Haemaphysalis ticks are pathogenic vectors that threaten human and animal health and were identified in Chongming,the third largest island in China.To understand the distribution of these ticks and determine their pot...Haemaphysalis ticks are pathogenic vectors that threaten human and animal health and were identified in Chongming,the third largest island in China.To understand the distribution of these ticks and determine their potential invasion risk,this study aimed to identify the habitat suitability of the dominant tick H.flava based on natural environmental factors.Geographic information system(GIS)images were combined with sample points from tick investigations to map the spatial distribution of H.flava.Data on 19 bioclimatic variables,environmental variables,and satellite-based landscapes of Chongming Island were retrieved to create a landcover map related to natural environmental determinants of H.flava.These data included 38 sites associated with the vectors to construct species distribution models with MaxEnt,a model based on the maximum entropy principle,and to predict habitat suitability for H.flava on Chongming Island in 2050 and 2070 under different climate scenarios.The model performed well in predicting the H.flava distribution,with a training area under the curve of 0.84 and a test area under the curve of 0.73.A habitat suitability map of the whole study area was created for H.flava.The resulting map and natural environment analysis highlighted the importance of the normalized difference vegetation index and precipitation in the driest month for the bioecology of H.flava,with 141.61 km^(2)(11.77%),282.94 km^(2)(23.35%),and 405.30 km^(2)(33.69%)of highly,moderately,and poorly suitable habitats,respectively.The distribution decreased by 135.55 km^(2) and 138.82 km^(2) in 2050 and 2070,respectively,under the shared socioeconomic pathway(SSP)1.2.6 climate change scenario.However,under SSP 5.8.5,the total area will decrease by 128.5 km^(2) in 2050 and increase by 151.64 km^(2) in 2070.From a One Health perspective,this study provides good knowledge that will guide tick control efforts to prevent the spread of Haemaphysalis ticks or transmission risk of Haemaphysalis-borne infections at the human-animal-environment interface on the island.展开更多
Background:A One Health approach has been increasingly mainstreamed by the international community, as it provides for holistic thinking in recognizing the close links and inter-dependence of the health of humans, ani...Background:A One Health approach has been increasingly mainstreamed by the international community, as it provides for holistic thinking in recognizing the close links and inter-dependence of the health of humans, animals and the environment. However, the dearth of real-world evidence has hampered application of a One Health approach in shaping policies and practice. This study proposes the development of a potential evaluation tool for One Health performance, in order to contribute to the scientific measurement of One Health approach and the identification of gaps where One Health capacity building is most urgently needed.Methods:We describe five steps towards a global One Health index (GOHI), including (i) framework formulation;(ii) indicator selection;(iii) database building;(iv) weight determination;and (v) GOHI scores calculation. A cell-like framework for GOHI is proposed, which comprises an external drivers index (EDI), an intrinsic drivers index (IDI) and a core drivers index (CDI). We construct the indicator scheme for GOHI based on this framework after multiple rounds of panel discussions with our expert advisory committee. A fuzzy analytical hierarchy process is adopted to determine the weights for each of the indicators.Results:The weighted indicator scheme of GOHI comprises three first-level indicators, 13 second-level indicators, and 57 third-level indicators. According to the pilot analysis based on the data from more than 200 countries/territories the GOHI scores overall are far from ideal (the highest score of 65.0 out of a maximum score of 100), and we found considerable variations among different countries/territories (31.8–65.0). The results from the pilot analysis are consistent with the results from a literature review, which suggests that a GOHI as a potential tool for the assessment of One Health performance might be feasible.Conclusions:GOHI—subject to rigorous validation—would represent the world’s first evaluation tool that constructs the conceptual framework from a holistic perspective of One Health. Future application of GOHI might promote a common understanding of a strong One Health approach and provide reference for promoting effective measures to strengthen One Health capacity building. With further adaptations under various scenarios, GOHI, along with its technical protocols and databases, will be updated regularly to address current technical limitations, and capture new knowledge.展开更多
