Abstract
Background
Syphilis has emerged as a major public health challenge in China and is characterized by increasing incidence rates and shifting epidemiological patterns. Despite national control efforts, latent syphilis dominates case burdens, and older adults have become a high-risk subgroup, highlighting the need for updated prevention strategies.
Methods
We analyzed data from China’s National Notifiable Disease Surveillance System (2005–2020), including 5,899,261 syphilis cases and 994 deaths, to describe incidence, mortality, and stage-specific trends. Joinpoint regression was used to model annual percentage changes (APCs) in incidence/mortality, and descriptive statistics were used to assess age/regional distributions.
Results
Latent syphilis accounted for 64.02% of the total cases, with the incidence increasing rapidly from 2005 to 2010 (APC = 29.99%) before slowing (2010–2020: APC = 8.44%). Individuals aged ≥ 60 years presented the highest burden, with an incidence rate of 46.9224 /100,000 (23.90% of cases) and a mortality rate of 0.0133/100,000 (40.24% of deaths), driven by latent syphilis (80.25% of mortality). Regional disparities were evident, with eastern provinces as endemic hotspots and western regions experiencing rapid growth (e.g., Xizang). Primary/secondary syphilis initially increased but then decreased, whereas tertiary/congenital syphilis remained low but persistent.
Conclusion
Western regions such as Xizang have shown a notable syphilis incidence growth rate, surpassing eastern endemic hotspots and revealing a distinct “reverse gradient”. Dominated by asymptomatic latent infections and marked by the aging population’s vulnerability, China’s syphilis epidemiology demands targeted interventions: universal screening, age-tailored education for older adults, and strengthened western-region surveillance. These measures tackle transmission dynamics, align with global STI elimination goals, and address regional inequities to advance tailored public health strategies.
Keywords: Syphilis epidemiology, Latent syphilis, Elderly, Public health
Introduction
Syphilis, a sexually transmitted infection caused by Treponema pallidum, remains a significant global public health challenge, with an estimated 7.1 million new cases annually, exerting profound impacts on maternal and fetal health, cardiovascular diseases, and neurosyphilis [1]. In China, since the late 20th century, the incidence of syphilis has risen sharply due to demographic changes, urbanization, and evolving sexual behaviors, transforming it from a rare infection into one of the most reported sexually transmitted infections (STIs). Despite national control measures, the disease burden continues to evolve, characterized by an increasing prevalence of latent infection, age-specific disparities, and regional inequalities [2]. Globally, 11 million new syphilis cases occur annually among adults aged 15–49 years, and the disease has reemerged in multiple regions, including North America, Western Europe, China, and Australia [3]. From 2005 to 2020, the annual number of syphilis cases in China tripled, with latent syphilis accounting for 64% of all reported cases (Table 1), highlighting critical gaps in early diagnosis and screening. Primary and secondary syphilis present with distinct symptoms that more readily prompt medical attention, whereas the asymptomatic progression of latent syphilis leads to unrecognized transmission, increasing the risk of vertical transmission and late-stage complications. Moreover, the aging population has emerged as a high-risk subgroup, exceeding all other age groups in both case burden and mortality [4]. These trends challenge traditional STI prevention frameworks, historically focused on younger populations, and underscore the need for age-tailored interventions.
Table 1.
Number of syphilis cases, deaths, incidence rates, and mortality rates in Mainland China, 2005–2020
| Years/Syphilis classification | Syphilis | |||
|---|---|---|---|---|
| Number of cases | Number of deaths | Incidence rate (1/100,000) | Mortality rate (1/100,000) | |
| 2005 | 126,445 | 74 | 9.7274 | 0.0057 |
| 2006 | 167,370 | 86 | 12.8002 | 0.0066 |
| 2007 | 208,784 | 59 | 15.8834 | 0.0045 |
| 2008 | 257,474 | 60 | 19.4866 | 0.0045 |
| 2009 | 306,381 | 63 | 23.0705 | 0.0047 |
| 2010 | 358,534 | 69 | 26.8617 | 0.0052 |
| 2011 | 395,182 | 75 | 29.4712 | 0.0056 |
| 2012 | 410,074 | 79 | 30.4356 | 0.0059 |
| 2013 | 406,772 | 69 | 30.0414 | 0.0051 |
| 2014 | 419,091 | 69 | 30.9254 | 0.0051 |
| 2015 | 433,974 | 58 | 31.8521 | 0.0043 |
| 2016 | 438,199 | 53 | 31.9670 | 0.0039 |
| 2017 | 475,860 | 45 | 34.4867 | 0.0033 |
| 2018 | 494,867 | 39 | 35.6251 | 0.0028 |
| 2019 | 535,819 | 42 | 38.3677 | 0.0030 |
| 2020 | 464,435 | 54 | 33.0831 | 0.0038 |
| Total | 5,899,261 | 994 | 27.3038 | 0.0046 |
In addition, regional disparities pose significant challenges to syphilis control in China. Eastern provinces such as Guangdong and Zhejiang, which are characterized by high population mobility and urbanization, have long been endemic hotspots, whereas western regions such as Tibet and Yunnan are experiencing rapid increases in incidence [5]. This spatial heterogeneity, reflective of evolving social determinants of health and healthcare accessibility gaps, underscores the need for a nuanced understanding of epidemiological patterns to inform decentralized public health strategies. Spatially heterogeneous trends in STI incidence are evident, with historically low-prevalence western regions showing growth that highlights broader health inequities, where resource-rich regions outperform western provinces in STI control. Although post-2012 mortality declined (APC = −7.23%) because of improved penicillin-based treatment access [6], regional variations in healthcare infrastructure threaten sustained progress. Against this backdrop, this study aims to characterize the epidemiological features of syphilis in mainland China from 2005 to 2020, focusing on disease staging, age-specific trends, and regional distribution. Through an analysis of national surveillance data, the study endeavors to (1) describe the temporal dynamics of syphilis incidence and mortality across clinical stages; (2) quantify the disease burden across age groups, with a particular emphasis on emerging risks among older adults; and (3) identify regional differences in disease distribution and trends. These objectives address critical knowledge gaps in China’s syphilis epidemiology, providing evidence for targeted prevention and control measures aligned with global STI elimination goals. While international studies have explored the burden of syphilis in the elderly population [4, 7], this study, which leverages national surveillance data from 2005 to 2020, uniquely reveals the association between the high proportion of latent syphilis (65.52%) and the mortality rate (2.72 per 100,000) in this demographic. Additionally, an intriguing “reverse gradient” phenomenon is revealed, where the incidence growth rate in underdeveloped western areas surpasses that in traditional eastern high-incidence regions. By comprehensively analyzing long time series, all age groups, and disease stages, this study offers a novel perspective on the syphilis epidemic under the dual contexts of population aging and regional economic disparities, advancing the understanding of syphilis epidemiology in China.
