Syphilis-related mortality in the United States, 2021–2025: U.S trends, demographic disparities, and implications for urological practice

Syphilis-related mortality in the United States, 2021–2025: U.S trends, demographic disparities, and implications for urological practice | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Syphilis-related mortality in the United States, 2021–2025: U.S trends, demographic disparities, and implications for urological practice Kanza Atif, Eshal Atif, Vishan Das, Asad Ullah Farooq, Sadia Qazi, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9520864/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Syphilis-related mortality in the United States remains incompletely characterized during the post-pandemic period. This study aimed to quantify U.S trends, demographic disparities, and geographic distribution of syphilis-related mortality from 2021 to 2025 using multiple causes of death data, with attention to urological and clinical implications. Methods: A retrospective cross-sectional analysis was conducted using the CDC WONDER Multiple Cause-of-Death database. Decedents with ICD-10 codes A50–A53 listed as contributing causes were included. Age-adjusted mortality rates (AAMRs) were calculated per 100,000 population using the 2000 US Standard Population. Poisson regression was used to estimate annual percent change (APC) for temporal trends and rate ratios (RRs) for demographic comparisons. Eight pre-specified sensitivity analyses were performed, including restriction to the underlying cause of death only and assessment of HIV and COVID-19 co-occurrence. Results: A total of 1,148 syphilis-related deaths were identified, yielding an overall AAMR of 0.06 per 100,000 (95% CI: 0.06–0.07). No significant temporal trend was identified (APC: −1.24%, p = 0.550). Late-stage syphilis accounted for 51.4% of the deaths. Men had 2.5-fold higher mortality than women (RR: 2.50; 95% CI: 2.20–2.83). Non-Hispanic Black individuals had nearly five-fold higher mortality than non-Hispanic White individuals (RR: 4.81; 95% CI: 4.20–5.50). The South accounted for 50.3% of the deaths. HIV was co-listed in 27.5% of deaths, with a borderline increasing trend (APC: +8.25%; p = 0.047). More than half of the deaths occurred outside the inpatient hospital settings. Conclusions: Syphilis-related mortality remained stable but was concentrated in identifiable high-risk groups and geographies. The predominance of late-stage disease, high HIV co-occurrence, and substantial proportion of deaths in community and long-term care settings collectively indicate persistent failures in early detection and treatment retention. These findings have direct implications for urological practice, public health screening programs, and targeted interventions in underserved populations. syphilis mortality multiple cause of death age-adjusted mortality rate health disparities sexually transmitted infections Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Syphilis has re-emerged as a major public health concern in the United States, with a steadily increasing incidence over the past two decades. National surveillance data indicate that reported cases have increased annually since 2000, reaching the highest levels in more than 70 years, with primary and secondary syphilis rates rising across all demographic groups [ 1 ]. The resurgence has been most pronounced among men who have sex with men (MSM), Black or African American populations, and individuals with limited access to healthcare, reflecting the persistent structural and social determinants of disease transmission [ 2 – 4 ]. Despite well-documented increases in incidence, contemporary patterns of syphilis-related mortality remain poorly defined. Clinically, syphilis-related mortality is largely driven by late-stage diseases, including neurosyphilis, cardiovascular involvement, and systemic complications that may involve the genitourinary tract. These manifestations intersect with urological and sexual medicine practices, where clinicians may encounter patients with unexplained lower urinary tract or neurological symptoms attributable to tertiary infections [ 3 ]. In addition, the HIV-syphilis syndemic contributes to accelerated disease progression and adverse outcomes, reinforcing the importance of integrated clinical management [ 5 ]. Therefore, understanding mortality patterns is critical for both clinical prioritization and public health responses. Prior studies on syphilis mortality have important limitations. Many have relied on underlying cause of death (UCOD) definitions, which underestimate the true burden by excluding deaths in which syphilis is a contributing condition. Multiple cause of death (MCOD) approaches provide a more comprehensive assessment, particularly given that syphilis frequently functions as a contributing rather than the primary cause of death. Furthermore, contemporary analyses incorporating post-2020 data are limited, despite the known disruptions in STI services during the COVID-19 pandemic [ 6 ]. This study aimed to characterize syphilis-related mortality in the United States from 2021 to 2025 using MCOD data stratified by sex, age, race/ethnicity, geography, and place of death, and to estimate temporal trends using Poisson regression. The secondary aim was to assess the robustness of the findings across alternative case definitions. The results were interpreted in the context of urological and sexual medicine practices. 2. Materials and Methods 2.1. Study Design and Data Source This retrospective cross-sectional study analyzed national mortality data from the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) Multiple Cause of Death (MCOD) database [ 7 ]. Data were extracted for 2021–2024 using final mortality files and supplemented by 2025 provisional data [ 8 ], yielding a five-year study window. The MCOD file records all conditions listed on the U.S. standard death certificate, including the underlying cause of death (UCOD) and up to 20 contributing causes, enabling the identification of deaths in which syphilis contributed to, but was not designated as, the primary cause [ 7 ]. This study was exempt from institutional review board approval because it used de-identified, publicly available aggregate data. 2.2. Case Identification Decedents were included if any of the following ICD-10 codes appeared as either the underlying or contributing cause of death: A50 (congenital syphilis), A51 (early syphilis), A52 (late syphilis, including neurosyphilis and cardiovascular syphilis), or A53 (other and unspecified syphilis), constituting the any-mention MCOD case definition. This approach is consistent with prior U.S. syphilis mortality surveillance analyses using CDC WONDER MCOD data and ICD-10 codes A50–A53 as underlying or contributing causes of death [ 9 ]. Cases were classified by diagnostic stage to characterize the clinical profile of mortality. HIV co-occurrence was identified by the additional presence of ICD-10 codes B20-B24 or R75 on the same death certificate. COVID-19 co-occurrence was identified using ICD-10 code U07.1. Cells with fewer than 10 deaths were suppressed according to CDC WONDER data-use restrictions [ 10 ]. 2.3. Outcome Measures The primary outcome was syphilis-related mortality, defined by any-mention MCOD criteria. Age-adjusted mortality rates (AAMRs) were calculated per 100,000 population using the 2000 United States Standard Population, enabling valid comparisons across subgroups and time periods with different age structures [ 11 ]. Crude mortality rates were reported alongside AAMRs for descriptive context. 2.4. Statistical Analysis Two separate Poisson regression models were used in this study. To estimate demographic disparities, a cross-sectional Poisson model was fitted with pooled death counts (2021–2025) as the outcome, ln(population) as an offset, and demographic group as the predictor, yielding rate ratios (RRs) with 95% confidence intervals (CIs). NH White individuals served as the reference for race/ethnicity comparisons, and females served as the reference for sex comparisons. To estimate temporal trends, a separate longitudinal Poisson model was fitted for each stratum with the annual death count as the outcome, ln(annual population) as the offset, and calendar year (centered on the stratum mean to reduce collinearity) as a continuous predictor. The annual percent change (APC) was derived as (e^β − 1) × 100, where β is the year coefficient, and 95% CIs were computed on the log scale and back-transformed. A five-year observation window precludes reliable joinpoint segmentation because NCI/NCHS guidance recommends caution when estimating joinpoints in short time series with limited data around candidate segments and endpoints [ 12 ]. Poisson regression is the appropriate alternative for short time series with count outcomes. Overdispersion was assessed using the Pearson chi-squared statistic divided by residual degrees of freedom; strata with dispersion > 2 (age 0–24 years and congenital syphilis) are flagged in the results. Statistical significance was set at p < 0.05 (two-tailed). All analyses were conducted in Python (version 3.13) using the statsmodels library (version 0.14.6) [ 13 ]. 2.5. Stratification Mortality was stratified by sex (male, female), age group (0–24, 25–44, 45–64, and ≥ 65 years), race, and ethnicity using the CDC WONDER Non-Hispanic Single Race 6 classification (NH White, NH Black or African American, NH American Indian or Alaska Native [AI/AN], and NH Asian) and Hispanic or Latino ethnicity from a separate query; these classifications are not mutually exclusive. Mortality was also stratified by census region (Northeast, Midwest, South, and West), state of residence, and place of death. Age-stratified analyses reported crude rates; age adjustment within age strata was methodologically inappropriate and was not performed. 2.6. Sensitivity Analyses Eight sensitivity analyses were performed. (1) Restriction to UCOD only, quantifying the proportion of deaths in which syphilis was the primary cause rather than a contributing condition. (2) Restriction to A53.0 and A53.9 only, assessing the contribution of diagnostically unspecified coding. (3–5) Restriction to individual ICD-10 stage categories: congenital syphilis (A50), early syphilis (A51), and late-stage syphilis (A52). (6) Co-occurrence of COVID-19 (U07.1) and syphilis, evaluating pandemic-related diagnostic displacement. (7) Co-occurrence of HIV (B20–B24) and syphilis, quantifying the HIV–syphilis co-mortality burden. (8) Restriction to 2021–2024 final data only, excluding the provisional 2025 records. The full results are presented in Supplementary Table 7. 3. Results 3.1. Overall Mortality Between 2021 and 2025, 1,148 syphilis-related deaths were identified using the MCOD criteria, yielding an overall AAMR of 0.06 per 100,000 population (95% CI: 0.06–0.07). The annual death counts ranged from 209 in 2023 to 243 in 2022. Poisson regression identified no statistically significant temporal trend over the study period (APC: −1.24%; 95% CI: −5.20% to 2.88%; p = 0.550). Late syphilis (A52) was the most common stage, accounting for 51.4% of deaths (n = 590), followed by unspecified syphilis (A53.0/A53.9, n = 453, 39.5%), congenital syphilis (A50, n = 95, 8.3%), and early syphilis (A51, n = 12, 1.0%). The annual counts and AAMRs are presented in Supplementary Table 1 and Fig. 1 . The distribution of clinical stages is shown in Table 1 . Table 1 Syphilis-related mortality by clinical stage, United States, 2021–2025 Clinical stage Deaths (n) % of total Early syphilis (A51) 12 1.0% Congenital syphilis (A50) 95 8.3% Late syphilis (A52) 590 51.4% Unspecified syphilis (A53.0/A53.9) 453 39.5% Total 1,148 100% Notes: ICD-10 codes: A50 = congenital syphilis; A51 = early syphilis; A52 = late syphilis (including neurosyphilis and cardiovascular syphilis); A53 = other and unspecified syphilis. Deaths were identified using the any-mention multiple causes of death criteria. 3.2. Sex Males accounted for 71.0% of deaths (n = 815; AAMR 0.10 per 100,000, 95% CI: 0.09–0.11) compared with females (n = 333; AAMR 0.03, 95% CI: 0.03–0.03). Poisson regression confirmed a significantly higher mortality risk in males (RR: 2.50; 95% CI: 2.20–2.83; p < 0.001). Temporal trends were stable in both sexes: male APC − 0.36% (95% CI: −5.08% to 4.60%; p = 0.886); female APC − 3.32% (95% CI: −10.39% to 4.31%; p = 0.384). Annual data by sex are presented in Supplementary Table 1 and are summarized in Table 2 and Fig. 2 . Table 2 Syphilis-related mortality by sex, United States, 2021–2025 Sex Deaths (n) % of total AAMR (95% CI) RR (95% CI) APC (95% CI) p-value (APC) Female 333 29.0% 0.03 (0.03–0.03) 1.00 (referent) — — Male 815 71.0% 0.10 (0.09–0.11) 2.50 (2.20–2.83)* −0.36% (− 5.08% to 4.60%) 0.886 Total 1,148 100% 0.06 (0.06–0.07) — — — Note: AAMR = age-adjusted mortality rate per 100,000 population (2000 U.S. standard population). RR, rate ratio; Poisson regression; female, referent. APC = annual percent change; Poisson regression. * p < 0.001 for RR. Annual data are presented in Supplementary Table 1. 3.3. Age Mortality was concentrated among older adults. Those aged ≥ 65 years accounted for 45.5% of deaths (n = 522; AAMR 0.16 per 100,000, 95% CI: 0.14–0.18), and those aged 45–64 years accounted for 31.3% (n = 359; AAMR 0.10, 95% CI: 0.09–0.11). A secondary concentration was observed in the 0–24 age group (n = 90, 7.8%; AAMR 0.02, 95% CI: 0.01–0.02), largely due to congenital syphilis. No statistically significant temporal trends were identified in any age group (all p > 0.05). The 0–24 age group showed overdispersion (Pearson dispersion 4.21), consistent with high year-to-year variability in small counts; this APC estimate should be interpreted cautiously. The annual data are presented in Supplementary Table 2 and summarized in Table 3 and Fig. 3 . Table 3 Syphilis-related mortality by age group, United States, 2021–2025 Age group (years) Deaths (n) % of total AAMR† (95% CI) APC (95% CI) p-value 0–24 90 7.8% 0.02 (0.01–0.02) −2.88% (− 16.08% to 12.39%)‡ 0.695 25–44 177 15.4% 0.05 (0.05–0.06) + 3.09% (− 7.12% to 14.41%) 0.568 45–64 359 31.3% 0.10 (0.09–0.11) −2.31% (− 9.19% to 5.10%) 0.531 ≥ 65 522 45.5% 0.16 (0.14–0.18) −2.72% (− 8.46% to 3.39%) 0.375 Total 1,148 100% 0.06 (0.06–0.07) — — Notes: † AAMR = age-adjusted mortality rate per 100,000 (2000 U.S. standard population). Age-stratified rates are crude rates, and age adjustment within strata is methodologically inappropriate. APC = annual percent change; Poisson regression. ‡ Pearson dispersion = 4.21 in the 0–24 group; APC estimate is unstable and should be interpreted with caution. The annual data are presented in Supplementary Table 2. 