中国血吸虫病防治杂志最新文献

Objective: To investigate the knowledge, attitudes and practices (KAP) towards scrub typhus control and analyse the influencing factors among residents in Longling County, Yunnan Province in 2023, so as to provide insights into management of scrub typhus in the county.

Methods: Two townships were randomly sampled from Longling County, Baoshan City, Yunnan Province in July 2023, and 2 to 3 administrative villages were randomly selected from each township. Then, 20 to 40 households were randomly selected from each village, and 1 to 2 villagers were surveyed in each household. Residents' KAP towards scrub typhus control was investigated, and factor affecting residents' KAP towards scrub typhus control were identified with independent samples t test or analysis of variance (ANOVA) and multiple linear regression analysis.

Results: A total of 417 questionnaires were allocated, and 410 valid questionnaires were recovered, with an effective recovery rate of 98.32%. Of all respondents, 65.85% (270/410) heard of scrub typhus but were not familiar with it, and 12.68% (52/410) and 1.95% (8/410) were familiar and very familiar with it, respectively. Residents mainly acquired scrub typhus control knowledge via their relatives and friends. The knowledge, attitude, and behavior scores of the respondents with regard to scrub typhus were (34.14 ± 13.07), (55.04 ± 6.69), and (21.40 ± 5.61), respectively, and the total score for knowledge, belief, and behavior in relation to scrub typhus prevention and control was (110.57 ± 18.80). Univariate analysis revealed that age (F = 3.12, P < 0.05), education (F = 10.77, P < 0.05), occupation (F = 4.89, P < 0.05), frequency of outdoor activities (F = 3.61, P < 0.05), and type of place of residence (t = 1.33, P < 0.05) were the factors that influenced the participants' scores for knowledge of the prevention and control of scrub typhus. Multiple linear regression analysis revealed that literacy level (β = 10.20 to 16.71, P < 0.05) and category of residence (β = -7.23, P < 0.05) were the factors that influenced residents' current knowledge and trust behavior in relation to scrub typhus.

Conclusions: Place of residence and educational level are critical factors affecting scrub typhus control among residents in Longling County, Yunnan Province. Intensified health education pertaining to scrub typhus control and appropriate behavioral interventions are required among residents living in urban areas, with a low educational level and frequent outdoor activities.

This paper reports the diagnosis and treatment of the first imported case of schistosomiasis haematobia in Xihu District of Hangzhou. The patient was an international student from Zimbabwe, and experienced repeated gross hematuria without obvious motivation. Cystoscopy displayed bladder masses, and a large number of fresh or calcified parasite eggs were found in pathological sections. In addition, urine microscopy identified Schistosoma haematobium eggs. The case was therefore definitively diagnosed as overseas imported case of imported schistosomiasis haematobia. Another case of schistosomiasis mansoni was identified among international students in the same school with the patient above by indirect haemagglutination test and urine and stool etiology examination. It is recommended to intensify health education and monitoring among overseas floating populations and improve the diagnostic skills of overseas imported schistosomiasis among professionals working in medical and disease control and prevention institutions, in order to prevent misdiagnosis and mistreatment.

Toxoplasma gondii is an obligatory intracellular parasite which infects a variety of warm-blooded animals and causes toxoplasmosis. Toxoplasmosis seriously endangers human health and animal husbandry production. As one of the effective gene editing tools, the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated proteins (Cas) system has been widely used for knockout of genes in T. gondii. This review summarizes the applications of the CRISPR/Cas9 technology in vaccines against single- and double-gene deletion strains of T. gondii, so as to provide insights into development of toxoplasmosis vaccines.

Schistosomiasis is a major public health concern in the world, and precision control is crucial to combating this disease. Due to the complex and diverse transmission route of schistosomiasis, conventional statistical models have significant limitations for precision control of schistosomiasis. As an important branch of artificial intelligence, machine learning has shown remarkable advantages in schistosomiasis control and research. It has been shown that machine learning is highly effective for disease prediction and risk assessment, so as to optimize the disease control strategy and resource allocation and achieve the precision control target. This review summarizes the characteristics of machine learning models and their applications in the research of intermediate host snails and schistosomiasis.

Objective: To evaluate the molluscicidal effect of spraying different formulations of niclosamide ethanolamine salt with drones against Oncomelania hupensis in ditches.