Data and methods
Data sources and diagnostic criteria for syphilis
The dataset utilized in this study was obtained from the National Science and Technology Resources Service System (https://www.phsciencedata.cn/Share/ky_sjml.jsp?id=3b00c675-b975-4505-a48f-e086519c7b49). Since the dataset does not include detailed patient-level information, the use of these publicly available data does not necessitate ethical approval. This study adheres to the STROBE guidelines [8]. For syphilis diagnostic criteria, the “Diagnostic Criteria for Syphilis” (WS 273–2007) were applied before July 31, 2018 [9], while the updated criteria (WS 273–2018) were implemented from August 1, 2018 onward [10].
Variable definition
Syphilis Classification: Patients were classified into five stages on the basis of clinical guidelines: primary syphilis, the presence of chancres, or primary lesions. Secondary syphilis: Mucocutaneous manifestations (e.g., rash, condyloma lata). Tertiary syphilis: Late-stage disease (e.g., gummatous, cardiovascular, or neurosyphilis). Congenital syphilis: Transmitted from mother to fetus, diagnosed in infants ≤ 1 year old. Latent syphilis: Asymptomatic infection confirmed by serological testing (e.g., rapid plasma reagin, treponemal antibody tests). Age Groups: Seven categories: 0–9, 10–19, 20–29, 30–39, 40–49, 50–59, and ≥ 60 years old. Geographic Regions: Provinces were grouped into three regions on the basis of socioeconomic and geographical criteria: Eastern Region: 11 provinces/municipalities (e.g., Guangdong, Zhejiang, Jiangsu). Central region: 8 provinces (e.g., Hunan, Anhui, Henan). Western region: 12 provinces/autonomous regions (e.g., Xizang, Yunnan, Gansu).
Statistical analysis
Descriptive statistics: The annual incidence rate (per 100,000 population) and mortality rate (per 100,000 population) were calculated as follows: incidence rate = (number of cases/mid-year population or cumulative population count) × 100,000; mortality rate = (number of deaths/mid-year population or cumulative population count) × 100,000. Age-specific and stage-specific incidences/mortalities were similarly computed (The rate for each age group is calculated as (number of cases or deaths in the group/population of the group) × 100,000). The proportions of cases and deaths were calculated for each stage and age group. Trend analysis: The joinpoint regression program (Joinpoint version 5.4.0, National Cancer Institute) was used to model annual percentage changes (APCs) in incidence and mortality rates. The model identifies optimal joinpoints (change points) and estimates the APC for each segment, with significance defined as P < 0.05. Regional Disparities: Cumulative cases and growth rates were calculated for each province. Provinces were ranked by cumulative incidence and annual growth rate (AGR) to identify hotspots and regions with emerging epidemics. Spatial distribution maps were generated via ArcGIS (version 10.8) to visualize the case concentrations. Other data visualizations were conducted via Origin 2022 software (OriginLab Corp., Northampton, MA, USA).
Results
Reported cases and epidemic trends of syphilis from 2005 to 2020
From 2005 to 2020, a total of 5,899,261 syphilis cases and 994 deaths were reported in mainland China. The annual average incidence rate was 27.3038 per 100,000 people, and the annual average mortality rate was 0.0046 per 100,000 people (Table 1). Joinpoint regression analysis (Fig. 1C-D) showed a significant increase in syphilis incidence from 2005 to 2020: it rose rapidly from 2005 to 2010 with an annual percentage change (APC) of 22.23% (P < 0.05). From 2010 to 2020, the increasing trend of syphilis incidence slowed, with an APC of 2.60% (P < 0.05). The mortality rate of syphilis gradually increased from 2005 to 2012, with an APC of 0.71% (P > 0.05). Conversely, the mortality rate decreased significantly from 2012 to 2020, with an APC of −7.23% (P < 0.05).
Fig. 1.
(A) Composition of syphilis stages, (B) mortality composition by stage, and trends of (C) incidence and (D) mortality of syphilis in Mainland China, 2005–2020
Syphilis stages and epidemiological trends, 2005–2020
From 2005 to 2020, a total of 1,154,087 stage I syphilis cases (146 deaths), 819,055 stage II syphilis cases (51 deaths), 42,412 stage III syphilis cases (40 deaths), 107,504 fetal syphilis cases (151 deaths), and 3,776,203 latent syphilis cases (606 deaths) were reported in mainland China (Table 2). The proportions of syphilis stages were as follows: latent syphilis (64.02%), stage I syphilis (19.56%), stage II syphilis (13.88%), fetal syphilis (1.82%), and stage III syphilis (0.72%) (Fig. 1A). The proportions of mortality across stages were as follows: latent syphilis (60.97%), fetal syphilis (15.19%), stage I syphilis (14.69%), stage II syphilis (5.13%), and stage III syphilis (4.02%) (Fig. 1B). Joinpoint regression analysis (Fig. 2A–E) revealed that the incidence rate of stage I syphilis increased rapidly from 2005 to 2011 (APC = 15.15%; P < 0.05) and declined rapidly from 2011 to 2020 (APC = − 11.90%; P < 0.05). For Stage II syphilis, the incidence rate increased rapidly from 2005 to 2012 (APC = 8.54%; P < 0.05) and declined rapidly from 2012 to 2020 (APC = − 8.17;% P < 0.05). The incidence of stage III syphilis increased rapidly from 2005 to 2011 (APC = 17.36%; P < 0.05) but slowed from 2011 to 2020 (APC = 1.17%; P < 0.05). The fetal syphilis incidence increased rapidly from 2005 to 2011 (APC = 16.13%; P < 0.05) and declined rapidly from 2011 to 2020 (APC = − 18.53%; P < 0.05). The latent syphilis incidence increased rapidly from 2005 to 2010 (APC = 29.99%; P < 0.05) but increased more slowly from 2010 to 2020 (APC = 8.44%; P < 0.05).
Table 2.