3.4. Race and Ethnicity NH AI/AN individuals had the highest AAMR at 0.30 per 100,000 (95% CI: 0.21–0.42; RR: 7.00; 95% CI: 4.98–9.84; p < 0.001 vs. NH White), although annual counts were suppressed in four of five study years, and this estimate should be interpreted with caution. NH Black or African American individuals accounted for the largest share of deaths (n = 430; AAMR 0.20, 95% CI: 0.18–0.22; RR: 4.81; 95% CI: 4.20–5.50; p < 0.001). Hispanic or Latino individuals (n = 227; AAMR 0.09, 95% CI: 0.08–0.10) had an RR of 1.70 (95% CI: 1.44–2.00; p < 0.001). NH Asian individuals (n = 42; AAMR 0.03, 95% CI: 0.02–0.04) did not differ significantly from the NH White reference (RR: 0.92; 95% CI: 0.67–1.27; p = 0.614). Temporal trends were stable across all groups, with sufficient non-suppressed annual data. Annual data are presented in Supplementary Table 3 and summarized in Tables 4 and 5 and Fig. 4 . Table 4 Syphilis-related mortality by race/ethnicity, United States, 2021–2025 Race/ethnicity Deaths (n) AAMR (95% CI) RR (95% CI) p-value NH White (referent) 413 0.03 (0.02–0.03) 1.00 (referent) — NH AI/AN† 36 0.30 (0.21–0.42) 7.00 (4.98–9.84) < 0.001 NH Black or African American 430 0.20 (0.18–0.22) 4.81 (4.20–5.50) < 0.001 Hispanic or Latino‡ 227 0.09 (0.08–0.10) 1.70 (1.44–2.00) < 0.001 NH Asian 42 0.03 (0.02–0.04) 0.92 (0.67–1.27) 0.614 Total 1,148 0.06 (0.06–0.07) — — Note: AAMR = age-adjusted mortality rate per 100,000 (2000 U.S. standard population). RR: rate ratio; Poisson regression; NH White: referent. NH = non-Hispanic. † NH AI/AN AAMR and RR should be interpreted with caution: annual counts suppressed in four of five years; estimate based on 36 total deaths. ‡ Hispanic estimates derived from a separate CDC WONDER ethnicity query; not mutually exclusive of the NH race groups. The annual data are presented in Supplementary Table 3. Table 5 Annual percent change in syphilis-related mortality by race/ethnicity, United States, 2021–2025 Race/ethnicity APC (95% CI) p-value NH White −2.57% (− 8.99% to 4.31%) 0.455 NH Black or African American −1.30% (− 7.68% to 5.53%) 0.702 Hispanic or Latino + 3.50% (− 5.62% to 13.51%) 0.465 Note: APC = annual percent change, Poisson regression. NH AI/AN and NH Asian excluded: annual counts suppressed in ≥ 4 of 5 years, precluding reliable trend estimation. All APCs non-significant (p > 0.05). Annual data in Supplementary Table 3. 3.5. Geography The South (Census Region 3) accounted for 50.3% of all deaths (n = 578; AAMR 0.08 per 100,000, 95% CI: 0.07–0.09; RR vs. national: 1.29, 95% CI: 1.17–1.43; p < 0.001). The West contributed 25.5% (n = 293; AAMR 0.07, 95% CI: 0.06–0.08; RR: 1.10, 95% CI: 0.97–1.25; p = 0.151, not significant). The Midwest showed a statistically significant declining trend over the study period (APC: −12.46%; 95% CI: −22.26% to − 1.42%; p = 0.028) and had the lowest mortality burden relative to the national average (RR: 0.59, 95% CI: 0.49–0.70; p < 0.001). The Northeast also had below-national mortality (RR 0.70 [95% CI 0.59–0.84]; p < 0.001). The regional data are summarized in Table 6 and presented annually in Supplementary Table 5. At the state level, Mississippi (AAMR 0.18, RR: 2.64, 95% CI: 1.80–3.87), Oklahoma (AAMR 0.18, RR: 2.55, 95% CI: 1.82–3.59), Louisiana (AAMR 0.14, RR: 2.33, 95% CI: 1.68–3.23), South Carolina (AAMR 0.13, RR: 2.22, 95% CI: 1.63–3.03), and Maryland (AAMR 0.13, RR: 2.08, 95% CI: 1.54–2.81) had the highest mortality rates relative to the national rate (all p < 0.001). California (n = 164, RR = 1.24, p = 0.010) and Florida (n = 106, RR = 1.36, p = 0.003) had significantly elevated rates. Texas (n = 118, RR: 1.12, 95% CI: 0.93–1.36; p = 0.231) did not show statistical significance. Full state-level data are presented in Supplementary Table 4, selected Poisson comparisons are presented in Table 7 , and regional trends are shown in Fig. 5 . Table 6 Syphilis-related mortality by U.S. Census region, 2021–2025 Census region Deaths (n) % of total AAMR (95% CI) RR vs. national (95% CI) p-value APC (95% CI) APC p-value South 578 50.3% 0.08 (0.07–0.09) 1.29 (1.17–1.43) < 0.001 + 0.39% (− 5.24% to 6.35%) 0.895 West 293 25.5% 0.07 (0.06–0.08) 1.10 (0.97–1.25) 0.151 −2.96% (− 10.51% to 5.22%) 0.466 Midwest 139 12.1% 0.02 (0.02–0.03) 0.59 (0.49–0.70) < 0.001 −12.46% (− 22.26% to − 1.42%)* 0.028 Northeast 138 12.0% 0.03 (0.02–0.04) 0.70 (0.59–0.84) < 0.001 + 7.18% (− 4.77% to 20.64%) 0.250 National 1,148 100% 0.06 (0.06–0.07) 1.00 (referent) — −1.24% (− 5.20% to 2.88%) 0.550 Note: AAMR = age-adjusted mortality rate per 100,000 (2000 U.S. standard population). RR, rate ratio; Poisson regression, national rate = referent. APC = annual percent change; Poisson regression. * Statistically significant declining trend (p = 0.028). The annual data are presented in Supplementary Table 5. Table 7 State-level Poisson regression results for syphilis-related mortality, United States, 2021–2025 (selected states) State Deaths (n) AAMR (95% CI) RR vs. national (95% CI) p-value Mississippi 27 0.18 (0.12–0.27) 2.64 (1.80–3.87)† < 0.001 Oklahoma 34 0.18 (0.13–0.25) 2.55 (1.82–3.59) < 0.001 Louisiana 37 0.14 (0.10–0.20) 2.33 (1.68–3.23) < 0.001 South Carolina 41 0.13 (0.10–0.19) 2.22 (1.63–3.03) < 0.001 Maryland 44 0.13 (0.09–0.18) 2.08 (1.54–2.81) < 0.001 Florida 106 0.05 (0.04–0.07) 1.36 (1.11–1.66) 0.003 California 164 0.08 (0.07–0.10) 1.24 (1.05–1.46) 0.010 Texas 118 0.09 (0.07–0.10) 1.12 (0.93–1.36) 0.231 (ns) National 1,148 0.06 (0.06–0.07) 1.00 (referent) — Note: Table shows the states with statistically significantly elevated RRs and the two highest-volume states. AAMR = age-adjusted mortality rate per 100,000 (2000 U.S. standard population). RR, rate ratio; Poisson regression, national rate = referent. † Mississippi, n = 27; interpreted with caution. Texas RR was not statistically significant (p = 0.231). ns = not significant. DC and 18 other states had suppressed data; full data are presented in Supplementary Table 4. 3.6. Place of Death Among the 1,148 decedents, 46.1% (n = 529) died in inpatient medical facilities, 21.9% (n = 251) at home, 14.6% (n = 168) in nursing homes or long-term care facilities, and 7.7% (n = 88) in a hospice facility. Combined, 53.9% of deaths occurred outside inpatient hospital settings, suggesting that a substantial proportion of syphilis-related deaths may occur without active hospital-level care. Population denominators and rates were not available for place-of-death stratification in the CDC WONDER. The full distribution is presented in Table 8 and Supplementary Table 6. Table 8 Syphilis-related mortality by place of death, United States, 2021–2025 Place of death Deaths (n) % of total deaths Medical facility – inpatient 529 46.1% Decedent's home 251 21.9% Nursing home / long-term care 168 14.6% Hospice facility 88 7.7% Medical facility – outpatient or ER 58 5.1% Other 54 4.7% Medical facility – dead on arrival / unknown 0 0.0% Total 1,148 100% Notes: Population denominators and age-adjusted rates were not available for place-of-death stratification in the CDC WONDER. The data represent the cumulative 2021–2025 totals. 3.7. Sensitivity Analyses When restricted to UCOD only, 245 deaths were identified (21.3% of the MCOD total), confirming that syphilis functions predominantly as a contributing rather than primary cause on U.S. death certificates, with a 4.7-fold difference between case definitions. The UCOD-only APC was not significant (+ 1.41%; 95% CI: −7.18% to 10.80%; p = 0.756), consistent with the primary analysis. Late syphilis (A52, n = 590) showed a statistically significant declining trend over the study period (APC: −7.55%; 95% CI: −12.70% to − 2.11%; p = 0.007), In contrast, deaths coded to unspecified syphilis (A53.0/A53.9, n = 453) increased significantly (APC: +9.05%; 95% CI: +2.14% to + 16.43%; p = 0.009). These opposing trends suggest a shift in death certificate coding practices toward less specific syphilis classifications over time, rather than a true change in disease burden. HIV (B20–B24) was co-listed in 316 deaths (27.5%), with a borderline significant increasing trend in HIV–syphilis co-mortality (APC: +8.25%; 95% CI: +0.10% to + 17.08%; p = 0.047). COVID-19 (U07.1) was co-listed in 44 deaths (3.8%), concentrated in 2021 (n = 19) and 2022 (n = 15), and subsequent years were suppressed. Congenital syphilis (A50, n = 95) showed no significant trend (APC: −5.24%; p = 0.459), although overdispersion (Pearson dispersion = 5.88) limited confidence in this estimate. Early syphilis (A51) contributed only 12 deaths over five years, with most annual cells suppressed, and no trend model was estimable. Restriction to 2021–2024 final data only (n = 919; AAMR 0.05, 95% CI: 0.05–0.06; APC: −1.78%, 95% CI: −7.30% to 4.06%; p = 0.541) was fully consistent with the primary five-year analysis, confirming that the inclusion of provisional 2025 data did not materially alter the findings. The full sensitivity analysis data are presented in Supplementary Table 7 and Fig. 6 . 4. Discussion 4.1. Overall mortality and preventable burden In this national analysis of syphilis-related mortality from 2021 to 2025, mortality remained stable over the study period, with no statistically significant temporal trends. This stability occurs in the context of a steadily rising syphilis incidence in the United States, suggesting a complex relationship between infection trends and mortality outcomes [ 2 , 4 ]. The 2023 CDC STI surveillance report documented over 209,000 syphilis cases nationally, with primary and secondary syphilis declining for the first time since 2001, while late and unknown-duration syphilis increased by 12.2%, a divergence that likely reflects the same diagnostic and treatment access pressures captured in the mortality data presented here [ 14 ]. Potential explanations for mortality stability include improved access to treatment for incident infections, prolonged latency between infection and fatal complications, and persistence of a fixed pool of individuals with longstanding untreated infections. Stable mortality should not be interpreted as reassuring: 1,148 deaths over five years from a treatable bacterial infection represent a substantial and largely preventable burden. That preventability is not unconditional, the 2023 shortage of benzathine penicillin G, the only recommended treatment for several syphilis stages, constrained treatment access across the latter portion of the study window and may have delayed care for non-pregnant adults during peak shortage periods [ 15 ]. 4.2. Late-stage disease and coding specificity The predominance of late syphilis (51.4%) confirms that fatal syphilis in the United States is primarily a consequence of chronically untreated or undiagnosed infections rather than acute disease. The observed decline in late-stage syphilis mortality, alongside a concurrent increase in unspecified syphilis coding, likely reflects a shift in death certificate coding practices rather than a true epidemiological reduction in late-stage disease. Similar patterns of declining diagnostic specificity have been described in other infectious disease mortality analyses using ICD-10 data [ 16 ]. The 2024 CDC laboratory recommendations for syphilis testing explicitly revised the diagnostic algorithms to address the mismatch between serologic detection patterns and clinical staging, providing a plausible institutional mechanism for the ICD-10 coding drift observed in this study [ 17 ]. This coding drift has important implications for surveillance, as analyses restricted to specific ICD-10 categories may underestimate the true burden of advanced diseases. The any-mention MCOD methodology provides a more robust assessment of syphilis-related mortality and should be the preferred approach for future analyses. 4.3. Sex disparities and urological relevance The marked male predominance observed in this study is consistent with national incidence patterns, where syphilis disproportionately affects males, particularly MSM [ 2 , 4 ]. From a urological perspective, late syphilis encompasses several conditions that are directly relevant to clinical practice. Neurogenic lower urinary tract dysfunction is a recognized complication of neurosyphilis, with urodynamic studies in contemporary cases demonstrating low-capacity bladders with detrusor overactivity, urge incontinence, and urinary retention [ 18 , 19 ]. The spectrum of lower urinary tract dysfunction associated with infectious and inflammatory neurological conditions, including neurosyphilis, was systematically characterized in a recent multinational neuro-urology study. [ 20 ]. Tabes dorsalis, the dorsal column demyelinating form of late neurosyphilis, remains clinically active in the modern antibiotic era and continues to present with bladder dysfunction as a prominent feature, including in HIV-negative patients [ 21 , 22 ]. Beyond the lower urinary tract, late syphilis encompasses gummatous involvement of the genitourinary tract and cardiovascular complications, such as syphilitic aortitis [ 18 ]. The broader clinical and translational context of the syphilis resurgence, including emerging treatment strategies relevant to late-stage disease, has been reviewed by Xiong et al. [ 23 ]. Despite increasing awareness of the resurgence of syphilis, the absence of a significant decline in male mortality suggests persistent gaps in early detection and management. Primary, secondary, and early latent syphilis remain treatable with a single intramuscular dose of benzathine penicillin G, and the deaths recorded here likely represent infections that were diagnosed late, lost to follow-up, or never identified [ 24 ]. For MSM, the demographic carrying the greatest incidence burden, the 2024 CDC guidelines on doxycycline post-exposure prophylaxis represent a now-available prevention tool: three large randomized controlled trials demonstrated that 200 mg doxycycline taken within 72 hours of sex reduces syphilis acquisition by more than 70% in this population [ 25 ]. Clinicians, including urologists, should maintain a high index of suspicion for syphilis in patients presenting with unexplained genitourinary or neurological symptoms, and eligible MSM patients should be informed of doxyPEP as part of a comprehensive sexual health strategy. 4.4. Racial and ethnic disparities Substantial racial and ethnic disparities were evident, with NH Black individuals experiencing a nearly five-fold higher mortality risk and NH American Indian or Alaska Native individuals demonstrating the highest rates overall. These disparities reflect well-documented structural inequities in the STI burden, including differences in healthcare access, socioeconomic conditions, and continuity of care [ 2 , 26 ]. The magnitude of these disparities suggests that excess mortality is not solely attributable to a higher incidence but also to downstream failures in treatment and retention in care. Hispanic populations also demonstrated an elevated mortality risk, highlighting the need for targeted public health investment in demographically vulnerable communities. 4.5. Geographic variation Geographic variation further highlighted the disproportionate burden of syphilis mortality in the Southern United States, which accounted for over half of all deaths and exhibited significantly higher mortality rates than the national average mortality rate. This pattern aligns with longstanding regional disparities in the STI burden, healthcare infrastructure, and socioeconomic determinants of health [ 14 , 27 ]. The observed decline in mortality in the Midwest represents a novel finding, although it should be interpreted cautiously, given the smaller case counts and potential statistical instability. State-level variation, with Mississippi, Oklahoma, Louisiana, South Carolina, and Maryland each exceeding double the national mortality risk, provides actionable geographic targets for interventions. 