |
ID-NAT sensitivity | N.S. | 0.002 (p<.001) | N.S. | N.S. | 0.002 (p<.001) | N.S. | N.S. | N.S. | 0.001 (p<.001) |
Prob. Donor ZIKV is travel-acquired | N.S. | N.S. | N.S. | N.S. | 0.000 (p<.001) | N.S. | N.S. | N.S. | N.S. |
1Each cell contains coefficients (ßj) and p-value. Coefficients can be interpreted as: “Holding all other parameters at their expected value, a one standard-deviation increase in the parameter will increase the outcome variable by ßj.” N.S. indicates that the coefficient was not statistically significant with the Benjamini-Yekuteils multiple comparison p-value adjustment applied. | |||||||||
Input Parameters | ID1 | MP1 | 1/2-ID1 | 1/2-MP1 | 1/2-ID-MP1 | SI-ID1 | SI-ID-MP1 |
Prob. CZS given maternal TTZ | -306,401 (p<.001) | -200,023 (p<.001) | -172,963 (p<.001) | -115,117 (p<.001) | -248,296 (p<.001) | -1,034,851 (p<.001) | -299,045 (p<.001) |
Duration of febrile illness, recipient | -370,721 (p<.001) | -225,272 (p<.001) | -189,280 (p<.001) | -110,115 (p<.001) | -291,187 (p<.001) | -737,587 (p<.001) | -354,101 (p<.001) |
Cost separate inventory | N.S. | N.S. | N.S. | N.S. | N.S. | 404,322 (p<.001) | 61,809 (p<.001) |
Prob. Febrile illness | -133,041 (p<.001) | -85,887 (p<.001) | -74,936 (p<.001) | -49,295 (p<.001) | -107,361 (p<.001) | -242,353 (p<.001) | -127,282 (p<.001) |
Prob. recipient pregnant | -54,921 (p<.001) | -35,521 (p<.001) | -31,104 (p<.001) | -20,486 (p<.001) | -44,304 (p<.001) | -230,132 (p<.001) | -54,063 (p<.001) |
ZIKV+ rate, high season | -48,030 (p<.001) | -32,428 (p<.001) | -28,283 (p<.001) | -18,984 (p<.001) | -39,539 (p<.001) | -137,708 (p<.001) | -48,875 (p<.001) |
Transmissi-bility in RBC | -56,593 (p<.001) | -37,047 (p<.001) | -31,786 (p<.001) | -21,159 (p<.001) | -45,883 (p<.001) | -120,514 (p<.001) | -55,372 (p<.001) |
Cost ID-NAT | 113,899 (p<.001) | N.S. | 61,985 (p<.001) | N.S. | 59,127 (p<.001) | 91,918 (p<.001) | N.S. |
Cost MP-NAT | -21,386 (p=0.006) | 99,944 (p<.001) | -11,388 (p=0.006) | 54,666 (p<.001) | 35,875 (p<.001) | N.S. | 83,041 (p<.001) |
Util. febrile illness, F 20-34 recipient | N.S. | N.S. | N.S. | N.S. | N.S. | 98,570 (p<.001) | N.S. |
ZIKV+ rate, low season | -23,333 (p=0.002) | -14,075 (p=0.003) | N.S. | N.S. | -17,581 (p=0.003) | -70,250 (p=0.022) | -22,272 (p=0.002) |
Transmissi-bility in FFP | -23,867 (p=0.001) | -16,008 (p<.001) | -13,368 (p<.001) | -9,067 (p<.001) | -19,556 (p<.001) | -67,357 (p=0.034) | -23,916 (p<.001) |
Prob. GBS | -19,382 (p=0.020) | -11,802 (p=0.028) | -10,242 (p=0.022) | -6,051 (p=0.039) | -15,220 (p=0.020) | N.S. | -19,519 (p=0.011) |
Util. GBS, year 1 | -19,862 (p=0.015) | -11,907 (p=0.025) | -10,504 (p=0.017) | -6,116 (p=0.035) | -15,561 (p=0.015) | N.S. | -19,079 (p=0.015) |
Util. febrile illness, M 65+ recipient | 29,430 (p<.001) | 17,545 (p<.001) | 14,733 (p<.001) | 8,284 (p<.001) | 22,954 (p<.001) | N.S. | 27,755 (p<.001) |