Number of cases, deaths, incidence rates, and mortality rates of different stages of syphilis in Mainland China, 2005–2020
| Years/Syphilis classification | Stage I syphilis | Stage II syphilis | Stage III syphilis | Fetal syphilis | latent syphilis | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| Number of cases (Incidence rate 1/100,000) | Number of deaths (Mortality rate 1/100,000) | Number of cases (Incidence rate 1/100,000) | Number of deaths (Mortality rate 1/100,000) | Number of cases (Incidence rate 1/100,000) | Number of deaths (Mortality rate 1/100,000) | Number of cases (Incidence rate 1/100,000) | Number of deaths (Mortality rate 1/100,000) | Number of cases (Incidence rate 1/100,000) | Number of deaths (Mortality rate 1/100,000) | |
| 2005 | 46,296(3.5616) | 16(0.0012) | 34,776(2.6753) | 5(0.0004) | 929(0.0715) | 4(0.0003) | 3968(0.3053) | 34(0.0026) | 40,476(3.1138) | 15(0.0012) |
| 2006 | 55,930(4.2774) | 20(0.0015) | 39,174(2.9960) | 7(0.0005) | 1375(0.1052) | 2(0.0002) | 5892(0.4506) | 29(0.0022) | 64,999(4.9710) | 28(0.0021) |
| 2007 | 65,618(4.9919) | 14(0.0011) | 44,576(3.3912) | 3(0.0002) | 1612(0.1226) | 1(0.0001) | 7553(0.5746) | 13(0.0010) | 89,425(6.8031) | 28(0.0021) |
| 2008 | 78,743(5.9596) | 10(0.0008) | 52,011(3.9364) | 4(0.0003) | 1774(0.1343) | 3(0.0002) | 8494(0.6429) | 12(0.0009) | 116,452(8.8135) | 31(0.0023) |
| 2009 | 90,923(6.8465) | 9(0.0007) | 58,905(4.4356) | 2(0.0002) | 2136(0.1608) | 5(0.0004) | 10,002(0.7532) | 9(0.0007) | 144,415(10.8745) | 38(0.0029) |
| 2010 | 100,730(7.5468) | 13(0.0010) | 61,784(4.6289) | 8(0.0006) | 2610(0.1955) | 2(0.0001) | 11,347(0.8501) | 9(0.0007) | 182,063(13.6403) | 37(0.0028) |
| 2011 | 107,691(8.0312) | 16(0.0012) | 63,985(4.7718) | 6(0.0004) | 2773(0.2068) | 3(0.0002) | 12,042(0.8980) | 5(0.0004) | 208,691(15.5634) | 45(0.0034) |
| 2012 | 106,689(7.9184) | 10(0.0007) | 65,285(4.8454) | 3(0.0002) | 3030(0.2249) | 4(0.0003) | 11,007(0.8169) | 10(0.0007) | 224,063(16.6299) | 52(0.0039) |
| 2013 | 98,128(7.2471) | 8(0.0006) | 63,976(4.7248) | 2(0.0001) | 3113(0.2299) | 5(0.0004) | 8600(0.6351) | 7(0.0005) | 232,955(17.2044) | 47(0.0035) |
| 2014 | 86,592(6.3898) | 7(0.0005) | 62,200(4.5898) | 2(0.0001) | 3287(0.2426) | 1(0.0001) | 8116(0.5989) | 5(0.0004) | 258,896(19.1043) | 54(0.0040) |
| 2015 | 73,539(5.3975) | 5(0.0004) | 56,137(4.1202) | 3(0.0002) | 3107(0.2280) | 1(0.0001) | 6157(0.4519) | 8(0.0006) | 295,034(21.6544) | 41(0.0030) |
| 2016 | 59,446(4.3366) | 6(0.0004) | 48,541(3.5411) | 3(0.0002) | 3275(0.2389) | 1(0.0001) | 4552(0.3321) | 0(0) | 322,385(23.5183) | 43(0.0031) |
| 2017 | 57,123(4.1398) | 3(0.0002) | 46,387(3.3618) | 0(0) | 3151(0.2284) | 3(0.0002) | 3846(0.2787) | 5(0.0004) | 365,353(26.4780) | 34(0.0025) |
| 2018 | 50,536(3.6380) | 3(0.0002) | 44,953(3.2361) | 0(0) | 3401(0.2448) | 1(0.0001) | 2792(0.2010) | 2(0.0001) | 393,185(28.3051) | 33(0.0024) |
| 2019 | 43,653(3.1258) | 3(0.0002) | 42,141(3.0175) | 1(0.0001) | 3626(0.2596) | 1(0.0001) | 1934(0.1385) | 2(0.0001) | 444,465(31.8262) | 35(0.0025) |
| 2020 | 32,450(2.3115) | 3(0.0002) | 34,224(2.4379) | 2(0.0001) | 3213(0.2289) | 3(0.0002) | 1202(0.0856) | 1(0.0001) | 393,346(28.0192) | 45(0.0032) |
| Total | 1,154,087 (5.3415) | 146(0.0007) | 819,055(3.7909) | 51(0.0002) | 42,412(0.1963) | 40(0.0002) | 107,504(0.4976) | 151(0.0007) | 3,776,203 (17.4776) | 606(0.0028) |
Deaths attributed to stage I and latent syphilis should be interpreted cautiously. Stage I syphilis (localized chancre) and latent syphilis (asymptomatic) rarely cause direct mortality; these deaths may be due to unrecorded comorbidities or misattribution. Tertiary syphilis, though clinically linked to mortality, is underrepresented in death counts, possibly due to underdiagnosis
Fig. 2.
Trends in the incidence rates of different stages (A: Stage I syphilis; B: Stage II syphilis; C: Stage III syphilis; D: Fetal syphilis; E: Latent syphilis) of syphilis and join-point regression analysis in Mainland China, 2005–2020
Regional case distribution and epidemic trends of syphilis from 2005 to 2020
From 2005 to 2020, the top ten regions with the highest cumulative number of syphilis cases were Guangdong, Zhejiang, Jiangsu, Sichuan, Fujian, Guangxi, Hunan, Anhui, Xinjiang, and Henan. In contrast, the ten regions with the lowest cumulative cases were Xizang, Qinghai, Ningxia, Tianjin, Hainan, Gansu, Beijing, Jilin, Hebei, and Shanxi (Table 3). Additionally, the ten regions with the highest rates of increase in syphilis cases over this period were Xizang, Yunnan, Hunan, Guizhou, Hebei, Xinjiang, Shanxi, Henan, Hubei, and Neimenggu (Fig. 3A). Conversely, the ten regions with the lowest increase rates were Guangxi, Hainan, Jilin, Heilongjiang, Tianjin, Guangdong, Jiangsu, Fujian, Zhejiang, Beijing, and Shanghai (Fig. 3B). Notably, Xizang experienced a rapid increase in syphilis cases starting in 2012, whereas Guangxi witnessed a steady decline in cases since 2013 (Fig. 3B).
Table 3.
