Abstract
Background
Syphilis is increasing globally, with limited monitoring of risk factors in asymptomatic, low‐risk populations. Here, we investigate contemporary demographic and behavioral risk factors associated with active syphilis infection (ASI) in US blood donors.
Study Design and Methods
Beginning with donations in October 2020, four US blood centers implemented standardized risk factor interviews for ASI in blood donors as part of a larger case–control study. Logistic regression models were used to assess ASI associations with demographics and behaviors within 12 months before donation. A conceptual framework explored causal ASI pathways.
Results
Responses were obtained from 369 ASI cases and 868 controls; from all eligible cases, the enrollment rate was 16%. Risk factors in the multivariable‐adjusted model included age between 40 and 54 years old (compared to 55+), Black race (compared to White), lower income, single/never married and separated/divorced or widowed status (compared to married or living together), first‐time donation, gay/homosexual sexual orientation, having ≥2 male or ≥2 female sexual partners in the 12 months before donation, and a history of sexually transmitted infection. The conceptual risk framework suggests that important determinants of ASI include complex variables and mediators that may have not been fully captured by the questionnaire and regression analyses.
Discussion
Although not fully defining causal relationships with ASI, our findings establish a baseline for factors associated with ASI among US blood donors, which can be used to refine the donor history questionnaire following the implementation of individual risk assessment and further surveillance efforts.
Keywords: blood donation, blood safety, risk factors, sexual behavior, syphilis
1. INTRODUCTION
Syphilis is a bacterial infection with increasing incidence in many countries including the US, 1 , 2 , 3 despite the availability of effective antibiotics for many decades. 4 Although the causative agent, Treponema pallidum, is predominantly transmitted through sexual contact, it has been recognized as a transfusion‐transmitted infection (TTI) since the early 20th century, and testing of blood donations is routinely performed in most countries. 5 , 6
Because many cases are asymptomatic, monitoring syphilis may be challenging, particularly in low‐risk populations who do not undergo routine screening. Testing of blood donation samples offers a monitoring opportunity, particularly if the testing algorithm includes assays that can help identify active infections. In a recent analysis conducted between October/2020 and September/2022, the prevalence of active syphilis infections (ASI) in US blood donors increased 22% in the second year of the study compared to the first year, reflecting a national trend. 3 , 7
Risk factors for syphilis have been extensively investigated and include both direct determinants, such as sexual exposure, and distal determinants, including race, income, region of residency, and sexual orientation, which do not confer direct risk but may affect the likelihood of exposure. 8 , 9 Studies addressing demographic and behavioral risk factors for syphilis in low‐risk, asymptomatic populations have been mostly performed in antenatal care settings, 10 with limited availability of confirmatory assays indicating ASI, 11 and limited assessment of behavioral factors. 12 Moreover, changes in behavior patterns in the past years, including differences in sexual identity and the increasing adoption of HIV biomedical prevention, also highlight the need for a contemporary evaluation of demographic and behavioral risk factors for ASI in low‐risk populations. 13 , 14
The Transfusion‐Transmissible Infections Monitoring System (TTIMS) 15 designed and implemented a risk factors questionnaire (RFQ) to elicit detailed information on exposures and behaviors that could be associated with TTIs, in addition to a standardized testing algorithm allowing infection status confirmation including that of ASI. Here, we use TTIMS datasets to investigate contemporary demographic and behavioral risk factors associated with ASI in US blood donors. A conceptual framework analysis was also developed to explore determinants in the causal pathways of ASI, including mediators and complex variables that may not be entirely captured by surveys or other traditional research instruments.
