Abstract
Background:
The Transfusion-Transmissible Infections Monitoring System assesses trends in ~60% of the US blood supply. Donors with high-risk behaviors, including injection drug users, men having sex with other men, or those exchanging sex for money/drugs, were deferred for 12 months (12 M) from 2016 to 2020 and 3 months (3M) from 2020 to 2023. Here we evaluate HIV, HBV, and HCV donation prevalence annually from 2015 to 2023 and in two comparison periods of pre-3M (2015–2020) and 3M (2020–2023) to identify differences between the two periods.
Methods:
Annual prevalence was assessed for 8 TTIMS years (2015–2023) and compared between the pre-3M and 3M periods. HIV, HBV, and HCV prevalence/100,000 donations (phtd) was calculated based on serology and nucleic acid testing results. Negative binomial regression assessed prevalence using 1-year intervals. Fisher’s exact test evaluated prevalence changes between the two periods (α = 0.05).
Results:
Annual HIV and HBV prevalence remained stable, changing slightly from year 1 to 8 (2.5–2.1 phtd for HIV and 6.3–6.6 phtd for HBV). HCV prevalence declined (19.7–9.6 phtd; p <.01). HIV (2.5–2.0 phtd) and HCV (18.4–9.8 phtd) prevalence decreased from pre-3M to 3M (p <.01), while HBV prevalence remained stable (6.5–6.2 phtd; p = .06).
Conclusions:
Despite reducing donor deferral periods for many infectious risk behaviors, HIV and HBV prevalence were stable, while HCV prevalence declined over 8 years. Either slight or significant declines occurred from the pre-3M to 3M period for all agents. Thus, changes in policy did not adversely impact the current safety of the blood supply with respect to the major infectious disease agents.
Keywords: infectious disease testing, transfusion-transmitted disease—hepatitis, transfusion-transmitted disease—HIV
1 |. INTRODUCTION
Prior to 2015, no routine, centralized mechanism to monitor the safety of the US blood supply existed due to the largely distributed nature of the US blood collection system. National monitoring of transfusion-transmissible infectious disease (TTID) rates was deemed necessary, as tracking TTID rates in donors and donations is one key measure used to assess the safety of the US blood supply.1,2 Therefore, in light of low TTID rates in donated blood, comprehensive national datasets were needed. In 2015, the US Food and Drug Administration (FDA), along with the National Heart, Lung, and Blood Institute (NHLBI) and The Office for the Assistant Secretary of Health, established the Transfusion Transmissible Infections Monitoring System (TTIMS) to accomplish this goal.1,3 Four major Blood Collection Organizations (BCOs) participate in TTIMS: the American Red Cross (ARC), New York Blood Center Enterprises (NYBCe), One Blood, and Vitalant. Together, these organizations collect approximately 60% of the US blood supply. TTIMS currently tracks the frequency of detection of HIV, HBV, HCV, and syphilis in the blood supply.
FDA updated donor eligibility guidance to reduce the donor deferral period for those presenting donors with high exposure risks currently defined by FDA; examples include men having sex with men (MSM), injection drug use, or exchanging sex for money or drugs. In 2016, deferral periods were decreased from indefinite to 12 months (12M) since the last exposure for MSM4 and in 2020, from 12 months to three months (3M) for MSM plus other high-risk exposures,5 prior to implementing individual donor assessment (IDA) in 20236 (Figure 1).
Figure 1:
Timeline of FDA donor deferral policy updates by TTIMS-participating blood collection organizations (BCOs), 2015–2023.
*Pink bars represent the periods in which each BCO started implementing an updated policy, with BCO-specific start dates provided in the figure.
Syphilis was added to the list of TTIDs monitored by TTIMS in 2020 with the initial trends published elsewhere.7 The prevalence of HIV, HBV, and HCV for the first 4 years of TTIMS (2015–2019) including most of the 12M period has been published.1 There has not been a study of longer-term prevalence trends for HIV, HBV, and HCV in the US blood supply since the implementation of TTIMS and the impact of updated national donor management policies available. This study assesses the annual prevalence and overall trends for HIV, HBV, and HCV in 8 years of TTIMS, from 2015 to 2023, and evaluates and compares agent-specific prevalence for two periods of donor deferral: Pre-3M and 3M (approximately corresponding to 2015–2020 and 2020–2023, respectively).
2 |. MATERIALS AND METHODS
2.1 |. Study participants and human subject protection
Deidentified demographic data related to donors and their donations is provided by BCOs participating in TTIMS monthly. Infectious disease testing results are provided by Creative Testing Solutions for ARC, One-Blood, and Vitalant, and by Rhode Island Blood Center and Minneapolis Memorial Blood Centers for NYBCe.
Each participating BCO obtained institutional review board approval for TTIMS research. Donor consent was obtained at the time of the donation, describing the possible use of deidentified demographic and test data for blood safety-related research.
2.2 |. Data source, data dictionary, and donor demographics
A subset of available TTIMS data from October 1, 2015, to September 30, 2023, was compiled and analyzed. A data dictionary was developed at the outset of TTIMS. Only donations from allogeneic donors (including COVID-19 convalescent plasma) and directed donors whose donations completed index sample testing with valid test results (reactive and nonreactive) for HIV, HBV, and HCV during this period were analyzed. Donor demographics are self-reported at the time of the donation. Data were limited to those with self-reported sex of male or female and age of 16–105. US Census Regions were determined based on published CDC classification.8 All statistical analyses were conducted using SAS, Version 9.4, SAS Institute, Cary, North Carolina.
2.3 |. Consensus-positive definitions
All licensed BCOs are required to perform serology and nucleic acid testing (mini-pool, MP-NAT, used by most BCOs in the US) for HIV, HBV, and HCV using FDA-licensed assays. As confirmatory or supplemental testing may vary between BCOs, consensus-positive definitions were developed for each monitored agent at the start of TTIMS to ensure consistent interpretation of results among all BCOs. Several categories of consensus positivity were defined based on serology and NAT results, including concordant positives. Additionally, for HIV, low-level NAT (low-level RNA reactivity) and seropositive categories, and for HBV, HBsAg-yield category (HBV surface antigen positive only) were defined (full descriptions in Tables 1a–1c). The additional yield category for HBV extends the number of acute infections identified.
Table 1a.
TTIMS consensus-positive definitions, count of positive donations, and prevalence per 100 000 donations and associated 95% confidence intervals (CIs) for HIV by year and overall, Oct 1 2015 - Sep 30 2023.
| Year 1 (2015–2016) |
Year 2 (2016–2017) |
Year 3 (2017–2018) |
Year 4 (2018–2019) |
Year 5 (2019–2020) |
Year 6 (2020–2021) |
Year 7 (2021–2022) |
Year 8 (2022–2023) |
Overall (2015–2023) |
P value* | |
|---|---|---|---|---|---|---|---|---|---|---|
| Total Donations (N) | 6 993 134 | 6 927 969 | 6 843 510 | 6 700 915 | 6 614 399 | 7 575 290 | 7 169 129 | 7 217 515 | 56 041 861 | |
| Consensus-positive definitions |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
|
| HIV concordant positive: HIV Ab RR + dHIV R | 169 | 180 | 141 | 185 | 131 | 93 | 115 | 125 | 1139 | |
| 2.42 | 2.60 | 2.06 | 2.76 | 1.98 | 1.23 | 1.60 | 1.73 | 2.03 | 0.02↓ | |
| (2.08–2.81) | (2.25–3.01) | (1.75–2.43) | (2.39–3.19) | (1.67–2.35) | (1.00–1.50) | (1.34–1.93) | (1.45–2.06) | (1.92–2.15) | ||
| HIV NAT yield positive: HIV Ab NR + dHIV R and dHIV R in an independent or follow-up sample | 4 | 2 | 5 | 3 | 2 | 2 | 1 | 3 | 22 | |
| 0.06 | 0.03 | 0.07 | 0.04 | 0.03 | 0.03 | 0.01 | 0.04 | 0.04 | 0.27 | |
| (0.02–0.15) | (0.01–0.11) | (0.03–0.17) | (0.02–0.13) | (0.01–0.11) | (0.01–0.10) | (0.00–0.08) | (0.01–0.12) | (0.03–0.06) | ||
| HIV low-level NAT confirmed: HIV Ab confirmed positive or indeterminate** + dHIV NR, confirmed by subsequent testing of an independent sample as HIV-1 Ab confirmed positive and R in ≥1 of 10 replicate dHIV tests | 3 | 6 | 6 | 11 | 4 | 21 | 22 | 24 | 97 | |
| 0.04 | 0.09 | 0.09 | 0.16 | 0.06 | 0.28 | 0.31 | 0.33 | 0.17 | <0.01↑ | |
| (0.01–0.13) | (0.04–0.19) | (0.04–0.19) | (0.09–0.29) | (0.02–0.16) | (0.18–0.42) | (0.20–0.46) | (0.22–0.49) | (0.14–0.21) | ||
| HIV Seropositive: HIV Ab confirmed positive or indeterminate** + dHIV NR, confirmed by subsequent testing of an independent sample as HIV-1 Ab confirmed positive and NR in replicate dHIV tests | 1 | 4 | 0 | 2 | 2 | 11 | 10 | 7 | 37 | |
| 0.01 | 0.06 | 0 | 0.03 | 0.03 | 0.15 | 0.14 | 0.10 | 0.07 | <0.01↑ | |
| (0.00–0.08) | (0.02–0.15) | (0.00–0.06) | (0.01–0.11) | (0.01–0.11) | (0.08–0.26) | (0.08–0.26) | (0.05–0.20) | (0.05–0.09) | ||
| Total HIV consensus positive: HIV-concordant positive + HIV-yield positive + HIV-low-level NAT confirmed positive + HIV- seropositive | 177 | 192 | 152 | 201 | 139 | 127 | 148 | 159 | 1295 | |
| 2.53 | 2.77 | 2.22 | 3.00 | 2.10 | 1.68 | 2.06 | 2.20 | 2.31 | 0.06 | |
| (2.18–2.93) | (2.41–3.19) | (1.89–2.60) | (2.61–3.44) | (1.78–2.48) | (1.41–1.99) | (1.76–2.42) | (1.89–2.57) | (2.19–2.44) |
p-value for trend analysis using negative binomial regression, significance p ≤0.05; arrows indicate the direction of the significant trend.