4.6. Place of death and missed clinical opportunities The finding that more than half of the syphilis-related deaths occurred outside inpatient hospital settings is particularly notable. Deaths at home or in long-term care facilities likely represent advanced disease in patients with limited engagement in healthcare systems and raise concerns about missed opportunities for diagnosis and treatment in community and institutional settings. The 2022 US Preventive Services Task Force reaffirmation recommends syphilis screening in all persons at increased risk (Grade A recommendation), and current CDC STI screening guidance specifically identifies high-risk populations for targeted serological testing [ 28 , 29 ]. However, the concentration of deaths in nursing homes and long-term care facilities suggests that these recommendations are not being systematically applied to older institutionalized adults. Routine syphilis serology in older patients with unexplained neurological or cardiovascular decline in long-term care settings is warranted. 4.7. HIV co-occurrence and pandemic context The high prevalence of HIV co-occurrence (27.5%) and its borderline significant increasing trend (APC + 8.25%, p = 0.047) reinforce the importance of the HIV-syphilis syndemic in shaping mortality. HIV infection accelerates syphilis progression, elevates the viral load, and reduces CD4 counts in co-infected individuals, increasing the risk of severe and late-stage manifestations [ 5 , 30 ]. The observed increase in co-mortality likely reflects multiple converging factors: an aging cohort of people living with HIV who acquired the infection before effective antiretroviral therapy was available and are now entering the age groups with the highest syphilis mortality; rising syphilis incidence among HIV-positive MSM; and potential underutilization of doxyPEP in HIV-positive individuals, for whom the 2024 CDC guidelines are explicitly applicable [ 25 , 31 ]. These findings support the use of integrated screening and co-management strategies that simultaneously address both infections. The COVID-19 pandemic likely influenced syphilis-related mortality patterns during the early stages of the study period. Disruptions in STI screening, reduced access to clinical services, and reallocation of public health resources during 2020–2022 have been well documented [ 6 , 32 ], and delayed diagnosis during this period may have expanded the pool of individuals at risk for late-stage complications [ 33 ]. The low COVID-19 co-listing rate (3.8%, concentrated in 2021–2022) and the stability of the primary trend estimate when restricted to the 2021–2024 final data suggest that the pandemic period did not materially confound the overall findings, although its longer-term effects on the late-stage disease pipeline warrant continued surveillance. 4.8. Sensitivity analyses and methodological robustness Restricting syphilis deaths to the underlying cause of death only identified 245 cases (21.3% of the any-mention MCOD total), confirming that syphilis functions predominantly as a contributing rather than a primary condition on U.S. death certificates, with a 4.7-fold difference between case definitions. This pattern is consistent with MCOD analyses of other chronic infectious conditions and reinforces why any-mention methodology is the appropriate standard for surveillance of diseases that contribute to, rather than directly cause, death [ 34 ]. The UCOD-only APC was non-significant (+ 1.41%; 95% CI: −7.18% to 10.80%; p = 0.756), fully concordant with the primary analyses. The opposing trends in late syphilis (A52: APC − 7.55%, p = 0.007) and unspecified syphilis (A53.0/A53.9: APC + 9.05%, p = 0.009) are the most methodologically important sensitivity findings. These trends move in opposite directions with nearly identical magnitudes, far more consistent with a coding drift toward less specific classifications than with a genuine divergence in stage-specific disease burden. The 2024 CDC laboratory recommendations' revision of syphilis diagnostic algorithms may accelerate this drift by altering how clinicians document the syphilis stage at the time of death certification [ 17 ]. Surveillance systems relying solely on A52 to track late syphilis mortality will increasingly underestimate the true burden. The any-mention, broad-code MCOD definition is more resistant to misclassification and should be preferred in future analyses. COVID-19 co-listing was low (3.8%, n = 44) and concentrated in 2021–2022, consistent with declining COVID-19 mortality rather than pandemic-related diagnostic displacement. Restricting the analysis to 2021–2024 final data yielded an APC of − 1.78% (95% CI: −7.30% to 4.06%; p = 0.541) and an AAMR of 0.05 per 100,000 (95% CI: 0.05–0.06), fully consistent with the five-year primary estimate and confirming that the provisional 2025 data did not introduce meaningful instability. 4.9. Limitations This study has several limitations. First, syphilis mortality captured on death certificates depends on the accuracy and completeness of clinical coding [ 7 ]. Syphilis may be under-documented as a contributing cause in older decedents, where late-stage complications overlap with cardiovascular disease and dementia, leading to potential underestimation of the true burden. Second, the cross-sectional surveillance design precludes causal inference; rate ratios describe population-level associations and cannot be attributed to individual causal pathways. Third, the five-year observation window limits the statistical power of trend analyses. Poisson regression CIs are wide in strata with small annual counts, and APC estimates for the 0–24 age group (Pearson dispersion 4.21) and congenital syphilis (Pearson dispersion 5.88) are unstable and should be treated as descriptive. Fourth, CDC WONDER suppression rules resulted in missing data for 19 states and the District of Columbia [ 10 ]. The NH AI/AN rate ratio of 7.00 rests on 36 total deaths, with four of five annual cells suppressed and should be read as a directional signal; this caution is reinforced by the known racial misclassification of AI/AN individuals on death certificates [ 35 ]. Fifth, race and Hispanic ethnicity data were extracted from separate CDC WONDER queries and were not mutually exclusive. Finally, the place-of-death data lack population denominators, precluding rate estimation for that stratum. 4.10. Conclusions Between 2021 and 2025, syphilis-related mortality in the United States remained stable but concentrated in identifiable groups: older adults, males, NH Black and AI/AN individuals, and residents of the South, with more than half of all deaths occurring outside inpatient hospital settings. Late syphilis accounted for 51.4% of deaths, HIV was co-listed in 27.5%, and opposing ICD-10 coding trends between A52 and A53 reflected the progressive loss of diagnostic specificity on death certificates rather than a genuine reduction in late-stage burden. These patterns reflect failures of early detection and treatment retention rather than therapeutic failures. For urologists and sexual medicine practitioners, the 71% male predominance, neurogenic bladder, genitourinary manifestations of late neurosyphilis, and HIV co-occurrence signal justify routine syphilis serology in sexually active male patients particularly those living with HIV and prompt co-management with infectious disease services when late-stage disease is identified. The concentration of deaths in nursing homes and long-term care facilities supports systematic screening in older patients with unexplained neurological or cardiovascular decline. Geographically, the South accounted for 50.3% of deaths at 1.3 times the national rate, and the Midwest's statistically significant declining trend warrants investigation as a regional model. Syphilis mortality in the U.S. is not intractable; at-risk populations and geographies are identifiable, and prevention and treatment tools exist to address them. Abbreviations The following abbreviations are used in this manuscript: Age-adjusted mortality rate (AAMR); annual percent change (APC); average annual percent change (AAPC); Centers for Disease Control and Prevention (CDC); confidence interval (CI); coronavirus disease 2019 (COVID-19); doxycycline post-exposure prophylaxis (doxyPEP); human immunodeficiency virus (HIV); International Classification of Diseases, 10th Revision (ICD-10); institutional review board (IRB); lower urinary tract dysfunction (LUTD); lower urinary tract symptoms (LUTS); men who have sex with men (MSM); multiple cause of death (MCOD); non-Hispanic (NH); non-Hispanic American Indian or Alaska Native (NH AI/AN); non-Hispanic Black or African American (NH Black); Neurourology and Pelvic Floor Committee (NUPC); rate ratio (RR); sexually transmitted infection (STI); underlying cause of death (UCOD); US Preventive Services Task Force (USPSTF); Wide-ranging Online Data for Epidemiologic Research (WONDER). Declarations Ethics approval and consent to participate This study used de-identified, publicly available aggregate mortality data obtained from the CDC WONDER Multiple Cause of Death database which is publicly available, de-identified data and exempted from institutional review board review. No individual patient data were accessed, and no patient consent was required. Consent for publication Not applicable. Availability of data and materials All data analyzed in this study are publicly available through the CDC WONDER Multiple Cause of Death database at https://wonder.cdc.gov/mcd.html and found in supplementary file. Competing interests The authors declare that they have no competing interests. Funding The authors received no specific funding for this work. The APC was covered by Alfaisal University Authors' contributions KA contributed to conceptualization, literature review, data interpretation, and writing of the original draft. EA contributed to data curation, formal analysis, and writing of the original draft. VD contributed to methodology, statistical analysis, and writing — review and editing. AUF contributed to data curation, visualization, and writing — review and editing. SQ contributed to conceptualization, supervision, methodology, project administration, and writing — review and editing. MAM contributed to supervision, critical appraisal of intellectual content, and writing — review and editing. All authors read and approved the final manuscript. Acknowledgements: None References County-level syphilis data: STI statistics. Centers for Disease Control and Prevention. March 3, 2025. Accessed June 29, 2025. https://www.cdc.gov/sti-statistics/county-level-syphilis-data/index.html Schmidt R, Carson PJ, Jansen RJ. Resurgence of syphilis in the United States: an assessment of contributing factors. Infect Dis (Auckl). 2019;12:1178633719883282. doi:10.1177/1178633719883282. PMID: 31666795; PMCID: PMC6798162. French P. Syphilis. BMJ. 2007;334(7585):143-147. doi:10.1136/bmj.39085.518148.BE. PMID: 17235095; PMCID: PMC1779891. Do D, Rodriguez PJ, Gratzl S, Cartwright BMG, Baker C, Stucky NL. Trends in incidence of syphilis among US adults from January 2017 to October 2024. Am J Prev Med. 2025 Apr 2:S0749-3797(25)00106-0. doi:10.1016/j.amepre.2025.03.008. Epub ahead of print. PMID: 40185421. Zetola NM, Klausner JD. Syphilis and HIV infection: an update. Clin Infect Dis. 2007;44(9):1222-1228. doi:10.1086/513427. PMID: 17407043. Rogers B, Tao J, Murphy M, Chan PA. The COVID-19 pandemic and sexually transmitted infections: where do we go from here? Sex Transm Dis. 2021;48(7):e94-e96. doi:10.1097/OLQ.0000000000001445. PMID: 33872225; PMCID: PMC8570344. Multiple Cause of Death Data on CDC WONDER. Centers for Disease Control and Prevention. Accessed April 24, 2026. https://wonder.cdc.gov/mcd.html Provisional Mortality by Multiple Cause of Death. Centers for Disease Control and Prevention. Accessed April 24, 2026. https://wonder.cdc.gov/wonder/help/mcd-provisional.html Barragan NC, Wickramasekaran RN, Sorvillo F, Smith LV, Kuo T. Current trends in syphilis mortality in the United States, 2015–2020. Venereology. 2023;2(2):59-64. doi:10.3390/venereology2020005. Data Use Restrictions. Centers for Disease Control and Prevention. Accessed April 24, 2026. https://wonder.cdc.gov/datause.html Klein RJ, Schoenborn CA. Age adjustment using the 2000 projected U.S. population. Healthy People Statistical Notes, no. 20. Hyattsville, MD: National Center for Health Statistics; 2001. Irimata KE, Bastian BA, Clarke TC, Curtin SC, Rui P. Guidance for selecting model options in the National Cancer Institute Joinpoint Regression Software. Vital Health Stat 2. 2022;(194):1-24. doi:10.15620/cdc:118050. Seabold S, Perktold J. Statsmodels: econometric and statistical modeling with Python. Proceedings of the 9th Python in Science Conference. 2010:92-96. doi:10.25080/Majora-92bf1922-011. Centers for Disease Control and Prevention. Sexually transmitted infections surveillance, 2023. Atlanta: U.S. Department of Health and Human Services; 2024. Available from: https://www.cdc.gov/sti-statistics/annual/index.html Faghihi I, King HL, Kwon Y. Benzathine penicillin G shortage and effects on syphilis patient outcomes. Open Forum Infect Dis. 2026 Jan 11;13(Suppl 1):ofaf695.935. doi:10.1093/ofid/ofaf695.935. PMCID: PMC12793167. Liu B, Hadzi-Tosev M, Liu Y, Lucier KJ, Garg A, Li S, Heddle NM, Rochwerg B, Ning S. Accuracy of International Classification of Diseases, 10th Revision codes for identifying sepsis: a systematic review and meta-analysis. Crit Care Explor. 2022;4(11):e0788. doi:10.1097/CCE.0000000000000788. PMID: 36382338; PMCID: PMC9649267. Papp JR, Park IU, Fakile Y, Pereira L, Pillay A, Bolan GA. CDC laboratory recommendations for syphilis testing, United States, 2024. MMWR Recomm Rep. 2024 Feb 8;73(1):1-32. doi:10.15585/mmwr.rr7301a1. PMID: 38319847; PMCID: PMC10849099. Erturk E, Sheinfeld J, Davis RS. Voiding dysfunction in tertiary syphilis. Urology. 1987;30(3):284-286. doi:10.1016/0090-4295(87)90259-7. PMID: 3629778. Playfair M, Welk B. Neurosyphilis — an uncommon cause of neurogenic lower urinary tract dysfunction. Continence Rep. 2023;6:100024. doi:10.1016/j.contre.2023.100024. Konstantinidis C, Sakakibara R, Vrijens D, Werneburg GT, Welk B, Kotes S, Drake MJ, Rapidi CA, Gomes CM, Abranches-Monteiro L, Onem K, de Wachter S, Sinha M. Lower urinary tract dysfunction in uncommon neurological diseases — part IV: infections, inflammatory, toxic, and structural disorders — a NUPC report. Continence. 2025. doi:10.1016/j.cont.2025.102274. Epub ahead of print. Bloch N, Brugger F, Notter J. Tabes dorsalis: a rare presentation of neurosyphilis in Western Europe. BMJ Case Rep. 2025 Feb 3;18(2):e262492. doi:10.1136/bcr-2024-262492. PMID: 39900398; PMCID: PMC11795238. Zhu Z, Gong H, Liu M, Zhang H, Yang L, Zhang X, Li J. Diagnosing tabes dorsalis in HIV-negative patients: clinical features, neuroimaging, and laboratory insights in the modern antibiotic era. Infect Drug Resist. 