2. METHODS
2.1. Design and setting
TTIMS is a coordinated monitoring effort established in September/2015, consisting of four large blood collection organizations (BCOs) and their testing laboratories, agencies within the US Department of Health and Human Services (HHS); the Food and Drug Administration (FDA), the National Heart, Lung, and Blood Institute (NHLBI), and the Office of the Assistant Secretary for Health (OASH). 15 One part of the monitoring program is risk exposure interviews of blood donors using a case–control design. Cases are defined as all donors having an HIV confirmed‐positive donation (nucleic acid testing [NAT]‐positive, antigen/antibody assay‐reactive; NAT confirmed‐positive, antigen/antibody assay‐nonreactive; or antigen/antibody assay confirmed‐reactive, NAT‐negative); hepatitis B virus (HBV) NAT confirmed‐positive donation with or without reactivity for HBV surface antigen (HBsAg) and nonreactive for HBV core antibodies; and/or hepatitis C virus (HCV) NAT confirmed‐positive donation. In October/2020, ASIs (defined as Treponema pallidum confirmed‐positive and rapid plasma reagin (RPR)‐positive) were added to the list of cases. Telephone interviews are conducted by trained BCO staff using a standardized RFQ.
2.2. Donor notification and recruitment
Following blood donation screening and supplemental testing, state laws require notification of all donors with confirmed‐positive results. Notification is performed by letter for all infections except HIV, where in‐person counseling is attempted. Letters are also sent to all donors with false‐positive tests, informing them of their results and future donation eligibility.
As part of TTIMS, each BCO provides a study‐specific information sheet to eligible donors via email, postal mail, or in person by trained research coordinators following routine notification, indicating that the donor may be contacted by telephone for participation in the study. A maximum of three contact attempts are made by telephone, mail, and/or e‐mail before these donors are considered lost to follow up (LTFU). An electronic study management system (SMS) is used to manage the recruitment and interview of potential participants.
2.3. Selection of participants
A donor was considered an ASI case if their donation tested positive for RPR (Arlington Scientific, Springville, UT) after screening reactive on the PK7300 automated agglutination system (PK‐TP System, Fujirebio, Inc., Tokyo, Japan) used through May/2022, after which the PK7400 and TP HA REAGENT (Newmarket Biomedical Ltd., Kentford, UK) were used for T. pallidum antibody detection. All PK‐screen‐reactives were tested by the CAPTIA™ Syphilis (T. pallidum)‐G EIA (Trinity Biotech, Jamestown, NY) for confirmation; all confirmed‐positive and indeterminate infections were then tested by RPR. While a reactive result on the PK‐screen or on the CAPTIA™ indicates either a past or an ASI, an RPR‐reactive result suggests an active or recently treated infection. 16
Following a completed case interview, a list of eligible controls (donors testing only false‐positive for HBsAg or only anti‐HIV false‐positive) from the same BCO who donated at approximately the same time was generated by the SMS. No additional matching criteria were used. Lists of potential controls were used until two control interviews were completed for each case.
We excluded cases and controls who donated blood after the implementation of individual donor assessment (IDA) since significant changes in the profile of blood donors likely occurred following this major eligibility policy change, and the number of completed interviews to date is insufficient for multivariable analysis.
2.4. Data collection instrument and procedures
The RFQ was developed in consultation with experts at the US Centers for Disease Control and Prevention (CDC) and NHLBI, National Institutes of Health (NIH), and includes questions on sexual orientation; behaviors associated with known and putative risk for human‐to‐human transmission of HIV, syphilis, HCV, and HBV, including sexual contact, parenteral exposure (blood transfusion, injection drug use, tattooing, body piercing), transplantation, perinatal exposure, close personal contact by cohabitation or fluids exposure 17 ; data on lifetime exposure to HIV pre‐exposure prophylaxis (PrEP) or post‐exposure prophylaxis (PEP); and information on other socioeconomic and risk indicators such as educational attainment, income, and former incarceration. We have refined the questionnaire content as routes and types of exposures have changed. For example, use of PrEP now includes content on oral, injected, and implant PrEP use (in preapproval clinical studies). Questionnaire data were captured electronically at the time of interviews directly into the SMS RFQ database. Demographic characteristics reported at the time of donation were also collected in the SMS, including age at donation, race, ethnicity, and region of residency (Midwest, Northeast, South, and West regions of the US). Prior donation history was used to categorize participants as first‐time (FT) or repeat donors.