Two definitions implemented for HIV Ab testing on index samples to identify HIV low-level NAT confirmed and HIV seropositive donations in TTIMS1 and TTIMS2: TTIMS1 definition – HIV Ab confirmed positive on index sample and TTIMS2 definition – HIV Ab confirmed positive or indeterminate on index sample.
2.4 |. Prevalence
Eight annual prevalence periods were defined between October 1, 2015, and September 30, 2023, in accordance with TTIMS years that began on October 1 of a year and ended on September 30 of the subsequent year. Primary analyses were conducted for annual periods and overall. Additionally, two periods were distinguished to evaluate any differences in prevalence between the period prior to the implementation of 3-month deferral (pre-3M) in 2020 and the period of 3-month deferral (3M). We found that the pre-3M period, including the 12M period, was not significantly different; therefore, we used the entire pre-3M period (including the 12M period) to compare to the 3M period. The 3M deferral policy was implemented by BCOs on different dates (Figure 1). Therefore, the pre-3M period was defined as the period between Oct 1, 2015, and the BCO-specific 3M-deferral implementation date in 2020, while the 3M period was defined as the BCO-specific start date of the 3M-deferral implementation and September 30, 2023. Prevalence was defined as the total number of TTIMS consensus-positive donations in first-time (FT) and repeat (RPT) donors divided by all evaluable donations meeting the inclusion criteria. RPT donor incidence will be managed in a separate dedicated manuscript. The 95% confidence intervals (CIs) were calculated using the Wilson Score method. The negative binomial regression method was used to assess the presence of temporal trends in TTID-marker prevalence and to establish the final regression model adjusted for demographic and regional characteristics of the study population. Fisher’s exact test was used to compare pre-3M and 3M period-specific prevalence estimates. All statistical significance was assessed at α = 0.05.
3 |. RESULTS
3.1 |. TTIMS study population and demographics
The first 8 years, covering October 1, 2015, to September 30, 2023, included 56,041,861 donations from 15,841,010 unique donors (average 3.5 donations/donor). Of participating sites, ARC contributed data for 66.7% of donations, NYBCe 7.0%, OneBlood 11.5%, and Vitalant 14.8%. Donations from FT donors accounted for 17.4% of the total, with females slightly fewer than males (48.5% vs. 51.5%; Table S1). Donations from donors 25 years and older had the largest overall proportion (42.9% for 25–54-year-olds and 42.7% for those 55 years and older), declining by decreasing age to the lowest for 16–17-year-olds (5.3%), likely attributable to the COVID-19 pandemic due to limited high-school blood drives and increased donation from older donors.7 The oldest donors were most prevalent in the last 3-year period. Donations from donors residing in US census regions ranged from 19.4% in the Northeast to 30.8% in the South. Regarding race/ethnicity, 83.1% of total donations were given by donors identifying as White, 7.5% as Hispanic, 3.5% as Black, and 2.7% as Asian. In the last 3 years of TTIMS, there was a shift toward the oldest donors, and the proportion of FT versus RPT donors and their donations changed. These changes highlight the increase in the proportion of RPT donations (35% and 65% (12M) vs. 28% and 72% (3M), for FT and RPT donations, respectively) and were also likely attributable to COVID-19.9
3.2 |. Prevalence
3.2.1 |. Overall
There were 1295 HIV consensus-positive donations contributing to a prevalence of 2.31 per hundred thousand donations (phtd), 3553 (6.34 phtd) for HBV, and 8251 (14.72 phtd) for HCV (Tables 1a–1c). Prevalence of concordant positives was 2.03, 6.07, and 14.40 phtd for HIV, HBV, and HCV, respectively. For NAT-yield positives, an indicator of a recent infection, overall prevalence was 0.04 phtd for HIV, 0.13 phtd for HBV, and 0.32 phtd for HCV. Additionally, for HIV, prevalence was 0.17 phtd for low-level NAT positives and 0.07 phtd for seropositive donations (the group lacking detectable RNA). For these last two HIV groups, there was an approximate 3–5-fold increase in number and rates in the last 3-year period.
Table 1c.
TTIMS consensus-positive definitions, count of positive donations, and prevalence per 100 000 donations and associated 95% confidence intervals (CIs) for HCV by year and overall, Oct 1 2015 - Sep 30 2023.
| Year 1 (2015–2016) |
Year 2 (2016–2017) |
Year 3 (2017–2018) |
Year 4 (2018–2019) |
Year 5 (2019–2020) |
Year 6 (2020–2021) |
Year 7 (2021–2022) |
Year 8 (2022–2023) |
Overall (2015–2023) |
P value* | |
|---|---|---|---|---|---|---|---|---|---|---|
| Total Donations (N) | 6 993 134 | 6 927 969 | 6 843 510 | 6 700 915 | 6 614 399 | 7 575 290 | 7 169 129 | 7 217 515 | 56 041 861 | |
| Consensus-positive definitions |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
|
|
HCV concordant positive: HCV Ab RR + dHCV R |
1326 | 1364 | 1245 | 1132 | 915 | 681 | 723 | 686 | 8072 | |
| 18.96 | 19.69 | 18.19 | 16.89 | 13.83 | 8.99 | 10.08 | 9.50 | 14.40 | <0.01↓ | |
| (17.97–20.01) | (18.67–20.76) | (17.21–19.23) | (15.94–17.91) | (12.97–14.76) | (8.34–9.69) | (9.38–10.85) | (8.82–10.24) | (14.09–14.72) | ||
| HCV NAT-yield positive: dHCV R + HCV Ab NR and dHCV R in an independent or follow-up sample | 51 | 35 | 36 | 29 | 9 | 6 | 8 | 5 | 179 | |
| 0.73 | 0.51 | 0.53 | 0.43 | 0.14 | 0.08 | 0.11 | 0.07 | 0.32 | <0.01↓ | |
| (0.55–0.96) | (0.36–0.70) | (0.38–0.73) | (0.30–0.62) | (0.07–0.26) | (0.04–0.17) | (0.06–0.22) | (0.03–0.16) | (0.28–0.37) | ||
| Total HCV consensus positive : HCV concordant positive + HCV-yield positive | 1377 | 1399 | 1281 | 1161 | 924 | 687 | 731 | 691 | 8251 | |
| 19.69 | 20.19 | 18.72 | 17.33 | 13.97 | 9.07 | 10.20 | 9.57 | 14.72 | ||
| (18.68–20.76) | (19.16–21.28) | (17.72–19.77) | (16.36–18.35) | (13.10–14.90) | (8.42–9.77) | (9.48–10.96) | (8.89–10.31) | (14.41–15.04) | <0.01↓ |
p-value for trend analysis using negative binomial regression, significance p ≤ 0.05; arrows indicate the direction of the significant trend.
Overall HIV prevalence was higher among males (3.7 phtd), FT donors (8.8 phtd), those who resided in the South (5.0 phtd), were 18–24 years old (5.9 phtd), and those who identified as Black (24.1 phtd) (Table 2). For HBV, similarly, the highest prevalence was observed among males (8.7 phtd), FT donors (31.9 phtd), and residents of the Southern census region (9.6 phtd). However, for age groups and race/ethnicity, HBV prevalence was highest among 25–54-year-olds (9.1 phtd) and those who identified as Asian (85.9 phtd) or Black (39.6 phtd). The highest prevalence of HCV was reported among males (19.0 phtd), FT donors (72.1 phtd), those who resided in the South (32.7 phtd), who were 25–54 years old (23.2 phtd), and identified as American Indian (55.4 phtd) or did not report their race/ethnicity (38.8 phtd), followed by Black (26.2 phtd) and Hispanic/Latino (19.7 phtd). For all agents, the highest prevalence occurred in donors who were male, FT, non-White, 18–54 years old, and from the South.