2024;17:2567-2577. doi:10.2147/IDR.S464581. Xiong S, Liu Z, Zhang X, Huang S, Ding X, Zhou J, Yao J, Li W, Liu S, Zhao F. Resurgence of syphilis: focusing on emerging clinical strategies and preclinical models. J Transl Med. 2023 Dec 18;21(1):917. doi:10.1186/s12967-023-04685-4. PMID: 38105236; PMCID: PMC10726518. Workowski KA, Bachmann LH, Chan PA, Johnston CM, Muzny CA, Park I, et al. Sexually transmitted infections treatment guidelines, 2021. MMWR Recomm Rep. 2021;70(4):1-187. doi:10.15585/mmwr.rr7004a1. Bachmann LH, Barbee LA, Chan P, Reno H, Workowski KA, Hoover K, Mermin J, Mena L. CDC clinical guidelines on the use of doxycycline postexposure prophylaxis for bacterial sexually transmitted infection prevention, United States, 2024. MMWR Recomm Rep. 2024 Jun 6;73(2):1-8. doi:10.15585/mmwr.rr7302a1. PMID: 38833414; PMCID: PMC11166373. Yearby R, Clark B, Figueroa JF. Structural racism in historical and modern US health care policy. Health Aff (Millwood). 2022;41(2):187-194. doi:10.1377/hlthaff.2021.01466. PMID: 35130059. Benavidez GA, Zahnd WE, Hung P, Eberth JM. Chronic disease prevalence in the US: sociodemographic and geographic variations by zip code tabulation area. Prev Chronic Dis. 2024;21:E14. doi:10.5888/pcd21.230267. PMID: 38426538; PMCID: PMC10944638. US Preventive Services Task Force; Mangione CM, Barry MJ, Nicholson WK, Cabana M, Chelmow D, Coker TR, Davis EM, Donahue KE, Jaén CR, Kubik M, Li L, Ogedegbe G, Pbert L, Ruiz JM, Stevermer J, Wong JB. Screening for syphilis infection in nonpregnant adolescents and adults: US Preventive Services Task Force reaffirmation recommendation statement. JAMA. 2022 Sep 27;328(12):1243-1249. doi:10.1001/jama.2022.15322. PMID: 36166020. STI Screening Recommendations. Centers for Disease Control and Prevention. Accessed April 24, 2026. https://www.cdc.gov/std/treatment-guidelines/screening-recommendations.htm Buchacz K, Patel P, Taylor M, Kerndt PR, Byers RH, Holmberg SD, Klausner JD. Syphilis increases HIV viral load and decreases CD4 cell counts in HIV-infected patients with new syphilis infections. AIDS. 2004;18(15):2075-2079. doi:10.1097/00002030-200410210-00012. PMID: 15577629; PMCID: PMC6763620. Roberts CP, Klausner JD. Global challenges in human immunodeficiency virus and syphilis coinfection among men who have sex with men. Expert Rev Anti Infect Ther. 2016;14(11):1037-1046. doi:10.1080/14787210.2016.1236683. PMID: 27626361; PMCID: PMC5859941. Wright SS, Kreisel KM, Hitt JC, Pagaoa MA, Weinstock HS, Thorpe PG. Impact of the COVID-19 pandemic on Centers for Disease Control and Prevention-funded sexually transmitted disease programs. Sex Transm Dis. 2022;49(4):e61-e63. doi:10.1097/OLQ.0000000000001566. PMID: 34654769; PMCID: PMC9214625. Bonett S, Teixeira da Silva D, Lazar N, Makeneni S, Wood SM. Trends in sexually transmitted infection screening during COVID-19 and missed cases among adolescents. Public Health. 2022;213:171-176. doi:10.1016/j.puhe.2022.10.007. PMID: 36423495; PMCID: PMC9576220. Meyers DJ, Hood ME, Stopka TJ. HIV and hepatitis C mortality in Massachusetts, 2002-2011: spatial cluster and trend analysis of infectious disease mortality. PLoS One. 2014;9(12):e114822. doi:10.1371/journal.pone.0114822. Jim MA, Arias E, Seneca DS, Hoopes MJ, Jim CC, Johnson NJ, et al. Racial misclassification of American Indians and Alaska Natives by Indian Health Service Contract Health Service Delivery Area. Am J Public Health. 2014;104 Suppl 3(Suppl 3):S295-S302. doi:10.2105/AJPH.2014.301933. Additional Declarations No competing interests reported. Supplementary Files 25AprilSyphylisSupplementaryTables.docx Supplementary File: Supplementary Table 1. Annual death counts and age-adjusted mortality rates by sex, United States, 2021–2025. Supplementary Table 2. Annual death counts and age-adjusted mortality rates by age group, United States, 2021–2025. Supplementary Table 3. Annual death counts and age-adjusted mortality rates by race/ethnicity, United States, 2021–2025. Supplementary Table 4. State-level Poisson regression results for syphilis-related mortality, United States, 2021–2025 (all states with non-suppressed data). Supplementary Table 5. Annual death counts and age-adjusted mortality rates by US Census region, United States, 2021–2025. Supplementary Table 6. Syphilis-related mortality by place of death, United States, 2021–2025. Supplementary Table 7. Sensitivity analyses: alternative case definitions, stage-specific trends, and co-occurrence analyses, United States, 2021–2025. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9520864","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":633869131,"identity":"99293423-edcd-4270-b9d3-3aee2ecc680d","order_by":0,"name":"Kanza Atif","email":"","orcid":"","institution":"College of Medicine, Alfaisal University, Riyadh, Saudi Arabia","correspondingAuthor":false,"prefix":"","firstName":"Kanza","middleName":"","lastName":"Atif","suffix":""},{"id":633869132,"identity":"ee3daa2b-85c9-4845-ac2c-a7c4b5fee478","order_by":1,"name":"Eshal Atif","email":"","orcid":"","institution":"College of Medicine, Alfaisal University, Riyadh, Saudi Arabia","correspondingAuthor":false,"prefix":"","firstName":"Eshal","middleName":"","lastName":"Atif","suffix":""},{"id":633869133,"identity":"1207c50c-5516-4858-965e-1866056eb9e0","order_by":2,"name":"Vishan Das","email":"","orcid":"","institution":"Liaquat University of Medical \u0026 Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Vishan","middleName":"","lastName":"Das","suffix":""},{"id":633869134,"identity":"5dfe7918-0999-49e6-81ad-18ddb6976480","order_by":3,"name":"Asad Ullah Farooq","email":"","orcid":"","institution":"King Edward Medical University","correspondingAuthor":false,"prefix":"","firstName":"Asad","middleName":"Ullah","lastName":"Farooq","suffix":""},{"id":633869135,"identity":"88af970f-0991-4ef3-823a-47b42b111f86","order_by":4,"name":"Sadia Qazi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYLCChAoGGfYGxgYGhgIg7wBRWs4w8PAcAGkxIFYLYxtIC4hFjBb59uTHHx7Os+PhYT/c/OGHAYMc340E/FoMzjwzMEjclszDw5PYJtljwGAsSVCLRIJBQuI2Zh57hkSg8wwYEjcQ0iI/I/3DgcQ59Tw8/A+bP/4xYKgnqIXhRo5hQ2LDYR4eicQGaaAtCQaE/fKmmCHh2HGglodt0jIGEoYzzzwg4LD29M0ff9RUy/Hwpz/++KbCRp7vOCGHMaAqkCCkHFPLKBgFo2AUjAJMAACWFkRqKyLh0gAAAABJRU5ErkJggg==","orcid":"","institution":"Department of Anatomy, College of Medicine, Alfaisal University","correspondingAuthor":true,"prefix":"","firstName":"Sadia","middleName":"","lastName":"Qazi","suffix":""},{"id":633869136,"identity":"a4cce5af-b087-41a1-872a-07cf29705159","order_by":5,"name":"Muhammad Atif Mazhar","email":"","orcid":"","institution":"Department of Anatomy, College of Medicine, Alfaisal University","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"Atif","lastName":"Mazhar","suffix":""}],"badges":[],"createdAt":"2026-04-24 21:53:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9520864/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9520864/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108470282,"identity":"5321fccf-ea65-4524-be0f-74e893f245f8","added_by":"auto","created_at":"2026-05-05 05:16:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":646462,"visible":true,"origin":"","legend":"\u003cp\u003eAnnual deaths and age-adjusted mortality rates for syphilis-related mortality, United States, 2021–2025.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9520864/v1/5055592b97136e94bdedd05f.png"},{"id":108494030,"identity":"73bd0ed1-550b-4eb4-bb14-93c653147aeb","added_by":"auto","created_at":"2026-05-05 10:02:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":642918,"visible":true,"origin":"","legend":"\u003cp\u003eSex-specific syphilis-related mortality, United States, 2021–2025.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9520864/v1/b345d367798a8a4b280fe177.png"},{"id":108470289,"identity":"77e733af-306c-42a5-8773-26a40ba46eca","added_by":"auto","created_at":"2026-05-05 05:16:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":630283,"visible":true,"origin":"","legend":"\u003cp\u003eSyphilis-related mortality by age group, United States, 2021–2025.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9520864/v1/4579fe5b8ec2511e26c7f84f.png"},{"id":108470285,"identity":"10ea7fd9-ed1c-4fa3-b279-30a2c4881f27","added_by":"auto","created_at":"2026-05-05 05:16:22","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":478873,"visible":true,"origin":"","legend":"\u003cp\u003eSyphilis-related mortality by race and ethnicity, United States, 2021–2025.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9520864/v1/6471830ed199bc1baa233cfe.png"},{"id":108494083,"identity":"e3d4c791-32e0-4757-b473-95c4f8dd6c75","added_by":"auto","created_at":"2026-05-05 10:02:32","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1021727,"visible":true,"origin":"","legend":"\u003cp\u003eAge-adjusted syphilis-related mortality rates by U.S. Census region, United States, 2021–2025.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-9520864/v1/d36285ae9ff27d84022b50e2.png"},{"id":108803930,"identity":"4ea11124-7c0c-4963-b7c4-226b0fa58ab5","added_by":"auto","created_at":"2026-05-08 15:11:51","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":735828,"visible":true,"origin":"","legend":"\u003cp\u003eSensitivity analyses of syphilis-related mortality using alternative case definitions and restricted time windows, United States, 2021–2025.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-9520864/v1/d90b008730519822a6dc5cc9.png"},{"id":108809200,"identity":"bab741da-25be-430b-81d8-7173e0154b34","added_by":"auto","created_at":"2026-05-08 15:50:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4379907,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9520864/v1/cb000857-4044-4038-a224-ace56c204715.pdf"},{"id":108494011,"identity":"8c92f144-4347-4d02-962e-9145b98a21a9","added_by":"auto","created_at":"2026-05-05 10:02:17","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":44037,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary File: Supplementary Table 1. Annual death counts and age-adjusted mortality rates by sex, United States, 2021–2025. Supplementary Table 2. Annual death counts and age-adjusted mortality rates by age group, United States, 2021–2025. Supplementary Table 3. Annual death counts and age-adjusted mortality rates by race/ethnicity, United States, 2021–2025. Supplementary Table 4. State-level Poisson regression results for syphilis-related mortality, United States, 2021–2025 (all states with non-suppressed data). Supplementary Table 5. Annual death counts and age-adjusted mortality rates by US Census region, United States, 2021–2025. Supplementary Table 6. Syphilis-related mortality by place of death, United States, 2021–2025. Supplementary Table 7. Sensitivity analyses: alternative case definitions, stage-specific trends, and co-occurrence analyses, United States, 2021–2025.\u003c/p\u003e","description":"","filename":"25AprilSyphylisSupplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-9520864/v1/4a162238f18fa1b1e8f2439d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Syphilis-related mortality in the United States, 2021–2025: U.S trends, demographic disparities, and implications for urological practice","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSyphilis has re-emerged as a major public health concern in the United States, with a steadily increasing incidence over the past two decades. National surveillance data indicate that reported cases have increased annually since 2000, reaching the highest levels in more than 70 years, with primary and secondary syphilis rates rising across all demographic groups [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The resurgence has been most pronounced among men who have sex with men (MSM), Black or African American populations, and individuals with limited access to healthcare, reflecting the persistent structural and social determinants of disease transmission [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Despite well-documented increases in incidence, contemporary patterns of syphilis-related mortality remain poorly defined.\u003c/p\u003e \u003cp\u003eClinically, syphilis-related mortality is largely driven by late-stage diseases, including neurosyphilis, cardiovascular involvement, and systemic complications that may involve the genitourinary tract. These manifestations intersect with urological and sexual medicine practices, where clinicians may encounter patients with unexplained lower urinary tract or neurological symptoms attributable to tertiary infections [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In addition, the HIV-syphilis syndemic contributes to accelerated disease progression and adverse outcomes, reinforcing the importance of integrated clinical management [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Therefore, understanding mortality patterns is critical for both clinical prioritization and public health responses.\u003c/p\u003e \u003cp\u003ePrior studies on syphilis mortality have important limitations. Many have relied on underlying cause of death (UCOD) definitions, which underestimate the true burden by excluding deaths in which syphilis is a contributing condition. Multiple cause of death (MCOD) approaches provide a more comprehensive assessment, particularly given that syphilis frequently functions as a contributing rather than the primary cause of death. Furthermore, contemporary analyses incorporating post-2020 data are limited, despite the known disruptions in STI services during the COVID-19 pandemic [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study aimed to characterize syphilis-related mortality in the United States from 2021 to 2025 using MCOD data stratified by sex, age, race/ethnicity, geography, and place of death, and to estimate temporal trends using Poisson regression. The secondary aim was to assess the robustness of the findings across alternative case definitions. The results were interpreted in the context of urological and sexual medicine practices.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Design and Data Source\u003c/h2\u003e \u003cp\u003eThis retrospective cross-sectional study analyzed national mortality data from the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) Multiple Cause of Death (MCOD) database [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Data were extracted for 2021\u0026ndash;2024 using final mortality files and supplemented by 2025 provisional data [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], yielding a five-year study window. The MCOD file records all conditions listed on the U.S. standard death certificate, including the underlying cause of death (UCOD) and up to 20 contributing causes, enabling the identification of deaths in which syphilis contributed to, but was not designated as, the primary cause [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This study was exempt from institutional review board approval because it used de-identified, publicly available aggregate data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Case Identification\u003c/h2\u003e \u003cp\u003eDecedents were included if any of the following ICD-10 codes appeared as either the underlying or contributing cause of death: A50 (congenital syphilis), A51 (early syphilis), A52 (late syphilis, including neurosyphilis and cardiovascular syphilis), or A53 (other and unspecified syphilis), constituting the any-mention MCOD case definition. This approach is consistent with prior U.S. syphilis mortality surveillance analyses using CDC WONDER MCOD data and ICD-10 codes A50\u0026ndash;A53 as underlying or contributing causes of death [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Cases were classified by diagnostic stage to characterize the clinical profile of mortality. HIV co-occurrence was identified by the additional presence of ICD-10 codes B20-B24 or R75 on the same death certificate. COVID-19 co-occurrence was identified using ICD-10 code U07.1. Cells with fewer than 10 deaths were suppressed according to CDC WONDER data-use restrictions [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Outcome Measures\u003c/h2\u003e \u003cp\u003eThe primary outcome was syphilis-related mortality, defined by any-mention MCOD criteria. Age-adjusted mortality rates (AAMRs) were calculated per 100,000 population using the 2000 United States Standard Population, enabling valid comparisons across subgroups and time periods with different age structures [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Crude mortality rates were reported alongside AAMRs for descriptive context.