2.5. Statistical analysis
Per study design, after each completed case interview, a list of six potential controls was used for recruitment until two control interviews were obtained; however, because multiple controls were simultaneously contacted, for some cases more than two controls agreed to be interviewed, resulting in a final control: case ratio that is higher than 2:1. We describe participants' demographic and behavioral characteristics using frequencies and percentages. Age and income were categorized for analysis. We used univariable and multivariable‐adjusted conditional logistic regression models to estimate the associations between independent variables and ASI. The multivariable model included key demographic factors (age; race; ethnicity; region of residency) and donor category (FT or repeat); other variables, including behavioral factors reported in the 12 months before donation, were included if significantly or marginally associated with ASI in univariate analyses (p ≤.1). To improve the precision of computational estimates, at least 25 total donors had to report each behavioral exposure of interest to be included in the multivariable model. For the final model, we retained key demographic variables, and other independent variables were selected using a backwards approach. Results are reported as adjusted odds ratios (aOR). Analyses were conducted using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA) and Stata version 17 (StataCorp College Station, TX: StataCorp LP), with a 0.05 significance level.
2.6. Conceptual causal framework
Not all identified associations have a direct causal relationship with ASI, with some independent variables only indirectly influencing the likelihood of exposure to true risk factors, and others representing potential spurious associations resulting from confounding or other biases. Moreover, instruments such as the RFQ may fail to collect information on complex exposures that influence ASI risk, such as social vulnerability; access to healthcare; sexual health knowledge/literacy; and perceived risk. Aiming to define the complex underlying mechanisms that may drive the observed relationships between multiple independent variables and ASI, we used an exploratory causal diagram to assess direct predictors, their precursors (ancestors), potential confounders, and mediators in a conceptual framework. Causal diagrams are useful tools for critical evaluation of results obtained in traditional epidemiologic studies, providing a qualitative framework of determinants and pathways behind the occurrence of an outcome of interest, including variables that may have been inadequately captured by available data collection instruments such as the RFQ. 18 The causal diagram has been developed using DAGitty v3.1 (https://www.dagitty.net/).
2.7. Ethical aspects
The study was reviewed and approved by the Institutional Review Boards at each participating BCOs and FDA, as well as the RFQ receiving US Office of Management and Budget clearance. Verbal consent was obtained from all participants and documented electronically by the interviewer before initiating the RFQ. All participants who completed the RFQ received a reimbursement payment.
3. RESULTS
3.1. Study participants
During the study period there were 2249 eligible ASI cases, from whom 130 females and 239 males were interviewed between July/2021 and October/2023, at a median of 6.4 (interquartile range [IQR] 4.7–9.2) months after the ASI donation. Overall, 171 ASI cases refused participation, 1705 were LTFU, and 4 were excluded due to donation after the implementation of IDA, resulting in a case enrollment rate of 16% (n = 369). Interviews of 868 control donors were completed between October/2017 and October/2023 at a median of 10.5 (IQR 8.1–18.0) months after donation (Figure 1). The final ratio of controls to ASI cases was 2.4:1.
FIGURE 1.
Selection of participants included in the study.
The proportions of donors with coinfections, males, and donors residing in the Southern US were significantly lower for enrolled ASI cases compared to those who refused participation or those LTFU. Participation was higher for White race compared to those LTFU. Supplementary Table 1 describes demographic characteristics of enrolled participants compared to those who refused or those LTFU.