The number of syphilis in Chinese cities from 2005 to 2020
| City/Years | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | Total |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Guangdong | 17,682 | 23,220 | 27,243 | 31,559 | 35,400 | 40,410 | 46,742 | 48,279 | 48,228 | 50,843 | 50,019 | 52,863 | 55,777 | 56,180 | 62,760 | 53,483 | 700,688 |
| Zhejiang | 20,343 | 26,827 | 32,046 | 38,418 | 43,142 | 49,156 | 43,514 | 34,168 | 31,821 | 33,257 | 32,693 | 34,432 | 35,813 | 31,049 | 30,708 | 24,201 | 541,588 |
| Jiangsu | 9236 | 12,408 | 16,498 | 21,321 | 24,641 | 24,684 | 23,635 | 22,938 | 21,700 | 23,917 | 23,594 | 23,688 | 25,019 | 27,256 | 28,054 | 25,309 | 353,898 |
| Sichuan | 5769 | 7015 | 8286 | 9738 | 15,053 | 20,073 | 21,479 | 22,670 | 19,941 | 19,491 | 22,652 | 23,259 | 27,335 | 29,185 | 37,367 | 34,515 | 323,828 |
| Fujian | 8562 | 9898 | 12,594 | 15,731 | 16,489 | 17,676 | 18,433 | 19,927 | 21,651 | 23,447 | 23,963 | 22,461 | 23,932 | 24,358 | 27,241 | 21,635 | 307,998 |
| Guangxi | 12,882 | 18,084 | 21,212 | 25,099 | 30,351 | 37,216 | 40,067 | 27,802 | 12,480 | 9843 | 8211 | 7391 | 6243 | 10,053 | 17,488 | 14,653 | 299,075 |
| Hunan | 2266 | 4283 | 5869 | 7343 | 10,684 | 15,403 | 18,595 | 20,938 | 20,850 | 20,839 | 20,910 | 22,653 | 27,475 | 32,043 | 33,276 | 30,569 | 293,996 |
| Anhui | 3438 | 4390 | 5507 | 6397 | 8302 | 10,188 | 12,234 | 14,382 | 16,182 | 17,944 | 20,800 | 22,819 | 25,963 | 25,577 | 30,422 | 27,248 | 251,793 |
| Xinjiang | 2135 | 3940 | 5806 | 8120 | 10,563 | 10,831 | 15,333 | 19,323 | 21,780 | 21,159 | 24,710 | 21,016 | 22,013 | 23,602 | 21,442 | 16,937 | 248,710 |
| Henan | 2620 | 3614 | 5080 | 6772 | 9669 | 13,560 | 18,431 | 24,257 | 23,736 | 17,964 | 16,075 | 14,638 | 15,209 | 17,361 | 18,279 | 17,503 | 224,768 |
| Liaoning | 3489 | 4669 | 6182 | 7579 | 9273 | 12,509 | 15,920 | 17,243 | 19,437 | 19,594 | 17,752 | 16,393 | 16,733 | 16,007 | 15,730 | 13,456 | 211,966 |
| Shanghai | 8688 | 10,657 | 11,986 | 14,228 | 15,103 | 14,680 | 14,137 | 13,864 | 13,260 | 13,370 | 13,616 | 13,783 | 13,389 | 12,002 | 12,216 | 9264 | 204,243 |
| Chongqing | 3397 | 4121 | 5489 | 7562 | 7206 | 8457 | 9708 | 10,708 | 11,364 | 11,992 | 14,522 | 16,550 | 19,306 | 18,243 | 20,158 | 17,571 | 186,354 |
| Shandong | 2161 | 2352 | 2873 | 3971 | 5463 | 6536 | 7643 | 10,657 | 12,792 | 14,243 | 14,680 | 15,305 | 17,806 | 18,923 | 20,501 | 17,691 | 173,597 |
| Yunnan | 1105 | 1659 | 2285 | 3072 | 4279 | 5003 | 6023 | 8666 | 9542 | 12,976 | 15,563 | 17,051 | 16,833 | 16,651 | 19,393 | 18,312 | 158,413 |
| Jiangxi | 2632 | 3271 | 3827 | 5021 | 5408 | 5728 | 6377 | 7077 | 8706 | 9882 | 11,406 | 13,105 | 16,171 | 17,385 | 18,693 | 15,579 | 150,268 |
| Hubei | 1769 | 2652 | 3510 | 6249 | 7908 | 9218 | 9319 | 9452 | 9408 | 10,368 | 12,024 | 12,678 | 13,724 | 15,204 | 14,658 | 11,026 | 149,167 |
| Guizhou | 1081 | 1377 | 2057 | 2900 | 4640 | 5991 | 6225 | 7761 | 8394 | 9632 | 11,356 | 10,718 | 13,151 | 15,095 | 17,583 | 19,501 | 137,462 |
| Shanxi | 2140 | 3085 | 4243 | 4949 | 5950 | 6889 | 8112 | 10,367 | 10,158 | 10,231 | 9813 | 9270 | 11,028 | 12,360 | 13,540 | 11,569 | 133,704 |
| Heilongjiang | 2716 | 3592 | 4792 | 5989 | 7036 | 7910 | 8787 | 9321 | 9836 | 9954 | 9703 | 9265 | 9146 | 8811 | 8601 | 5874 | 121,333 |
| Neimenggu | 1426 | 2323 | 3139 | 3846 | 4442 | 5856 | 7123 | 9011 | 10,791 | 11,314 | 10,873 | 9572 | 10,546 | 11,153 | 10,160 | 7824 | 119,399 |
| Shanxi | 1088 | 1525 | 1993 | 2578 | 3619 | 4617 | 5571 | 6917 | 7543 | 8548 | 9404 | 9896 | 10,682 | 10,799 | 10,642 | 9917 | 105,339 |
| Hebei | 819 | 1073 | 1316 | 1722 | 2251 | 3214 | 4612 | 6207 | 7432 | 8508 | 9966 | 9561 | 10,060 | 10,810 | 10,804 | 9040 | 97,395 |
| Jilin | 1682 | 2262 | 3471 | 4584 | 4813 | 5679 | 8082 | 7456 | 7058 | 6266 | 5874 | 5054 | 4429 | 4697 | 4526 | 3373 | 79,306 |
| Beijing | 2714 | 3581 | 3973 | 3786 | 4002 | 4382 | 4671 | 4438 | 5137 | 5646 | 5310 | 4975 | 5193 | 5557 | 5084 | 3648 | 72,097 |
| Gansu | 1251 | 1375 | 1734 | 2156 | 3003 | 4039 | 4954 | 4616 | 3517 | 3650 | 4348 | 4837 | 5876 | 6504 | 7177 | 6535 | 65,572 |
| Hainan | 1121 | 1277 | 1685 | 1712 | 2060 | 2382 | 2415 | 3080 | 3499 | 3445 | 4390 | 4617 | 5447 | 5772 | 6809 | 6619 | 56,330 |
| Tianjin | 1053 | 1689 | 2334 | 3211 | 3186 | 2995 | 2951 | 3129 | 3345 | 3186 | 2938 | 2568 | 3164 | 2857 | 2879 | 2650 | 44,135 |
| Ningxia | 465 | 569 | 848 | 1007 | 1094 | 1478 | 2264 | 2716 | 3565 | 3531 | 3254 | 3787 | 3710 | 3632 | 3527 | 2750 | 38,197 |
| Qinghai | 694 | 567 | 862 | 814 | 1310 | 1553 | 1618 | 2482 | 3150 | 3342 | 2489 | 2852 | 3381 | 3895 | 4351 | 4551 | 37,911 |
| Xizang | 21 | 15 | 44 | 40 | 41 | 221 | 207 | 222 | 469 | 709 | 1066 | 1142 | 1306 | 1846 | 1750 | 1632 | 10,731 |
| Total | 126,445 | 167,370 | 208,784 | 257,474 | 306,381 | 358,534 | 395,182 | 410,074 | 406,772 | 419,091 | 433,974 | 438,199 | 475,860 | 494,867 | 535,819 | 464,435 | 5,899,261 |
Fig. 3.
The growth of syphilis cases in China: (A) Top10 High-Growth and (B) Low-Growth Cities and (C) the Spatial Distribution of Syphilis from 2005 to 2020
Staged cases and epidemic trends of syphilis in the region from 2005 to 2020
The regional distribution and epidemic trends of staged syphilis cases from 2005 to 2020 are illustrated in Fig. 3C. Geographically, syphilis cases were predominantly concentrated in the eastern and central regions (within the longitudinal range of 110°E–125°E and latitudinal range of 25°N–40°N), whereas the western region (within the longitudinal range of 80°E–100°E) presented relatively few cases within the same latitudinal range. Over time, the overall spatial distribution pattern remained consistent across years, with the eastern and central regions consistently being the areas with the highest concentration of syphilis cases. However, certain changes were observed in specific years (C10 - C16), particularly in the central and eastern regions, where the proportion of latent syphilis cases gradually increased, whereas the proportions of cases in other stages decreased. Furthermore, the number of syphilis cases in the western region has increased over time, with latent syphilis being the predominant type.
