In recent years, with the continuous advancement of technology, unmanned aerial vehicle (UAV) technology has been widely applied across various fields. UAVs can be directly deployed in patriotic health initiatives, including epidemic prevention and control, disease vector surveillance and control, and urban management, significantly reducing labor requirements and minimizing the adverse health effects of related chemical agents on workers. Currently, the application of UAVs in patriotic health initiatives is still in its early stages. Experience from their use in agriculture and other sectors has helped identify several challenges. These include safety issues related to droplet drift, the lack of a comprehensive quality evaluation system, the absence of standardized personnel training and reserve talent pools, inadequate production and development of supporting supplies, and insufficient national policy support. It is recommended that the government and relevant authorities proactively integrate UAVs into future patriotic health efforts by expanding their application and research, incorporating new technologies such as artificial intelligence, improving personnel training and reserves, and securing policy support.

Objective: To explore the application value of unmanned aerial vehicles (UAVs) and deep learning object detection algorithms for identifying Meriones unguiculatus burrows, and improve the efficiency of plague surveillance. Methods: Kangbao County, a natural plague focus in Hebei Province, was selected as the study area. A DJI Matrice 300 RTK UAV equipped with a Surveyor PSDK 102S V3 five-lens camera was used for aerial photography and remote sensing data acquisition. The captured images were imported into an intelligent burrow identification system. Burrows in each image were automatically annotated and counted, and images containing burrows were exported. Burrows were manually identified in the photographs, misidentified and unidentified burrows were marked and counted. The performance of the intelligent burrow identification system was evaluated using precision, recall, and F1-score. Data were organized using Excel 2021 software and analyzed statistically with SPSS 19.0 software. An R×C Chi-square test was used to compare differences in precision and recall for images captured by lenses in different directions and from different habitats. Results: A total of 12 sampling sites were surveyed in Kangbao County, covering an aerial area of 32.27 hm². A total of 30 635 remote sensing images were captured, of which 1 530 showed M. unguiculatus burrows. Analysis of images from the five lens directions at the same sample site showed that the intelligent burrow identification system achieved a detection precision of 81.13%, a recall of 81.92%, and an F1-score of 81.52%. There was no statistically significant difference in precision for burrow identification across the five lens directions (χ²=3.853, P=0.426), but a significant difference was found in recall (χ²=14.084, P=0.007). For different habitats, the precision was 86.19%, the recall was 69.93%, and the F1-score was 77.22%. A statistically significant difference was observed in precision across habitats (χ²=12.878, P=0.002), but the difference in recall was insignificant (χ²=4.471, P=0.102). Conclusions: The intelligent burrow identification system can meet the requirements for burrow detection in routine plague surveillance and provide valuable support for these activities. The integration of UAV technology and deep learning model can reduce the labor burden associated with traditional surveillance method, expand the monitored area, and enhance the overall efficiency of plague surveillance.

Objective: To address the technical challenges of isolating and identifying exosomes from complex whole-body Dermatophagoides farinae, and to establish stable and reliable methods for their isolation and identification. Methods: The purity of collected D. farinae was assessed using the 18S rRNA gene V4 region as a DNA barcode. Exosomes were isolated via differential centrifugation. The structure of exosomes was observed using transmission electron microscopy, and particle size distribution and concentration were measured using nanoparticle tracking analysis (NTA). Results: Amplicon sequencing revealed that the sample consisted of Dermatophagoides (77.61%), Saccharomyces (9.70%), Triticum (9.54%), Gregarina (1.62%), Secale (0.51%), and Hordeum (0.09%). Clear exosome-like structures characterized by a cup-shaped or saucer-shaped bilayer membrane were observed under transmission electron microscopy. Characterization of the exosomes based on NTA showed an average particle size of (122.9±3.4) nm, with 92.26% of particles distributed within the 30-200 nm range. Conclusion: A novel method for isolating D. farinae exosomes is established.

Objective: To investigate the resistance levels of Aedes aegypti to commonly used insecticides in Xishuangbanna Dai Autonomous Prefecture (Xishuangbanna), a key area with dengue fever control in Yunnan Province, preliminarily explore its metabolic resistance mechanisms at the enzymatic level, to provide a scientific basis for the control and resistance management of Ae. aegypti in this region. Methods: In August 2024, Ae. aegypti larvae were collected from Jinghong City, Mengla County, and Menghai County in Xishuangbanna. The larvae were reared to the F₁ generation of adult mosquitoes. The resistance of adult mosquitoes to permethrin, lambda-cyhalothrin, malathion, fipronil, and propoxur was tested using the World Health Organization tube method. The Pearson's Chi-square test or Fisher's exact test was used to compare the knockdown rates and 24-hour mortality rates of mosquitoes from different regions. The activities of cytochrome P450 enzyme system (CYP450), glutathione S-transferase (GST), and non-specific esterase (NSE) in female mosquitoes were detected by enzyme linked immunosorbent assay. Differences between groups were compared using the Wilcoxon rank-sum test or the Kruskal-Wallis H rank-sum test. Box plots of enzyme activity were generated using Origin 2024 software. Results: The 24-hour mortality rates of Ae. aegypti in Xishuangbanna after exposure to insecticides were: 1.69%-7.46% for permethrin, 0.98%-16.92% for lambda-cyhalothrin, 82.14%-97.85% for malathion, 0.71%-28.57% for fipronil, and 69.09%-97.70% for propoxur. The mortality rates of Ae. aegypti populations from Jinghong City, Mengla County, and Menghai County after exposure to four insecticides were significantly different (lambda-cyhalothrin: P < 0.001; malathion: χ²=12.939, P=0.002; fipronil: χ²=15.594, P < 0.001; propoxur: χ²=23.198, P < 0.001). The activities of CYP450, GST, and NSE in Ae. aegypti from Jinghong City were 1.96, 1.74, and 2.00 times those of the sensitive strain, respectively. Conclusions: The Ae. aegypti in Xishuangbanna has developed varying degrees of resistance to multiple types of insecticides, with regional differences and relatively high resistance levels in some areas. Elevated metabolic enzyme activities may be associated with the development of insecticide resistance in Ae. aegypti in Xishuangbanna. It is recommended to further strengthen research on resistance surveillance and mechanisms in Xishuangbanna, formulate precise insecticide rotation strategies based on regional resistance profiles, and scientifically select insecticides with the principle of integrated vector management to delay the development of resistance.

