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The diagnosis of paucibacillary (PB) leprosy often possesses a diagnostic challenge, especially for pure neuritic and lesser skin lesions with the zero bacillary load, requiring a sensitive and accurate diagnostic tool. We have included 300 clinically diagnosed new leprosy cases (comprising 98 PB cases) and analyzed the sensitivity and specificity of PB leprosy cases by nested PCR with folP, gyrA, rpoB, RLEP, and 16SrRNA and Enzyme-linked Immunospot Assay test (ELISPOT) with MMPII, NDO-BSA, and LID-1 antigens by detecting interferon gamma (IFN-γ) release. The overall positivity rates of genes tested in 300 clinical specimens were identified as 55% of 16SrRNA, 59% of RLEP, 59.3% of folP, 57.3% of rpoB, 61% of gyrA while 90% of nested folP, 92.6% of nested rpoB, and 95% of nested gyrA, and 285 (95%) of at least one gene positive cases. For PB specimens, 95% PCR positivity was achieved by three tested genes in nested PCR. The data obtained from ELISPOT for three antigens were analyzed for IFN-γ expression with 600 subjects. Among 98 PB leprosy cases, the sensitivity of MMP II, LID-1, and NDO-BSA was 90%, 87%, and 83%, respectively, and the specificity was 90%, 91%, and 86%, respectively. The total number of cases positive for at least one antigen was 90 (91.8%) in PB, which is significantly higher than that in multibacillary (MB) leprosy (56.7%). The combination of multi-targets nested PCR and ELISPOT assay provides a specific tool to early clinical laboratory diagnosis of PB leprosy cases. The two assays are complementary to each other and beneficial for screening PB patients.

BackgroundAfter the elimination of leprosy in 1995, there were 10-30 newly detected leprosy cases every year in Zhejiang Province, and the epidemiological characteristics of the newly detected leprosy cases have changed. While most of the newly detected cases came from other provinces in China, not Zhejiang, it brought a new challenge for leprosy prevention and control in post- elimination era in Zhejiang, China. This study was aimed to understand the temporal-spatial distribution characteristics of newly detected leprosy cases, and provide the scientific rationales for the development of leprosy control strategy.MethodsData on the demographic of Zhejiang Province from 2011 to 2019 were obtained from the China Information System for Disease Control and Prevention, and the epidemiological data on leprosy cases newly detected in Zhejiang Province from 2011 to 2019 were obtained from the LEPROSY MANAGEMANT INFORMATION SYSTEM IN CHINA (LEPMIS), and temporal-spatial distributions were described. The geographic information system software-ArcGIS 10.4 was used to draw the statistical maps, and Geoda 1.14.0 was used for local spatial autocorrelation analysis (local Getis coefficient method). Ridley-Jopling classification was used to classify the clinical types into I, TT, BT, BB, BL or LL. Two-group classification system developed by the World Health Organization (WHO) was used and cases were classified into multibacillary (MB) type or paucibacillary (PB) type.ResultsA total of 167 leprosy cases were reported in Zhejiang Province during 2011-2019, including 107 cases in males and 60 in females. The mean age at diagnosis was 37.99±14.81 years, and 94.01% of the cases were detected through the examination at skin-clinics. The number of workers, MB cases, G2D cases were 81 (48.50%), 159 (94.01%), 24 (14.37%) respectively, and the rate of early detection increased from 45.16% in 2011 to 90.91% in 2019. Leprosy cases were reported in all the prefectures of Zhejiang except Zhoushan City. The cases in local population accounted for 23.35% (39 cases), and the cases in floating population (especially coming from high epidemic provinces in China) accounted for 76.65% (128 cases). The annual number of newly detected cases showed a decreasing trend, from 31 cases in 2011 to 11 in 2019. Time of the floating population living in Zhejiang Province ranged from several months to more than 10 years. The annual proportion of new cases with G2D declined from 22.58% in 2011 to 9.09% in 2019. The results of local indicators of autocorrelation (LISA) analysis showed that the high-high areas were mainly concentrated in the middle and northeast of Zhejiang Province, while the low-low areas were in the east and southwest.ConclusionA few scattered cases still can be seen in post-elimination era, and there was a spatial clustering of the newly detected leprosy cases in Zhejiang Province. Most of the cases in Zhejiang Province were from other high epidemic provinces in China, which brought a new challenge for leprosy control and prevention in post- elimination era in Zhejiang, and it is also necessary to strengthen the early detection and standard management of the leprosy cases in floating population in Zhejiang.

Context • Gonorrhea, a highly communicable, sexually transmitted infection, remains a major public-health concern globally. In recent years, Zhejiang province, an eastern province, has had the highest incidence of gonorrhea in China. Objective • The study intended to identify the geographic distribution patterns and spaciotemporal clustering characteristics of the disease’s incidence in Zhejiang between 2016 and 2020, to understand the spatial epidemiology of gonorrhea and to pinpoint the locations with relatively high risks of gonorrhea, the hotspots, which could be the key areas for disease prevention and control. Design • The research team performed a retrospective, spaciotemporal-clustering analysis of data about newly reported gonorrhea cases from January 2016 to December 2020 in Zhejiang province, using the China Information System for Disease Control and Prevention. Setting • The study took place at the Zhejiang Provincial Institute of Dermatology in Huzhou, China. Outcome Measures • The research team: (1) used the Geographic Information System software-ArcGIS 10.8 software to draw statistical maps; (2) conducted a spatialpattern clustering analysis at the district or county level; (3) performed an autocorrelation analysis using Getis-Ord (Gi*) statistics to detect spatial patterns and the hotspots of gonorrhea incidence; and (4) used SaTScan9.7 to analyze the space-time clusters. Results • Zhejiang province reported 85 904 gonorrhea cases from 2016 to 2020, with a male to female ratio of 3.81:1. The average annual incidence rate of gonorrhea was 30.50 per 100 000 individuals in the population, ranging from 22.73 cases to 39.65 cases, and the annual incidence showed a significant downward trend over the five years (χ²=16.142, P<.001). The northern and central areas had a higher incidence than the southern area did. Autocorrelation analysis showed that the gonorrhea incidence had a significantly clustered distribution (Moran’s I from 0.197 to 0.295, Z score from 4.749 to 6.909, P<.001). The high-high cluster areas were mainly in the urban districts of Hangzhou and some counties and districts of Jiaxing. The Gi* statistics further indicated that the hotspots of gonorrhea were mainly in Hangzhou, Jiaxing, and Huzhou. The Kuldorff ’s scan identified two clusters, mainly composed of 36 counties or districts in northern Zhejiang, such as Hangzhou and Jiaxing, and central Zhejiang, such as Jinhua and Shaoxing. Conclusions • The gonorrhea incidence rates in northern and central Zhejiang from 2016 to 2020 were higher than those in southern Zhejiang. An area of relatively higher risk for gonorrhea existed mainly in the urban districts of Hangzhou and some counties and districts of Jiaxing, Jinhua, and Shaoxing. In the future, the research team plans to focus on strengthening the prevention and control measures against gonorrhea in those areas. [ABSTRACT FROM AUTHOR]