Age distribution of reported syphilis cases, 2005–2020
The age distribution of syphilis patients reported in mainland China from 2005 to 2020 is shown in Table 4. Specifically, the overall age composition of incident cases was as follows: 0–9 years (2.02%), 10–19 years (2.61%), 50–59 years (13.48%), 40–49 years (17.17%), 30–39 years (19.78%), 20–29 years (21.04%), and 60 years and above (23.39%). The overall age composition of the syphilis mortality patients was as follows: 10–19 years (0.10%), 20–29 years (4.73%), 30–39 years (10.66%), 40–49 years (12.78%), 50–59 years (15.29%), 0–9 years (16.20%), and 60 years and above (40.24%). The incidence rates of syphilis, listed in ascending order, were as follows: 0–9 years (4.7119), 10–19 years (5.4048), 40–49 years (28.1233), 50–59 years (28.7570), 30–39 years (34.5093), 20–29 years (35.7148), and 60 years and above (46.9224). The mortality rates of syphilis, listed in ascending order from lowest to highest, were as follows: 10–19 years (0.0000), 20–29 years (0.0014), 30–39 years (0.0031), 40–49 years (0.0035), 50–59 years (0.0055), 0–9 years (0.0064), and 60 years and above (0.0133).The incident cases, mortality cases, incidence rates, and mortality rates were the highest among those aged 60 years and above.
Table 4.
Age distribution of syphilis cases, deaths, incidence rates, and mortality rates in Mainland China, 2005–2020
| Age | cumulative population count(Composition ratio/%) | Syphilis | |||
|---|---|---|---|---|---|
| Number of cases(Composition ratio/%) | Number of deaths(Composition ratio/%) | Incidence rate (1/100,000) | Mortality rate (1/100,000) | ||
| 0–9 years old | 2,531,253,076 (11.72%) | 119,270 (2.02%) | 161 (16.20%) | 4.7119 | 0.0064 |
| 10–19 years old | 2,846,146,520 (13.17%) | 153,828 (2.61%) | 1 (0.10%) | 5.4048 | 0.0000 |
| 20–29 years old | 3,476,106,857 (16.09%) | 1,241,485 (21.04%) | 47 (4.73%) | 35.7148 | 0.0014 |
| 30–39 years old | 3,381,457,464 (15.65%) | 1,166,918 (19.78%) | 106 (10.66%) | 34.5093 | 0.0031 |
| 40–49 years old | 3,601,298,135 (16.67%) | 1,012,804 (17.17%) | 127 (12.78%) | 28.1233 | 0.0035 |
| 50–59 years old | 2,765,546,256 (12.80%) | 795,288 (13.48%) | 152 (15.29%) | 28.7570 | 0.0055 |
| 60 years old and above | 3,004,193,320 (13.90%) | 1,409,640 (23.90%) | 400 (40.24%) | 46.9224 | 0.0133 |
| Unknown | - | 28 (0.00%) | 0 (100%) | - | - |
| Total | 21,606,001,628 (100%) | 5,899,261 (100%) | 994 (100%) | 27.3038 | 0.0046 |
Classification of syphilis in reported cases aged 60 years and above, 2005–2020
From 2005 to 2020, a total of 1,409,640 syphilis cases (23.90%) and 400 deaths (40.24%) were reported in individuals aged 60 years and above in mainland China, with an incidence rate of 46.9224 per 100,000 people and a mortality rate of 0.0133 per 100,000 people (Table 4). Joinpoint regression analysis (Fig. 4A–B) revealed that the incidence rate of syphilis in those aged 60 years and above significantly increased from 2005 to 2020. Specifically, the incidence rate rose rapidly from 2005 to 2010 (APC = 30.15%, P < 0.05), and the increasing trend weakened from 2010 to 2020 (APC = 5.14%, P < 0.05). The mortality rate of syphilis increased slowly from 2005 to 2011 (APC = 7.04%, P < 0.05) but decreased rapidly from 2014 to 2020 (APC = − 8.68%, P < 0.05).
Fig. 4.
Distribution of Syphilis Cases and Deaths by Age Group, Trends in Incidence and Mortality Rates of Syphilis and Latent Syphilis in Individuals Aged 60 Years and Above in Mainland China, 2005–2020 Note: A: Trend of syphilis incidence rate in individuals aged 60 years and above; B: Trend of syphilis mortality rate in individuals aged 60 years and above; C: Composition of syphilis stages in individuals aged 60 years and above; D: Composition of mortality syphilis stages in individuals aged 60 years and above; E: Trend of latent syphilis incidence rate in individuals aged 60 years and above; F: Trend of latent syphilis mortality rate in individuals aged 60 years and above
The classification of syphilis in individuals aged 60 years and above is shown in Table 5. There were 189,610 stage I syphilis cases (57 deaths), with an incidence rate of 6.3115 per 100,000 population and a mortality rate of 0.0019 per 100,000 population; 88,735 stage II syphilis cases (15 deaths), with an incidence rate of 2.9537 per 100,000 population and a mortality rate of 0.0005 per 100,000 population; 14,007 stage III syphilis cases (7 deaths), with an incidence rate of 0.4662 per 100,000 population and a mortality rate of 0.0002 per 100,000 population; 351 fetal syphilis cases (0 deaths), with an incidence rate of 0.0117 per 100,000 population and a mortality rate of 0.0000 per 100,000 population; and 1,116,937 latent syphilis cases (321 deaths), with an incidence rate of 37.1793 per 100,000 population and a mortality rate of 0.0107 per 100,000 population. Among these cases, the incidence (79.24%) and mortality cases (80.25%) of latent syphilis in individuals aged 60 years and older were significantly higher compared to those in other stages of syphilis. (Fig. 4C-D). Joinpoint regression analysis (Fig. 4E–F) revealed that the incidence rate of latent syphilis in individuals aged 60 years and above increased rapidly from 2005 to 2020 (APC = 9.63%, P < 0.05). The mortality rate of latent syphilis increased slowly from 2005 to 2014 (APC = 5.42%, P < 0.05) and decreased rapidly from 2014 to 2020 (APC = − 11.17%, P < 0.05).
Table 5.