Objective: To investigate the species composition, density dynamics, and seasonal fluctuation patterns of mosquitoes in Yunnan Province, and provide a scientific basis for risk assessment and precise prevention and control of mosquito-borne infectious diseases. Methods: In accordance with the National Vector Surveillance Implementation Plan, monthly surveillance of adult mosquitoes was carried out continuously for four years from 2021 to 2024 using the mosquito light trap method. Mosquito species were identified morphologically. The Kruskal-Wallis H test was used to compare mosquito density, the Chi-square test was used to analyze differences in species composition, the dynamic trend of mosquito density was analyzed by Joinpoint log-linear regression model, and a Pearson correlation analysis was used to access the correlation between adult mosquito density and meteorological data. Results: Over the four years, the average mosquito density in Yunnan Province was 8.56 mosquitoes/(lamp·night), and the total mosquito density showed an upward trend from 2021 to 2024, with an annual percent change of 30.05 (95% confidence interval: 8.14-56.94, Z=5.271, P=0.034). Culex tritaeniorhynchus (47.56%, 65 357/137 420) and Cx. pipiens pallens/quinquefasciatus (36.16%, 49 692/137 420) were the dominant species, followed by Anopheles sinensis (9.89%, 13 592/137 420) and Aedes albopictus (1.16%, 1 596/137 420). The mosquito density peak period was mainly between June and September, showing a unimodal pattern (2021-2022) or a bimodal pattern (2023-2024). The mosquito density in livestock farms, cattle sheds, pigsties, rural households, residential areas, parks, and hospitals was 149.08, 21.92, 18.77, 7.87, 6.45, 4.09, and 3.84 mosquitoes/(lamp·night), respectively. There was a statistically significant difference in the species composition of mosquitoes among different habitats (χ²=24 211.241, P < 0.001). Culex tritaeniorhynchus was the dominant species in livestock-related places (cattle sheds, pigsties, and livestock farms). There was a statistically significant difference in the species composition of mosquitoes among different regions (χ²=45 287.397, P < 0.001). The mosquito density was higher in Baoshan and Zhaotong, with values of 26.31 and 25.16 mosquitoes/(lamp·night), while Honghe Hani and Yi Autonomous Prefecture had the lowest density at 1.72 mosquitoes/(lamp·night). The total mosquito density in Yunnan Province was significantly negatively correlated with mean air pressure and mean wind speed (r=-0.719, P < 0.001; r=-0.354, P=0.014), and significantly positively correlated with mean temperature, relative humidity and monthly precipitation (r=0.749, P < 0.001; r=0.491, P < 0.001; r=0.795, P < 0.001). Conclusions: The mosquito density in Yunnan Province showed a significant upward trend from 2021 to 2024. Livestock breeding environments were areas with high incidence of mosquitoes, and the period between June and September was critical for mosquito prevention and control. It is necessary to strengthen interventions in high-density areas such as western Yunnan Province (Baoshan), northeastern Yunnan Province (Zhaotong), and livestock farms/cattle sheds/pigsties.