3.2. Univariable models addressing factors associated with ASI
Table 1 shows the responses concerning sociodemographic characteristics for cases and controls, along with results of univariable models addressing sociodemographic factors associated with ASI. Male sex, younger age (<55 years old), non‐White race, Hispanic ethnicity, lower education level, lower household income, and FT donation were significantly associated with higher odds of being a case; being married/living together and unemployed status were associated with lower odds. Heterosexual orientation was associated with lower odds of being a case compared to both bisexual and homosexual orientation, and residency in the Western US was associated with higher odds compared to residency in the Northeastern US.
TABLE 1.
Sociodemographic characteristics of study participants and univariable models addressing factors associated with ASI.
| ASI cases N = 369 | Controls N = 868 | OR (95%CI) | p‐value | ||
|---|---|---|---|---|---|
| Sex at birth (%) | Male | 239 (65) | 421 (49) | 1.90 (1.48–2.46) | <.001 |
| Female | 130 (35) | 447 (52) | 1 | ‐ | |
| Age category (%) | 18–24 | 57 (15) | 91 (10) | 3.22 (2.10–4.94) | <.001 |
| 25–39 | 146 (40) | 207 (24) | 3.73 (2.65–5.26) | <.001 | |
| 40–54 | 93 (25) | 200 (23) | 2.58 (1.79–3.72) | <.001 | |
| 55 and older | 73 (20) | 370 (43) | 1 | ‐ | |
| Race (%) | White | 173 (47) | 717 (83) | 1 | ‐ |
| Black | 76 (21) | 14 (2) | 24.91 (12.76–48.60) | <.001 | |
| Asian/multiple/other | 120 (33) | 137 (16) | 3.97 (2.86–5.52) | <.001 | |
| Ethnicity (%) | Non‐Hispanic | 271 (74) | 781 (90) | 1 | ‐ |
| Hispanic | 96 (26) | 86 (10) | 3.10 (2.23–4.32) | <.001 | |
| Education (%) | High school or less | 168 (46) | 205 (24) | 2.71 (2.06–3.56) | <.001 |
| College or above | 201 (54) | 663 (76) | 1 | ‐ | |
| Annual household income (%) | <=30K | 122 (34) | 68 (8) | 6.16 (4.19–9.07) | <.001 |
| >30K | 232 (66) | 739 (92) | 1 | ‐ | |
| Employment status (%) | Employed | 293 (83) | 572 (76) | 1 | ‐ |
| Unemployed | 62 (17) | 183 (24) | 0.61 (0.43–0.86) | .005 | |
| Marital Status (%) | Single, never married | 217 (59) | 213 (25) | 7.01 (5.02–9.79) | <.001 |
| Married, living together | 82 (22) | 560 (65) | 1 | ‐ | |
| Separated/divorced/widowed | 69 (19) | 93 (11) | 5.02 (3.32–7.61) | <.001 | |
| Sexual orientation (%) | Heterosexual | 242 (66) | 829 (96) | 1 | ‐ |
| Bisexual | 56 (15) | 25 (3) | 7.07 (4.19–11.94) | <.001 | |
| Gay/lesbian/homosexual | 70 (19) | 13 (2) | 17.26 (9.13–32.64) | <.001 | |
| Donor status (%) | First | 245 (66) | 209 (24) | 6.53 (4.79–8.91) | <.001 |
| Repeat | 124 (34) | 659 (76) | 1 | ‐ | |
| Region of residency (%) | Midwest | 60 (16) | 225 (26) | 0.84 (0.54–1.33) | .462 |
| Northeast | 50 (14) | 143 (16) | 1 | ‐ | |
| South | 149 (40) | 300 (35) | 1.53 (0.99–2.37) | .057 | |
| West | 110 (30) | 200 (23) | 1.70 (1.10–2.62) | .017 | |
Table 2 shows the counts and percentages of responses concerning behavioral exposures in the 12 months before donation, along with results of univariable models addressing ASI associations. We found statistically significant associations with ≥2 male or female sex partners; condom use with female sexual partners reported as “always”; sexual contact with a partner who is an intravenous drug user; having sex while intentionally chemically impaired; a history of sexually transmitted infection (STI), exposure to illegal drugs, steroids, or vitamins; incarceration; exposure to body fluids; having a household member with HIV, HCV, and/or HBV infection; and having ever used PEP. Among cases, 36 donors (10%) reported ever using PrEP, in contrast with no donors in the control group.