Number of Cases, Deaths, incidence rate, and mortality rate of syphilis classification in individuals aged 60 years and above in Mainland China, 2005–2020
| Years/Syphilis classification | Stage I syphilis | Stage II syphilis | Stage III syphilis | Fetal syphilis | Latent syphilis | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| Number of cases (Incidence rate 1/100,000) | Number of deaths (Mortality rate 1/100,000) | Number of cases (Incidence rate 1/100,000) | Number of deaths (Mortality rate 1/100,000) | Number of cases (Incidence rate 1/100,000) | Number of deaths (Mortality rate 1/100,000) | Number of cases (Incidence rate 1/100,000) | Number of deaths (Mortality rate 1/100,000) | Number of cases (Incidence rate 1/100,000) | Number of deaths (Mortality rate 1/100,000) | |
| 2005 | 4193(2.8914) | 7(0.0048) | 2428(1.6743) | 0(0.0000) | 276(0.1903) | 1(0.0007) | 15(0.0103) | 0(0.0000) | 7068(4.8739) | 11(0.0076) |
| 2006 | 5698(3.8549) | 4(0.0027) | 2974(2.0120) | 1(0.0007) | 395(0.2672) | 0(0.0000) | 17(0.0115) | 0(0.0000) | 12,388(8.3809) | 15(0.0101) |
| 2007 | 7411(4.9074) | 5(0.0033) | 3511(2.3249) | 3(0.0020) | 494(0.3271) | 0(0.0000) | 32(0.0212) | 0(0.0000) | 18,586(12.3072) | 16(0.0106) |
| 2008 | 9574(6.1803) | 4(0.0026) | 4274(2.7590) | 2(0.0013) | 503(0.3247) | 0(0.0000) | 26(0.0168) | 0(0.0000) | 25,188(16.2597) | 12(0.0077) |
| 2009 | 12,218(7.6867) | 6(0.0038) | 5247(3.3011) | 2(0.0013) | 650(0.4089) | 3(0.0019) | 28(0.0176) | 0(0.0000) | 34,436(21.6648) | 17(0.0107) |
| 2010 | 14,578(8.8752) | 5(0.0030) | 5678(3.4568) | 3(0.0018) | 831(0.5059) | 0(0.0000) | 34(0.0207) | 0(0.0000) | 44,809(27.2800) | 24(0.0146) |
| 2011 | 15,853(8.9908) | 7(0.0040) | 5839(3.3115) | 1(0.0006) | 898(0.5093) | 1(0.0006) | 24(0.0136) | 0(0.0000) | 51,448(29.1778) | 23(0.0130) |
| 2012 | 17,811(9.7060) | 3(0.0016) | 6391(3.4827) | 1(0.0005) | 1016(0.5537) | 0(0.0000) | 26(0.0142) | 0(0.0000) | 59,259(32.2927) | 22(0.0120) |
| 2013 | 17,746(9.6227) | 3(0.0016) | 6831(3.7041) | 1(0.0005) | 1043(0.5656) | 1(0.0005) | 27(0.0146) | 0(0.0000) | 62,745(34.0231) | 25(0.0136) |
| 2014 | 15,964(8.2550) | 2(0.0010) | 7108(3.6756) | 0(0.0000) | 1132(0.5854) | 0(0.0000) | 23(0.0119) | 0(0.0000) | 72,691(37.5887) | 33(0.0171) |
| 2015 | 14,114(7.2530) | 3(0.0015) | 7159(3.6789) | 0(0.0000) | 1033(0.5308) | 0(0.0000) | 26(0.0134) | 0(0.0000) | 87,393(44.9100) | 26(0.0134) |
| 2016 | 12,379(5.8704) | 1(0.0005) | 6821(3.2347) | 1(0.0005) | 1117(0.5297) | 0(0.0000) | 28(0.0133) | 0(0.0000) | 99,422(47.1481) | 22(0.0104) |
| 2017 | 12,641(5.9401) | 2(0.0009) | 6741(3.1676) | 0(0.0000) | 1070(0.5028) | 0(0.0000) | 16(0.0075) | 0(0.0000) | 118,329(55.6033) | 19(0.0089) |
| 2018 | 11,901(5.3049) | 2(0.0009) | 6873(3.0637) | 0(0.0000) | 1231(0.5487) | 0(0.0000) | 17(0.0076) | 0(0.0000) | 131,520(58.6257) | 15(0.0067) |
| 2019 | 10,223(4.1310) | 0(0.0000) | 6294(2.5434) | 0(0.0000) | 1273(0.5144) | 0(0.0000) | 8(0.0032) | 0(0.0000) | 155,410(62.7998) | 21(0.0085) |
| 2020 | 7306(2.8706) | 3(0.0012) | 4566(1.7940) | 0(0.0000) | 1045(0.4106) | 1(0.0004) | 4(0.0016) | 0(0.0000) | 136,245(53.5319) | 20(0.0079) |
| Total | 189,610(6.3115) | 57(0.0019) | 88,735(2.9537) | 15(0.0005) | 14,007(0.4662) | 7(0.0002) | 351(0.0117) | 0(0.0000) | 1,116,937(37.1793) | 321(0.0107) |
The 57 deaths from stage I syphilis and 321 deaths from latent syphilis in this age group are unlikely to be directly caused by these stages. Older adults with multiple comorbidities may have died from unrelated conditions, with syphilis detected incidentally
Discussion
This study examined the epidemiological landscape of syphilis in mainland China from 2005 to 2020, highlighting a continuously increasing incidence (average annual incidence: 27.13 per 100,000) and a shift toward the dominance of latent syphilis (comprising 64.02% of total cases) (Table 1; Fig. 1A). These findings align with global trends where asymptomatic latent syphilis drives unrecognized transmission, underscoring the critical role of early screening in breaking transmission chains [11]. The rapid increase in latent syphilis incidence from 2005 to 2010 (APC = 29.99%) reflects gaps in routine screening, especially in nonclinical settings, where undiagnosed cases can transmit to sexual partners and, in congenital syphilis, to fetuses. Stage-specific trends revealed divergent patterns: primary and secondary syphilis, which present with symptomatic manifestations conducive to early intervention, first increased but then declined (APC = 15.15% and 8.54% for 2005–2011/2012, respectively), likely influenced by strengthened case management and sex education campaigns. In contrast, tertiary syphilis, although rare (0.72% of cases), has shown a sustained low-level increase, highlighting the consequences of delayed diagnosis and treatment [12]. These findings mirror observations in low- and middle-income countries, where inadequate healthcare access allows progression to late stages. A paradigm shift in age-specific burden emerged, particularly among older adults.The most striking demographic change was the disproportionate burden on individuals aged ≥ 60 years, who accounted for 13.90% of cases but 40.24% of deaths, with an incidence rate (46.9224 per 100,000) higher than that of other age groups (Table 4). This subgroup also had the highest mortality rate (0.0133 per 100,000), which was driven primarily by latent syphilis (80.25% mortality composition), reflecting age-related immunosenescence and delayed manifestation of complications [13]. The rapid growth in this population from 2005 to 2020 (APC = 9.63%, P < 0.05) suggests evolving risk behaviors, including increased sexual activity among older adults and reduced stigma in seeking sexual health services [14, 15]. These findings align with global reports of syphilis resurgence linked to population aging [7, 14], emphasizing the need for age-tailored interventions. Due to the absence of standardized population data and the application of revised diagnostic criteria, the data in this study could not be standardized. Nevertheless, segmented Joinpoint regression analysis (2005–2010 vs. 2010–2020) revealed that the growth rate of the crude incidence rate declined from 22.23% to 2.60% (P < 0.05; see Sect. 3.1). This decline aligns with the observed increase in the proportion of individuals aged over 60 years, which rose from 13.26% to 18.70% (estimated based on the 2010 and 2020 censuses), suggesting that population aging has influenced the crude incidence rate. However, the reduced growth rate also indicates the effectiveness of disease control measures. (2) Analysis of the key population (≥ 60 years old): The crude incidence rate among individuals aged 60 years or older increased from 9.6403 per 100,000 in 2005 to 58.6087 per 100,000 in 2020 (Fig. 4). This growth rate was significantly higher than that of the overall population (33.0831 per 100,000), and latent syphilis accounted for 79.24% of cases within this group (Fig. 4). These findings suggest that age - related risk factors are independent of broader demographic changes. Unlike Western studies focusing on young adults, this study highlights that elderly Chinese (≥ 60 years) account for 40.24% of syphilis deaths, with latent syphilis as the primary cause (80.25%), indicating unique epidemiological characteristics in aging populations.