Objective: To analyze the population fluctuation patterns of mosquitoes in the suburban rural areas of Changsha City from 2017 to 2024, to provide a scientific basis for comprehensive mosquito control in the suburban rural areas of Changsha City. Methods: From April to November each year, mosquito surveillance was conducted using the light trap method in residential houses and pig pens in the suburban rural areas of Changsha City. Species composition, annual density fluctuations, and seasonal density fluctuations were analyzed. The Chi-square test was used to compare mosquito species compositions, Wilcoxon rank-sum test was applied to compare mosquito densities in different habitats, and Kruskal-Wallis H test was employed to compare mosquito densities across different years and months. Results: The dominant mosquito species in the suburban rural areas of Changsha City from 2017 to 2024 were Culex pipiens pallens/quinquefasciatus, Cx. tritaeniorhynchus, and Armigeres subalbatus, which accounted for 51.38%, 33.26%, and 11.50%, respectively. The differences in species composition were statistically significant across years (χ²=14 080.873, P < 0.001). The average mosquito density from 2017 to 2024 was 70.47 mosquitoes/(light·night). The density increased in 2017 and 2018, decreased rapidly between 2018 and 2020, and then increased slowly between 2020 and 2024. The highest density of 138.61 mosquitoes/(light·night) was observed in 2018 and the lowest density of 44.13 mosquitoes/(light·night) was recorded in 2020. The differences in mosquito density were not statistically significant across these years (H=6.098, P=0.528). The average annual mosquito density in pig pens [95.44 mosquitoes/(light·night)] was higher than in residential houses [45.50 mosquitoes/(light·night)] (Z=-3.948, P < 0.001). The seasonal fluctuations of mosquitoes throughout the year exhibited a bimodal distribution, with density peaked in June and September, and statistically significant differences in density across months (H=73.928, P < 0.001). Mosquito activity peaked in May-July and September each year, with densities of 117.22, 195.08, 93.95, and 62.18 mosquitoes/(light·night), respectively. Conclusions: From 2017 to 2024, mosquito density in the suburban rural areas of Changsha City followed a trend of increase, rapid decrease, and slow increase, with activity peaked mainly in May-July and September each year. Comprehensive mosquito control plans should be developed by considering the ecological environmental characteristics and mosquito activity peaks in suburban rural areas.

Objective: To investigate the tick species composition, density, and seasonal variation in selected parts of Hulun Buir City. Methods: From March to September in each year between 2022 and 2025, ticks were monitored in rural outdoor environments, scenic areas, parks, and wild grasslands in Hulun Buir City. The dragging-flagging method was used to monitor questing ticks, and the host body checking method was used to monitor on-host ticks. Excel 2010 and SPSS 22.0 were used for data processing and analysis. For count data, inter-group comparisons were performed using the Chi-square test or Fisher's exact test. For measurement data, the Kruskal-Wallis H rank-sum test was used for comparisons. Results: The on-host tick index was 0.39, and the density of questing ticks was 0.60 ticks/(flag·100 m). Dermacentor silvarum was the dominant species and accounted for 55.40% of the total number of captured ticks. The differences in the species composition of on-host ticks among different host animals (χ²=560.539, P < 0.001) and in the species composition of questing ticks across different habitats (χ²=1 386.520, P < 0.001) were both statistically significant. Significant differences were observed in the on-host tick index among different host animals (H=15.878, P=0.044) and in the density of questing ticks among different habitats (H=14.654, P=0.041). Donkeys had the highest tick index (5.33), followed by horses (0.69). Wild grasslands had the highest questing tick density of 1.14 ticks/(flag·100 m), while suburban parks had the lowest density of 0.20 ticks/(flag·100 m). There was no significant difference in the on-host tick index among different regions (H=5.270, P=0.261). However, a significant difference was found in the density of questing ticks among different regions (H=11.007, P=0.026). Specifically, Yakeshi City had the highest density of 1.18 ticks/(flag·100 m), while Manzhouli City had the lowest density of 0.22 ticks/(flag·100 m). Both questing tick density and on-host tick index showed significant differences across different months (H=31.625, P < 0.01; H=20.646, P < 0.01). The number of captured ticks peaked in April and May and declined in June and July, and no ticks were captured in March and September. Conclusions: D. silvarum was the dominant tick species in the Hulun Buir area. The species composition of on-host ticks varied among host animals. Wild grasslands is the environment with the highest tick occurrence. The number of ticks peaked in April and May in the Hulun Buir area.

Objective: To investigate the species composition, seasonal dynamics, and distribution of ticks in Huangshan, Anhui Province, and provide a scientific basis for the control and prevention of ticks and tick-borne diseases in the region. Methods: From 2023 to 2024, surveillance for questing ticks (using the dragging-flagging method) and on-host ticks (using host body tick checking method) was conducted once in March, May, July, September, and October in mountain forest and tea garden habitat within She County and Yi County of Huangshan. All collected ticks (on-host and questing) were placed by host or by habitat into labeled centrifuge tubes. Information including collection time, location, host/habitat type, parasitic site, and quantity was recorded. Tick species identification involved preliminary morphological identification by the Huangshan Center for Disease Control and Prevention, and morphological re-identification by the Institute of Zoology, Chinese Academy of Sciences. Data were managed using WPS 12.1.0.22529 and analyzed using SPSS 20.0. The Kruskal-Wallis H test was used to compare questing tick densities between different habitat types, and the Chi-square test was used to compare the composition of tick species. Results: A total of 10 tick species belonging to 4 genera and 1 family were collected. These included 5 species of Haemaphysalis (H. flava, H. longicornis, H. hystricis, H. doenitzi, H. campanulata), 3 species of Rhipicephalus (R. sanguineus, R. microplus, R. haemaphysaloides), 1 species of Ixodes (I. sinensis), and 1 species of Amblyomma (A. testudinarium). Statistically significant differences were observed in the composition ratios among different tick species (χ²=227.289, P < 0.001). During the 2023-2024 surveillance period, 503 ticks were collected by dragging-flagging over a total distance of 62 100 m, yielding an overall density of 0.81 ticks/ (flag·100 m). Habitat comparison showed a higher tick density of 0.91 ticks/ (flag·100 m) in tea gardens than the 0.72 ticks/(flag·100 m) in mountain forests. The density differences of questing ticks among different habitat types were statistically significant (H=10.575, P < 0.001). A total of 586 host animals were examined, of which 59 were infested with ticks, yielding 263 on-host ticks. Sheep had the highest tick infestation rate (20.91%), while cattle had the lowest (3.03%), there was a statistically significant difference in tick infestation rates among different host animals (χ²=23.057, P < 0.001). Tick seasonal dynamics showed a unimodal pattern: questing tick density was relatively low in March and peaked in May, while on-host tick density peaked in July. Conclusions: Ticks are present in both mountain forests and tea garden habitats in Huangshan, exhibiting rich species diversity. Habitats with sheep activity and tea gardens are key areas for tick control. Tick activity shows distinct seasonal dynamics. It is recommended to provide multi-faceted health education on tick bite prevention for tea farmers and tourists during the seasons with peak tick densities.