TABLE 2.
Behavioral exposures in the 12 months prior to donation reported by cases and controls in the RFQ and univariable models addressing factors associated with ASI.
| Syphilis cases N = 369 | Controls N = 868 | OR (95% CI) | p‐value | ||
|---|---|---|---|---|---|
| Number of male sex partners (%) | 0 | 171 (47) | 531 (61) | 1 | ‐ |
| 1 | 95 (26) | 311 (36) | 0.93 (0.69–1.26) | .636 | |
| 2+ | 100 (27) | 24 (3) | 12.28 (7.41–20.35) | <.001 | |
| Condom use with male partners (%) | Always | 20 (10) | 28 (10) | 1 | ‐ |
| Never, sometimes | 171 (90) | 265 (90) | 0.81 (0.37–1.78) | .597 | |
| Number of female sex partners (%) | 0 | 211 (58) | 502 (58) | 1 | ‐ |
| 1 | 85 (23) | 337 (39) | 0.59 (0.43–0.79) | <.001 | |
| 2+ | 66 (18) | 29 (3) | 6.14 (3.69–10.23) | <.001 | |
| Condom use with female partners (%) | Always | 27 (18) | 25 (8) | 1 | ‐ |
| Never, sometimes | 123 (82) | 288 (92) | 0.43 (0.19–0.98) | .044 | |
| Sex with MSM (%) a | No | 120 (94) | 444 (100) | 1 | ‐ |
| Yes | 7 (6) | 1 (<1) | 6.59e+17 (0‐∞) | 1.000 | |
| Sex with PID (%) | No | 335 (95) | 862 (100) | 1 | ‐ |
| Yes | 16 (5) | 2 (<1) | 17.40 (3.95–76.75) | <.001 | |
| Sex while intentionally chemically impaired (%) | No | 288 (79) | 764 (88) | 1 | ‐ |
| Yes | 77 (21) | 102 (12) | 1.99 (1.43–2.77) | <.001 | |
| Sexually transmitted infection (%) | No | 314 (86) | 850 (98) | 1 | ‐ |
| Yes | 53 (14) | 18 (2) | 7.75 (4.33–13.86) | <.001 | |
| Illegal drugs, steroids, or vitamins (%) | No | 332 (90) | 852 (98) | 1 | ‐ |
| Yes | 36 (10) | 16 (2) | 5.41 (2.95–9.93) | <.001 | |
| Any non‐injecting illegal drug use (%) | No | 362 (99) | 867 (100) | 1 | ‐ |
| Yes | 5 (1) | 1 (<1) | 8.00 (0.89–71.57) | .063 | |
| Incarceration (%) | No | 312 (91) | 748 (99) | 1 | ‐ |
| Yes | 31 (9) | 6 (1) | 11.06 (4.21–29.06) | <.001 | |
| Tattoo not applied at tattoo/beauty parlor (%) | No | 204 (87) | 230 (94) | 1 | ‐ |
| Yes | 31 (13) | 16 (7) | 1.90 (0.83–4.33) | .130 | |
| Fluids exposure (%) a | No | 358 (97) | 856 (99) | 1 | ‐ |
| Yes | 11 (3) | 6 (1) | 3.81 (1.38–10.53) | .010 | |
| HIV/HCV/HBV‐infected member in household (%) | No | 342 (96) | 750 (99) | 1 | ‐ |
| Yes | 13 (4) | 5 (1) | 9.44 (2.65–33.64) | .001 | |
| PrEP use, ever (%) | No | 330 (90) | 867 (100) | ‐ | ‐ |
| Yes | 36 (10) | 0 (0) | ‐ | ‐ | |
| PEP use, ever (%) | No | 362 (98) | 867 ((100) | 1 | ‐ |
| Yes | 6 (2) | 1 (<1) | 11.08 (1.33–92.54) | .026 | |
Restricted to female donors CI, confidence interval; HBV, hepatitis B virus; HCV, hepatitis C virus; MSM, men who have sex with men; OR, odds ratio; PID, person who injects drugs; PrEP, HIV pre‐exposure prophylaxis; PEP, HIV post‐exposure prophylaxis. Fluids exposure has been ascertained with the following question: “In the 12 months before your last blood donation, did you get someone else's blood, body fluids, vomit, or feces splashed into your eyes, mouth, or in an open skin wound.”