Util. febrile illness, F 65+ recipient | 25,572 (p<.001) | 13,952 (p=0.004) | 13,085 (p<.001) | 6,762 (p=0.012) | 19,303 (p<.001) | N.S. | 23,728 (p<.001) |
Prob. Sexual transmission | -22,072 (p=0.004) | -14,348 (p=0.002) | -11,533 (p=0.005) | -7,424 (p=0.004) | -17,767 (p=0.003) | N.S. | -19,733 (p=0.010) |
Cost febrile illness, recipient | -24,417 (p<.001) | -24,697 (p<.001) | -24,092 (p<.001) | -24,202 (p<.001) | -24,532 (p<.001) | N.S. | -24,321 (p<.001) |
MP-NAT sensitivity | N.S. | -18,034 (p<.001) | N.S. | -9,694 (p<.001) | N.S. | N.S. | -22,858 (p=0.001) |
1Each cell contains coefficients (ßj) and p-value. Coefficients can be interpreted as: “Holding all other parameters at their expected value, a one standard-deviation increase in the parameter will increase the outcome variable by ßj.” N.S. indicates that the coefficient was not statistically significant with the Benjamini-Yekuteils multiple comparison p-value adjustment applied. | |||||||
Input Parameters | ID1 | MP1 | LA-ID1 | TA-ID1 | LA-MP1 | TA-MP1 | SI-ID1 | SI-ID-MP |
Prob. CZS given maternal TTZ | -267,474,301 (p<.001) | -172,181,794 (p<.001) | -12,389,948 (p<.001) | -28,628,243 (p<.001) | -7,974,396 (p<.001) | -18,429,442 (p<.001) | -985,424,299 (p<.001) | -985,424,299 (p<.001) |
Duration of febrile illness, recipient | -363,974,038 (p<.001) | -234,644,862 (p<.001) | -17,049,267 (p<.001) | -38,903,072 (p<.001) | -10,976,884 (p<.001) | -25,075,788 (p<.001) | -803,589,168 (p<.001) | -803,589,168 (p<.001) |
Cost separate inventory | N.S. | N.S. | N.S. | N.S. | N.S. | N.S. | 419,015,996 (p<.001) | 419,015,996 (p<.001) |
Prob. Febrile illness | -124,662,427 (p<.001) | -78,565,605 (p<.001) | -5,884,680 (p<.001) | -13,372,687 (p<.001) | -3,705,786 (p<.001) | -8,423,068 (p<.001) | -296,494,601 (p<.001) | -296,494,601 (p<.001) |
Prob. recipient pregnant | -51,815,116 (p<.001) | -33,939,105 (p<.001) | -2,425,650 (p<.001) | -5,600,717 (p<.001) | -1,571,730 (p<.001) | -3,651,414 (p<.001) | -223,999,822 (p<.001) | -223,999,822 (p<.001) |
ZIKV+ rate, other donors | -58,313,246 (p<.001) | -37,261,271 (p<.001) | N.S. | -6,280,765 (p<.001) | N.S. | -4,017,665 (p<.001) | -149,671,225 (p=0.003) | -149,671,225 (p=0.003) |
Transmissi-bility in RBC | -66,755,730 (p<.001) | -42,109,024 (p<.001) | -3,083,321 (p<.001) | -7,095,700 (p<.001) | -1,942,050 (p<.001) | -4,485,401 (p<.001) | -137,313,280 (p=0.009) | -137,313,280 (p=0.009) |
ZIKV-infectious rate, FL KLT | -73,569,307 (p<.001) | -46,392,936 (p<.001) | -5,596,488 (p<.001) | -7,918,639 (p<.001) | -3,551,895 (p<.001) | -4,997,530 (p<.001) | -126,309,829 (p=0.025) | -126,309,829 (p=0.025) |
Cost MP-NAT | N.S. | 103,862,911 (p<.001) | N.S. | N.S. | 4,807,112 (p<.001) | 11,126,318 (p<.001) | N.S. | N.S. |