Objective: To clarify the epidemic pattern and spatial clustering characteristics of severe fever with thrombocytopenia syndrome (SFTS) in Linyi City from 2011 to 2024, to provide a scientific basis for developing scientific and effective SFTS prevention and control strategies in Linyi City. Methods: SFTS case data were obtained from the Chinese Disease Prevention and Control Information System. Descriptive analysis, spatial autocorrelation, and spatiotemporal scan analysis were used to systematically analyze the epidemiological and spatial clustering characteristics of SFTS in Linyi City. Categorical data were analyzed using the Chi-square test or Fisher's exact test. Results: From 2011 to 2024, a total of 820 SFTS cases were reported in Linyi City, with an average annual incidence of 0.54/100 000. The incidence occurred predominantly from April to October. Farmers (787/820, 95.98%) accounted for the majority of cases, the middle-aged and elderly population (747/820, 91.10%) was the most affected group, and a higher incidence was recorded in females than in males. All counties (sub-districts) in Linyi City reported SFTS cases during these years, and the number of affected townships (sub-streets) gradually increased. A total of 87 townships (sub-streets) were affected from 2011 to 2024. Global spatial autocorrelation analysis indicated significant spatial clustering of SFTS cases in all years except 2011 and 2013 (P < 0.05). Local spatial autocorrelation analysis revealed that "high-high" clustering townships (sub-streets) were identified each year, mainly concentrated in the northwestern part of the city. Spatiotemporal scan analysis revealed two clustering areas of SFTS cases in Linyi City from 2011 to 2024, and the differences between the observed and expected values were statistically significant (both P < 0.01). The most likely clustering areas included 23 townships (sub-streets) in Mengyin County, the northern part of Yishui County, and the northern part of Yinan County. Conclusions: The SFTS epidemic in Linyi City exhibits a rapid upward trend and continuous geographic expansion, with spatial clustering of cases. Enhanced prevention and control efforts should be prioritized in key areas such as Mengyin County and Yishui County.

Objective: To analyze the control and prevention strategies implemented at different stages of a localized cluster of chikungunya fever outbreak in an urban community in Nanhai District, Foshan City in 2025 and evaluate their effectiveness, so as to provide a scientific reference for epidemic prevention and control in similar urban communities. Methods: Data on the basic information of the epidemic, case diagnosis and reporting, case isolation management, indoor and outdoor mosquito vector breeding site cleanup, emergency mosquito control, and administrative organizational actions were collected and reviewed. The implementation and effectiveness of control and prevention strategies at different stages were investigated, analyzed, and summarized. Results: A total of 11 cases were reported in this outbreak, with a mean interval of (0.82±0.75) days from symptom onset to hospitalization and isolation. The epidemic progression exhibited three distinct phases. In the first phase, routine community-led prevention and control efforts were in place, but the epidemic continued to develop. In the second phase, a level Ⅲ public health emergency response was initiated, leading to increased administrative interventions; however, control and prevention still relied on community-based efforts, and the epidemic continued to spread. In the third phase, administrative coordination and professional resources were strengthened, achieving full coverage of household investigations and breeding site cleanup, which rapidly brought the epidemic under control. Conclusions: An efficient case surveillance and early warning system is fundamental for timely epidemic detection. Furthermore, a comprehensive intervention model combining multi-departmental collaboration, professional mosquito vector control, and community mobilization is crucial for effectively containing the spread of chikungunya fever.

Objective: To analyze the emergency response to a dengue fever outbreak in a special urban environment, evaluate the practical application value of integrated prevention and control measures in complex settings, and provide practical references for optimizing dengue fever prevention and control strategies in similar areas in the background of climate change. Methods: Based on the epidemiological characteristics of a local dengue fever outbreak in Lucheng District, Wenzhou, Zhejiang Province, from August to October 2024, big data trajectory intersection technology was applied to accurately identify high-risk exposure sites. A dynamic surveillance network for vector Aedes mosquitoes was established by integrating the Breteau index method, double mosquito net trap method, and BG-trap mosquito surveillance. Drone-based ultra-low volume spray technology was applied to overcome vector control challenges in complex terrain. Spatial management and community-coordinated breeding site cleanup were implemented for multi-dimensional vector control. The Mann-Whitney U test was used to evaluate control effectiveness. Results: The outbreak lasted 19 days, with a total of 8 confirmed cases showing significant spatial clustering. The onset dates were concentrated between August 13 and 17. The male-to-female ratio was 1:0.60, and all cases were middle-aged and elderly individuals (median age: 64.50 years). The average time from symptom onset to confirmed diagnosis decreased from 2.03 days to 0.46 days. The average Breteau index in the core area decreased from 9.06 to 2.86 (U=551.500, P=0.006). The average adult mosquito density decreased from 4.67 mosquitoes/(net·hour) to 1.44 mosquitoes/(net·hour) (U=41.000, P=0.047). Conclusions: Urban mountain parks present a special risk for dengue transmission. The prevention and control model integrating precise tracing, spatial management, multi-dimensional vector management, and community coordination can significantly improve the effectiveness of dengue outbreak response in complex environments.