Table 2:
Overall prevalence of HIV, HBV, and HCV per 100 000 donations and their associated 95% confidence intervals (CIs) for TTIMS, Oct 1 2015 - Sep 30 2023.
| HIV |
HBV |
HCV |
||||
|---|---|---|---|---|---|---|
| Rate | 95% CI | Rate | 95% CI | Rate | 95% CI | |
| Total Donations N= 56 041 861 |
||||||
| Overall | 2.3 | (2.2–2.4) | 6.3 | (6.1–6.6) | 14.7 | (14.4–15.0) |
| Sex | ||||||
| Female | 0.8 | (0.7–0.9) | 3.8 | (3.6–4.1) | 10.2 | (9.8–10.6) |
| Male | 3.7 | (3.5–3.9) | 8.7 | (8.4–9.0) | 19.0 | (18.5–19.5) |
| Donation Status | ||||||
| First-time donors | 8.8 | (8.2–9.4) | 31.9 | (30.8–33.1) | 72.1 | (70.4–73.8) |
| Repeat donors | 0.9 | (0.9–1.0) | 1.0 | (0.9–1.1) | 2.7 | (2.5–2.8) |
| Age group | ||||||
| 16 to 17 | 2.7 | (2.2–3.3) | 5.6 | (4.8–6.5) | 3.7 | (3.1–4.5) |
| 18 to 24 | 5.9 | (5.3–6.6) | 6.1 | (5.5–6.9) | 10.9 | (10–11.8) |
| 25 to 54 | 3.2 | (3.0–3.4) | 9.1 | (8.7–9.5) | 23.2 | (22.6–23.8) |
| 55+ | 0.6 | (0.5–0.7) | 3.7 | (3.5–4.0) | 8.4 | (8.1–8.8) |
| Race/Ethnicity | ||||||
| Asian | 1.9 | (1.3–2.7) | 85.9 | (81.3–90.7) | 5.2 | (4.1–6.4) |
| White | 1.0 | (0.9–1.1) | 2.0 | (1.9–2.2) | 13.6 | (13.3–13.9) |
| Hispanic/Latino | 5.5 | (4.9–6.3) | 5.5 | (4.9–6.3) | 19.7 | (18.4–21.1) |
| Black | 24.1 | (22.1–26.4) | 39.6 | (36.9–42.5) | 26.3 | (24.1–28.7) |
| American Indian | 6.3 | (3.7–10.8) | 6.3 | (3.7–10.8) | 55.4 | (46.2–66.6) |
| Other/>1 race | 4.3 | (3.1–5.9) | 19.2 | (16.5–22.3) | 12.9 | (10.8–15.5) |
| Not reported | 5.4 | (3.9–7.4) | 18.8 | (15.9–22.4) | 38.8 | (34.5–43.8) |
| Census Region | ||||||
| Midwest | 1.0 | (0.8–1.1) | 3.3 | (3.1–3.6) | 6.2 | (5.8–6.6) |
| Northeast | 1.0 | (0.8–1.2) | 5.2 | (4.8–5.6) | 6.2 | (5.7–6.6) |
| South | 5.0 | (4.7–5.3) | 9.6 | (9.2–10.1) | 32.7 | (31.9–33.6) |
| West | 1.4 | (1.2–1.6) | 6.4 | (6.0–6.9) | 7.8 | (7.3–8.3) |
3.2.2 |. Pre-3M and 3M prevalence
For HIV, overall prevalence decreased from 2.5 phtd in the pre-3M period to 2.0 phtd in the 3M period (p <.01; Table 3). All prevalence estimates either remained unchanged or declined from the pre-3M period to the 3M period, except FT donors (8.2 phtd and 9.9 phtd, respectively) and those who were 55 years or older (0.5 phtd and 0.7 phtd, respectively), both of which increased (p = .01).
Table 3:
Prevalence of HIV, HBV, and HCV per 100 000 donations and their associated 95% confidence intervals (CIs) for pre-3M and 3M periods of TTIMS, Oct 1 2015 - Sep 30 2023.
| HIV - Rate (95% CI) | HBV - Rate (95% CI) | HCV - Rate (95% CI) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Pre-3M | 3M | P value* | Pre-3M | 3M | P value | Pre-3M | 3M | P value | |
|
| |||||||||
| Total donations | 32,075,637 | 23,966,224 | 32,075,637 | 23,966,224 | 32,075,637 | 23,966,224 | |||
| All | 2.5 (2.4–2.7) | 2.0 (1.8–2.2) | <0.01↓ | 6.5 (6.2–6.7) | 6.2 (5.9–6.5) | 0.24 | 18.4 (18.0–18.9) | 9.8 (9.4–10.2) | <0.01↓ |
| Sex | |||||||||
| Female | 1.0 (0.8–1.1) | 0.6 (0.5–0.8) | <0.01↓ | 3.9 (3.6–4.3) | 3.7 (3.4–4.1) | 0.38 | 13.5 (12.9–14.0) | 6.0 (5.6–6.5) | <0.01↓ |
| Male | 3.9 (3.7–4.3) | 3.4 (3.0–3.7) | <0.01↓ | 8.7 (8.3–9.2) | 8.7 (8.2–9.2) | 1.00 | 22.9 (22.2–23.6) | 13.5 (12.9–14.2) | <0.01↓ |
| Donation status | |||||||||
| First-time donors | 8.2 (7.5–8.9) | 9.9 (8.9–11.0) | 0.01↑ ** | 29.2 (27.9–30.6) | 37.1 (35.1–39.3) | <0.01↑ | 78.8 (76.7–81.0) | 59.2 (56.6–61.9) | <0.01↓ |
| Repeat donors | 1.1 (1.0–1.3) | 0.7 (0.6–0.8) | <0.01↓ | 0.8 (0.7–0.9) | 1.2 (1.0–1.3) | <0.01↑ | 3.4 (3.2–3.6) | 1.8 (1.6–1.9) | <0.01↓ |
| Age group | |||||||||
| 16 to 17 | 2.7 (2.1–3.4) | 2.8 (1.8–4.3) | 0.89 | 6.2 (5.2–7.3) | 3.6 (2.5–5.3) | 0.01↓ | 3.8 (3.1–4.7) | 3.5 (2.3–5.2) | 0.74 |
| 18 to 24 | 6.3 (5.6–7.2) | 4.8 (3.8–6.0) | 0.04↓ | 6.6 (5.8–7.5) | 4.9 (3.9–6.2) | 0.03↓ | 14.1 (12.9–15.4) | 3.1 (2.3–4.1) | <0.01↓ |
| 25 to 54 | 3.4 (3.1–3.7) | 2.9 (2.6–3.3) | 0.05 | 9.6 (9.1–10.1) | 8.5 (7.9–9.0) | <0.01↓ | 29 (28.1–29.9) | 15.4 (14.6–16.1) | <0.01↓ |
| 55+ | 0.5 (0.4–0.6) | 0.7 (0.6–0.9) | 0.01↑ | 3.0 (2.7–3.3) | 4.5 (4.1–4.9) | <0.01↑ | 10.7 (10.1–11.3) | 6.0 (5.6–6.5) | <0.01↓ |
| Race | |||||||||
| Asian | 2.0 (1.3–3.3) | 1.7 (0.9–3.0) | 0.70 | 90.9 (84.7–97.6) | 79.4 (72.9–86.6) | 0.02↓ | 6.8 (5.3–8.8) | 3.0 (2.0–4.7) | <0.01↓ |
| White | 1.1 (1.0–1.2) | 0.9 (0.8–1.0) | 0.03↓ | 1.9 (1.7–2.1) | 2.2 (2.0–2.4) | 0.04↑ | 17.2 (16.7–17.7) | 9.0 (8.6–9.4) | <0.01↓ |
| Hispanic/Latino | 5.3 (4.5–6.2) | 6.1 (5.0–7.6) | 0.24 | 5.0 (4.2–5.9) | 6.5 (5.3–7.9) | 0.05 | 23.0 (21.3–24.9) | 13.5 (11.7–15.5) | <0.01↓ |
| Black | 24.8 (22.2–27.6) | 22.9 (19.5–26.9) | 0.44 | 35.9 (32.8–39.3) | 47.0 (42–52.5) | <0.01↑ | 28.6 (25.9–31.6) | 21.7 (18.4–25.5) | <0.01↓ |
| American Indian | 4.6 (2.1–10.1) | 9.2 (4.5–19) | 0.25 | 7.7 (4.2–14.2) | 3.9 (1.3–11.6) | 0.40 | 61.8 (49.7–76.9) | 44.6 (31.9–62.3) | 0.12 |
| Other/>1 race | 3.7 (2.4–5.8) | 5.2 (3.3–8.2) | 0.32 | 21.5 (17.9–25.8) | 15.5 (11.9–20.2) | 0.05 | 15.5 (12.5–19.3) | 8.9 (6.3–12.6) | <0.01↓ |
| Not reported | 4.7 (3.0–7.6) | 6.0 (3.9–9.3) | 0.51 | 20.3 (16.2–25.5) | 17.2 (13.3–22.3) | 0.38 | 51.5 (44.6–59.4) | 25.1 (20.2–31.1) | <0.01↓ |
| Census Region | |||||||||
| Midwest | 1.0 (0.8–1.3) | 0.9 (0.7–1.1) | 0.36 | 3.3 (2.9–3.7) | 3.4 (2.9–3.8) | 0.89 | 8.0 (7.5–8.7) | 3.9 (3.4–4.4) | <0.01↓ |
| Northeast | 1.2 (1.0–1.5) | 0.7 (0.5–1.0) | <0.01↓ | 5.8 (5.3–6.5) | 4.2 (3.6–4.8) | <0.01↓ | 8.1 (7.4–8.8) | 3.5 (3–4.1) | <0.01↓ |
| South | 5.4 (4.9–5.8) | 4.5 (4.0–5.0) | 0.01↓ | 9.5 (8.9–10.1) | 9.9 (9.2–10.7) | 0.34 | 39.6 (38.4–40.9) | 22.8 (21.8–24) | <0.01↓ |
| West | 1.5 (1.2–1.8) | 1.2 (0.9–1.5) | 0.14 | 6.4 (5.8–7.0) | 6.5 (5.9–7.2) | 0.83 | 9.8 (9.1–10.6) | 5.2 (4.7–5.9) | <0.01↓ |
Fisher’s exact test
Arrows indicate the direction of the significant change from pre-3M period to 3M period for a given subgroup
While HBV prevalence was 6.5 phtd in the pre-3M period, there was an observed decrease in the 3M period to 6.2 phtd that was not significant (Table 3). Both periods were characterized by the lowest prevalence among donations from RPT donors (0.8 phtd and 1.2 phtd for pre-3M and 3M periods, respectively). The prevalence of HBV increased both for donations from FT and RPT donors from the pre-3M to the 3M period (29.2 phtd vs. 37.1 phtd and 0.8 phtd vs. 1.2 phtd, respectively; p ≤0.01) in contrast to overall prevalence (6.5 phtd vs. 6.2 phtd, respectively). This contrast is primarily due to the change in donor presentation profile in the 3M period characterized by decreased FT donations, which affected the overall population in prevalence estimations. HBV prevalence in donations from Black donors (35.9 phtd vs. 47.0 phtd, respectively), as well as those who were 55 years or older (3.0 phtd vs. 4.5 phtd, respectively) increased. Additionally, there were non-significant increases in prevalence for Hispanic/Latino race/ethnicity and all regional subgroups except those residing in the Northeast. Prevalence was unchanged or decreased from the pre-3M to the 3M periods in all other demographic and regional subgroups.