ZIKV-infectious rate, TX KLT | -30,767,763 (p<.001) | -19,128,096 (p<.001) | -2,503,795 (p<.001) | -3,315,561 (p<.001) | -1,573,477 (p<.001) | -2,065,397 (p<.001) | N.S. | N.S. |
Cost ID-NAT | 87,277,318 (p<.001) | N.S. | 3,987,975 (p<.001) | 9,369,583 (p<.001) | N.S. | N.S. | N.S. | N.S. |
Prob. GBS | -24,359,640 (p=0.001) | -15,922,100 (p=0.002) | -1,045,089 (p=0.009) | -2,594,413 (p=0.002) | -674,597 (p=0.013) | -1,698,739 (p=0.002) | N.S. | N.S. |
Transmissi-bility in FFP | -23,574,132 (p=0.002) | -13,823,518 (p=0.013) | -1,121,686 (p=0.003) | -2,560,321 (p=0.002) | -657,075 (p=0.017) | -1,500,887 (p=0.012) | N.S. | N.S. |
Util. febrile illness, F 65+ recipient | 26,683,493 (p<.001) | 18,771,527 (p<.001) | 1,139,250 (p=0.003) | 2,850,535 (p<.001) | 822,884 (p<.001) | 1,995,582 (p<.001) | N.S. | N.S. |
Util. febrile illness, M 65+ recipient | 25,477,637 (p<.001) | 15,931,270 (p=0.002) | 1,193,339 (p=0.001) | 2,722,173 (p<.001) | 762,610 (p=0.002) | 1,708,299 (p=0.002) | N.S. | N.S. |
Proportion of donors with travel | N.S. | N.S. | N.S. | 5,434,257 (p<.001) | N.S. | 3,525,994 (p<.001) | N.S. | N.S. |
1Each cell contains coefficients (ßj) and p-value. Coefficients can be interpreted as: “Holding all other parameters at their expected value, a one standard-deviation increase in the parameter will increase the outcome variable by ßj.” N.S. indicates that the coefficient was not statistically significant with the Benjamini-Yekuteils multiple comparison p-value adjustment applied. | ||||||||
Input Parameters | ID1 | MP1 | 1/2-ID1 | 1/2-MP1 | 1/2-ID-MP1 | SI-ID1 | SI-ID-MP1 |
Duration of febrile illness, recipient | -22,276,269 (p<.001) | -7,379,222 (p<.001) | -2,363,139 (p<.001) | -113,815 (p<.001) | -2,274,137 (p<.001) | -749,806 (p<.001) | N.S. |
Cost separate inventory | N.S. | N.S. | N.S. | N.S. | N.S. | 413,037 (p<.001) | N.S. |
Cost MP-NAT | -14,346,682 (p<.001) | 8,509,091 (p<.001) | -2,972,987 (p<.001) | 60,597 (p<.001) | N.S. | N.S. | N.S. |
ZIKV+ rate, high season | N.S. | N.S. | N.S. | -19,126 (p<.001) | N.S. | -141,911 (p<.001) | N.S. |
MP-NAT sensitivity | 20,808,452 (p<.001) | N.S. | 1,246,698 (p=0.007) | -10,901 (p<.001) | 1,057,304 (p<.001) | N.S. | N.S. |
Prob. CZS given maternal TTZ | -14,723,838 (p<.001) | N.S. | -1,522,049 (p<.001) | -110,409 (p<.001) | -1,585,273 (p<.001) | -1,022,266 (p<.001) | N.S. |
Util. febrile illness, M 65+ recipient | 11,863,566 (p=0.017) | N.S. | 1,413,159 (p<.001) | 9,526 (p=0.004) | 800,282 (p=0.004) | N.S. | N.S. |
Util. febrile illness, F 20-34 recipient | N.S. | N.S. | N.S. | N.S. | N.S. | 103,798 (p<.001) | N.S. |
Prob. Sexual transmission | N.S. | N.S. | N.S. | -11,640 (p<.001) | N.S. | N.S. | N.S. |
ZIKV+ rate, low season | -12,479,855 (p=0.008) | N.S. | -1,072,977 (p=0.050) | N.S. | -793,079 (p=0.004) | -79,656 (p=0.017) | N.S. |
ID-NAT sensitivity | -19,700,948 (p<.001) | N.S. | -1,596,973 (p<.001) | N.S. | -1,229,658 (p<.001) | N.S. | N.S. |