Objective: To analyze the epidemiological characteristics of hemorrhagic fever with renal syndrome (HFRS) cases in Liuyang City, Hunan Province and investigate the distribution and virus-carrying status of HFRS host animals, so as to provide a reference for HFRS prevention and control in Liuyang. Methods: Descriptive epidemiological methods were used to analyze the epidemiological characteristics of HFRS cases and the monitoring data of host animals in Liuyang City from 2020 to 2024. The night snap-trapping method was used for outdoor surveillance of host animals, while both the night snap-trapping method and the glue board method were used for indoor surveillance. Statistical analysis was conducted using SPSS 27.0 software. The Chi-square test was applied for rate comparisons. The Joinpoint 5.4.0 software was used to calculate the average annual percent change (AAPC) of incidence of HFRS. Results: From 2020 to 2024, a total of 117 HFRS cases were reported in Liuyang City, yielding an average annual reported incidence rate of 1.65/100 000. The AAPC was -22.80% (P=0.190). The majority of patients were middle-aged and elderly male farmers. Cases were concentrated in the northern rural region (townships and towns) of Liuyang City, accounting for 68.38% (80/117) and demonstrating an average annual incidence rate of 3.66/100 000. A statistically significant difference was observed in incidence rates among the eastern, western, southern, and northern rural regions and the urban region (χ²=81.015, P < 0.001). A total of 521 small mammals were captured between 2020 and 2024, resulting in an overall density of 4.68% (521/11 132). The indoor density (203/3 249, 6.25%) was higher than the outdoor density (318/7 883, 4.03%). The indoor capture rate of small mammals by glue board method (128/1 291, 9.91%) was higher than that by the night snap-trapping method (63/1 958, 3.21%) (χ²=63.068, P < 0.001). The density in the first half of the year (286/5 077, 5.63%) was higher than that in the second half (235/6 055, 3.88%) (χ²=19.004, P < 0.001). Apodemus agrarius (266/318, 83.65%) was the dominant species of small mammals captured in the outdoor environment, while Rattus tanezumi (116/203, 57.14%) and R. norvegicus (39/203, 19.21%) were the dominant species in the indoor environment. A total of 460 rodent lung samples were analyzed, with 26 testing positive for Hantavirus nucleic acid, including 24 positives for Hantaan virus and 2 for Seoul virus. The virus-carrying rate of small mammals was 5.65% (26/460). The Hantavirus-carrying rate for outdoor rodents (23/271, 8.49%) was higher than that for indoor rodents (3/189, 1.59%) (χ²=10.571, P < 0.001). Conclusions: The incidence of HFRS epidemic in Liuyang City has decreased over the past five years. Both Hantaan virus and Seoul virus are present, with Hantaan virus being the dominant species. Based on the HFRS epidemiological surveillance data over the years, rodent control should be strengthened in the northern rural region of Liuyang City. Additionally, health education should be enhanced among key or high-risk populations, such as farmers, to enhance public awareness of disease prevention and timely medical treatment.

