Suspicious symptom monitoring for leprosy: an optimal practice for early detection under a low endemic situation in Zhejiang Province, China.

BACKGROUND: Leprosy is a chronic infectious disease that causes disabilities and deformities. Early detection is a major strategy for leprosy control. This study reported a new practice of suspicious symptom monitoring for early detection of leprosy. METHODS: A descriptive and comparative analysis between a non-strategy group of pre-implementation of suspicious symptom monitoring in 2005-2011 and a strategy group of strategy implementation in 2012-2018 was conducted through indicators of the number of times of misdiagnoses, delayed period, proportion of early detected cases, and proportion of disabilities. RESULT: Compared with the non-strategy group in 2005-2011, the median number of times of misdiagnoses was decreased from two times to zero times (z = 4.387, P < 0.001), and the median delayed period of newly detected cases were shortened from 24 months to 13 months (z = 2.381, P < 0.001), the proportion of early detected cases was increased from 43.7% to 75.2% (χ2 = 29.464, P < 0.001), the proportion of grade 2 disabilities was decreased from 28.6% in the highest year of 2005 to 4.0% in the lowest year of 2014, and the average proportion of disabilities was decreased from 33.5% to 17.6% (χ2 = 9.421, P = 0.002) in the strategy group in 2012-2018, respectively. CONCLUSION: Suspicious symptom monitoring promoted early detection of cases by reducing the number of times misdiagnosis of leprosy patients, shortening the delayed period, increasing the proportion of early detection, and decreasing the proportion of disabilities. It is an important and recommendable public health strategy for leprosy prevention and control in a low epidemic condition.

[Effects of rush mat dust exposure and smoking on workers' FEV1.0].

OBJECTIVE: To study the effect of smoking and rush-mat dust exposure on pulmonary function. METHOD: 122 rush-mat dust exposed workers and 118 controls without dust exposure were selected. Questionnaire and FEVY1.0 measurement were performed on them. RESULTS: For dust exposure, FEV1.0% of cases (81.8% +/- 13.9%) was statistically lower than controls (95.9% +/- 15.3%) (t = -7.49, P < 0.01), the abnormal rate of FEV1.0% was 46.7% (57/122) for cases, statistically higher than controls (8.5%, 10/118), chi2 = 43.6, P < 0.01. For smoking, FEV1.0% of cases (82.02% +/- 12.9%) was statistically lower than controls (93.33% +/- 12.4%), t = -5.18, P < 0.05, the abnormal rate of FEV1.0% is 55.9% for cases, statistically higher than controls (16.7%), chi2 = 22.2, P < 0.05. The exposing ages of workers has negative correlation with FEV1.0% (R(S1) = -0.299, P = 0.0008). Exposure and smoking could affect FEV1.0% (Fe = 259.06, P < 0.01, F(s) = 42.42, P < 0.01), and their interactive effect on FEV1.0% was greater than single ones (F = 34.70, P < 0.01). CONCLUSION: Rush-mat dust exposure, smoking and their interaction have influence on FEV1.0%.

Single-Nucleotide Polymorphisms in Genes Predisposing to Leprosy in Leprosy Household Contacts in Zhejiang Province, China.

PURPOSE: Genome-wide association studies (GWAS) have identified multiple genetic variants associated with leprosy. To investigate the single and combined associations between single-nucleotide polymorphisms (SNPs) and the development of leprosy, we therefore performed generalized multi-analytical (GMDR) analysis in Chinese leprosy household contacts and constructed a risk prediction model. PATIENTS AND METHODS: This case-control study included 229 leprosy cases and 233 healthy household contacts in Zhejiang province, China. Participants were genotyped for 17 polymorphisms selected from GWAS. The Pearson χ2 test, logistic regression and GMDR analysis were performed to investigate gene-gene interactions and construct a risk prediction model for leprosy. RESULTS: The genotype and the allele distributions of rs142179458, rs2275606, rs663743 and rs73058713 were significantly different between patients and controls. rs2275606, rs6478108, rs663743 and rs73058713 showed an association after adjusting for sex and age in the logistic regression. A five-way interaction model consisting of rs2058660, rs2275606, rs4720118, rs6478108 and rs780668 was chosen as the optimal model for determining leprosy susceptibility. The model classified 237 (51.3%) into the low-risk group and 225 (48.7%) individuals into the high-risk group. The area under the curve (AUC) of this model was 0.757 (95% CI: 0.712-0.803), and the odds ratio for leprosy between the high- and low-risk groups was 9.733 (95% CI: 6.384-14.960; P<0.001). The sensitivity and specificity of the model were observed to be 74.7% and 76.8%, respectively. CONCLUSION: Our results suggest that rs2058660, rs2275606, rs4720118, rs6478108 and rs780668, five SNPs with a significant sole effect on leprosy, interact to confer a higher risk for the disease in leprosy household contacts (HHCs).