Prob. Febrile illness | N.S. | N.S. | N.S. | -48,847 (p<.001) | -811,235 (p=0.003) | -241,278 (p<.001) | N.S. |
Cost ID-NAT | N.S. | N.S. | 2,048,190 (p<.001) | N.S. | N.S. | 99,911 (p<.001) | N.S. |
Util. febrile illness, F 65+ recipient | N.S. | N.S. | N.S. | 9,711 (p=0.004) | N.S. | N.S. | N.S. |
Transmissi-bility in RBC | N.S. | N.S. | N.S. | -21,870 (p<.001) | N.S. | -112,589 (p<.001) | N.S. |
Prob. recipient pregnant | N.S. | N.S. | N.S. | -16,809 (p<.001) | N.S. | -215,546 (p<.001) | N.S. |
Cost febrile illness, recipient | N.S. | N.S. | N.S. | -26,867 (p<.001) | N.S. | N.S. | N.S. |
1Each cell contains coefficients (ßj) and p-value. Coefficients can be interpreted as: “Holding all other parameters at their expected value, a one standard-deviation increase in the parameter will increase the outcome variable by ßj.” N.S. indicates that the coefficient was not statistically significant with the Benjamini-Yekuteils multiple comparison p-value adjustment applied. | |||||||
Input Parameters | ID1 | MP1 | LA-ID1 | TA-ID1 | LA-MP1 | TA-MP1 | SI-ID1 | SI-ID-MP |
Duration of febrile illness, recipient | -87,400,120,014 (p<.001) | -51,644,718,978 (p<.001) | -114,479,819 (p<.001) | -261,206,158 (p<.001) | -10,976,884 (p<.001) | -114,479,819 (p<.001) | N.S. | -18,801,743,439 (p<.001) |
Prob. CZS given maternal TTZ | -64,739,110,011 (p<.001) | -38,510,674,370 (p<.001) | -87,139,078 (p<.001) | -202,307,233 (p<.001) | -7,974,396 (p<.001) | -87,139,078 (p<.001) | N.S. | -21,801,701,742 (p<.001) |
ZIKV+ rate, other donors | -39,290,679,694 (p<.001) | -21,629,822,858 (p<.001) | N.S. | -43,951,101 (p<.001) | N.S. | N.S. | N.S. | -5,366,536,489 (p<.001) |
Prob. Febrile illness | -29,581,748,837 (p<.001) | -17,289,320,046 (p<.001) | -43,718,764 (p<.001) | -99,824,545 (p<.001) | -3,705,786 (p<.001) | -43,718,764 (p<.001) | N.S. | -6,755,112,738 (p<.001) |
Prob. Donor ZIKV is travel-acquired | 27,689,727,005 (p<.001) | 16,334,039,430 (p<.001) | N.S. | N.S. | N.S. | N.S. | N.S. | 2,400,294,343 (p=0.003) |
Cost ID-NAT | 22,211,445,793 (p<.001) | 10,553,269,342 (p<.001) | 72,090,109 (p<.001) | 163,382,023 (p<.001) | N.S. | 72,090,109 (p<.001) | N.S. | 3,557,819,496 (p<.001) |
Transmissi-bility in RBC | -16,603,092,389 (p<.001) | -9,936,453,919 (p<.001) | -21,619,450 (p<.001) | -48,626,161 (p<.001) | -1,942,050 (p<.001) | -21,619,450 (p<.001) | N.S. | -2,957,758,395 (p<.001) |
Prob. recipient pregnant | -12,324,110,746 (p<.001) | -7,177,643,210 (p<.001) | -20,125,371 (p<.001) | -46,327,563 (p<.001) | -1,571,730 (p<.001) | -20,125,371 (p<.001) | N.S. | -5,572,913,657 (p<.001) |
MP-NAT sensitivity | N.S. | N.S. | 80,016,118 (p<.001) | 182,443,548 (p<.001) | N.S. | 80,016,118 (p<.001) | N.S. | 11,221,852,283 (p<.001) |