3.3. Multivariable model addressing factors associated with ASI
The final multivariable model included sex at birth; age categories; race; ethnicity; region of residency; income; marital status; donor status; sexual orientation; number of male and female sexual partners; sex while intentionally chemically impaired; and STI (Figure 2). Factors significantly associated with higher odds of ASI were age between 40 and 54 years old (compared to ≥55 years old), Black race (compared to White), lower income, being separated, divorced, or widowed or being single (compared to married or living together), being gay or homosexual (compared to heterosexual), and FT donation (compared to repeat donation). Having ≥2 sexual partners was associated with higher odds of ASI for both female and male partners compared to no sexual partner; however, while having one male partner was associated with slightly higher odds of being a case compared to no male partners, having one female partner was not significantly associated with ASI compared to having no female partner. Finally, donors with a history of any STI had on average 15.5 times the odds of ASI compared to those without.
FIGURE 2.
Multivariable model addressing factors associated with ASI.
3.4. Conceptual framework of risk factors for ASI
Figure 3 shows the conceptual diagram depicting potential determinants of ASI, including independent variables explored in our study, as well as other complex nominal variables comprising ASI causal networks. In this diagram, it is notable that a few variables such as perceived risk, access to healthcare, and social network have not been measured by the current version of the RFQ. For most complex variables like these, instruments to quantify exposure with appropriate construct, content, and face validity are often unavailable, highlighting the limitations of informative causal analyses for these types of exposures.
FIGURE 3.
Conceptual causal framework for syphilis infection showing directional pathways for direct and distal factors related to the likelihood of infection.
4. DISCUSSION
In this case–control analysis of factors associated with ASI in US blood donors, we found that age between 40 and 54 years old (compared to 55 and older), Black race (compared to White), lower income, being separated, divorced, or widowed, or being single (compared to married or living together), FT donation, having ≥2 male or female sex partners, gay or homosexual orientation, and a history of STI were associated with increased odds of ASI. Our model estimates are presented alongside a conceptual framework using those risk factors and other variables that may influence ASI risk, emphasizing the complex relations of direct and indirect determinants, mediators, and confounders in a causal network.
While results generated in observational studies may be limited in generating causal inference, the associations detected are useful to identify subgroups that should be the focus for educational and prevention interventions. Furthermore, for BCOs and regulatory agencies, the ongoing identification of behaviors that correlate with TTIs is useful for updating and validating questions included in the donor history questionnaire (DHQ). The analysis combining a theoretical causal framework may guide the development of more advanced risk assessment instruments for future implementation.