Regional disparities in syphilis incidence are also evident [5]. Geographically, cases clustered in eastern provinces (e.g., Guangdong, Zhejiang) may be associated with higher population mobility, urbanization, and socioeconomic activity. Notably, western regions like Tibet exhibited rapid incidence growth (Fig. 3A), a pattern that may reflect broader health inequities—resource-rich regions have historically shown better STI control outcomes, as supported by studies linking healthcare access to syphilis prevalence [16]. This ecological association requires confirmation through individual-level studies to disentangle causality. While the post-2012 decline in mortality (APC = −7.23%) reflects improved access to penicillin-based treatments [6], the sustained progress is challenged by regional variations in healthcare infrastructure. The rapid incidence growth in western provinces (e.g., Tibet, Yunnan) stems from a combination of factors: population mobility is a potential driver, but local social dynamics—including limited sexual health education and cultural stigma around STI diagnosis—also interact with healthcare access barriers to exacerbate transmission [16]. For instance, western counties often lack standardized STI clinics, potentially leading to underdiagnosis of latent infections and sustained transmission. These associations are inferred from ecological data and require individual-level validation. Concurrently, imbalanced allocation of medical resources exacerbates this issue; in some western counties, the absence of standardized STI diagnosis and treatment institutions leads to high rates of missed latent infections, facilitating further transmission [16]. Additionally, tourism-driven temporary population aggregation creates localized transmission hotspots, yet the existing monitoring system lacks adequate capacity to track floating populations, undermining effective intervention strategies. These converging factors highlight the need for context-specific interventions that address both structural inequities and regional epidemiological dynamics. Importantly, this study did not incorporate stratified analyses based on sex, occupation, or socioeconomic status (e.g., income level and educational attainment), which might introduce limitations in comprehending the driving factors of syphilis epidemics. For example, disparities may exist in the risk of syphilis transmission and clinical manifestations between males and females. Additionally, occupational distribution (e.g., sex workers, long-distance transportation professionals) and socioeconomic status could indirectly influence the incidence rate by shaping sexual behavior patterns and access to healthcare services [17–19]. Moreover, the study lacked detailed data on transmission networks (e.g., dynamics of same-sex sexual behavior, commercial sexual activity) and antibiotic resistance patterns, thereby restricting the development of precise intervention strategies. Notably, the syphilis infection rate among men who have sex with men (MSM) could be considerably higher than that in the general population. The emergence of penicillin-resistant strains might also impact the choice of treatment regimens [20, 21]. Future research could enhance understanding by integrating national census data, specialized epidemiological investigations, or pathogen genomic sequencing to provide a more comprehensive understanding of the social and ecological mechanisms underlying syphilis epidemics.
Our study suggests a three-pronged approach for targeted STI prevention and control while also acknowledging the challenges that may impede implementation. First, universal screening with population-specific prioritization is crucial. Given the prevalence of latent syphilis, integrating serological testing into routine healthcare visits, particularly for older adults, pregnant individuals, and high-risk groups such as men who have sex with men, is essential. A Shanghai study showed that syphilis screening in geriatric clinics increased the detection rate by 37%, underscoring the effectiveness of nonstigmatizing, elder-friendly services [22]. However, implementing this strategy in western regions may face resource constraints, with primary medical institutions potentially suffering from shortages of syphilis test reagents and professional staff. To mitigate this, promoting resource flow from the eastern region through “medical alliance” models and leveraging telemedicine to enhance diagnostic capabilities are recommended. Second, age-tailored education and service delivery should be emphasized. For adults over 60 years of age, campaigns to dispel misconceptions about syphilis and encourage regular sexual health checks are vital. For younger adults aged 20–39, who account for 42% of cases, promoting condom use and harm reduction services remains a priority [23]. However, screening the elderly population may be hindered by the psychological barrier of “sexual shame.” Community health education, such as integrating relevant content into senior university courses and utilizing community grid workers for promotion, can help overcome this resistance. Third, decentralized surveillance and adaptive resource allocation are necessary. Strengthening laboratory capacities in western regions such as Tibet and Yunnan and implementing real-time epidemic forecasting can address regional disparities. Prioritizing latent syphilis in national STI elimination plans, as advocated by the World Health Organization [24], requires cross-sectoral collaboration. Additionally, a significant challenge is the lack of national syphilis drug resistance data. Establishing a multicenter drug resistance monitoring network and dynamically adjusting treatment plans [25, 26] are imperative steps to ensure the long-term effectiveness of interventions. Overall, implementing these prevention and control strategies necessitates proactive measures to overcome resource, cultural, and monitoring-related challenges, underscoring the need for a comprehensive, coordinated approach across sectors. While this study provides robust temporal and demographic insights, it is limited by the absence of stratified data on syphilis incidence by sex, occupation, and socioeconomic factors, which precludes a comprehensive analysis of the relationship between syphilis incidence and economic development. Additionally, detailed information on transmission networks (e.g., heterosexual vs. men who have sex with men) and antibiotic resistance patterns—both critical for designing precision public health interventions—is unavailable. Furthermore, although joinpoint regression analysis was employed to examine the incidence trend, potential confounding factors such as population aging and the uneven distribution of medical resources were not adequately controlled. For example, the rapid increase in the incidence rate observed in the western region may partly reflect population mobility and improvements in diagnostic capabilities rather than true epidemiological changes. To disentangle independent influencing factors more accurately, future studies should consider incorporating relevant covariates, such as socioeconomic variables and geographic accessibility to healthcare, into advanced regression models, such as negative binomial regression or spatial autoregressive models [27]. Future research should explore the role of population aging in disease ecology and assess the cost-effectiveness of screening algorithms for older populations. Continued data collection and analysis of additional factors influencing the incidence of syphilis will optimize future prevention and control strategies.