Cost MP-NAT | N.S. | 11,197,903,550 (p<.001) | -76,226,325 (p<.001) | -172,045,461 (p<.001) | 4,807,112 (p<.001) | -76,226,325 (p<.001) | N.S. | N.S. |
Util. febrile illness, F 65+ recipient | 6,637,931,910 (p<.001) | 3,834,139,152 (p=0.002) | N.S. | N.S. | 822,884 (p<.001) | N.S. | N.S. | N.S. |
ID-NAT sensitivity | N.S. | N.S. | -57,212,070 (p<.001) | -130,917,194 (p<.001) | N.S. | -57,212,070 (p<.001) | N.S. | -6,490,452,472 (p<.001) |
Prob. GBS | -5,731,030,778 (p=0.002) | -3,952,786,957 (p=0.001) | N.S. | N.S. | -674,597 (p=0.014) | N.S. | N.S. | N.S. |
Util. febrile illness, M 65+ recipient | 5,713,229,922 (p=0.002) | 3,682,379,003 (p=0.004) | N.S. | N.S. | 762,610 (p=0.002) | N.S. | N.S. | N.S. |
Transmissi-bility in FFP | -4,966,755,642 (p=0.013) | N.S. | N.S. | N.S. | -657,075 (p=0.019) | N.S. | N.S. | N.S. |
Cost separate inventory | N.S. | N.S. | N.S. | N.S. | N.S. | N.S. | N.S. | 4,238,069,204 (p<.001) |
ZIKV-infectious rate, FL KLT | N.S. | N.S. | -37,452,093 (p<.001) | -52,141,997 (p<.001) | -3,551,895 (p<.001) | -37,452,093 (p<.001) | N.S. | -3,014,948,912 (p<.001) |
ZIKV-infectious rate, TX KLT | N.S. | N.S. | -17,923,927 (p<.001) | N.S. | -1,573,477 (p<.001) | -17,923,927 (p<.001) | N.S. | N.S. |
Proportion of donors with travel | N.S. | N.S. | N.S. | 33,758,187 (p=0.002) | N.S. | N.S. | N.S. | N.S. |
1Each cell contains coefficients (ßj) and p-value. Coefficients can be interpreted as: “Holding all other parameters at their expected value, a one standard-deviation increase in the parameter will increase the outcome variable by ßj.” N.S. indicates that the coefficient was not statistically significant with the Benjamini-Yekuteils multiple comparison p-value adjustment applied. | ||||||||
Outcome | Recipients experiencing TTZ | Other recipients | Significance |
Total components transfused | 12.000 | 3.600 | Welch two-sample T-test p<.0001 |
Proportion of components FFP ( FFP/[PLT+RBC+FFP] ) | 0.360 | 0.200 | Welch two-sample T-test p<.0001 |
Proportion of recipients < 14 years of age | 0.027 | 0.041 | 2-sample test for equality of proportions with continuity correction p=0.02 |
Proportion of recipients > 75 years of age | 0.601 | 0.709 | 2-sample test for equality of proportions with continuity correction p<0.0001 |
Intervention1 | QALYs lost | Transfusion-transmissions | Mild febrile cases | Guillain-Barre cases | Congenital Zika syndrome cases |
Puerto Rico | |||||
NS | 1.31 | 156.5 | 28.7 | 0.0413 | 0.0201 |
1/2-MP | 0.19 | 23.1 | 4.2 | 0.0062 | 0.003 |
SI-ID | 0.72 | 143.5 | 26.3 | 0.0382 | 0.0028 |
1/2-ID | 0.11 | 13.5 | 2.5 | 0.0036 | 0.0018 |
MP | 0.1 | 12 | 2.2 | 0.0032 | 0.0015 |
1/2-ID-1/2-MP | 0.02 | 2.4 | 0.4 | 0.0006 | 0.0003 |
SI-ID-MP | 0.06 | 11.1 | 2 | 0.0029 | 0.0004 |
ID | 0.01 | 1.6 | 0.3 | 0.0004 | 0.0002 |
50 states | |||||
NS | 0.075 | 9.11 | 1.67 | 0.00248 | 0.00114 |
LA-MP | 0.019 | 2.21 | 0.41 | 0.00059 | 0.00028 |