Overall HCV prevalence was 18.4 phtd vs. 9.8 phtd in the pre-3M and the 3M periods, respectively (p <.01, Table 3). The highest prevalence was observed among FT donations in both periods (78.8 phtd and 59.2 phtd, respectively). Prevalence declined from the pre-3M period to the 3M period for all demographic and regional subgroups (p <.01). The youngest subgroup of 16–17-year-olds (3.8 phtd vs. 3.5 phtd, respectively) and those reporting their race/ethnicity as American Indian (61.8 phtd vs. 44.6 phtd, respectively) also decreased, but not significantly.
3.2.3 |. Overall trends
Annual HIV and HBV prevalence remained stable, changing slightly from 2.5 phtd in year 1 to 2.1 phtd in year 8 for HIV (p = .06) and from 6.3 phtd in year 1 to 6.6 phtd in year 8 for HBV (p = .75) (Tables 4a and 4b; Figure 2). HCV prevalence decreased significantly from 19.7 phtd in year 1 to 9.6 phtd in year 8 (p <.01) (Table 4c; Figure 2), although years 6–8 rates that corresponded to the 3M-deferral period plateaued.
Table 4a:
TTIMS Years 1 to 8 prevalence per 100 000 donations and associated 95% confidence intervals (CIs) for HIV for demographic characteristics, Oct 1 2015 - Sep 30 2023.
| Year 1 (2015–2016) |
Year 2 (2016–2017) |
Year 3 (2017–2018) |
Year 4 (2018–2019) |
Year 5 (2019–2020) |
Year 6 (2020–2021) |
Year 7 (2021–2022) |
Year 8 (2022–2023) |
P value* | |
|---|---|---|---|---|---|---|---|---|---|
| Rate 95% CI | Rate 95% CI | Rate 95% CI | Rate 95% CI | Rate 95% CI | Rate 95% CI | Rate 95% CI | Rate 95% CI | ||
| Total Donations | N= 6 993 134 | N= 6 927 969 | N= 6 843 510 | N= 6 700 915 | N= 6 614 399 | N= 7 575 290 | N= 7 169 129 | N= 7 217 515 | |
| Overall | 2.5 (2.2–2.9) | 2.8 (2.4–3.2) | 2.2 (1.9–2.6) | 3.0 (2.6–3.4) | 2.1 (1.8–2.5) | 1.7 (1.4–2.0) | 2.1 (1.8–2.4) | 2.1 (1.8–2.5) | 0.06 |
| Sex | |||||||||
| Female | 1.0 (0.7–1.4) | 1.1 (0.8–1.6) | 0.6 (0.4–1) | 1.2 (0.9–1.7) | 0.9 (0.6–1.3) | 0.6 (0.4–0.9) | 0.6 (0.4–1.0) | 0.6 (0.4–1.0) | 0.05 |
| Male | 3.9 (3.3–4.6) | 4.2 (3.6–4.9) | 3.7 (3.1–4.3) | 4.6 (3.9–5.3) | 3.3 (2.8–4.0) | 2.8 (2.3–3.4) | 3.5 (2.9–4.2) | 3.5 (3.0–4.2) | 0.12 |
| Donation Status | |||||||||
| First-time donors | 7.2 (5.9–8.7) | 8.4 (7–10.1) | 7.4 (6.1–9) | 10.4 (8.8–12.3) | 7.4 (6.1–9.0) | 9.6 (7.9–11.8) | 10.5 (8.7–12.8) | 10.5 (8.6–12.7) | 0.02↑ |
| Repeat donors | 1.4 (1.1–1.7) | 1.4 (1.1–1.7) | 0.9 (0.7–1.2) | 1.2 (0.9–1.5) | 0.8 (0.6–1.1) | 0.5 (0.4–0.7) | 0.7 (0.6–1.0) | 0.8 (0.6–1.0) | <0.01↓ |
| Age group | |||||||||
| 16 to 17 | 2.6 (1.6–4.3) | 3.0 (1.8–4.8) | 3.8 (2.5–6.0) | 1.9 (0.9–3.7) | 1.1 (0.4–3.1) | 0.0 (0.0–2.9) | 3.2 (1.6–6.4) | 3.7 (2.1–6.6) | 0.91 |
| 18 to 24 | 5.8 (4.4–7.6) | 6.2 (4.8–8.2) | 6.0 (4.5–8.0) | 8.3 (6.4–10.8) | 5.2 (3.6–7.5) | 4.5 (2.9–6.9) | 3.6 (2.2–5.8) | 5.9 (4.1–8.5) | 0.22 |
| 25 to 54 | 3.4 (2.8–4.2) | 3.6 (3–4.3) | 2.7 (2.1–3.3) | 4.1 (3.4–4.9) | 3.0 (2.5–3.7) | 2.4 (1.9–3.0) | 3.2 (2.6–3.9) | 3.1 (2.6–3.9) | 0.42 |
| 55+ | 0.3 (0.1–0.6) | 0.7 (0.4–1.1) | 0.3 (0.2–0.6) | 0.6 (0.4–1.0) | 0.7 (0.4–1.0) | 0.7 (0.5–1.0) | 0.8 (0.6–1.2) | 0.6 (0.4–1.0) | 0.03↑ |
| Race | |||||||||
| Asian | 1.2 (0.3–4.4) | 2.2 (0.9–5.8) | 0.5 (0.1–3.1) | 3.7 (1.8–7.7) | 3.1 (1.3–7.2) | 1.6 (0.6–4.8) | 2 (0.8–5.1) | 0.9 (0.2–3.2) | 0.83 |
| White | 1.0 (0.8–1.3) | 1.3 (1–1.6) | 0.9 (0.7–1.2) | 1.3 (1–1.6) | 1 (0.8–1.3) | 0.8 (0.6–1) | 0.8 (0.6–1.1) | 0.9 (0.7–1.2) | 0.15 |
| Hispanic/Latino | 4.1 (2.8–5.9) | 6.4 (4.7–8.7) | 5.4 (3.8–7.7) | 6.3 (4.6–8.8) | 4.4 (2.8–6.8) | 5.8 (3.9–8.6) | 5.7 (3.8–8.3) | 6.5 (4.6–9.1) | 0.40 |
| Black | 27.4 (22.1–34.0) | 21.1 (16.5–26.9) | 21.5 (16.8–27.6) | 29.8 (24–37) | 24.6 (18.7–32.4) | 18.2 (12.9–25.7) | 27.6 (21.3–35.9) | 21.4 (16.2–28.3) | 0.62 |
| American Indian | 3.6 (0.6–20.7) | 3.5 (0.6–20) | 0.0 (0–12.9) | 7.3 (2–26.6) | 8.6 (2.4–31.4) | 21.5 (9.2–50.4) | 4.3 (0.8–24.4) | 4.2 (0.7–23.5) | 0.28 |
| Other/>1 race | 2.7 (0.9–7.9) | 5.1 (2.4–11.2) | 4.2 (1.8–9.9) | 3.5 (1.4–9) | 2 (0.5–7.3) | 5.9 (2.7–12.8) | 3.8 (1.5–9.8) | 7 (3.6–13.9) | 0.23 |
| Not reported | 3.7 (1.7–8.2) | 10.0 (4.3–23.4) | 5.7 (1.9–16.8) | 1.9 (0.3–10.6) | 3.4 (0.9–12.3) | 6.4 (3–14.1) | 6.7 (3.2–13.8) | 6 (2.9–12.4) | 0.35 |
| Census Region | |||||||||
| Midwest | 1.0 (0.7–1.6) | 1.3 (0.8–1.9) | 0.9 (0.6–1.5) | 1.2 (0.8–1.8) | 0.9 (0.5–1.4) | 0.5 (0.3–0.9) | 1 (0.6–1.5) | 1.1 (0.7–1.7) | 0.49 |
| Northeast | 1.6 (1.0–2.4) | 1.1 (0.7–1.8) | 0.6 (0.3–1.2) | 1.8 (1.2–2.7) | 0.9 (0.5–1.6) | 0.3 (0.1–0.7) | 0.7 (0.4–1.4) | 1.1 (0.7–1.8) | 0.47 |
| South | 5.3 (4.4–6.3) | 5.2 (4.4–6.3) | 5.1 (4.2–6.1) | 6.4 (5.4–7.6) | 4.3 (3.5–5.3) | 4.3 (3.5–5.3) | 4.8 (3.9–5.8) | 4.4 (3.6–5.4) | 0.09 |
| West | 1.2 (0.8–1.9) | 2.5 (1.8–3.4) | 1.1 (0.7–1.8) | 1.3 (0.8–2) | 1.4 (0.9–2.1) | 0.9 (0.6–1.5) | 1.1 (0.7–1.7) | 1.4 (1–2.1) | 0.28 |
p-values for trend analysis using negative binomial regression analysis for 8-year period; significance at p<0.05; arrows indicate the direction of the significant trend.