Objective: To investigate the distribution characteristics of host animals for hemorrhagic fever with renal syndrome (HFRS) and their carriage of Hantavirus antigens and antibodies in Guyuan City, Ningxia Hui Autonomous Region, China, from 2022 to 2024, so as to provide an evidence-based foundation for host animal surveillance and early warning for the prevention of HFRS outbreaks in the human population in this region. Methods: From 2022 to 2024, in accordance with the National Surveillance Program for Hemorrhagic Fever with Renal Syndrome, surveillance of host animals was conducted in the wild and residential areas of Jingyuan County, Yuanzhou District, Xiji County, Longde County, and Pengyang County in Guyuan City during the spring and autumn each year. The density and species composition of rodents were monitored using the 5-meter night snap-trapping method. Lung and blood samples were collected for Hantavirus antigen and antibody testing. A statistical analysis was conducted using SPSS 23.0 software. Categorical data were expressed as rates and analyzed intergroup differences using the Chi-squared test of Fisher' exact test, with a significance level of P < 0.05. Results: From 2022 to 2024, a total of 3 216 rodents (including four shrews, due to their small numbers, they were classified as rodents for statistical analysis in this paper) were captured in Guyuan City, with an average rodent density of 1.58%. The rodent density in wild habitats (1 857/100 613, 1.85%) was significantly higher than that in residential areas (1 359/103 493, 1.31%) (χ²=93.298, P < 0.001). Jingyuan County had the highest rodent densities in both wild habitats (560/17 280, 3.24%) and residential areas (171/7 898, 2.17%). In other regions, rodent densities in wild habitats were below 2.50%, and those in residential areas were ≤1.80%. The dominant rodent species in wild habitats and their respective proportions were as follows: Cricetulus longicaudatus in Xiji County (423/506, 83.60%), Mus musculus in Pengyang County (215/259, 83.01%), M. musculus in Longde County (193/330, 58.48%), Apodemus agrarius in Jingyuan County (227/560, 40.53%), and A. agrarius in Yuanzhou District (73/202, 36.14%). In residential areas, the dominant species was M. musculus in all counties except Yuanzhou District, where Rattus norvegicus (241/403, 59.80%) was dominant. The proportions of dominant species exceeded 70.00% in all residential areas except Jingyuan County. The three-year average positive rate for Hantavirus antibodies in rodent sera was 19.53% (628/3 216), while the average positive rate for Hantavirus antigens in rodent lungs was 0.56% (18/3 216). The difference between antibody and antigen positive rates was statistically significant (χ²=64.317, P < 0.001). Rodent lung antigen positivity was detected only in Jingyuan County (13/731, 1.78%) and Longde County (5/635, 0.79%), and the Fisher's exact test showed no significant difference between these positive rates (P=0.109). The positive rate for rodent serum antibodies was highest in Yuanzhou District (165/605, 27.27%) and lowest in Jingyuan County (102/731, 13.95%), with a statistically significant difference between different counties (districts) (χ²=65.822, P < 0.001). In wild habitats, the rodent lung antigen positive rate was 0.75% (14/1 857) and the serum antibody positive rate was 15.89% (295/1 857), with a statistically significant difference (χ²=278.727, P < 0.001). In residential areas, the rodent lung antigen positive rate was 0.29% (4/1 359) and the serum antibody positive rate was 24.50% (333/1 359), with a statistically significant difference (χ²=366.650, P < 0.001). Lung antigen positivity was predominantly found in A. agrarius and A. peninsulae, which together accounted for 61.11% (11/18) of positive cases. Serum antibody positivity was mainly found in M. musculus and R. norvegicus, which together accounted for 64.81% (407/628) of positive cases. Hantavirus genotyping showed that all hantaviruses detected in the captured rodents were identified as Hantaan virus. Conclusions: From 2022 to 2024, the overall distribution characteristics of HFRS host animals in Guyuan City have shown little difference from previous surveillance results. Antigen-positive host animals are primarily detected in Apodemus species in Jingyuan County, indicating a relatively high risk of HFRS transmission in this area. It is necessary to strengthen surveillance and early warning to prevent potential HFRS outbreaks in the human population.

Objective: To confirm the identity of the first suspected Aedes albopictus larvae collected from the Sanqi Flower Market in Chengbei District, Xining City, Qinghai Province in 2023. Methods: Suspected Ae. albopictus larvae were captured during mosquito surveillance in September 2023 at the Sanqi Flower Market (101°39′13.69″E, 36°39′34.24″N; altitude: 2 260.8 m). The larvae were reared under uncontrolled in the laboratory. The emerged adults were morphologically identified and DNA was extracted. The genes encoding mitochondrial cytochrome C oxidase subunit Ⅰ (COⅠ) and the reduced nicotinamide adenine dinucleotide (NADH) dehydrogenase subunit 5 (ND5) were amplified and sequenced. The obtained sequences were aligned against the National Center for Biotechnology Information (NCBI) database. A phylogenetic tree of the ND5 gene was constructed using the maximum likelihood method. Results: The collected larvae developed and emerged into adults under uncontrolled room conditions. The emerged adults matched the morphological characteristics of Ae. albopictus. The obtained ND5 gene sequences showed > 99.00% identity with the Ae. albopictus sequence in the NCBI database and clustered with the known Ae. albopictus sequence in the phylogenetic tree. The COⅠ gene sequences exhibited > 98.00% identity with the Ae. albopictus sequence. Conclusions: The larvae captured in Xining City, Qinghai Province, were confirmed to be Ae. albopictus, representing the first record of this species in Qinghai Province. However, its distribution in Qinghai Province is characterized by habitat specificity (found only in the flower market) and regional limitation (only in Chengbei District, Xining City). The summer and autumn seasons in Xining City are suitable for the growth of Ae. albopictus. This discovery expands the records of Ae. albopictus distribution both in China and in Qinghai Province.

Objective: To explore the hotspot distribution and evolution patterns of topics in the field of dengue fever, and clarify the research focuses and development trends of the disease. Methods: English language articles related to dengue fever published between January 1994 and July 2025 were retrieved from the Web of Science core collection, and statistical charts of literature characteristics were drawn. Topic modeling was conducted based on deep learning to analyze topic characteristics, correlations, and evolution trends. Results: A total of 13 851 articles were included. The overall number of publications showed an upward trend, with a significant increase after 2005. The number peaked in 2021, followed by a slight decline, but remained at a relatively high levels. Analysis of high-frequency terms in keywords and abstracts identified dengue, virus, fever, and infection as the core high-frequency terms. Among the top 15 keywords calculated using the term frequency-inverse document frequency algorithm, dengue, achieved the highest scores. PLOS Neglected Tropical Diseases ranked first in the number of published dengue fever-related studies. Cluster analysis revealed that the top three clusters by proportion were Cluster 1 (research on prevention and control strategies of degue fever, 22.90%), Cluster 0 (basic medical research on Dengue virus, 19.80%), and Cluster 2 (research on mosquito borne transmission of Dengue virus, 18.20%). Furthermore, topic modeling identified 116 research topics. Through K-means clustering, ten core research topics were identified, including dengue fever modeling and epidemiology, clinical case, viral infection and immune mechanisms, detection technology, transmission vector, antiviral drug, novel viral detection equipment, viral RNA replication and protein functions, vaccine development, and vector prevention and control research. The chart of topic popularity trends indicated that the popularity of four topics increased rapidly, namely dengue fever modeling and epidemiology, clinical case, viral infection and immune mechanisms, and antiviral drug research. Conclusions: Current research hotspots in dengue fever primarily focus on dengue fever modeling and epidemiology, clinical case, and viral infection and immune mechanisms. In the future, deepening research in these core hotspot areas, advancing the iteration of detection technologies, innovating mosquito prevention and control methods, achieving breakthroughs in drug research and development, and promoting the application of novel virus detection devices are expected to become important research directions in the field of dengue fever.