LA-ID | 0.015 | 1.73 | 0.32 | 0.00045 | 0.00022 |
TA-MP | 0.006 | 0.7 | 0.13 | 0.00019 | 0.00009 |
TA-ID | 0.001 | 0.11 | 0.02 | 0.00003 | 0.00001 |
SI-ID | 0.042 | 8.34 | 1.53 | 0.00228 | 0.00015 |
MP | 0.006 | 0.68 | 0.13 | 0.00019 | 0.00009 |
SI-ID-MP | 0.003 | 0.63 | 0.12 | 0.00017 | 0.00002 |
ID | 0.001 | 0.09 | 0.02 | 0.00002 | 0.00001 |
Intervention | Blood center costs | Total costs | CER | ICER | |
Puerto Rico | |||||
NS | $0 | $114,985 | $0 | $0 | |
1/2-MP | $248,054 | $265,098 | $134,754 | $134,754 | |
SI-ID | $289,780 | $336,168 | $377,172 | Dominated | |
1/2-ID | $405,889 | $415,860 | $251,931 | $1,877,391 | |
MP | $483,400 | $492,230 | $312,389 | Dominated | |
1/2-ID-1/2-MP | $641,235 | $642,993 | $409,971 | $2,425,638 | |
SI-ID-MP | $733,949 | $738,163 | $499,712 | Dominated | |
ID | $797,620 | $798,799 | $528,241 | $23,627,387 | |
50 states | |||||
NS | $0 | $12,172 | $0 | $0 | |
LA-MP | $2,077,571 | $2,080,560 | $36,375,084 | $36,375,084 | |
LA-ID | $3,463,220 | $3,465,563 | $56,743,839 | $346,551,104 | |
TA-MP | $8,050,416 | $8,051,350 | $115,504,526 | $524,616,382 | |
TA-ID | $13,420,713 | $13,420,856 | $180,001,266 | $1,097,693,931 | |
SI-ID | $46,508,214 | $46,514,910 | $1,374,130,019 | Dominated | |
MP | $75,536,284 | $75,537,197 | $1,083,132,743 | Dominated | |
SI-ID-MP | $115,915,239 | $115,915,792 | $1,610,877,436 | Dominated | |
ID | $125,929,213 | $125,929,335 | $1,687,243,490 | $822,713,232,642 | |
1In the 50 states, assuming IgM-positive donations are non-infectious, ZIKV-infectious rates were: 2 in 196,993 donations for the Texas gulf during known local transmission; 7 in 176,423 donations for south Florida during known local transmission; 1.98 (2*0.99) in 1,074,020 donations for donors with travel exposure; and 0.02 (2*0.01) in 12,132,789 donations for donors with no travel or local exposure. In Puerto Rico, ZIKV-infectious rates were: 149.76 (234*0.64) in 35,461 donations during the high mosquito season and 345.6 (23*0.64) in 42,585 donations the low mosquito season. | |||||
Setting | interventions | True positives interdicted | False positives interdicted | Positive predictive value |
Puerto Rico1 | NS | 0.0 | 0.0e+00 | - |
1/2-MP | 153.0 | 0.0e+00 | 1 | |
SI-ID | 14.4 | 1.9e-01 | 0.987 | |
1/2-ID | 163.8 | 1.2e+00 | 0.993 | |
MP | 165.5 | 1.0e-04 | 1 | |
1/2-ID-1/2-MP | 176.3 | 1.2e+00 | 0.993 | |
SI-ID-MP | 166.5 | 1.9e-01 | 0.999 | |
ID | 177.2 | 2.3e+00 | 0.987 | |
50 states | NS | 0.0 | 0.0e+00 | |
LA-MP | 7.7 | 3.0e-04 | 1 | |
LA-ID | 8.3 | 1.0e+01 | 0.443 | |
TA-MP | 9.4 | 1.3e-03 | 1 | |
TA-ID | 10.1 | 4.0e+01 | 0.2 | |
SI-ID | 0.8 | 3.1e+01 | 0.026 | |
MP | 9.4 | 1.3e-02 | 0.999 | |
SI-ID-MP | 9.5 | 3.1e+01 | 0.236 | |
ID | 10.1 | 3.8e+02 | 0.026 | |