Other authors have investigated factors associated with syphilis infection in recent studies. Using national case report data among 9883 pregnant women in the United States, Trivedi et al. found a 61% increase in syphilis cases between 2012 and 2016, with risk factors including a history of a STI (43%) and >1 sex partner in the past year (30%), although 49% of the participants in this study denied all 15 queried risk factors. 11 In a study comprising 1974 patients tested for syphilis at an emergency department, factors significantly associated with new syphilis diagnoses included unhoused status, HIV diagnosis, smoking, and substance use. 9 A recent study investigating the association between selected indicators and HIV/STI acquisition risk reported strong evidence linking a previous bacterial STI, chemsex, and increasing numbers of sexual partners to acquisition risk. 19 Our group investigated factors associated with syphilis reactivity among US blood donors between 2011 and 2012, and found that male sex, age between 20 and 29 years old, FT donation, and Black or Hispanic race/ethnicity were independently associated with ASI. 12 Among Brazilian blood donors, older age, Black/Mixed race (compared to White), lower education, FT donation, and replacement donation were significantly associated with ASI, while younger age, male sex, Black/Mixed race (relative to White), and lower education were independently associated with incident syphilis in repeat donors. 20 Risk factors for syphilis reactivity identified in other blood donor studies include multiple sexual partners, 21 , 22 reporting male–male sex in the past 12 months, 22 FT donation, 23 and lower educational attainment. 23
Risk factors can evolve over time due to changes in social context, behaviors, healthcare practices, and public health interventions. While regular surveillance and monitoring of syphilis trends are crucial for identifying emerging risk factors, asymptomatic persons in the general population are rarely tested for syphilis infection or systematically surveyed for relevant exposures and behaviors. Here, we found that PrEP use was reported by 10% of the case population, while a history of PEP use and reporting sex while intentionally chemically impaired were associated with higher odds of ASI in univariable analyses. These emerging exposures have been expanding in the past decade in the US as well as other countries. 24 , 25 , 26 , 27 , 28 Persons who meet criteria to receive PrEP are typically at high risk of syphilis infection before PrEP is initiated, and some studies suggest that PrEP use may be associated with a further increase in the risk of incident syphilis and other STIs not prevented by antiretrovirals. 29 , 30 Since 2023, the US FDA recommends deferral for those who have taken oral PrEP in the 3 months before donation, or those having had injectable PrEP in the 2 years before donation, due to potential false‐negative HIV screening test results. 31 Additionally, the intentional use of psychoactive substances to enhance sexual experiences, also known as chemsex, has been associated with increased risk of STIs. 32 , 33 , 34 In our study, donors were probed about having sex while intentionally chemically impaired, a somewhat broader concept than the usual chemsex definition. These exposures have not been previously described in association with syphilis in US blood donors. The potential inclusion of specific questions concerning the use of psychoactive substances to enhance sexual experiences should be explored for inclusion in the DHQ.
IDA, implemented in 2023, may have an impact on deferring additional ASI cases prior to donation as it involves a more individualized and comprehensive evaluation of recent exposures to TTI risk factors, such as new sex partners <3 months before donation. 31 The profile of selected blood donors will likely change due to IDA implementation, highlighting the need for future reassessments of factors associated with TTIs among blood donors.
In our analysis, region of residency was not significantly associated with ASI after adjustment for covariates. These findings contrast with those previously reported, restricted to one BCO and including donations collected between 2011 and 2012; in this analysis, donors living in the South had 2.6 times the odds of being seropositive for T. pallidum compared to those living in the Northern region. 12 While our model included multiple demographics and behavior factors, the model in the study published by Kane et al. included a different set of demographic variables, in addition to HIV and HCV test results, and did not include risk factor elicitation by interview. Similarly, a recent TTIMS publication found significantly higher rates of ASI in donors from the South compared to donors from other regions. 7 Since region of residency is a distal determinant of ASI, it is expected that adjustment using different sets of covariates will result in different OR estimates. In addition, our LTFU and refusals for case interviews were significantly higher among donors from the South; thus, we may not have a complete picture of ASI infections in US blood donors from this analysis.