Objective: To evaluate the trapping effectiveness of different baits for flies, and provide a scientific basis for ecological surveillance and control of fly populations. Methods: From September to October 2024, sweet and sour bait, carrion bait, fruit bait, and commercial attractants were used as lures in the Dabie Mountain area of Anhui Province to compare their fly-trapping effects via cage trapping. Data were organized and summarized using Excel 2021. Kruskal-Wallis H tests and Mann-Whitney U tests were conducted in R 4.4.0 software to assess the differences in the density of trapped flies among the baits. The Chi-square test was used to analyze the differences in attractive effect of the baits on flies from different fly families. Charts were generated using Origin 2022. Results: The median fly-trapping densities of carrion bait, sweet and sour bait, fruit bait, and commercial attractant were 53.27, 3.51, 1.73, and 1.28 individuals/cage, respectively. There were statistically significant differences in the median fly-trapping densities among different baits (H=34.176, P < 0.001), while no significant differences were found in the pairwise comparisons of median fly-trapping densities among the sweet and sour bait, fruit bait, and commercial attractant (all P > 0.05). Sweet and sour bait attracted the greatest number of fly species (53 species), followed by carrion bait (44 species). Commercial attractant and fruit bait demonstrated relatively poor trapping effectiveness and attracted 36 and 35 species, respectively. Chrysomya megacephala was the most frequently captured species across all four baits. Different fly species showed varying preferences for bait types. Except for Drosophilidae, Scathophagidae, and Platystomatidae, the trapping effectiveness of the four baits on different fly families differed significantly (all P < 0.05). Conclusions: Combining carrion bait with sweet and sour bait is recommended in routine surveillance to enhance the representativeness of the trapped fly community. For specific species, specialized commercial attractants and fruit bait may be selected.

Objective: To investigate the status of viruses carried in the intestinal tissues of bats inhabiting Quzhou, Zhejiang Province, China, and provide a scientific basis for formulating local public health strategies. Methods: From August to October 2023, 167 bats were captured at 6 sampling sites in Quzhou. Taxonomic identification revealed 94 individuals as Rhinolophus sinicus and 73 as Hipposideros armiger. Rectal samples (including fecal matter) were collected via dissection. At each of the 6 sampling sites, 50 μg each of intestinal tissue samples from 24 randomly selected bats were pooled into a composite sample. DNA and RNA were extracted using the AllPrep Power Viral DNA/RNA Kit, followed by the construction of an rRNA-depleted RNA transcriptome library and a DNA metagenomic library. The extracted nucleic acid samples were subjected to Illumina sequencing. High-quality sequencing data were generated using fastp 0.23.2. Virus-associated reads were retrieved from the high-quality data using Centrifuge 1.0.4, Bowtie2 2.5.1, and SortMeRNA 4.3.6. After assembly with metaSPAdes 3.15.5, annotations were performed against viral nucleotide and amino acid databases using BLASTn 2.14.0 and DIAMOND Blastx 2.1.8.162, respectively. An alpha diversity analysis was conducted using the Vegan package in R Studio 4.3.3.3, beta diversity was analyzed via principal coordinate analysis, and the pheatmap package was employed for abundance analysis. Welch's t-test, Mann-Whitney U test, Kruskal-Wallis H test, Dunn's test, and permutational multivariate analysis of variance were performed using R Studio 4.3.3.3 to compare the differences in virus carriage between R. sinicus and H. armiger. Results: Illumina sequencing analysis was conducted on bat intestinal tissue samples, yielding 13 522-187 260 sequences from the RNA virome, and annotations identified 25 RNA viral families. For the DNA virome, 105 553-177 241 sequences were obtained, and 35 DNA viral families were annotated. At the species level of RNA and DNA viruses, R. sinicus showed higher alpha diversity compared to H. armiger. However, Welch's t-test indicated that the differences were not significant (for RNA viruses at the species level: Shannon index, t=2.093, P=0.110; Simpson index, t=2.121, P=0.129; for DNA viruses at the species level: Shannon index, t=1.356, P=0.247; Simpson index, t=1.585, P=0.215). Bray-Curtis distance showed no significant differences between RNA and DNA viruses (RNA viruses: F=2.305, R²=0.366, P=0.188; DNA viruses: F=1.437, R²=0.264, P=0.175). The abundance of Retroviridae was significantly higher in R. sinicus tha in H. armiger (U=2.004, P=0.002). There was a significant difference in the abundance of Inoviridae among different samples (H=10.301, P=0.035), and the abundance of Inoviridae in bat samples from Longyou County was significantly lower than those in samples from other counties (cities and districts) (all P < 0.05). Conclusions: The intestinal virus communities in bats from Quzhou, Zhejiang Province exhibit high diversity. There is no significant difference in the number of viral species about RNA and DNA virus carried between R. sinicus and H. armiger. Their RNA virome community structures show obvious clustering by host species, while DNA viromes show no such pattern..