Table 4b:
TTIMS Years 1 to 8 prevalence per 100 000 donations and associated 95% confidence intervals (CIs) for HBV for demographic characteristics, Oct 1 2015 - Sep 30 2023.
| Year 1 (2015–2016) |
Year 2 (2016–2017) |
Year 3 (2017–2018) |
Year 4 (2018–2019) |
Year 5 (2019–2020) |
Year 6 (2020–2021) |
Year 7 (2021–2022) |
Year 8 (2022–2023) |
P value* | |
|---|---|---|---|---|---|---|---|---|---|
| Rate 95% CI | Rate 95% CI | Rate 95% CI | Rate 95% CI | Rate 95% CI | Rate 95% CI | Rate 95% CI | Rate 95% CI | ||
| Total Donations | N= 6 993 134 | N= 6 927 969 | N= 6 843 510 | N= 6 700 915 | N= 6 614 399 | N= 7 575 290 | N= 7 169 129 | N= 7 217 515 | |
| Overall | 6.3 (5.7–6.9) | 6.6 (6–7.2) | 6.3 (5.7–6.9) | 6.6 (6.0–7.3) | 6.6 (6–7.2) | 5.3 (4.8–5.8) | 6.6 (6.0–7.2) | 6.6 (6.0–7.2) | 0.75 |
| Sex | |||||||||
| Female | 4.1 (3.5–4.9) | 3.8 (3.2–4.5) | 3.6 (3.0–4.3) | 4.4 (3.7–5.2) | 4 (3.4–4.8) | 2.9 (2.4–3.5) | 4.2 (3.6–4.9) | 3.9 (3.3–4.6) | 0.67 |
| Male | 8.1 (7.3–9.1) | 9.1 (8.1–10.1) | 8.7 (7.8–9.8) | 8.6 (7.7–9.7) | 9.1 (8.1–10.2) | 7.8 (6.9–8.7) | 9.0 (8.1–10.1) | 9.1 (8.2–10.2) | 0.64 |
| Donation Status | |||||||||
| First-time donors | 28.2 (25.6–31.2) | 29.8 (27–32.8) | 28.7 (26.0–31.6) | 30.4 (27.6–33.5) | 29.1 (26.4–32.2) | 33.5 (30.1–37.4) | 41.1 (37.3–45.3) | 39.8 (36.1–43.9) | <0.01↑ |
| Repeat donors | 0.9 (0.6–1.1) | 0.8 (0.6–1.1) | 0.7 (0.5–0.9) | 0.7 (0.5–1.0) | 0.9 (0.7–1.2) | 1.1 (0.9–1.4) | 1.2 (1.0–1.5) | 1.2 (1.0–1.5) | <0.01↑ |
| Age group | |||||||||
| 16 to 17 | 5.6 (3.9–7.9) | 6.7 (4.8–9.3) | 7.1 (5.1–9.8) | 5.3 (3.6–8.0) | 5.7 (3.5–9.2) | 0.8 (0.1–4.5) | 4.0 (2.2–7.4) | 4.7 (2.8–7.9) | 0.07 |
| 18 to 24 | 6.8 (5.3–8.7) | 8.4 (6.6–10.6) | 5.1 (3.7–7.0) | 7.2 (5.4–9.5) | 4.8 (3.2–7.1) | 4.9 (3.3–7.5) | 5.8 (4.0–8.6) | 4.1 (2.6–6.3) | 0.03↓ |
| 25 to 54 | 9.6 (8.5–10.7) | 9.5 (8.5–10.7) | 9.6 (8.6–10.8) | 9.8 (8.7–11.0) | 8.8 (7.8–10) | 6.9 (6.0–7.8) | 9.2 (8.1–10.3) | 9.7 (8.6–10.9) | 0.34 |
| 55+ | 2.3 (1.8–3.0) | 2.6 (2.1–3.3) | 2.8 (2.2–3.5) | 3.2 (2.6–4.0) | 4.6 (3.9–5.5) | 3.9 (3.3–4.6) | 4.7 (4.1–5.5) | 4.5 (3.9–5.3) | <0.01↑ |
| Race | |||||||||
| Asian | 97.4 (83.5–113.5) | 90.9 (77.9–106) | 80.0 (68.1–94) | 96.4 (83.3–111.5) | 95.6 (81.7–111.9) | 74.2 (62.7–87.7) | 87 (75.1–100.8) | 71.1 (60.9–82.9) | 0.04↓ |
| White | 1.7 (1.4–2.1) | 1.8 (1.5–2.2) | 1.9 (1.6–2.3) | 2.0 (1.7–2.4) | 2.2 (1.8–2.6) | 1.8 (1.5–2.2) | 2.2 (1.8–2.6) | 2.5 (2.1–2.9) | <0.01↑ |
| Hispanic/Latino | 4.2 (2.9–6.1) | 4.3 (3.0–6.3) | 5.8 (4.1–8.1) | 5.3 (3.7–7.5) | 6.6 (4.6–9.4) | 7.5 (5.2–10.6) | 6.3 (4.4–9.1) | 5.5 (3.7–7.9) | 0.07 |
| Black | 35.0 (29.0–42.4) | 35.9 (29.7–43.3) | 35.4 (29.2–43) | 34.1 (27.9–41.8) | 43.3 (35.2–53.4) | 46 (37–57.2) | 49.4 (40.6–60.0) | 45.5 (37.5–55.1) | <0.01↑ |
| American Indian | 3.6 (0.6–20.7) | 10.6 (3.6–31.2) | 14.0 (5.4–35.9) | 7.3 (2.0–26.6) | 0.0 (0.0–15.9) | 4.3 (0.8–24.4) | 8.6 (2.4–31.4) | 0.0 (0.0–15.3) | 0.26 |
| Other/>1 race | 16.9 (10.8–26.4) | 31.7 (23.0–43.7) | 18.7 (12.3–28.3) | 18.4 (12.1–28.2) | 22.9 (15.3–34.4) | 12.7 (7.4–21.7) | 16.2 (10.1–26.0) | 14.9 (9.3–23.9) | 0.10 |
| Not reported | 16.9 (11.6–24.5) | 32 (19.7–52.0) | 26.7 (15.9–44.7) | 11.2 (5.2–24.5) | 27.0 (16.6–43.8) | 17.2 (10.6–27.9) | 18.1 (11.6–28.3) | 13.7 (8.4–22.2) | 0.30 |
| Census Region | |||||||||
| Midwest | 3.1 (2.4–4.0) | 3.2 (2.5–4.2) | 2.9 (2.2–3.8) | 3.5 (2.7–4.5) | 4.0 (3.2–5.1) | 2.9 (2.2–3.7) | 3.4 (2.7–4.3) | 3.8 (3–4.7) | 0.33 |
| Northeast | 5.6 (4.5–7.0) | 6.1 (5.0–7.6) | 5.0 (3.9–6.4) | 5.6 (4.5–7.1) | 6.6 (5.4–8.3) | 3.8 (2.9–4.9) | 4.5 (3.5–5.8) | 4.2 (3.2–5.4) | 0.05↓ |
| South | 8.7 (7.6–10.0) | 9.8 (8.6–11.2) | 10.0 (8.8–11.4) | 9.9 (8.7–11.3) | 9.1 (7.9–10.4) | 8.0 (6.9–9.3) | 10.8 (9.5–12.3) | 11.0 (9.6–12.5) | 0.29 |
| West | 7.2 (6.0–8.7) | 6.3 (5.2–7.7) | 6.2 (5.1–7.5) | 6.5 (5.4–8) | 5.9 (4.8–7.2) | 6.0 (5.0–7.3) | 6.9 (5.8–8.3) | 6.5 (5.4–7.8) | 0.75 |
p-values for trend analysis using negative binomial regression analysis for 8-year period; significance at p<0.05; arrows indicate the direction of the significant trend.
Figure 2:
Overall HIV, HBV, and HCV prevalence per 100 000 donations with 95% CIs at 1-year intervals, Oct 1 2015 - Sep 30 2023. P values show negative binomial regression significance estimates.
Table 4c:
TTIMS Years 1 to 8 prevalence per 100 000 donations and associated 95% confidence intervals (CIs) for HCV for demographic characteristics, Oct 1 2015 - Sep 30 2023.