Our study has other limitations. We enrolled 16% of all eligible cases, and the comparison of enrolled, refused, and LTFU showed significant sociodemographic differences beyond region of residency. The percentage of donors with coinfections was lower among enrolled cases, suggesting that donors with higher risk behaviors were not included. Although the RFQ responses were obtained under assurance of anonymity/confidentiality, it is possible that some exposures, particularly those concerning sensitive information, were underreported. Because the outcome status was known, underreporting of exposures was potentially differential for cases and controls, for example, sensitive information may have been disclosed less often by controls. This differential misclassification of exposures could lead to overestimation of OR estimates. Our definition of ASI, comprising donors testing positive for RPR after screening reactive on the treponemal test, may have misclassified donors with resolved infections and residual RPR reactivity after treatment. Our selection strategy may also have failed to select donors with very recent syphilis acquisition, with antibody responses still nonreactive. The RFQ was applied at a median of 6.4 months after donation for cases, and 10.5 months after donation for controls; this differential delay could have introduced recall bias. The conceptual causal framework defined additional limitations of this analysis. While variations of this framework could be proposed based on subject‐matter expertise or other exposure‐outcome relationships observed in specific populations, this diagram is a useful conceptual demonstration of how models using available predictors and a mathematical criterion for variable selection may be limited in providing accurate estimates of the association between independent and dependent variables in epidemiologic studies, including this one. Despite these limitations, our study presents data from a large case–control sample of blood donors representing all major US regions, with standardized laboratory ascertainment of ASI and detailed risk factors assessment, including newly investigated exposures.
Our findings establish a baseline for future comparisons of exposures associated with ASI among US blood donors, and potentially to compare with surveillance efforts from the general population from which blood donors are a subset. Our findings may also be used as a reference to refine the DHQ, to implement education/prevention interventions targeting more vulnerable subgroups, and to improve communication between blood collection organizations and donors by informing not only the factors that may predict active syphilis infection, but also the relationship between distal and direct determinants of infection. Future analyses should explore the geographic influences on ASI as well as potential motivators for donation.
FUNDING INFORMATION
The Transfusion Transmissible Infections Monitoring System (TTIMS) received funding support from the US Health and Human Services (HHS), 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 (OASH) via Contract 75F40121C00196. We are also grateful for the study guidance provided by these agencies.
CONFLICT OF INTEREST STATEMENT
The authors have disclosed no conflicts of interest.
Supporting information
Supplementary Table 1: Demographic characteristics of enrolled participants compared to those who refused and those LFTU.
ACKNOWLEDGMENTS
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, G. Conti, R. Fayed, D. Nelson, R. Townsend, G. Foster, J. Haynes, E. Crawford, E. Huseynova, 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: D. Kessler, 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, V.I. Avelino‐Silva, 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. NHLBI NIH: B. Hailu, Bethesda, MD; OASH‐HHS: J. Berger, Washington, DC. 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 Minneapolis, MN; Rita Reik, MD, and Tisha Foster, MD: OneBlood St. Petersburg, FL; Marion C. Lanteri, PhD: Creative Testing Solutions Tempe, AZ; Steven A. Anderson, PhD, MPP: US Food and Drug Administration, Silver Spring MD; Benyam Hailu, MD, MPH: National Institutes of Health Bethesda, MD.
Avelino‐Silva VI, Bruhn RL, Kaidarova Z, Hindes D, Notari E, Burke D, et al. Factors associated with active syphilis infection in US blood donors. Transfusion. 2025;65(8):1460–1471. 10.1111/trf.18313
Vivian I. Avelino‐Silva and Roberta L. Bruhn are the Co‐first authors.
The content of this manuscript is solely the responsibility of the authors and does not represent the views or the policies of the National Institutes of Health, the Food and Drug Administration, or the Office of the Assistant Secretary for Health, Department of Health and Human Services.
Contributor Information
Brian Custer, Email: bcuster@vitalant.org.
for the Transfusion‐Transmissible Infections Monitoring System (TTIMS):
Brian Custer, Susan Stramer, Jed Gorlin, Rita Reik, Tisha Foster, Marion C. Lanteri, Steven A. Anderson, and Benyam Hailu
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary Table 1: Demographic characteristics of enrolled participants compared to those who refused and those LFTU.