Epidemiology of pathogenic tick-borne viruses in China: a review / 中国血吸虫病防治杂志

Ticks are obligate, haematophagous arthropods that are distributed across the world, which may transmit more than 200 pathogens, including viruses, bacteria and parasites. A large number of tick species are widespread in China, and their transmitting tick-borne viral diseases pose a great threat to human health in endemic foci. This review describes the epidemiology of common, emerging and potentially pathogenic tick-borne viruses in China, and recommends the assessment of public health significance and pathogenicity of emerging tick-borne viruses using reverse microbial etiology, so as to provide insights into the management of emerging tick-borne diseases in China.

Spatial distribution of Oncomelania hupensis spread in Hubei Province from 2020 to 2022 / 中国血吸虫病防治杂志

OBJECTIVE@#To identify the spatial distribution pattern of Oncomelania hupensis spread in Hubei Province, so as to provide insights into precision O. hupensis snail control in the province.@*METHODS@#Data pertaining to emerging and reemerging snails were collected from Hubei Province from 2020 to 2022 to build a spatial database of O. hupensis snail spread. The spatial clustering of O. hupensis snail spread was identified using global and local spatial autocorrelation analyses, and the hot spots of snail spread were identified using kernel density estimation. In addition, the correlation between environments with snail spread and the distance from the Yangtze River was evaluated using nearest-neighbor analysis and Spearman correlation analysis.@*RESULTS@#O. hupensis snail spread mainly occurred along the Yangtze River and Jianghan Plain in Hubei Province from 2020 to 2022, with a total spread area of 4 320.63 hm2, including 1 230.77 hm2 emerging snail habitats and 3 089.87 hm2 reemerging snail habitats. Global spatial autocorrelation analysis showed spatial autocorrelation in the O. hupensis snail spread in Hubei Province in 2020 and 2021, appearing a spatial clustering pattern (Moran's I = 0.003 593 and 0.060 973, both P values < 0.05), and the mean density of spread snails showed spatial aggregation in Hubei Province in 2020 (Moran's I = 0.512 856, P < 0.05). Local spatial autocorrelation analysis showed that the high-high clustering areas of spread snails were mainly distributed in 50 settings of 10 counties (districts) in Hubei Province from 2020 to 2022, and the high-high clustering areas of the mean density of spread snails were predominantly found in 219 snail habitats in four counties of Jiangling, Honghu, Yangxin and Gong'an. Kernel density estimation showed that there were high-, secondary high- and medium-density hot spots in snail spread areas in Hubei Province from 2020 to 2022, which were distributed in Jingzhou District, Wuxue District, Honghu County and Huangzhou District, respectively. There were high- and medium-density hot spots in the mean density of spread snails, which were located in Jiangling County, Honghu County and Yangxin County, respectively. In addition, the snail spread areas negatively correlated with the distance from the Yangtze River (r = -0.108 9, P < 0.05).@*CONCLUSIONS@#There was spatial clustering of O. hupensis snail spread in Hubei Province from 2020 to 2022. The monitoring and control of O. hupensis snails require to be reinforced in the clustering areas, notably in inner embankments to prevent reemerging schistosomiasis.

Study on early warning threshold values for 7 common communicable diseases in Gansu province, 2016 / 中华流行病学杂志

Objective: To optimize the warning threshold values of common communicable diseases in Gansu province, and improve the early warning effect. Method: An early warning model was set up for influenza, scarlet fever, other infectious diarrheal diseases, dysentery, typhoid and paratyphoid, viral hepatitis type E and hand foot and mouth disease (HFMD) respectively in Gansu by using the moving percentile method and cumulative sum method. By calculating the sensitivity, specificity, predictive value of positive test, predictive value of negative test, Youden' index and receiver-operating characteristic curve, the optimum early warning threshold values for communicable diseases in Gansu were selected. Results: The optimum early warning boundary values of influenza, scarlet fever, other infectious diarrheal diseases, dysentery, typhoid and paratyphoid, and viral hepatitis type E were P(90), P(80), P(95), P(90), P(80) and P(90) respectively. The optimum early warning parameters of HFMD were k=1.2, H=5σ. Under the optimum early warning boundary values/parameters, the early warning sensitivities of influenza, scarlet fever, other infectious diarrheal diseases, dysentery, typhoid and paratyphoid, viral hepatitis type E and HFMD were 86.67%, 100.00%, 91.67%, 100.00%, 100.00%, 100.00% and 100.00%, the specificities were 86.49%, 62.22%, 75.00%, 100.00%, 97.92%, 89.13% and 74.47%. The predictive values of positive test were 72.22%, 29.17%, 52.38%, 100.00%, 80.00%, 54.55% and 29.41%, and the predictive values of negative test were 94.12%, 100.00%, 96.77%, 100.00%, 100.00%, 100.00% and 100.00%, and the Youden' indexes were 0.73, 0.62, 0.67, 1.00, 0.98,0.89 and 0.74. Receiver-operating characteristic curve showed that the values/parameters of this warning boundary were the points closest to the upper left of the coordinate diagram. Conclusion: The early warning thresholds of influenza, other infectious diarrheal diseases, dysentery and hepatitis E in Gansu may be raised appropriately and the early warning parameters of HFMD need to be adjusted to improve the effectiveness of early warning.