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Statistical Analysis\u003c/h2\u003e \u003cp\u003eTwo separate Poisson regression models were used in this study. To estimate demographic disparities, a cross-sectional Poisson model was fitted with pooled death counts (2021\u0026ndash;2025) as the outcome, ln(population) as an offset, and demographic group as the predictor, yielding rate ratios (RRs) with 95% confidence intervals (CIs). NH White individuals served as the reference for race/ethnicity comparisons, and females served as the reference for sex comparisons. To estimate temporal trends, a separate longitudinal Poisson model was fitted for each stratum with the annual death count as the outcome, ln(annual population) as the offset, and calendar year (centered on the stratum mean to reduce collinearity) as a continuous predictor. The annual percent change (APC) was derived as (e^β \u0026minus;\u0026thinsp;1) \u0026times; 100, where β is the year coefficient, and 95% CIs were computed on the log scale and back-transformed. A five-year observation window precludes reliable joinpoint segmentation because NCI/NCHS guidance recommends caution when estimating joinpoints in short time series with limited data around candidate segments and endpoints [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Poisson regression is the appropriate alternative for short time series with count outcomes. Overdispersion was assessed using the Pearson chi-squared statistic divided by residual degrees of freedom; strata with dispersion\u0026thinsp;\u0026gt;\u0026thinsp;2 (age 0\u0026ndash;24 years and congenital syphilis) are flagged in the results. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (two-tailed). All analyses were conducted in Python (version 3.13) using the statsmodels library (version 0.14.6) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Stratification\u003c/h2\u003e \u003cp\u003eMortality was stratified by sex (male, female), age group (0\u0026ndash;24, 25\u0026ndash;44, 45\u0026ndash;64, and \u0026ge;\u0026thinsp;65 years), race, and ethnicity using the CDC WONDER Non-Hispanic Single Race 6 classification (NH White, NH Black or African American, NH American Indian or Alaska Native [AI/AN], and NH Asian) and Hispanic or Latino ethnicity from a separate query; these classifications are not mutually exclusive. Mortality was also stratified by census region (Northeast, Midwest, South, and West), state of residence, and place of death. Age-stratified analyses reported crude rates; age adjustment within age strata was methodologically inappropriate and was not performed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Sensitivity Analyses\u003c/h2\u003e \u003cp\u003eEight sensitivity analyses were performed. (1) Restriction to UCOD only, quantifying the proportion of deaths in which syphilis was the primary cause rather than a contributing condition. (2) Restriction to A53.0 and A53.9 only, assessing the contribution of diagnostically unspecified coding. (3\u0026ndash;5) Restriction to individual ICD-10 stage categories: congenital syphilis (A50), early syphilis (A51), and late-stage syphilis (A52). (6) Co-occurrence of COVID-19 (U07.1) and syphilis, evaluating pandemic-related diagnostic displacement. (7) Co-occurrence of HIV (B20\u0026ndash;B24) and syphilis, quantifying the HIV\u0026ndash;syphilis co-mortality burden. (8) Restriction to 2021\u0026ndash;2024 final data only, excluding the provisional 2025 records. The full results are presented in Supplementary Table\u0026nbsp;7.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Overall Mortality\u003c/h2\u003e \u003cp\u003eBetween 2021 and 2025, 1,148 syphilis-related deaths were identified using the MCOD criteria, yielding an overall AAMR of 0.06 per 100,000 population (95% CI: 0.06\u0026ndash;0.07). The annual death counts ranged from 209 in 2023 to 243 in 2022. Poisson regression identified no statistically significant temporal trend over the study period (APC: \u0026minus;1.24%; 95% CI: \u0026minus;5.20% to 2.88%; p\u0026thinsp;=\u0026thinsp;0.550). Late syphilis (A52) was the most common stage, accounting for 51.4% of deaths (n\u0026thinsp;=\u0026thinsp;590), followed by unspecified syphilis (A53.0/A53.9, n\u0026thinsp;=\u0026thinsp;453, 39.5%), congenital syphilis (A50, n\u0026thinsp;=\u0026thinsp;95, 8.3%), and early syphilis (A51, n\u0026thinsp;=\u0026thinsp;12, 1.0%). The annual counts and AAMRs are presented in Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The distribution of clinical stages is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSyphilis-related mortality by clinical stage, United States, 2021\u0026ndash;2025\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical stage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeaths (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e% of total\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEarly syphilis (A51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongenital syphilis (A50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLate syphilis (A52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnspecified syphilis (A53.0/A53.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNotes: ICD-10 codes: A50\u0026thinsp;=\u0026thinsp;congenital syphilis; A51\u0026thinsp;=\u0026thinsp;early syphilis; A52\u0026thinsp;=\u0026thinsp;late syphilis (including neurosyphilis and cardiovascular syphilis); A53\u0026thinsp;=\u0026thinsp;other and unspecified syphilis. Deaths were identified using the any-mention multiple causes of death criteria.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Sex\u003c/h2\u003e \u003cp\u003eMales accounted for 71.0% of deaths (n\u0026thinsp;=\u0026thinsp;815; AAMR 0.10 per 100,000, 95% CI: 0.09\u0026ndash;0.11) compared with females (n\u0026thinsp;=\u0026thinsp;333; AAMR 0.03, 95% CI: 0.03\u0026ndash;0.03). Poisson regression confirmed a significantly higher mortality risk in males (RR: 2.50; 95% CI: 2.20\u0026ndash;2.83; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Temporal trends were stable in both sexes: male APC\u0026thinsp;\u0026minus;\u0026thinsp;0.36% (95% CI: \u0026minus;5.08% to 4.60%; p\u0026thinsp;=\u0026thinsp;0.886); female APC\u0026thinsp;\u0026minus;\u0026thinsp;3.32% (95% CI: \u0026minus;10.39% to 4.31%; p\u0026thinsp;=\u0026thinsp;0.384). Annual data by sex are presented in Supplementary Table\u0026nbsp;1 and are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSyphilis-related mortality by sex, United States, 2021\u0026ndash;2025\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeaths (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e% of total\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAAMR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAPC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value (APC)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.03 (0.03\u0026ndash;0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00 (referent)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.10 (0.09\u0026ndash;0.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.50 (2.20\u0026ndash;2.83)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;0.36% (\u0026minus;\u0026thinsp;5.08% to 4.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.886\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.06 (0.06\u0026ndash;0.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: AAMR\u0026thinsp;=\u0026thinsp;age-adjusted mortality rate per 100,000 population (2000 U.S. standard population). RR, rate ratio; Poisson regression; female, referent. APC\u0026thinsp;=\u0026thinsp;annual percent change; Poisson regression. * p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for RR. Annual data are presented in Supplementary Table\u0026nbsp;1.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Age\u003c/h2\u003e \u003cp\u003eMortality was concentrated among older adults. Those aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years accounted for 45.5% of deaths (n\u0026thinsp;=\u0026thinsp;522; AAMR 0.16 per 100,000, 95% CI: 0.14\u0026ndash;0.18), and those aged 45\u0026ndash;64 years accounted for 31.3% (n\u0026thinsp;=\u0026thinsp;359; AAMR 0.10, 95% CI: 0.09\u0026ndash;0.11). A secondary concentration was observed in the 0\u0026ndash;24 age group (n\u0026thinsp;=\u0026thinsp;90, 7.8%; AAMR 0.02, 95% CI: 0.01\u0026ndash;0.02), largely due to congenital syphilis. No statistically significant temporal trends were identified in any age group (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The 0\u0026ndash;24 age group showed overdispersion (Pearson dispersion 4.21), consistent with high year-to-year variability in small counts; this APC estimate should be interpreted cautiously. The annual data are presented in Supplementary Table\u0026nbsp;2 and summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSyphilis-related mortality by age group, United States, 2021\u0026ndash;2025\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeaths (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e% of total\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAAMR\u0026dagger; (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.02 (0.01\u0026ndash;0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;2.88% (\u0026minus;\u0026thinsp;16.08% to 12.39%)\u0026Dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.695\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.05 (0.05\u0026ndash;0.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u0026thinsp;3.09% (\u0026minus;\u0026thinsp;7.12% to 14.41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.568\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.10 (0.09\u0026ndash;0.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;2.31% (\u0026minus;\u0026thinsp;9.19% to 5.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.531\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.16 (0.14\u0026ndash;0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;2.72% (\u0026minus;\u0026thinsp;8.46% to 3.39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.06 (0.06\u0026ndash;0.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNotes: \u0026dagger; AAMR\u0026thinsp;=\u0026thinsp;age-adjusted mortality rate per 100,000 (2000 U.S. standard population). Age-stratified rates are crude rates, and age adjustment within strata is methodologically inappropriate. APC\u0026thinsp;=\u0026thinsp;annual percent change; Poisson regression. \u0026Dagger; Pearson dispersion\u0026thinsp;=\u0026thinsp;4.21 in the 0\u0026ndash;24 group; APC estimate is unstable and should be interpreted with caution. The annual data are presented in Supplementary Table\u0026nbsp;2.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Race and Ethnicity\u003c/h2\u003e \u003cp\u003eNH AI/AN individuals had the highest AAMR at 0.30 per 100,000 (95% CI: 0.21\u0026ndash;0.42; RR: 7.00; 95% CI: 4.98\u0026ndash;9.84; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 vs. NH White), although annual counts were suppressed in four of five study years, and this estimate should be interpreted with caution. NH Black or African American individuals accounted for the largest share of deaths (n\u0026thinsp;=\u0026thinsp;430; AAMR 0.20, 95% CI: 0.18\u0026ndash;0.22; RR: 4.81; 95% CI: 4.20\u0026ndash;5.50; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Hispanic or Latino individuals (n\u0026thinsp;=\u0026thinsp;227; AAMR 0.09, 95% CI: 0.08\u0026ndash;0.10) had an RR of 1.70 (95% CI: 1.44\u0026ndash;2.00; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). NH Asian individuals (n\u0026thinsp;=\u0026thinsp;42; AAMR 0.03, 95% CI: 0.02\u0026ndash;0.04) did not differ significantly from the NH White reference (RR: 0.92; 95% CI: 0.67\u0026ndash;1.27; p\u0026thinsp;=\u0026thinsp;0.614). Temporal trends were stable across all groups, with sufficient non-suppressed annual data. Annual data are presented in Supplementary Table\u0026nbsp;3 and summarized in Tables\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSyphilis-related mortality by race/ethnicity, United States, 2021\u0026ndash;2025\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace/ethnicity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeaths (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAAMR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNH White (referent)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03 (0.02\u0026ndash;0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (referent)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNH AI/AN\u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.30 (0.21\u0026ndash;0.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.00 (4.98\u0026ndash;9.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNH Black or African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.20 (0.18\u0026ndash;0.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.81 (4.20\u0026ndash;5.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic or Latino\u0026Dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.09 (0.08\u0026ndash;0.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.70 (1.44\u0026ndash;2.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNH Asian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03 (0.02\u0026ndash;0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92 (0.67\u0026ndash;1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.614\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06 (0.06\u0026ndash;0.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: AAMR\u0026thinsp;=\u0026thinsp;age-adjusted mortality rate per 100,000 (2000 U.S. standard population). RR: rate ratio; Poisson regression; NH White: referent. NH\u0026thinsp;=\u0026thinsp;non-Hispanic. \u0026dagger; NH AI/AN AAMR and RR should be interpreted with caution: annual counts suppressed in four of five years; estimate based on 36 total deaths. \u0026Dagger; Hispanic estimates derived from a separate CDC WONDER ethnicity query; not mutually exclusive of the NH race groups. The annual data are presented in Supplementary Table\u0026nbsp;3.