Methods: A semi-dry and semi-wet ditch with O. hupensis snails was selected in the second branch field of Jiangbei Farm, Jiangling County, Hubei Province in May 2023, and divided into 4 experimental areas, named groups A1, A2, B1 and B2. Environmental cleaning was performed in groups A1 and B2, and was not conducted in groups A2 or B2. Then, 50% wettable powder of niclosamide ethanolamine salt was sprayed with drones at an effective dose of 2 g/m² in groups A1 and A2, and 5% niclosamide ethanolamine salt granule was sprayed with drones at an effective dose of 2 g/m² in groups B1 and B2. O. hupensis snails were surveyed using the systematic sampling method 1, 3, 5, 7, 14 days after spraying, and the natural mortality and corrected mortality of O. hupensis snails were calculated.

Results: The occurrence of frames with living snails, mean density of living snails and natural mortality of snails were 97.50% (117/120), 6.30 snails/0.1 m² and 1.18% (9/765) in the test ditch before spraying, respectively. There were significant differences in the mortality of snails among four groups 1, 3, 5, 7 and 14 days after spraying niclosamide formulations with drones (χ² = 17.230, 51.707, 65.184, 204.050 and 34.435, all P values < 0.01). The overall mortality rates of snails were 94.51% (1 051/1 112), 79.44% (908/1 143), 96.54% (977/1 012) and 88.55% (1 021/1 153) in groups A1, A2, B1 and B2 (χ² = 207.773, P < 0.05), respectively. In addition, there was no significant difference in the overall snail mortality between groups A1 and B1 (P > 0.05), and the snail mortality in groups A1 and B1 were both statistically different from that in groups A2 and B2 (all P values < 0.05).

Conclusions: Both 50% wettlable powder of niclosamide ethanolamine salt and 5% niclosamide ethanolamine salt granule sprayed with drones are active against O. hupensis snails in ditches, and environmental cleaning may improve the molluscicidal effect.

Leishmaniasis is a zoonotic parasitic disease caused by Leishmania infection and transmitted by sandflies. There are three main forms of leishmaniasis, including cutaneous leishmaniasis, visceral leishmaniasis and mucocutaneous leishmaniasis. China is mainly endemic for visceral leishmaniasis, which is a class C notifiable infectious disease in the country. Following concerted efforts, the transmission of visceral leishmaniasis had been controlled in most endemic foci of China by the end of 1958, with a few cases reported in western China. Due to global climate changes and population mobility, resurgence of visceral leishmaniasis has recently occurred in historical endemic areas of central and western China, which is characterized by gradual expansion of endemic areas and remarkable rebounding epidemics. Hereby, we summarize the national and global epidemiology and control strategy of visceral leishmaniasis, propose 8 key research areas and 12 key research topics for visceral leishmaniasis control, and recommend the establishment of the joint prevention and control mechanism of "human-animals-vectors" and the working mechanism of animal prevention for human diseases based on the One Health approach, so as to combat the resurgence of visceral leishmaniasis in China.

Objective: To establish an artificial intelligence (AI)-assisted platform for detection of parasite eggs, and to evaluate its detection efficiency and accuracy, so as to provide technical supports for elimination of parasitic diseases.

Methods: A total of 1 003 slides of Enterobius vermicularis, horkworm, Trichuris trichiura, Clonorchis sinensis, Taenia, Ascaris lumbricoides, Schistosoma japonicum, Paragonimus westermani and Fasciolopsis buski eggs were collected, and converted into digital images with an automatated scanning microscope to create a dataset. Based on the Object Detection platform on the Baidu Easy DL model, an AI-assisted platform for detection of parasite eggs was created through procedures of uploading, labeling, training, evaluation and optimization. Then, 70% of the datasets were randomly selected for model training, and the precision, recall and average accuracy were calculated to evaluate the effectiveness of platform for recognition of parasite eggs. In addition, the platform was deployed on the computer and smart phone terminals for use.

Results: An AI-assisted platform for detection of parasite eggs was successfully created. If the platform was deployed using the public cloud application programming interface (API), the average accuracy, precision and recall of the platform were 93.42%, 92.55% and 89.32% for recognition of parasite eggs. If the platform was deployed using the offline software development kit (SDK), the average accuracy, precision and recall of the platform were 92.97%, 94.78% and 87.63% for recognition of parasite eggs. In addition, the precision of the platform was 97.00% and 96.23% for identification of Taenia and C. sinensis eggs, respectively.

Conclusions: The AI-assisted platform for detection of parasite eggs has been successfully created, which is high in the accuracy for recognition of parasite eggs and convenient in use. This platform may provide a powerful technical support for parasitic disease diagnosis.