Study limitations
This study exhibits notable limitations in the statistical reporting of syphilis-related mortality, particularly in the attribution of deaths across disease stages, which significantly deviates from clinical reality. Primary syphilis is predominantly characterized by localized chancres without systemic involvement, and direct mortality is exceedingly rare. Nevertheless, 146 deaths—including 57 among individuals aged 60 years and older—were attributed to this stage, potentially due to unrecorded comorbidities (e.g., cardiovascular events or secondary infections) or misclassification. In many cases, syphilis may have been incidentally detected rather than being the actual cause of death. Latent syphilis, being asymptomatic, does not directly lead to mortality unless it progresses to tertiary syphilis, a process that typically requires more than ten years and is often underdiagnosed. The reported 606 deaths—321 of which occurred in adults aged 60 and above—are more likely attributable to undiagnosed progression to tertiary disease or coincidental comorbid conditions. Although tertiary syphilis can result in irreversible damage to the nervous and cardiovascular systems and should therefore be most strongly associated with mortality, only 40 deaths—including 7 in individuals aged 60 and above—have been documented. This underreporting may stem from nonspecific clinical presentations, prolonged incubation periods, and incomplete documentation of late-stage syphilis in death certificates. To address these challenges, the key solution lies in improving data accuracy through enhanced data collection, standardized diagnostic criteria, and systematic cause-of-death attribution. First, death registration forms should be refined to include specific items such as “basis for syphilis diagnosis” (e.g., serological test results and clinical manifestations) and “details of comorbidities” to prevent incidental findings from being erroneously recorded as primary causes of death. Second, a standardized diagnostic pathway for syphilis staging should be established, with unified guidelines for diagnosing tertiary syphilis incorporating serological testing, imaging findings, and patient history to reduce underdiagnosis. Third, the attribution of syphilis-related deaths should be standardized by adopting the ICD-10 framework, implementing a hierarchical recording system of “underlying cause of death – contributing cause of death.” Specifically, tertiary syphilis should be listed as the underlying cause only when it directly results in organ failure, thereby distinguishing between true causality and incidental comorbidity.
The primary limitation of this study is the absence of gender-stratified analysis. Owing to incomplete documentation of gender information in national surveillance datasets, the influence of gender on syphilis prevalence could not be evaluated. This gap may obscure critical transmission patterns, such as clusters of infection among men who engage in same-sex sexual activity or the risk of vertical transmission among women. Future research should incorporate comprehensive gender data to better identify high-risk subpopulations and refine targeted intervention strategies [20]– [21, 25]– [26].
This study utilizes data sourced from the national legal infectious disease surveillance system. Despite its nationwide coverage, several limitations should be acknowledged. For example, underreporting and revisions to diagnostic criteria (particularly those occurring in 2018) may compromise the consistency and comparability of the data. To address these concerns, future studies could estimate the underreporting rate via field epidemiological investigations and perform sensitivity analyses to assess the influence of data quality on the findings [28].
Furthermore, age standardization was not performed in this study, primarily due to limitations in accessing population data stratified by age group. Nevertheless, key subgroup analyses (e.g., individuals aged 60 years and older) and segmented trend tests still revealed a significant association between syphilis prevalence and aging. Future studies could enhance methodological rigor by incorporating national census data—such as age-specific population data from the 2020 Seventh National Census—to more accurately distinguish the effects of population structure from those of disease transmission.
This study’s ecological design limits causal inference between regional trends and socioeconomic factors (e.g., healthcare access, urbanization)—with observations of western regions’ rapid growth reflecting population-level associations rather than individual-level causality and thus necessitating future cohort studies to disentangle these relationships—and it also used administrative region data without correcting for migration, which may overestimate incidence in economically developed eastern areas.
Conclusion
From 2005 to 2020, syphilis in China emerged as a complex public health challenge, marked by asymptomatic latent infections, an aging high-risk population, and persistent regional disparities. These trends highlight the necessity of targeted interventions: integrating syphilis screening into primary care services, tailoring age-specific prevention strategies, and strengthening surveillance in underserved western regions. In alignment with the World Health Organization’s global strategy for eliminating sexually transmitted infections, such evidence-based approaches, coupled with sustained investment in sexual health infrastructure, can effectively reduce syphilis incidence and mortality. This study makes two significant contributions to the field. First, the elderly population (≥ 60 years old) has become the core group of syphilis-related deaths, with latent syphilis as the primary cause. This finding diverges from those of Western studies [7], which have focused primarily on the burden among young and middle-aged populations, thereby underscoring the urgency of prioritizing asymptomatic screening for elderly individuals in China. Second, this study first reports the “regional transfer” of syphilis incidence from east to west in China, providing a scientific basis for resource allocation strategies. Such as Tibet, exceeded that in eastern provinces after 2010. This discovery enriches the spatial dynamic theory of syphilis epidemics and provides a scientific basis for optimizing cross-regional resource allocation. Collectively, these findings deepen the understanding of the epidemiological characteristics of syphilis, offering valuable insights for countries facing similar challenges of population aging and unbalanced regional development. It is important to note that the syphilis-related mortality data in this study should be interpreted with caution. Stage I and latent syphilis are not clinically associated with direct mortality, and their linked deaths may reflect confounding factors or misclassification. Tertiary syphilis, while more plausibly associated with mortality, was underrepresented in death counts, likely due to diagnostic gaps.
Acknowledgements
We thank the Data Center of China Public Health Science for providing the resources used in this study.
Authors’ contributions
HB and ZS designed the study, collected the data, and wrote the manuscript. YQ, JG, RC and XZ analyzed the data and helped draft the manuscript. XL, HZ and LW contributed to the literature review and revised the manuscript for important intellectual content. All authors provided final approval for the submitted version of the manuscript.
Funding
This study was supported by the Natural Science Foundation of China (Grant No. 82171863), Special Funds for Central Government to Guide Local Scientific and Technological Development (2025ZY010), and the Innovation Platform Program of Qinghai Province (2021-ZJ-T02).
Data availability
The raw data analysed in this study were obtained from the China Public Health Science Data Center (URL: https://www.phsciencedata.cn/Share/ky_sjml.jsp?id=3b00c675-b975-4505-a48f-e086519c7b49). For access to the raw data used in this study, please contact the following personnel: Yajun Qiao, E-mail: qiaoyajun@nwipb.cas.cn; Hongtao Bi, E-mail: bihongtao@hotmail.com. All data supporting the findings of this study are available upon reasonable request to the above-mentioned contacts.
Declarations
Ethics aprroval and consent to participate
Since the dataset does not include detailed patient-level information, the use of these publicly available data does not necessitate ethical approval.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Yajun Qiao and Juan Guo contributed equally to this work.
Contributor Information
Zhongshu Shan, Email: zhongshu0320@163.com.
Hongtao Bi, Email: bihongtao@hotmail.com.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The raw data analysed in this study were obtained from the China Public Health Science Data Center (URL: https://www.phsciencedata.cn/Share/ky_sjml.jsp?id=3b00c675-b975-4505-a48f-e086519c7b49). For access to the raw data used in this study, please contact the following personnel: Yajun Qiao, E-mail: qiaoyajun@nwipb.cas.cn; Hongtao Bi, E-mail: bihongtao@hotmail.com. All data supporting the findings of this study are available upon reasonable request to the above-mentioned contacts.