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnnual percent change in syphilis-related mortality by race/ethnicity, United States, 2021\u0026ndash;2025\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace/ethnicity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAPC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNH White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;2.57% (\u0026minus;\u0026thinsp;8.99% to 4.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.455\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNH Black or African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;1.30% (\u0026minus;\u0026thinsp;7.68% to 5.53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.702\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic or Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u0026thinsp;3.50% (\u0026minus;\u0026thinsp;5.62% to 13.51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.465\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: APC\u0026thinsp;=\u0026thinsp;annual percent change, Poisson regression. NH AI/AN and NH Asian excluded: annual counts suppressed in \u0026ge;\u0026thinsp;4 of 5 years, precluding reliable trend estimation. All APCs non-significant (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Annual data in Supplementary Table\u0026nbsp;3.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Geography\u003c/h2\u003e \u003cp\u003eThe South (Census Region 3) accounted for 50.3% of all deaths (n\u0026thinsp;=\u0026thinsp;578; AAMR 0.08 per 100,000, 95% CI: 0.07\u0026ndash;0.09; RR vs. national: 1.29, 95% CI: 1.17\u0026ndash;1.43; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The West contributed 25.5% (n\u0026thinsp;=\u0026thinsp;293; AAMR 0.07, 95% CI: 0.06\u0026ndash;0.08; RR: 1.10, 95% CI: 0.97\u0026ndash;1.25; p\u0026thinsp;=\u0026thinsp;0.151, not significant). The Midwest showed a statistically significant declining trend over the study period (APC: \u0026minus;12.46%; 95% CI: \u0026minus;22.26% to \u0026minus;\u0026thinsp;1.42%; p\u0026thinsp;=\u0026thinsp;0.028) and had the lowest mortality burden relative to the national average (RR: 0.59, 95% CI: 0.49\u0026ndash;0.70; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The Northeast also had below-national mortality (RR 0.70 [95% CI 0.59\u0026ndash;0.84]; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The regional data are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and presented annually in Supplementary Table\u0026nbsp;5.\u003c/p\u003e \u003cp\u003eAt the state level, Mississippi (AAMR 0.18, RR: 2.64, 95% CI: 1.80\u0026ndash;3.87), Oklahoma (AAMR 0.18, RR: 2.55, 95% CI: 1.82\u0026ndash;3.59), Louisiana (AAMR 0.14, RR: 2.33, 95% CI: 1.68\u0026ndash;3.23), South Carolina (AAMR 0.13, RR: 2.22, 95% CI: 1.63\u0026ndash;3.03), and Maryland (AAMR 0.13, RR: 2.08, 95% CI: 1.54\u0026ndash;2.81) had the highest mortality rates relative to the national rate (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). California (n\u0026thinsp;=\u0026thinsp;164, RR\u0026thinsp;=\u0026thinsp;1.24, p\u0026thinsp;=\u0026thinsp;0.010) and Florida (n\u0026thinsp;=\u0026thinsp;106, RR\u0026thinsp;=\u0026thinsp;1.36, p\u0026thinsp;=\u0026thinsp;0.003) had significantly elevated rates. Texas (n\u0026thinsp;=\u0026thinsp;118, RR: 1.12, 95% CI: 0.93\u0026ndash;1.36; p\u0026thinsp;=\u0026thinsp;0.231) did not show statistical significance. Full state-level data are presented in Supplementary Table\u0026nbsp;4, selected Poisson comparisons are presented in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, and regional trends are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSyphilis-related mortality by U.S. Census region, 2021\u0026ndash;2025\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCensus region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeaths (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e% of total\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAAMR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRR vs. national (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAPC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAPC p-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08 (0.07\u0026ndash;0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.29 (1.17\u0026ndash;1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u0026thinsp;0.39% (\u0026minus;\u0026thinsp;5.24% to 6.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.895\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.07 (0.06\u0026ndash;0.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.10 (0.97\u0026ndash;1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;2.96% (\u0026minus;\u0026thinsp;10.51% to 5.22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.466\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMidwest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.02 (0.02\u0026ndash;0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.59 (0.49\u0026ndash;0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;12.46% (\u0026minus;\u0026thinsp;22.26% to \u0026minus;\u0026thinsp;1.42%)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNortheast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.03 (0.02\u0026ndash;0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.70 (0.59\u0026ndash;0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u0026thinsp;7.18% (\u0026minus;\u0026thinsp;4.77% to 20.64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.250\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNational\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.06 (0.06\u0026ndash;0.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00 (referent)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;1.24% (\u0026minus;\u0026thinsp;5.20% to 2.88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.550\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNote: AAMR\u0026thinsp;=\u0026thinsp;age-adjusted mortality rate per 100,000 (2000 U.S. standard population). RR, rate ratio; Poisson regression, national rate\u0026thinsp;=\u0026thinsp;referent. APC\u0026thinsp;=\u0026thinsp;annual percent change; Poisson regression. * Statistically significant declining trend (p\u0026thinsp;=\u0026thinsp;0.028). The annual data are presented in Supplementary Table\u0026nbsp;5.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eState-level Poisson regression results for syphilis-related mortality, United States, 2021\u0026ndash;2025 (selected states)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eState\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeaths (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAAMR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRR vs. national (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMississippi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.18 (0.12\u0026ndash;0.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.64 (1.80\u0026ndash;3.87)\u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOklahoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.18 (0.13\u0026ndash;0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.55 (1.82\u0026ndash;3.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLouisiana\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.14 (0.10\u0026ndash;0.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.33 (1.68\u0026ndash;3.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth Carolina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.13 (0.10\u0026ndash;0.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.22 (1.63\u0026ndash;3.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaryland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.13 (0.09\u0026ndash;0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.08 (1.54\u0026ndash;2.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlorida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.05 (0.04\u0026ndash;0.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.36 (1.11\u0026ndash;1.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalifornia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.08 (0.07\u0026ndash;0.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.24 (1.05\u0026ndash;1.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTexas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.09 (0.07\u0026ndash;0.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.12 (0.93\u0026ndash;1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.231 (ns)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNational\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06 (0.06\u0026ndash;0.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (referent)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: Table shows the states with statistically significantly elevated RRs and the two highest-volume states. AAMR\u0026thinsp;=\u0026thinsp;age-adjusted mortality rate per 100,000 (2000 U.S. standard population). RR, rate ratio; Poisson regression, national rate\u0026thinsp;=\u0026thinsp;referent. \u0026dagger; Mississippi, n\u0026thinsp;=\u0026thinsp;27; interpreted with caution. Texas RR was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.231). ns\u0026thinsp;=\u0026thinsp;not significant. DC and 18 other states had suppressed data; full data are presented in Supplementary Table\u0026nbsp;4.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.6. Place of Death\u003c/h2\u003e \u003cp\u003eAmong the 1,148 decedents, 46.1% (n\u0026thinsp;=\u0026thinsp;529) died in inpatient medical facilities, 21.9% (n\u0026thinsp;=\u0026thinsp;251) at home, 14.6% (n\u0026thinsp;=\u0026thinsp;168) in nursing homes or long-term care facilities, and 7.7% (n\u0026thinsp;=\u0026thinsp;88) in a hospice facility. Combined, 53.9% of deaths occurred outside inpatient hospital settings, suggesting that a substantial proportion of syphilis-related deaths may occur without active hospital-level care. Population denominators and rates were not available for place-of-death stratification in the CDC WONDER. The full distribution is presented in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e and Supplementary Table\u0026nbsp;6.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSyphilis-related mortality by place of death, United States, 2021\u0026ndash;2025\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlace of death\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeaths (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e% of total deaths\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical facility \u0026ndash; inpatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDecedent's home\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNursing home / long-term care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospice facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical facility \u0026ndash; outpatient or ER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical facility \u0026ndash; dead on arrival / unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNotes: Population denominators and age-adjusted rates were not available for place-of-death stratification in the CDC WONDER. The data represent the cumulative 2021\u0026ndash;2025 totals.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.7. Sensitivity Analyses\u003c/h2\u003e \u003cp\u003eWhen restricted to UCOD only, 245 deaths were identified (21.3% of the MCOD total), confirming that syphilis functions predominantly as a contributing rather than primary cause on U.S. death certificates, with a 4.7-fold difference between case definitions. The UCOD-only APC was not significant (+\u0026thinsp;1.41%; 95% CI: \u0026minus;7.18% to 10.80%; p\u0026thinsp;=\u0026thinsp;0.756), consistent with the primary analysis.\u003c/p\u003e \u003cp\u003eLate syphilis (A52, n\u0026thinsp;=\u0026thinsp;590) showed a statistically significant declining trend over the study period (APC: \u0026minus;7.55%; 95% CI: \u0026minus;12.70% to \u0026minus;\u0026thinsp;2.11%; p\u0026thinsp;=\u0026thinsp;0.007), In contrast, deaths coded to unspecified syphilis (A53.0/A53.9, n\u0026thinsp;=\u0026thinsp;453) increased significantly (APC: +9.05%; 95% CI: +2.14% to +\u0026thinsp;16.43%; p\u0026thinsp;=\u0026thinsp;0.009). These opposing trends suggest a shift in death certificate coding practices toward less specific syphilis classifications over time, rather than a true change in disease burden.\u003c/p\u003e \u003cp\u003eHIV (B20\u0026ndash;B24) was co-listed in 316 deaths (27.5%), with a borderline significant increasing trend in HIV\u0026ndash;syphilis co-mortality (APC: +8.25%; 95% CI: +0.10% to +\u0026thinsp;17.08%; p\u0026thinsp;=\u0026thinsp;0.047). COVID-19 (U07.1) was co-listed in 44 deaths (3.8%), concentrated in 2021 (n\u0026thinsp;=\u0026thinsp;19) and 2022 (n\u0026thinsp;=\u0026thinsp;15), and subsequent years were suppressed. Congenital syphilis (A50, n\u0026thinsp;=\u0026thinsp;95) showed no significant trend (APC: \u0026minus;5.24%; p\u0026thinsp;=\u0026thinsp;0.459), although overdispersion (Pearson dispersion\u0026thinsp;=\u0026thinsp;5.88) limited confidence in this estimate. Early syphilis (A51) contributed only 12 deaths over five years, with most annual cells suppressed, and no trend model was estimable.