| Year 1 (2015–2016) |
Year 2 (2016–2017) |
Year 3 (2017–2018) |
Year 4 (2018–2019) |
Year 5 (2019–2020) |
Year 6 (2020–2021) |
Year 7 (2021–2022) |
Year 8 (2022–2023) |
P value | |
|---|---|---|---|---|---|---|---|---|---|
| Rate 95% CI | Rate 95% CI | Rate 95% CI | Rate 95% CI | Rate 95% CI | Rate 95% CI | Rate 95% CI | Rate 95% CI | ||
| Total Donations | N= 6 993 134 | N= 6 927 969 | N= 6 843 510 | N= 6 700 915 | N= 6 614 399 | N= 7 575 290 | N= 7 169 129 | N= 7 217 515 | |
| Overall | 19.7 (18.7–20.8) | 20.2 (19.2–21.3) | 18.7 (17.7–19.8) | 17.3 (16.4–18.4) | 14 (13.1–14.9) | 9.1 (8.4–9.8) | 10.2 (9.5–11) | 9.6 (8.9–10.3) | <0.01 |
| Sex | |||||||||
| Female | 15.3 (14.0–16.7) | 14.6 (13.3–15.9) | 13.1 (11.9–14.4) | 12.9 (11.7–14.2) | 10.1 (9.1–11.3) | 5.6 (4.9–6.4) | 5.9 (5.2–6.8) | 5.7 (5.0–6.6) | <0.01 |
| Male | 23.5 (22.0–25.1) | 25.2 (23.6–26.8) | 23.8 (22.2–25.4) | 21.3 (19.8–22.9) | 17.8 (16.4–19.3) | 12.8 (11.7–14) | 14.5 (13.3–15.8) | 13.2 (12.1–14.4) | <0.01 |
| Donation Status | |||||||||
| First-time donors | 84.8 (80.1–89.8) | 87.3 (82.5–92.4) | 77.1 (72.6–81.9) | 75.6 (71.1–80.4) | 60.1 (56.1–64.4) | 59.7 (55–64.8) | 64.1 (59.3–69.4) | 57.5 (53–62.4) | <0.01 |
| Repeat donors | 3.6 (3.2–4.2) | 3.5 (3.1–4.1) | 4.0 (3.5–4.6) | 2.9 (2.4–3.3) | 2.4 (2.0–2.8) | 1.7 (1.4–2.0) | 1.8 (1.5–2.1) | 1.8 (1.5–2.2) | <0.01 |
| Age group | |||||||||
| 16 to 17 | 5.4 (3.8–7.6) | 4.5 (3.0–6.7) | 4.2 (2.8–6.5) | 1.4 (0.6–3.0) | 2.5 (1.2–5.1) | 3.2 (1.2–8.1) | 4.8 (2.8–8.4) | 2.4 (1.1–4.9) | 0.16 |
| 18 to 24 | 17.4 (14.9–20.4) | 15.3 (12.9–18.2) | 13.0 (10.7–15.9) | 13.3 (10.9–16.3) | 6.5 (4.7–9.1) | 3.1 (1.9–5.3) | 3.1 (1.9–5.3) | 2.9 (1.7–4.8) | <0.01 |
| 25 to 54 | 30.0 (28.1–32.0) | 31.4 (29.4–33.5) | 29.8 (27.9–31.9) | 27.9 (26–29.9) | 21.0 (19.4–22.7) | 13.2 (12.1–14.5) | 16.9 (15.5–18.5) | 16.5 (15.1–18) | <0.01 |
| 55+ | 11.5 (10.2–12.9) | 12.2 (10.9–13.6) | 10.6 (9.5–12.0) | 9.5 (8.4–10.8) | 9.1 (8.1–10.3) | 6.1 (5.3–6.9) | 5.8 (5.1–6.7) | 5.5 (4.7–6.3) | <0.01 |
| Race/Ethnicity | |||||||||
| Asian | 3.6 (1.6–7.8) | 6.2 (3.4–11.0) | 9.8 (6.2–15.5) | 8.5 (5.2–13.8) | 4.3 (2.1–8.9) | 2.7 (1.2–6.4) | 4.0 (2.0–7.8) | 2.6 (1.2–5.7) | 0.11 |
| White | 18.3 (17.2–19.5) | 19.1 (18.0–20.3) | 17.2 (16.2–18.3) | 16.4 (15.4–17.5) | 12.9 (12–13.8) | 8.4 (7.7–9.1) | 9.2 (8.5–10) | 8.8 (8.1–9.6) | <0.01 |
| Hispanic/Latino | 22.5 (19.2–26.4) | 22.8 (19.3–26.9) | 25.3 (21.5–29.8) | 23.9 (20.2–28.4) | 17.1 (13.7–21.4) | 11.5 (8.7–15.3) | 15.6 (12.3–19.7) | 13.7 (10.8–17.4) | <0.01 |
| Black | 30.1 (24.5–36.9) | 35.9 (29.7–43.3) | 25.4 (20.2–31.9) | 22.2 (17.3–28.5) | 28.1 (21.7–36.4) | 22.2 (16.2–30.3) | 24.7 (18.7–32.5) | 17.9 (13.2–24.3) | <0.01 |
| American Indian | 62.0 (38.7–99.3) | 53.1 (32.2–87.5) | 69.8 (45.2–107.8) | 58.3 (35.9–94.7) | 68.8 (42.4–111.8) | 47.3 (26.4–84.8) | 43.0 (23.4–79.1) | 37.4 (19.7–71) | 0.11 |
| Other/>1 race | 21.4 (14.4–31.8) | 16.3 (10.4–25.5) | 14.4 (9.0–23.1) | 11.4 (6.7–19.5) | 13 (7.6–22.2) | 5.9 (2.7–12.8) | 9.5 (5.2–17.5) | 10.5 (6–18.4) | <0.01 |
| Not reported | 44.3 (35.2–55.9) | 52.0 (35.5–76.2) | 85.7 (64.0–114.6) | 41.2 (27.2–62.4) | 52.2 (36.8–74.1) | 25.8 (17.3–38.4) | 21.0 (13.8–31.7) | 23.1 (15.9–33.6) | 0.01 |
| Census Region | |||||||||
| Midwest | 9.4 (8.1–10.9) | 9.3 (8.0–10.8) | 7.2 (6.1–8.5) | 7.2 (6–8.5) | 6.5 (5.4–7.9) | 3.6 (2.9–4.5) | 3.5 (2.8–4.5) | 3.8 (3.1–4.8) | <0.01 |
| Northeast | 10.3 (8.8–12.2) | 9.3 (7.8–11.1) | 8.2 (6.8–9.9) | 5.7 (4.5–7.2) | 5.8 (4.6–7.3) | 4.0 (3.1–5.1) | 2.7 (2–3.7) | 3.2 (2.4–4.3) | <0.01 |
| South | 39.5 (37.0–42.2) | 43 (40.4–45.8) | 41.6 (39.0–44.4) | 38.3 (35.8–41) | 29.0 (26.8–31.3) | 21.3 (19.5–23.3) | 25.2 (23.1–27.4) | 22.9 (21.0–25.1) | <0.01 |
| West | 11.7 (10.1–13.6) | 9.5 (8–11.2) | 9.3 (7.9–10.9) | 9.5 (8–11.1) | 8.2 (6.8–9.7) | 4.5 (3.6–5.7) | 5.8 (4.8–7.1) | 5.2 (4.3–6.4) | <0.01 |
p-values for trend analysis using negative binomial regression analysis for 8-year period; significance at p<0.05; arrows indicate the direction of the significant trend.
For HIV, concordant-positive prevalence declined significantly (p = .02) but not for NAT-yield positives (p = .27); however, the prevalence of low-level NAT-positive and seropositive donations increased (p <.01), both driven by increases in frequencies of positive donations during Years 6–8 (Table 1a).
No significant change occurred for the increase in HBV concordant positive prevalence from 5.93 phtd in year 1 to 6.07 phtd in year 8 (Table 1b; p = .77). HBV NAT-yield rate declined significantly (p = .02), while HBV surface antigen-yield positives (HBsAg-yield) remained stable (p = .07).
HCV demonstrated significant declines both for concordant and NAT-yield positives (both p <.01). The rate of the decrease flattened from 2020 to 2021 onwards, coinciding with significantly reduced availability of HCV anti-viral treatments during the COVID pandemic (Table 1c), which corresponds to a 50% reduction in the US for referrals for testing, sample testing, and the number of patients starting on treatment.10
3.2.4 |. Demographic trends and final adjusted model
Univariate negative binomial regression analysis demonstrated that HIV prevalence increased in donations from FT donors (p = .02), whereas it decreased in donations from RPT donors (p <.01) (Table 4a). An increase was observed among age group 55 and older (p = 0.03). The decrease in HIV overall prevalence was driven by significant decreases in the rates of RPT donors overall and RPT male donors (both p <.01).
HBV prevalence increased in both FT and RPT donors (both p <.01) driven by the last 3-year period. Additionally, increases occurred for those who identified as White, Black, or were 55 years and older (p <.01) (Table 4b). The increase in HBV prevalence in FT and RPT donors is likely the result of increases among the oldest FT donors, and to a lesser extent for 24–54-year-olds, who are anti-HBc reactive/DNA positive but HBsAg nonreactive (i.e., occult HBV infections [OBI], that are a subset of HBV concordant positives; Table S2). Although there was a significantly higher HBV prevalence in donations from FT donors in years 6–8 compared to years 1–5, overall prevalence did not increase due to the relatively low percentage of FT donors. In contrast, HBV prevalence in donations from donors aged 18–24 years (p = .03), those who identified as Asian (p = .04), and those residing in the Northeast (p = .05) declined.
HCV prevalence declined (p <.01) for nearly all demographic groups/geographic locations (Table 4c), except 16–17-year-olds and those identifying as Asian or American Indian, where declines were still observed without reaching statistical significance.
For all agents, donation status and sex were significant variables in the final adjusted negative binomial regression model. For HIV, the model estimated a 5.3% (95% CI: 2.4%–8.3%) annual prevalence increase among FT donations and a 9.7% (95% CI: 5.9%–13.3%) annual decrease in RPT donations (Figure S1a). There was no significant difference in slopes between males and females for both for FT and RPT donations. A 5.9% (95% CI: 4.4%–7.5%) yearly increase in HBV prevalence was identified for both for FT and RPT donations, with no significant difference in rates between males and females (Figure S1b). Finally, for HCV, the adjusted model estimated a decrease in rates for all combinations of donation status and sex. Estimated FT male and female donation prevalence decreased annually by 4.3% (95% CI: 2.6%–6.1%) and 9.3% (95% CI: 7.3%–11.3%), respectively. For RPT donations, the model estimated a 10.3% (95% CI: 7.7%–12.8%) decrease in the annual prevalence for males and a 14.9% (95% CI: 12.2%–17.6%) decrease for females (Figure S1c).