Objective: To investigate the current status of overwintering breeding sites of Aedes albopictus and its influencing factors in Keqiao District, Shaoxing, Zhejiang Province, and provide a scientific basis for developing precise and effective early mosquito vector control strategies. Methods: In February 2025, a stratified cluster random sampling method was employed to select 12 survey sites across 6 towns/streets within Keqiao District, where samples were collected from various types of water-holding containers. In the laboratory, the samples were incubated for three weeks with a photoperiod (L∶D) of 14 h∶10 h, a temperature of (26±1)℃, and a relative humidity of (65±5)%. The hatching of Ae. albopictus eggs was observed. Statistical analysis was performed using SPSS 27.0. Chi-square tests and binary logistic regression were applied to analyze factors influencing the positive rate of overwintering eggs. Results: A total of 236 samples were collected, and the positive rate of Ae. albopictus overwintering eggs was 18.64% (44/236). Univariable analysis revealed that the following factors were significantly associated with differences in the positive rate of overwintering eggs: region, whether it was a previous epidemic focus, container type, habitat, container water volume, turbidity, and pH value (all P < 0.05). However, the presence or absence of co-inhabiting organisms was not significant (χ²=2.793, P=0.095). Multivariable analysis indicated that the risks of overwintering egg presence in urban and suburban areas were 5.05 [95% confidence interval (CI): 1.52-16.81] times and 4.68 (95%CI: 1.49-14.70) times, respectively, that in rural areas. The risk of overwintering egg presence in vegetated containers was 8.73 (95%CI: 1.02-75.10) times that in fixed containers. The risk of overwintering egg presence in water with turbidity ≤5 was 2.92 (95%CI: 1.20-7.10) times that in water with turbidity > 5. Conclusions: The positive rates of Ae. albopictus overwintering eggs in Keqiao District, Shaoxing, were at relatively high levels. Mosquito vector control efforts in early spring should adopt a targeted strategy with urban and suburban areas as key regions, implement village and residential grid-based management, and emphasize the cleanup of small clear-water containers in residential areas (e.g., flowerpot trays and idle containers). In public education, it is necessary to emphasize that clear water environments are also suitable for Ae. albopictus breeding, and effectively reduce the population base of Ae. albopictus from the source.

Objective: To investigate deficiencies in tick-borne diseases prevention behaviors among residents in the mountainous areas of southwest Chongqing, China, identify their influencing factors, and provide evidence for targeted interventions. Methods: A cross-sectional questionnaire survey was conducted between March and April 2025 among residents of the Xituo area of Shizhu Tujia Autonomous County, Chongqing to assess their tick-borne disease prevention behaviors, knowledge, and belief perception. Data were analyzed using descriptive analysis, t-test, analysis of variance, and a quasi-Poisson generalized linear regression model. The focus was on exploring the influence of the core dimensions of the health belief model, knowledge, demographic variables, and socioeconomic factors on tick-borne disease prevention behaviors. Results: A total of 844 resident questionnaires was included in the analysis. 49.52% (418/844) of the residents every time/frequently wore long sleeves and trousers when engaging in high-risk activities. Preventive behaviors requiring additional economic and time investment were relatively lacking, for example, only 25.71% (217/844) of residents checked their bodies, showered, and washed their clothes every time/frequently after contact with animals infested by ticks. 92.06% (777/844) of residents possessed basic tick identification skills, 37.56% (527/844) were aware that ticks can transmit diseases, 40.17% (339/844) knew the correct method for removing ticks, 37.08% (313/844) knew that tick-borne diseases can be transmitted through bodily fluids, and 37.08% (313/844) knew that tick-borne diseases can be fatal. Barrier perception [adjusted odds ratio (aOR)=1.25, 95% confidence interval (CI): 1.16-1.35] and risk perception (aOR=1.09, 95%CI: 1.02-1.16) consistently exerted stable positive effects in multivariable regression models with and without interaction terms. Fear perception interacted with knowledge to enhance preventive behaviors (aOR=1.02, 95%CI: 1.01-1.03), whereas interacted with risk perception to inhibit preventive behaviors (aOR=0.97, 95%CI: 0.96-0.99). In addition, 37.68% (318/844) of residents had only average confidence in their ability to prevent tick-borne diseases. A monthly household income of 3 000-6 000 yuan (aOR=1.18, 95%CI: 1.05-1.32) improved preventive behavior, but there was no statistically significant association for either education levels or higher income with preventive behaviors (all P > 0.05). Conclusions: The core dilemma of tick-borne disease prevention behavioral deficits of residents in Xituo area of Shizhu County, Chongqing lies in knowledge gaps and the negative effect of fear perception. Therefore, interventions should focus on promoting self-efficacy, providing cognitive education, and specifically addressing financial and facility barriers.