\u003c/p\u003e \u003cp\u003eRestriction to 2021\u0026ndash;2024 final data only (n\u0026thinsp;=\u0026thinsp;919; AAMR 0.05, 95% CI: 0.05\u0026ndash;0.06; APC: \u0026minus;1.78%, 95% CI: \u0026minus;7.30% to 4.06%; p\u0026thinsp;=\u0026thinsp;0.541) was fully consistent with the primary five-year analysis, confirming that the inclusion of provisional 2025 data did not materially alter the findings. The full sensitivity analysis data are presented in Supplementary Table\u0026nbsp;7 and Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Overall mortality and preventable burden\u003c/h2\u003e \u003cp\u003eIn this national analysis of syphilis-related mortality from 2021 to 2025, mortality remained stable over the study period, with no statistically significant temporal trends. This stability occurs in the context of a steadily rising syphilis incidence in the United States, suggesting a complex relationship between infection trends and mortality outcomes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The 2023 CDC STI surveillance report documented over 209,000 syphilis cases nationally, with primary and secondary syphilis declining for the first time since 2001, while late and unknown-duration syphilis increased by 12.2%, a divergence that likely reflects the same diagnostic and treatment access pressures captured in the mortality data presented here [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Potential explanations for mortality stability include improved access to treatment for incident infections, prolonged latency between infection and fatal complications, and persistence of a fixed pool of individuals with longstanding untreated infections. Stable mortality should not be interpreted as reassuring: 1,148 deaths over five years from a treatable bacterial infection represent a substantial and largely preventable burden. That preventability is not unconditional, the 2023 shortage of benzathine penicillin G, the only recommended treatment for several syphilis stages, constrained treatment access across the latter portion of the study window and may have delayed care for non-pregnant adults during peak shortage periods [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Late-stage disease and coding specificity\u003c/h2\u003e \u003cp\u003eThe predominance of late syphilis (51.4%) confirms that fatal syphilis in the United States is primarily a consequence of chronically untreated or undiagnosed infections rather than acute disease. The observed decline in late-stage syphilis mortality, alongside a concurrent increase in unspecified syphilis coding, likely reflects a shift in death certificate coding practices rather than a true epidemiological reduction in late-stage disease. Similar patterns of declining diagnostic specificity have been described in other infectious disease mortality analyses using ICD-10 data [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The 2024 CDC laboratory recommendations for syphilis testing explicitly revised the diagnostic algorithms to address the mismatch between serologic detection patterns and clinical staging, providing a plausible institutional mechanism for the ICD-10 coding drift observed in this study [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. This coding drift has important implications for surveillance, as analyses restricted to specific ICD-10 categories may underestimate the true burden of advanced diseases. The any-mention MCOD methodology provides a more robust assessment of syphilis-related mortality and should be the preferred approach for future analyses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Sex disparities and urological relevance\u003c/h2\u003e \u003cp\u003eThe marked male predominance observed in this study is consistent with national incidence patterns, where syphilis disproportionately affects males, particularly MSM [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. From a urological perspective, late syphilis encompasses several conditions that are directly relevant to clinical practice. Neurogenic lower urinary tract dysfunction is a recognized complication of neurosyphilis, with urodynamic studies in contemporary cases demonstrating low-capacity bladders with detrusor overactivity, urge incontinence, and urinary retention [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The spectrum of lower urinary tract dysfunction associated with infectious and inflammatory neurological conditions, including neurosyphilis, was systematically characterized in a recent multinational neuro-urology study. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Tabes dorsalis, the dorsal column demyelinating form of late neurosyphilis, remains clinically active in the modern antibiotic era and continues to present with bladder dysfunction as a prominent feature, including in HIV-negative patients [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Beyond the lower urinary tract, late syphilis encompasses gummatous involvement of the genitourinary tract and cardiovascular complications, such as syphilitic aortitis [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The broader clinical and translational context of the syphilis resurgence, including emerging treatment strategies relevant to late-stage disease, has been reviewed by Xiong et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite increasing awareness of the resurgence of syphilis, the absence of a significant decline in male mortality suggests persistent gaps in early detection and management. Primary, secondary, and early latent syphilis remain treatable with a single intramuscular dose of benzathine penicillin G, and the deaths recorded here likely represent infections that were diagnosed late, lost to follow-up, or never identified [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. For MSM, the demographic carrying the greatest incidence burden, the 2024 CDC guidelines on doxycycline post-exposure prophylaxis represent a now-available prevention tool: three large randomized controlled trials demonstrated that 200 mg doxycycline taken within 72 hours of sex reduces syphilis acquisition by more than 70% in this population [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Clinicians, including urologists, should maintain a high index of suspicion for syphilis in patients presenting with unexplained genitourinary or neurological symptoms, and eligible MSM patients should be informed of doxyPEP as part of a comprehensive sexual health strategy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Racial and ethnic disparities\u003c/h2\u003e \u003cp\u003eSubstantial racial and ethnic disparities were evident, with NH Black individuals experiencing a nearly five-fold higher mortality risk and NH American Indian or Alaska Native individuals demonstrating the highest rates overall. These disparities reflect well-documented structural inequities in the STI burden, including differences in healthcare access, socioeconomic conditions, and continuity of care [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The magnitude of these disparities suggests that excess mortality is not solely attributable to a higher incidence but also to downstream failures in treatment and retention in care. Hispanic populations also demonstrated an elevated mortality risk, highlighting the need for targeted public health investment in demographically vulnerable communities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e4.5. Geographic variation\u003c/h2\u003e \u003cp\u003eGeographic variation further highlighted the disproportionate burden of syphilis mortality in the Southern United States, which accounted for over half of all deaths and exhibited significantly higher mortality rates than the national average mortality rate. This pattern aligns with longstanding regional disparities in the STI burden, healthcare infrastructure, and socioeconomic determinants of health [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The observed decline in mortality in the Midwest represents a novel finding, although it should be interpreted cautiously, given the smaller case counts and potential statistical instability. State-level variation, with Mississippi, Oklahoma, Louisiana, South Carolina, and Maryland each exceeding double the national mortality risk, provides actionable geographic targets for interventions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e4.6. Place of death and missed clinical opportunities\u003c/h2\u003e \u003cp\u003eThe finding that more than half of the syphilis-related deaths occurred outside inpatient hospital settings is particularly notable. Deaths at home or in long-term care facilities likely represent advanced disease in patients with limited engagement in healthcare systems and raise concerns about missed opportunities for diagnosis and treatment in community and institutional settings. The 2022 US Preventive Services Task Force reaffirmation recommends syphilis screening in all persons at increased risk (Grade A recommendation), and current CDC STI screening guidance specifically identifies high-risk populations for targeted serological testing [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. However, the concentration of deaths in nursing homes and long-term care facilities suggests that these recommendations are not being systematically applied to older institutionalized adults. Routine syphilis serology in older patients with unexplained neurological or cardiovascular decline in long-term care settings is warranted.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.7. HIV co-occurrence and pandemic context\u003c/h2\u003e \u003cp\u003eThe high prevalence of HIV co-occurrence (27.5%) and its borderline significant increasing trend (APC\u0026thinsp;+\u0026thinsp;8.25%, p\u0026thinsp;=\u0026thinsp;0.047) reinforce the importance of the HIV-syphilis syndemic in shaping mortality. HIV infection accelerates syphilis progression, elevates the viral load, and reduces CD4 counts in co-infected individuals, increasing the risk of severe and late-stage manifestations [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The observed increase in co-mortality likely reflects multiple converging factors: an aging cohort of people living with HIV who acquired the infection before effective antiretroviral therapy was available and are now entering the age groups with the highest syphilis mortality; rising syphilis incidence among HIV-positive MSM; and potential underutilization of doxyPEP in HIV-positive individuals, for whom the 2024 CDC guidelines are explicitly applicable [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. These findings support the use of integrated screening and co-management strategies that simultaneously address both infections.\u003c/p\u003e \u003cp\u003eThe COVID-19 pandemic likely influenced syphilis-related mortality patterns during the early stages of the study period. Disruptions in STI screening, reduced access to clinical services, and reallocation of public health resources during 2020\u0026ndash;2022 have been well documented [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], and delayed diagnosis during this period may have expanded the pool of individuals at risk for late-stage complications [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The low COVID-19 co-listing rate (3.8%, concentrated in 2021\u0026ndash;2022) and the stability of the primary trend estimate when restricted to the 2021\u0026ndash;2024 final data suggest that the pandemic period did not materially confound the overall findings, although its longer-term effects on the late-stage disease pipeline warrant continued surveillance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e4.8. Sensitivity analyses and methodological robustness\u003c/h2\u003e \u003cp\u003eRestricting syphilis deaths to the underlying cause of death only identified 245 cases (21.3% of the any-mention MCOD total), confirming that syphilis functions predominantly as a contributing rather than a primary condition on U.S. death certificates, with a 4.7-fold difference between case definitions. This pattern is consistent with MCOD analyses of other chronic infectious conditions and reinforces why any-mention methodology is the appropriate standard for surveillance of diseases that contribute to, rather than directly cause, death [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The UCOD-only APC was non-significant (+\u0026thinsp;1.41%; 95% CI: \u0026minus;7.18% to 10.80%; p\u0026thinsp;=\u0026thinsp;0.756), fully concordant with the primary analyses.\u003c/p\u003e \u003cp\u003eThe opposing trends in late syphilis (A52: APC\u0026thinsp;\u0026minus;\u0026thinsp;7.55%, p\u0026thinsp;=\u0026thinsp;0.007) and unspecified syphilis (A53.0/A53.9: APC\u0026thinsp;+\u0026thinsp;9.05%, p\u0026thinsp;=\u0026thinsp;0.009) are the most methodologically important sensitivity findings. These trends move in opposite directions with nearly identical magnitudes, far more consistent with a coding drift toward less specific classifications than with a genuine divergence in stage-specific disease burden. The 2024 CDC laboratory recommendations' revision of syphilis diagnostic algorithms may accelerate this drift by altering how clinicians document the syphilis stage at the time of death certification [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Surveillance systems relying solely on A52 to track late syphilis mortality will increasingly underestimate the true burden. The any-mention, broad-code MCOD definition is more resistant to misclassification and should be preferred in future analyses.\u003c/p\u003e \u003cp\u003eCOVID-19 co-listing was low (3.8%, n\u0026thinsp;=\u0026thinsp;44) and concentrated in 2021\u0026ndash;2022, consistent with declining COVID-19 mortality rather than pandemic-related diagnostic displacement. Restricting the analysis to 2021\u0026ndash;2024 final data yielded an APC of \u0026minus;\u0026thinsp;1.78% (95% CI: \u0026minus;7.30% to 4.06%; p\u0026thinsp;=\u0026thinsp;0.541) and an AAMR of 0.05 per 100,000 (95% CI: 0.05\u0026ndash;0.06), fully consistent with the five-year primary estimate and confirming that the provisional 2025 data did not introduce meaningful instability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e4.9. Limitations\u003c/h2\u003e \u003cp\u003eThis study has several limitations. First, syphilis mortality captured on death certificates depends on the accuracy and completeness of clinical coding [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Syphilis may be under-documented as a contributing cause in older decedents, where late-stage complications overlap with cardiovascular disease and dementia, leading to potential underestimation of the true burden. Second, the cross-sectional surveillance design precludes causal inference; rate ratios describe population-level associations and cannot be attributed to individual causal pathways.\u003c/p\u003e \u003cp\u003eThird, the five-year observation window limits the statistical power of trend analyses. Poisson regression CIs are wide in strata with small annual counts, and APC estimates for the 0\u0026ndash;24 age group (Pearson dispersion 4.21) and congenital syphilis (Pearson dispersion 5.88) are unstable and should be treated as descriptive. Fourth, CDC WONDER suppression rules resulted in missing data for 19 states and the District of Columbia [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The NH AI/AN rate ratio of 7.00 rests on 36 total deaths, with four of five annual cells suppressed and should be read as a directional signal; this caution is reinforced by the known racial misclassification of AI/AN individuals on death certificates [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Fifth, race and Hispanic ethnicity data were extracted from separate CDC WONDER queries and were not mutually exclusive. Finally, the place-of-death data lack population denominators, precluding rate estimation for that stratum.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e4.10. Conclusions\u003c/h2\u003e \u003cp\u003eBetween 2021 and 2025, syphilis-related mortality in the United States remained stable but concentrated in identifiable groups: older adults, males, NH Black and AI/AN individuals, and residents of the South, with more than half of all deaths occurring outside inpatient hospital settings. Late syphilis accounted for 51.4% of deaths, HIV was co-listed in 27.5%, and opposing ICD-10 coding trends between A52 and A53 reflected the progressive loss of diagnostic specificity on death certificates rather than a genuine reduction in late-stage burden. These patterns reflect failures of early detection and treatment retention rather than therapeutic failures. For urologists and sexual medicine practitioners, the 71% male predominance, neurogenic bladder, genitourinary manifestations of late neurosyphilis, and HIV co-occurrence signal justify routine syphilis serology in sexually active male patients particularly those living with HIV and prompt co-management with infectious disease services when late-stage disease is identified. The concentration of deaths in nursing homes and long-term care facilities supports systematic screening in older patients with unexplained neurological or cardiovascular decline. Geographically, the South accounted for 50.3% of deaths at 1.3 times the national rate, and the Midwest's statistically significant declining trend warrants investigation as a regional model. Syphilis mortality in the U.S. is not intractable; at-risk populations and geographies are identifiable, and prevention and treatment tools exist to address them.