■梅毒已经引起了数百年的流行,全球梅毒形势依然严峻。浙江省梅毒报告发病率连续多年在法定报告传染病方面居全省首位,为全国之最。本研究试图利用尺度定律理论研究人口规模与不同类型梅毒流行的关系,同时还探讨了影响不同地区梅毒发病的主要驱动因素。
■县级梅毒病例和受影响人群的数据来自中国疾病预防控制信息系统。用比例定律解释了梅毒不同阶段与种群规模之间的比例关系。通过连接点回归检验2016-2022年的发病率趋势。采用模拟与观测指标之间的距离指标(DISO)来评价联合点回归模型的整体性能。此外,采用多变量时间序列模型来确定影响县级梅毒发生的主要驱动因素。小于0.05的P值或置信区间(CI)不包括所有测试的0表示的统计显著性。
■2016年至2022年,浙江省共报告梅毒204719例,包括2人死亡,都是先天性梅毒。潜伏梅毒占梅毒总病例的79.47%。所有类型梅毒的年度变化百分比(APC),包括原发性梅毒,二期梅毒,三级梅毒,先天性梅毒和潜伏梅毒,为-21.70%(p<0.001,95%CI:-26.70至-16.30),-16.80%(p<0.001,95%CI:-20.30至-13.30),-8.70%(p<0.001,95%CI:-11.30至-6.00),-39.00%(p=0.001,95%CI:-49.30至-26.60)和-7.10%(p=0.008,95%CI:-11.20至-2.80),分别。原发性梅毒的综合比例指数,二期梅毒,三级梅毒,基于随机效应模型的先天性梅毒和潜伏梅毒分别为0.95(95%CI:0.88~1.01),1.14(95%CI:1.12至1.16),0.43(95%CI:0.37至0.49),0.0264(95%CI:-0.0047至0.0575)和0.88(95%CI:0.82至0.93),分别。地方性成分的总体平均影响值,各县的时空分量和自回归分量分别为0.24、0.035和0.72。大多数县的自回归分量值大于0.7。最高值排名前10位的县的地方病成分大于0.34。时空分量值大于0.1的两个县分别是西湖景观县和升寺县。2016-2022年各县的地方病成分和自回归成分均呈现明显的季节性变化。
■缩放指数在每种梅毒类型与种群大小之间的关联中既具有时间趋势特征,又具有显着的异质性。原发性梅毒和潜伏梅毒呈线性模式,二期梅毒呈现超线性模式,和三级梅毒表现出亚线性模式。这表明需要进一步预防高危人群中的感染和传播,并提高欠发达地区的诊断准确性。自回归成分和地方性成分是影响梅毒发生的主要驱动因素。必须根据各县疫情的主要驱动模式制定有针对性的防控策略。
Syphilis has caused epidemics for hundreds of years, and the global syphilis situation remains serious. The reported incidence rate of syphilis in Zhejiang Province has ranked first in the province in terms of notifiable infectious diseases for many years and is the highest in China. This study attempts to use the scaling law theory to study the relationship between population size and different types of syphilis epidemics, while also exploring the main driving factors affecting the incidence of syphilis in different regions.
Data on syphilis cases and affected populations at the county level were obtained from the China Disease Control and Prevention Information System. The scaling relationship between different stages of syphilis and population size was explained by scaling law. The trend of the incidence from 2016 to 2022 was tested by the joinpoint regression. The index of distance between indices of simulation and observation (DISO) was applied to evaluate the overall performance of joinpoint regression model. Furthermore, a multivariate time series model was employed to identify the main driving components that affected the occurrence of syphilis at the county level. The p value less than 0.05 or confidence interval (CI) does not include 0 represented statistical significance for all the tests.
From 2016 to 2022, a total of 204,719 cases of syphilis were reported in Zhejiang Province, including 2 deaths, all of which were congenital syphilis. Latent syphilis accounted for 79.47% of total syphilis cases. The annual percent change (APCs) of all types of syphilis, including primary syphilis, secondary syphilis, tertiary syphilis, congenital syphilis and latent syphilis, were - 21.70% (p < 0.001, 95% CI: -26.70 to -16.30), -16.80% (p < 0.001, 95% CI: -20.30 to -13.30), -8.70% (p < 0.001, 95% CI: -11.30 to -6.00), -39.00% (p = 0.001, 95% CI: -49.30 to -26.60) and - 7.10% (p = 0.008, 95% CI: -11.20 to -2.80), respectively. The combined scaling exponents of primary syphilis, secondary syphilis, tertiary syphilis, congenital syphilis and latent syphilis based on the random effects model were 0.95 (95% CI: 0.88 to 1.01), 1.14 (95% CI: 1.12 to 1.16), 0.43 (95% CI: 0.37 to 0.49), 0.0264 (95% CI: -0.0047 to 0.0575) and 0.88 (95% CI: 0.82 to 0.93), respectively. The overall average effect values of the endemic component, spatiotemporal component and autoregressive component for all counties were 0.24, 0.035 and 0.72, respectively. The values of the autoregressive component for most counties were greater than 0.7. The endemic component of the top 10 counties with the highest values was greater than 0.34. Two counties with value of the spatiotemporal component higher than 0.1 were Xihu landscape county and Shengsi county. From 2016 to 2022, the endemic and autoregressive components of each county showed obvious seasonal changes.
The scaling exponent had both temporal trend characteristics and significant heterogeneity in the association between each type of syphilis and population size. Primary syphilis and latent syphilis exhibited a linear pattern, secondary syphilis presented a superlinear pattern, and tertiary syphilis exhibited a sublinear pattern. This suggested that further prevention of infection and transmission among high-risk populations and improvement of diagnostic accuracy in underdeveloped areas is needed. The autoregressive components and the endemic components were the main driving factors that affected the occurrence of syphilis. Targeted prevention and control strategies must be developed based on the main driving modes of the epidemic in each county.