Parameter estimates for each agent’s final negative binomial regression model are provided in Tables S3 and S4.
4 |. DISCUSSION
The demand for safe blood transfusion continues to increase, driven by factors such as population growth and aging, increasing medical procedures, and the rising burden of trauma and chronic diseases.11,12 Therefore, ensuring the safety of the blood supply remains a critical task. Toward this goal, TTIMS remains an essential component in monitoring national trends in TTIDs, particularly as policies evolve along with changes in donor demographics or geographic outreach. This study extends TTIMS data on the prevalence of TTIDs among blood donations from 2015 to 2023, representing more than 56 million donations from nearly 60% of the US blood supply. During this period, there were significant changes in policy related to deferral for donors with a history of risk behaviors, particularly focused on changes from a 12-month through the end of 3-month deferrals. In addition, the data in the last 3-year period (corresponding to the 3M period) were influenced by the COVID-19 pandemic, which affected the demographic structure and behavior of the donor population.9 However, even with these changes, there was little overall variation in the prevalence of HIV and HBV, which were relatively stable with an overall prevalence of 2.3 phtd and 6.3 phtd (Figure 2). In contrast, there was a significant decline in HCV (14.7 phtd overall), potentially due to effective treatment protocols until the COVID-19 period, corresponding to the last 3 years of this study, and the consequent disruption of treatment availability.10 Even with these changes in policy and the impact of the COVID-19 pandemic, overall prevalence remained consistent with the prior TTIMS report of 2.5, 7.6, and 19.5 phtd for HIV, HBV, and HCV, respectively.1 A key aspect evaluated by TTIMS is whether FDA’s revised deferral policy from 12M to 3M had any impact on blood safety. The specific evaluation of pre-3M and 3M periods, as well as 8-year trends, found no significant difference related to policy change.
Similar to overall trends, the frequency of donations from recently infected donors, that is, those detected only by NAT, was very low, with overall rates of 0.04 phtd for HIV, 0.13 phtd for HBV, and 0.32 phtd for HCV. Trend analysis showed that HIV NAT-yield rates remained stable, while HBV and HCV NAT-yield rates declined significantly. These low rates are again consistent with prior TTIMS findings and confirm that recent infection is infrequent and thus infection risk is low.1 We also note that most infected donors were classified as concordant positives, meaning both the results of NAT and serology screening were reactive, and thus this double-screen-positive population poses the lowest infectivity risk (88%, 96%, and 98% of the total for HIV, HBV, and HCV). A significant increase (3–5-fold) in the frequency of low-level reactivity for HIV, with or without detectable RNA (i.e., those on antiretroviral medications or who naturally control their HIV infection), was observed, particularly in the last 3-year period; however, this increase was offset by a reduction in concordant positives during the same period, thus negating the impact on overall HIV rates. The increase in prevalence in the two HIV low-level groups may reflect changes in responses to the health history questionnaire or the result of changes in antiretroviral use during the COVID-19 pandemic, the latter of which had a significant effect on the demographic structure of the donor population.
The higher prevalence of HIV, HBV, and HCV among specific subgroups of blood donors including FT donors, males, non-White individuals, and individuals from the Southern US observed in this study is consistent with findings from several previous studies. FT blood donors have been shown to have a greater likelihood of being infected with blood-borne pathogens due to the lack of prior screening history and the potential for undiagnosed chronic infections, versus RPT donors who have been previously deemed healthy and have screened negative for TTIDs.13–15 The Southern US has long been associated with higher rates of TTIDs potentially due to a combination of economic and social factors, higher rates of risk behaviors, and barriers in access to health care.16–19 It is notable that the overall prevalence of HIV and HBV did not appear to be affected by infection risk deferral policies changing from 12 to 3 months, or by changes in the demographic structure of the donor population, presumably associated with the COVID-19 pandemic. As noted, the decline in HCV prevalence was potentially due to newly available highly effective anti-viral treatments. The availability of HCV treatments, as well as the expanding use of HIV pre-exposure prophylaxis (PrEP) during the study periods, are confounders that may alter the outcome of prevalence or incidence measures otherwise attributable to the investigated policy changes and therefore constitute a limitation of this study.
Detailed investigation of the changes in demographics did, however, identify trends in prevalence associated with the COVID-19 pandemic, which corresponded to the 3M period, including donation status, sex, and age. Corresponding with the COVID-19 period, the number of donations from RPT donors, females, and older donors (55+) increased significantly. Older donors are less likely to engage in high-risk behaviors such as injection drug use and sex work.20 As already mentioned, during the 3M period, significant increases in the rate of low-level HIV positives occurred, likely resulting from behavioral changes as a consequence of the pandemic. It is unclear whether the demographic changes in the donor profile that are often observed in natural emergencies will be maintained in the future or return to pre-pandemic levels.
The adjusted negative binomial regression model revealed important insights into the role of donation status and sex in influencing the prevalence of HIV, HBV, and HCV among blood donations. For HIV, while FT donors exhibited an estimated 5.3% annual increase in prevalence, RPT donors showed a significant 9.7% annual decrease. Similarly, HBV prevalence increased annually among both FT and RPT donors by 5.9%. Both for HIV and HBV, there were no notable sex-based differences in these trends. In contrast, HCV prevalence demonstrated a clear and consistent decline across all subgroups that was more pronounced among RPT female donors. These findings are reassuring, suggesting that while the policy changes may have affected individual subgroups differently, overall blood safety remains stable. These trends underscore the importance of ongoing monitoring to ensure that revised deferral policies continue to safeguard against transfusion-transmissible infections across all donor categories.
In summary, the 8-year prevalence of HIV, HBV, and HCV in the US blood supply, as monitored by TTIMS, remained either stable or decreased. The revised 3M deferral policy did not appear to have negatively impacted blood safety. It will be important to continue to monitor donor presentation profile dynamics following the pandemic and donation safety following individual donor assessment.
Supplementary Material
SUPPORTING INFORMATION
Additional supporting information can be found online in the Supporting Information section at the end of this article.
Table 1b.
TTIMS consensus-positive definitions, count of positive donations, and prevalence per 100 000 donations and associated 95% confidence intervals (CIs) for HBV by year and overall, Oct 1 2015 - Sep 30 2023.
| Year 1 (2015–2016) |
Year 2 (2016–2017) |
Year 3 (2017–2018) |
Year 4 (2018–2019) |
Year 5 (2019–2020) |
Year 6 (2020–2021) |
Year 7 (2021–2022) |
Year 8 (2022–2023) |
Overall (2015–2023) |
P value | |
|---|---|---|---|---|---|---|---|---|---|---|
| Total Donations (N) | 6 993 134 | 6 927 969 | 6 843 510 | 6 700 915 | 6 614 399 | 7 575 290 | 7 169 129 | 7 217 515 | 56 041 861 | |
| Consensus-positive definitions |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
n
Rate (95% CI) |
|
|
HBV concordant positive: 1. HBsAg RR with or without anti-HBc RR + dHBV R or 2. anti-HBcRR with or without HBsAg RR + dHBV R |
415 | 434 | 406 | 420 | 419 | 381 | 466 | 462 | 3403 | |
| 5.93 | 6.26 | 5.93 | 6.27 | 6.33 | 5.03 | 6.5 | 6.4 | 6.07 | 0.77 | |
| (5.39–6.53) | (5.70–6.88) | (5.38–6.54) | (5.70–6.9) | (5.76–6.97) | (4.55–5.56) | (5.94–7.12) | (5.84–7.01) | (5.87–6.28) | ||
|
HBV NAT-yield positive: HBsAg and HBc NR + dHBV R and dHBV R in an independent or follow-up sample |
13 | 13 | 7 | 8 | 10 | 9 | 5 | 6 | 71 | |
| 0.19 | 0.19 | 0.1 | 0.12 | 0.15 | 0.12 | 0.07 | 0.08 | 0.13 | 0.02↓ | |
| (0.11–0.32) | (0.11–0.32) | (0.05–0.21) | (0.06–0.24) | (0.08–0.28) | (0.06–0.23) | (0.03–0.16) | (0.04–0.18) | (0.1–0.16) | ||
|
HBsAg-yield positive: HBsAg RR + dHBV R, anti-HBc NR, HBsAg neutralization R or not done |
11 | 10 | 18 | 16 | 5 | 8 | 3 | 8 | 79 | |
| 0.16 | 0.14 | 0.26 | 0.24 | 0.08 | 0.11 | 0.04 | 0.11 | 0.14 | 0.07 | |
| (0.09–0.28) | (0.08–0.27) | (0.17–0.42) | (0.15–0.39) | (0.03–0.18) | (0.05–0.21) | (0.01–0.12) | (0.06–0.22) | (0.11–0.18) | ||
|
Total HBV consensus positive
: HBV concordant
positive + HBV-yield positive+HBsAg-yield positive |
439 | 457 | 431 | 444 | 434 | 398 | 474 | 476 | 3553 | |
| 6.28 | 6.6 | 6.3 | 6.63 | 6.56 | 5.25 | 6.61 | 6.6 | 6.34 | 0.75 | |
| (5.72–6.89) | (6.02–7.23) | (5.73–6.92) | (6.04–7.27) | (5.97–7.21) | (4.76–5.80) | (6.04–7.23) | (6.03–7.21) | (6.13–6.55) |
p-value for trend analysis using negative binomial regression, significance p ≤0.05; arrows indicate the direction of the significant trend.