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eThe following abbreviations are used in this manuscript: Age-adjusted mortality rate (AAMR); annual percent change (APC); average annual percent change (AAPC); Centers for Disease Control and Prevention (CDC); confidence interval (CI); coronavirus disease 2019 (COVID-19); doxycycline post-exposure prophylaxis (doxyPEP); human immunodeficiency virus (HIV); International Classification of Diseases, 10th Revision (ICD-10); institutional review board (IRB); lower urinary tract dysfunction (LUTD); lower urinary tract symptoms (LUTS); men who have sex with men (MSM); multiple cause of death (MCOD); non-Hispanic (NH); non-Hispanic American Indian or Alaska Native (NH AI/AN); non-Hispanic Black or African American (NH Black); Neurourology and Pelvic Floor Committee (NUPC); rate ratio (RR); sexually transmitted infection (STI); underlying cause of death (UCOD); US Preventive Services Task Force (USPSTF); Wide-ranging Online Data for Epidemiologic Research (WONDER).\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch4\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003eThis study used de-identified, publicly available aggregate mortality data obtained from the CDC WONDER Multiple Cause of Death database which is publicly available, de-identified data and exempted from institutional review board review. No individual patient data were accessed, and no patient consent was required.\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003eAll data analyzed in this study are publicly available through the CDC WONDER Multiple Cause of Death database at https://wonder.cdc.gov/mcd.html and found in supplementary file.\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003eThe authors received no specific funding for this work. The APC was covered by Alfaisal University\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003eKA contributed to conceptualization, literature review, data interpretation, and writing of the original draft. EA contributed to data curation, formal analysis, and writing of the original draft. VD contributed to methodology, statistical analysis, and writing \u0026mdash; review and editing. AUF contributed to data curation, visualization, and writing \u0026mdash; review and editing. SQ contributed to conceptualization, supervision, methodology, project administration, and writing \u0026mdash; review and editing. MAM contributed to supervision, critical appraisal of intellectual content, and writing \u0026mdash; review and editing. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements: None\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eCounty-level syphilis data: STI statistics. Centers for Disease Control and Prevention. March 3, 2025. Accessed June 29, 2025. https://www.cdc.gov/sti-statistics/county-level-syphilis-data/index.html\u003c/li\u003e\n \u003cli\u003eSchmidt R, Carson PJ, Jansen RJ. Resurgence of syphilis in the United States: an assessment of contributing factors. Infect Dis (Auckl). 2019;12:1178633719883282. doi:10.1177/1178633719883282. PMID: 31666795; PMCID: PMC6798162.\u003c/li\u003e\n \u003cli\u003eFrench P. Syphilis. BMJ. 2007;334(7585):143-147. doi:10.1136/bmj.39085.518148.BE. PMID: 17235095; PMCID: PMC1779891.\u003c/li\u003e\n \u003cli\u003eDo D, Rodriguez PJ, Gratzl S, Cartwright BMG, Baker C, Stucky NL. Trends in incidence of syphilis among US adults from January 2017 to October 2024. Am J Prev Med. 2025 Apr 2:S0749-3797(25)00106-0. doi:10.1016/j.amepre.2025.03.008. Epub ahead of print. PMID: 40185421.\u003c/li\u003e\n \u003cli\u003eZetola NM, Klausner JD. Syphilis and HIV infection: an update. Clin Infect Dis. 2007;44(9):1222-1228. doi:10.1086/513427. PMID: 17407043.\u003c/li\u003e\n \u003cli\u003eRogers B, Tao J, Murphy M, Chan PA. The COVID-19 pandemic and sexually transmitted infections: where do we go from here? Sex Transm Dis. 2021;48(7):e94-e96. doi:10.1097/OLQ.0000000000001445. PMID: 33872225; PMCID: PMC8570344.\u003c/li\u003e\n \u003cli\u003eMultiple Cause of Death Data on CDC WONDER. Centers for Disease Control and Prevention. Accessed April 24, 2026. https://wonder.cdc.gov/mcd.html\u003c/li\u003e\n \u003cli\u003eProvisional Mortality by Multiple Cause of Death. Centers for Disease Control and Prevention. Accessed April 24, 2026. https://wonder.cdc.gov/wonder/help/mcd-provisional.html\u003c/li\u003e\n \u003cli\u003eBarragan NC, Wickramasekaran RN, Sorvillo F, Smith LV, Kuo T. Current trends in syphilis mortality in the United States, 2015\u0026ndash;2020. Venereology. 2023;2(2):59-64. doi:10.3390/venereology2020005.\u003c/li\u003e\n \u003cli\u003eData Use Restrictions. Centers for Disease Control and Prevention. Accessed April 24, 2026. https://wonder.cdc.gov/datause.html\u003c/li\u003e\n \u003cli\u003eKlein RJ, Schoenborn CA. Age adjustment using the 2000 projected U.S. population. Healthy People Statistical Notes, no. 20. Hyattsville, MD: National Center for Health Statistics; 2001.\u003c/li\u003e\n \u003cli\u003eIrimata KE, Bastian BA, Clarke TC, Curtin SC, Rui P. Guidance for selecting model options in the National Cancer Institute Joinpoint Regression Software. Vital Health Stat 2. 2022;(194):1-24. doi:10.15620/cdc:118050.\u003c/li\u003e\n \u003cli\u003eSeabold S, Perktold J. Statsmodels: econometric and statistical modeling with Python. Proceedings of the 9th Python in Science Conference. 2010:92-96. doi:10.25080/Majora-92bf1922-011.\u003c/li\u003e\n \u003cli\u003eCenters for Disease Control and Prevention. Sexually transmitted infections surveillance, 2023. Atlanta: U.S. Department of Health and Human Services; 2024. Available from: https://www.cdc.gov/sti-statistics/annual/index.html\u003c/li\u003e\n \u003cli\u003eFaghihi I, King HL, Kwon Y. Benzathine penicillin G shortage and effects on syphilis patient outcomes. Open Forum Infect Dis. 2026 Jan 11;13(Suppl 1):ofaf695.935. doi:10.1093/ofid/ofaf695.935. PMCID: PMC12793167.\u003c/li\u003e\n \u003cli\u003eLiu B, Hadzi-Tosev M, Liu Y, Lucier KJ, Garg A, Li S, Heddle NM, Rochwerg B, Ning S. Accuracy of International Classification of Diseases, 10th Revision codes for identifying sepsis: a systematic review and meta-analysis. Crit Care Explor. 2022;4(11):e0788. doi:10.1097/CCE.0000000000000788. PMID: 36382338; PMCID: PMC9649267.\u003c/li\u003e\n \u003cli\u003ePapp JR, Park IU, Fakile Y, Pereira L, Pillay A, Bolan GA. CDC laboratory recommendations for syphilis testing, United States, 2024. MMWR Recomm Rep. 2024 Feb 8;73(1):1-32. doi:10.15585/mmwr.rr7301a1. PMID: 38319847; PMCID: PMC10849099.\u003c/li\u003e\n \u003cli\u003eErturk E, Sheinfeld J, Davis RS. Voiding dysfunction in tertiary syphilis. Urology. 1987;30(3):284-286. doi:10.1016/0090-4295(87)90259-7. PMID: 3629778.\u003c/li\u003e\n \u003cli\u003ePlayfair M, Welk B. Neurosyphilis \u0026mdash; an uncommon cause of neurogenic lower urinary tract dysfunction. Continence Rep. 2023;6:100024. doi:10.1016/j.contre.2023.100024.\u003c/li\u003e\n \u003cli\u003eKonstantinidis C, Sakakibara R, Vrijens D, Werneburg GT, Welk B, Kotes S, Drake MJ, Rapidi CA, Gomes CM, Abranches-Monteiro L, Onem K, de Wachter S, Sinha M. Lower urinary tract dysfunction in uncommon neurological diseases \u0026mdash; part IV: infections, inflammatory, toxic, and structural disorders \u0026mdash; a NUPC report. Continence. 2025. doi:10.1016/j.cont.2025.102274. Epub ahead of print.\u003c/li\u003e\n \u003cli\u003eBloch N, Brugger F, Notter J. Tabes dorsalis: a rare presentation of neurosyphilis in Western Europe. BMJ Case Rep. 2025 Feb 3;18(2):e262492. doi:10.1136/bcr-2024-262492. PMID: 39900398; PMCID: PMC11795238.\u003c/li\u003e\n \u003cli\u003eZhu Z, Gong H, Liu M, Zhang H, Yang L, Zhang X, Li J. Diagnosing tabes dorsalis in HIV-negative patients: clinical features, neuroimaging, and laboratory insights in the modern antibiotic era. Infect Drug Resist. 2024;17:2567-2577. doi:10.2147/IDR.S464581.\u003c/li\u003e\n \u003cli\u003eXiong S, Liu Z, Zhang X, Huang S, Ding X, Zhou J, Yao J, Li W, Liu S, Zhao F. Resurgence of syphilis: focusing on emerging clinical strategies and preclinical models. J Transl Med. 2023 Dec 18;21(1):917. doi:10.1186/s12967-023-04685-4. PMID: 38105236; PMCID: PMC10726518.\u003c/li\u003e\n \u003cli\u003eWorkowski KA, Bachmann LH, Chan PA, Johnston CM, Muzny CA, Park I, et al. Sexually transmitted infections treatment guidelines, 2021. MMWR Recomm Rep. 2021;70(4):1-187. doi:10.15585/mmwr.rr7004a1.\u003c/li\u003e\n \u003cli\u003eBachmann LH, Barbee LA, Chan P, Reno H, Workowski KA, Hoover K, Mermin J, Mena L. CDC clinical guidelines on the use of doxycycline postexposure prophylaxis for bacterial sexually transmitted infection prevention, United States, 2024. MMWR Recomm Rep. 2024 Jun 6;73(2):1-8. doi:10.15585/mmwr.rr7302a1. PMID: 38833414; PMCID: PMC11166373.\u003c/li\u003e\n \u003cli\u003eYearby R, Clark B, Figueroa JF. Structural racism in historical and modern US health care policy. Health Aff (Millwood). 2022;41(2):187-194. doi:10.1377/hlthaff.2021.01466. PMID: 35130059.\u003c/li\u003e\n \u003cli\u003eBenavidez GA, Zahnd WE, Hung P, Eberth JM. Chronic disease prevalence in the US: sociodemographic and geographic variations by zip code tabulation area. Prev Chronic Dis. 2024;21:E14. doi:10.5888/pcd21.230267. PMID: 38426538; PMCID: PMC10944638.\u003c/li\u003e\n \u003cli\u003eUS Preventive Services Task Force; Mangione CM, Barry MJ, Nicholson WK, Cabana M, Chelmow D, Coker TR, Davis EM, Donahue KE, Ja\u0026eacute;n CR, Kubik M, Li L, Ogedegbe G, Pbert L, Ruiz JM, Stevermer J, Wong JB. Screening for syphilis infection in nonpregnant adolescents and adults: US Preventive Services Task Force reaffirmation recommendation statement. JAMA. 2022 Sep 27;328(12):1243-1249. doi:10.1001/jama.2022.15322. PMID: 36166020.\u003c/li\u003e\n \u003cli\u003eSTI Screening Recommendations. Centers for Disease Control and Prevention. Accessed April 24, 2026. https://www.cdc.gov/std/treatment-guidelines/screening-recommendations.htm\u003c/li\u003e\n \u003cli\u003eBuchacz K, Patel P, Taylor M, Kerndt PR, Byers RH, Holmberg SD, Klausner JD. Syphilis increases HIV viral load and decreases CD4 cell counts in HIV-infected patients with new syphilis infections. AIDS. 2004;18(15):2075-2079. doi:10.1097/00002030-200410210-00012. PMID: 15577629; PMCID: PMC6763620.\u003c/li\u003e\n \u003cli\u003eRoberts CP, Klausner JD. Global challenges in human immunodeficiency virus and syphilis coinfection among men who have sex with men. Expert Rev Anti Infect Ther. 2016;14(11):1037-1046. doi:10.1080/14787210.2016.1236683. PMID: 27626361; PMCID: PMC5859941.\u003c/li\u003e\n \u003cli\u003eWright SS, Kreisel KM, Hitt JC, Pagaoa MA, Weinstock HS, Thorpe PG. Impact of the COVID-19 pandemic on Centers for Disease Control and Prevention-funded sexually transmitted disease programs. Sex Transm Dis. 2022;49(4):e61-e63. doi:10.1097/OLQ.0000000000001566. PMID: 34654769; PMCID: PMC9214625.\u003c/li\u003e\n \u003cli\u003eBonett S, Teixeira da Silva D, Lazar N, Makeneni S, Wood SM. Trends in sexually transmitted infection screening during COVID-19 and missed cases among adolescents. Public Health. 2022;213:171-176. doi:10.1016/j.puhe.2022.10.007. PMID: 36423495; PMCID: PMC9576220.\u003c/li\u003e\n \u003cli\u003eMeyers DJ, Hood ME, Stopka TJ. HIV and hepatitis C mortality in Massachusetts, 2002-2011: spatial cluster and trend analysis of infectious disease mortality. PLoS One. 2014;9(12):e114822. doi:10.1371/journal.pone.0114822.\u003c/li\u003e\n \u003cli\u003eJim MA, Arias E, Seneca DS, Hoopes MJ, Jim CC, Johnson NJ, et al. Racial misclassification of American Indians and Alaska Natives by Indian Health Service Contract Health Service Delivery Area. Am J Public Health. 2014;104 Suppl 3(Suppl 3):S295-S302. doi:10.2105/AJPH.2014.301933.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"syphilis mortality, multiple cause of death, age-adjusted mortality rate, health disparities, sexually transmitted infections","lastPublishedDoi":"10.21203/rs.3.rs-9520864/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9520864/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Syphilis-related mortality in the United States remains incompletely characterized during the post-pandemic period. This study aimed to quantify U.S trends, demographic disparities, and geographic distribution of syphilis-related mortality from 2021 to 2025 using multiple causes of death data, with attention to urological and clinical implications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A retrospective cross-sectional analysis was conducted using the CDC WONDER Multiple Cause-of-Death database. Decedents with ICD-10 codes A50–A53 listed as contributing causes were included. Age-adjusted mortality rates (AAMRs) were calculated per 100,000 population using the 2000 US Standard Population. Poisson regression was used to estimate annual percent change (APC) for temporal trends and rate ratios (RRs) for demographic comparisons. Eight pre-specified sensitivity analyses were performed, including restriction to the underlying cause of death only and assessment of HIV and COVID-19 co-occurrence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e A total of 1,148 syphilis-related deaths were identified, yielding an overall AAMR of 0.06 per 100,000 (95% CI: 0.06–0.07). No significant temporal trend was identified (APC: −1.24%, p = 0.550). Late-stage syphilis accounted for 51.4% of the deaths. Men had 2.5-fold higher mortality than women (RR: 2.50; 95% CI: 2.20–2.83). Non-Hispanic Black individuals had nearly five-fold higher mortality than non-Hispanic White individuals (RR: 4.81; 95% CI: 4.20–5.50). The South accounted for 50.3% of the deaths. HIV was co-listed in 27.5% of deaths, with a borderline increasing trend (APC: +8.25%; p = 0.047). More than half of the deaths occurred outside the inpatient hospital settings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Syphilis-related mortality remained stable but was concentrated in identifiable high-risk groups and geographies. The predominance of late-stage disease, high HIV co-occurrence, and substantial proportion of deaths in community and long-term care settings collectively indicate persistent failures in early detection and treatment retention. These findings have direct implications for urological practice, public health screening programs, and targeted interventions in underserved populations.\u003c/p\u003e","manuscriptTitle":"Syphilis-related mortality in the United States, 2021–2025: U.S trends, demographic disparities, and implications for urological practice","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-05 05:16:17","doi":"10.21203/rs.3.rs-9520864/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fdf79e70-1f60-4f9f-8564-14c790a320c6","owner":[],"postedDate":"May 5th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-05T05:16:17+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-05 05:16:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9520864","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9520864","identity":"rs-9520864","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}