基于三明治空间插值模型估算我国2019年各县(区)暗娼HIV感染率

Estimation of HIV prevalence among female sex workers based on Sandwich model,in-China,2019

目的 估算我国2019年各县(区)暗娼HIV感染率,为评估该人群HIV流行状况及实施精准防控措施提供依据。方法 以2019年141个暗娼监测哨点的HIV感染率为采样数据,以截至2019年底各县(区)现存活经商业性异性性行为感染HIV病例占当地15岁及以上人口比例(传染源因素)和当年县(区)国内生产总值(GDP)(经济因素)作为知识层数据,建立暗娼HIV感染率的三明治空间插值模型,估算2019年全国各县(区)暗娼HIV感染率。结果模型共估出我国98.2%县(区)(2 880/2 933)的暗娼HIV感染率,其中暗娼HIV感染率估算值<0.5%的县(区)占66.6%(1 954/2 933),分布于华东(435个)、华北(385个)、东北(264个)等地区;0.5%~1.0%的县(区)占24.9%(729/2 933),分布于中南(234个)、西南(193个)、华东(172个)等地区;1.0%~2.0%的县(区)占6.1%(180/2 933),主要分布于中南(50个)、西南(17个)、西北(13个)、华东(17个)等地区;≥2.0%的县(区)占0.6%(17/2 933),分布于华东(1个)、西北(1个)、中南(4个)、西南(11个)地区。模型R2为0.469,误差为0.000 4。结论 我国县(区)暗娼HIV感染率处于低流行水平,但其地区差异性大,尤以西南地区暗娼HIV感染率水平较高,应对该人群实施更有针对性的防制措施。

Objective To estimate the HIV prevalence of female sex workers(FSWs) in each county of China in2019 and provide a basis for implementing relevant prevention and control measures.Methods A Sandwich model was proposed to estimate the HIV prevalence among FSWs based on the HIV prevalence of 141 FSWs HSS in 2019 as the data for sampling.The proportion of alive HIV cases infected commercially in the local population aged 15 and over(risk factors) and county/district GDP(economic factors) in 2019 as knowledge stratification factors.Results HIV prevalence among FSWs in 98.2%(2880/2933) counties across China were estimated.The HIV prevalence was less than 0.5% in66.6%(1954/2933) of the counties,mainly distributed in the East(435),North(385),Northeast(264) parts of China.The HIV prevalence is 0.5%-1% in 24.9%(729/2933) of the counties,mainly in South Central(234),Southwest(193),East(172) parts of the country.6.1%(180/2933) of counties had an HIV prevalence of 1%-2%,mainly in South Central(50),Southwest(17),Northwest(13) East(17).The HIV prevalence in 0.6%(17/2933) of the counties exceeded 2%,distributed in East(1),Northwest(1),South Central(4),Southwest(11) parts of the country.The error mean of the model was 0.0004,with the R2of 0.469.Conclusions The HIV prevalence of FSWs in the county/distinct of China is at a low level.However,the regional difference appears significant,especially in the southwest areas where the HIV prevalence is high.More targeted prevention and control measures should be carried out in this population.