1Assumes that RNA+ donations that test IgM+ are released back into the blood supply. In the 50 states, ZIKV-infectious rates were: 2 in 196,993 donations for the Texas gulf during known local transmission; 7 in 176,423 donations for south Florida during known local transmission; 1.98 (2*0.99) in 1,074,020 donations for donors with travel exposure; and 0.02 (2*0.01) in 12,132,789 donations for donors with no travel or local exposure. In Puerto Rico, ZIKV-infectious rates were: 149.76 (234*0.64) in 35,461 donations during the high mosquito season and 345.6 (23*0.64) in 42,585 donations the low mosquito season. | ||||
Category | Description | Included? |
Former Health Care Sector | ||
Health effects | Longevity effects: Loss of life year simulated | Yes |
Health-related quality-of-life effects: The QALY lost due to transfusion-transmission of Zika was determined from the duration and utility of adverse events | Yes | |
Other health effects (e.g., adverse events and secondary transmission of infections): | Yes | |
the expected number of transfusion-transmissions, mild febrile illness cases, cases of Guillain-Barre syndrome, and congenital Zika syndrome resulting from transfusion-transmission were estimated under each policy. | ||
Medical costs | Paid for by third-party payers | Yes |
Paid for by patients out-of-pocket | Yes | |
Future related medical costs (payers and patients) | Yes | |
Future unrelated medical costs (payers and patients): We considered the impact of loss-of-life on future consumption, which included consumption of unrelated medical care. | Yes | |
Future unrelated medical costs (payers and patients): We considered the impact of loss-of-life on future consumption, which included consumption of unrelated medical care. | Yes | |
Informal Health Care Sector | ||
Additional costs | Patient-time costs | No |
Unpaid caregiver-time costs | No | |
Transportation costs | No | |
Transportation costs | No | |
Non-Health Care Sectors (with examples of possible items) | ||
Productivity | Labor market earnings lost | Yes |
Cost of unpaid lost productivity due to illness | Yes | |
Cost of uncompensated household production | Yes | |
Future consumption unrelated to health | Yes | |
Consumption | Cost of social services as part of intervention | Yes |
Social Services | Number of crimes related to intervention | NA |
Legal or Criminal Justice | Cost of crimes related to intervention | NA |
Impact of intervention on education achievement of population | NA | |
Education | Cost of intervention on home improvements (e.g., removing lead paint) | NA |
Housing | Production of toxic waste pollution by intervention | NA |
Environment | Other impacts | NA |
Other (specify) | We did not include the potential stress or unnecessary medical costs experienced by donors whose blood tested false-positive, nor the potential medical costs or health benefits conferred to the donor by notification of a true-positive test result. | |