ACKNOWLEDGMENTS
We are grateful for the funding support for the Transfusion Transmissible Infections Monitoring System (TTIMS) from the Food and Drug Administration (FDA), the National Heart, Lung and Blood Institute (NHLBI) of the National Institutes of Health (NIH), and the Office of the Assistant Secretary of Health, Health and Human Services (OASH-HHS) via Contract 75F40120C00101. We are also grateful for the study guidance provided by these agencies. We acknowledge those individuals who contributed to this study from the TTIMS-Donation and Donor Coordinating Center (DDCC), the TTIMS-Laboratory and Risk Factor Coordinating Center (LRCC), Creative Testing Solutions, and our Federal Partners, without whom this study and program would not be successful. Blood Center and Testing Organizations: The American Red Cross: E. Notari, S. Stramer, R. Dodd, E. Huseynova, R. Fayed, D. Nelson, R. Townsend, G. Foster, J. Haynes, E. Crawford, G. Conti, D. Krysztof, D. Burke, Rockville, MD. Creative Testing Solutions: M. Lanteri, V. Green, S. Cyrus, P. Williamson, Tempe, AZ. The New York Blood Center Enterprises: J. Gorlin, L. Milan-Benson, C. DelValle, P. Chien, and T. Brown, New York, NY. OneBlood: R. Reik, C. Shea, M. Lopez, K. Richards, T. Foster, St. Petersburg, FL. Quality Analytics, Inc.: J. Brodsky, M. Barr, T. Rains, Riverwoods, IL. Vitalant Research Institute: B. Custer, R. Bruhn, E. Grebe, M. Busch, M. Stone, C. Di Germanio, D. Hindes, Z. Kaidarova, K. Zurita, A. Tadena, L. Montalvo, A. Dayana, S. Hughes, San Francisco, CA. Vitalant: M. Townsend, M. Bravo, J. Vannoy, S. Fallon, and our other dedicated donor counselors, Scottsdale, AZ. Federal Partners: FDA: S. Anderson, B. Whitaker, H. Yang, A. Belov, A. Eder, Silver Spring, MD. OASH-HHS: J. Berger, Washington, DC. At the time that the study was conducted, the Transfusion Transmissible Infections Monitoring System 2 (TTIMS2) was the responsibility of the following individuals: Brian Custer, PhD, MPH: Vitalant Research Institute, San Francisco, CA. Susan Stramer, PhD, MS: American Red Cross, Rockville, MD. Jed Gorlin, MD, MBA: New York Blood Center Enterprises, New York, NY. Rita Reik, MD, and Tisha Foster, MD: OneBlood, St. Petersburg, FL. Phillip Williamson, PhD, through 2022, Marion C. Lanteri, PhD, afterwards: Creative Testing Solutions, Tempe, AZ. Steven A. Anderson, PhD, MPP: US Food and Drug Administration, Silver Spring, MD.
FUNDING INFORMATION
The content is solely the responsibility of the authors and does not represent the views or the policies of the Food and Drug Administration, the National Institutes of Health, or the Office of the Assistant Secretary for Health, Department of Health and Human Services. Contract 75F40120C00101.
Funding information
U.S. Food and Drug Administration
Abbreviations:
- 12M
12-month deferral period
- 3M
3-month deferral period
- Ab
antibody
- ARC
The American Red Cross
- BCO
Blood Collection Organization
- CI
confidence interval
- FDA
Food and Drug Administration
- FT
first-time
- HBsAg
hepatitis B surface antigen
- HBV
hepatitis B virus
- HCV
hepatitis C virus
- HIV
human immune deficiency virus
- IDA
individual donor assessment
- MP-NAT
minipool nucleic acid testing
- MSM
men having sex with men
- NHLBI
National Heart, Lung, and Blood Institute
- NYBCe
New York Blood Center Enterprises
- phtd
per hundred thousand donations
- RNA
ribonucleic acid
- RPT
repeat
- TTID
transfusion-transmissible infectious disease
- TTIMS
Transfusion Transmissible Infections Monitoring System
Footnotes
CONFLICT OF INTEREST STATEMENT
The authors have disclosed no conflicts of interest.
REFERENCES
- 1.Steele W, Notari EP, Dodd RY, Kessler D, Stramer SL. Changes in transfusion-transmissible infection prevalence and demographics among US blood donors from 2015–2019. Transfusion. 2020;60(5):1164–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.US Food and Drug Administration. Revised recommendations for reducing the risk of Human Immunodeficiency Virus transmission by blood and blood products: Guidance for industry. April 2, 2020. 85 Fed. Reg. 36595 (June 17, 2020). Available via Federal Register. [Google Scholar]
- 3.Custer BS. Transfusion-transmissible infection monitoring system: a tool to monitor changes in blood safety. Transfusion. 2016;56(6 Pt 2):1499–502. 10.1111/trf.13632 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.US Food and Drug Administration. Revised Recommendations for Reducing the Risk of Human Immunodeficiency Virus Transmission by Blood and Blood Products-Guidance for Industry. Silver Spring, MD: US Food and Drug Administration; 2015. [Google Scholar]
- 5.Revised Recommendations for Reducing the Risk of Human Immunodeficiency Virus Transmission by Blood and Blood Products—Guidance for Industry. US Food and Drug Administration Website. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/revised-recommendations-reducing-risk-human-immunodeficiency-virus-transmission-blood-and-blood Accessed Mar 17, 2024.
- 6.Recommendations for Evaluating Donor Eligibility Using Individual Risk-Based Questions to Reduce the Risk of Human Immunodeficiency Virus Transmission by Blood and Blood Products—Guidance for Industry. US Food and Drug Administration; Website. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/recommendations-evaluating-donor-eligibility-using-individual-risk-based-questions-reduce-risk-human Accessed Mar 17, 2025. Published May 2023. Last updated Jan 31, 2025 [Google Scholar]
- 7.Conti G, Notari EP, Dodd RY, Kessler D, Custer B, Reik R, et al. Syphilis seroprevalence and incidence in US blood donors from 2020 to 2022. Transfusion. 2024;64(2):325–33. 10.1111/trf.17707 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Centers for Disease Control and Prevention (CDC). Census Regions and Divisions of the United States. Accessed February 4, 2025 https://www2.census.gov/geo/pdfs/maps-data/maps/reference/us_regdiv.pdf
- 9.Conti G, Notari EP, Dodd RY, Kessler D, Custer B, Bruhn R, et al. Changes in transfusion-transmissible infection prevalence and demographics among US blood donors during the COVID-19 pandemic. Transfusion. 2024;63(6):1283–94. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Kondili LA, Buti M, Riveiro-Barciela M, Maticic M, Negro F, Berg T, et al. Impact of the COVID-19 pandemic on hepatitis B and C elimination: an EASL survey. JHEP Rep. 2022;4(9):100531. 10.1016/j.jhepr.2022.100531 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Greinacher A, Fendrich K, Hoffmann W. Demographic changes: the impact on safe blood supply. Transfus Med Hemother. 2010; 37(3):141–8. 10.1159/000313949 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Canadian Blood Services. Blood, Plasma, Stem Cells, Organs, and Tissues/About Us/Media/Newsroom. Accessed Feb 4, 2025 2024. https://www.blood.ca/en/about-us/media/newsroom/rapid-growth-demand-blood-products-could-cause-national-supply-dwindle#:~:text=The%20population%20is%20both%20growing,only%201%20in%2081%20did.
- 13.Khawar L, Cheng A, Styles C, Hoad V, McGregor S. Transfusion-transmissible infections in Australia: 2024 Surveillance Report. Sydney, Australia: Kirby Institute, UNSW Sydney, and Australian Red Cross Lifeblood; 2024. [Google Scholar]
- 14.Steele WR, Dodd RY, Notari EP, Haynes J, Anderson SA, Williams AE, et al. HIV, HCV, and HBV incidence and residual risk in US blood donors before and after implementation of the 12-month deferral policy for men who have sex with men. Transfusion. 2021;61(3):839–50. 10.1111/trf.16250 [DOI] [PubMed] [Google Scholar]
- 15.Niazkar HR, Dorgalaleh A, Rad F. First-time blood donors are double-edged swords for blood transfusion centers: a retrospective study in Southwest Iran. Turk J Haematol. 2020;37(1):30–5. 10.4274/tjh.galenos.2019.2019.0166 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Watson M, Johnson SD, Zhang T, Oster AM. Characteristics of and trends in HIV diagnoses in the deep south region of the United States, 2012–2017. AIDS Behav. 2019;23(Suppl 3):224–32. 10.1007/s10461-019-02659-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Rosenberg ES, Hall EW, Sullivan PS, Sanchez TH, Workowski KA, Ward JW, et al. Estimation of state-level prevalence of hepatitis C virus infection, US states and District of Columbia, 2010. Clin Infect Dis. 2017;64(11):1573–81. 10.1093/cid/cix202 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Rural Health Information Hub. Rural health disparities. Last Updated 11 Nov 2022 https://www.ruralhealthinfo.org/topics/rural-health-disparities. Accessed March 5 2025
- 19.Whitman A, De Lew N, Chappel A, Aysola V, Zuckerman R, and Sommers BD. Addressing social determinants of health: Examples of successful evidence-based strategies and current federal efforts. Assistant Secretary for Planning and Evaluation, U.S. Department of Health and Human Services. April 1, 2022 Accessed March 5, 2025. https://aspe.hhs.gov/sites/default/files/documents/e2b650cd64cf84aae8ff0fae7474af82/SDOH-Evidence-Review.pdf [Google Scholar]
- 20.Cai Y, Dai Z, Wen S, Bhandari R. Risk factors associated with infection of blood-borne virus among people who used methamphetamine. BMC Infect Dis. 2020;20(1):742. 10.1186/s12879-020-05464-y [DOI] [PMC free article] [PubMed] [Google Scholar]
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