Background:Schistosomiasis control is striving forward to transmission interruption and even elimination,evidence-lead control is of vital importance to eliminate the hidden dan gers of schistosomiasis.This study atte...Background:Schistosomiasis control is striving forward to transmission interruption and even elimination,evidence-lead control is of vital importance to eliminate the hidden dan gers of schistosomiasis.This study attempts to ide ntify high risk areas of schistosomiasis in China by using in formation value and machine learni ng.展开更多
Background:Pulmonary tuberculosis(PTB,both smear positive and smear negative)is an airborne infectious disease of major public health concern in China and other parts of the world where PTB endemicity is reported.This...Background:Pulmonary tuberculosis(PTB,both smear positive and smear negative)is an airborne infectious disease of major public health concern in China and other parts of the world where PTB endemicity is reported.This study aims at identifying PTB spatio-temporal clusters and associated risk factors in Zhaotong prefecture-level city,located in southwest China,where the PTB notification rate was higher than the average rate in the entire country.Methods:Space-time scan statistics were carried out using PTB registered data in the nationwide TB online registration system from 2011 to 2015,to identify spatial clusters.PTB patients diagnosed between October 2015 and February 2016 were selected and a structured questionnaire was administered to collect a set of variables that includes socio-economic status,behavioural characteristics,local environmental and biological characteristics.Based on the discovery of detailed town-level spatio-temporal PTB clusters,we divided selected subjects into two groups including the cases that resides within and outside identified clusters.Then,logistic regression analysis was applied comparing the results of variables between the two groups.Results:A total of 1508 subjects consented and participated in the survey.Clusters for PTB cases were identified in 38 towns distributed over south-western Zhaotong.Logistic regression analysis showed that history of chronic bronchitis(OR=3.683,95%CI:2.180-6.223),living in an urban area(OR=5.876,95%CI:2.381-14.502)and using coal as the main fuel(OR=9.356,95%CI:5.620-15.576)were independently associated with clustering.While,not smoking(OR=0.340,95%CI:0.137-0.843)is the protection factor of spatial clustering.Conclusions:We found PTB specially clustered in south-western Zhaotong.The strong associated factors influencing the PTB spatial cluster including:the history of chronic bronchitis,living in the urban area,smoking and the use of coal as the main fuel for cooking and heating.Therefore,efforts should be made to curtail these associated factors.展开更多
Background:Mosquito-based arbovirus surveillance can serve as an early warning in evaluating the status of mosquito-borne virus prevalence and thus prevent local outbreaks.Although Tengchong County in Yunnan Province-...Background:Mosquito-based arbovirus surveillance can serve as an early warning in evaluating the status of mosquito-borne virus prevalence and thus prevent local outbreaks.Although Tengchong County in Yunnan Province-which borders Myanmar-is abundant and diverse in mosquitoes,very few mosquito-based arbovirus investigations have been conducted in the recent decade.Herein,this study aims to evaluate the presence and the diffusion of mosquito-borne pathogens,currently prevalent in this region.展开更多
Background: Malaria cases have declined significantly along the China-Myanmar border in the past 10 years and this region is going through a process from control to elimination.The aim of this study is to investigate ...Background: Malaria cases have declined significantly along the China-Myanmar border in the past 10 years and this region is going through a process from control to elimination.The aim of this study is to investigate the epidemiology of malaria along the border,will identify challenges in the progress from control to elimination.Methods:: National reported malaria cases from China and Myanmar,along with the data of 18 Chinese border counties and 23 townships in Myanmar were obtained from a web-based diseases information reporting system in China and the national malaria control program of Myanmar,respectively.Epidemiological data was analyzed,including the number of reported cases,annual parasite index and proportion of vivax infection.Spatial mapping of the annual parasite index(API)at county or township level in 2014 and 2018 was performed by ArcGIS.The relationship of malaria endemicity on both sides of the border was evaluated by regression analysis.Results: The number of reported malaria cases and API declined in the border counties or townships.In 2014,392 malaria cases were reported from 18 Chinese border counties,including 8.4%indigenous cases and 91.6%imported cases,while the highest API(0.11)was occurred in Yingjiang County.There have been no indigenous cases reported since 2017,but 164 imported cases were reported in 2018 and 97.6%were imported from Myanmar.The average API in 2014 in 23 Myanmar townships was significantly greater than that of 18 Chinese counties(P<0.01).However,the API decreased significantly in Myanmar side from 2014 to 2018(P<0.01).The number of townships with an API between 0 and 1 increased to 15 in 2018,compared to only five in 2014,while still four townships had API>10.Plasmodium vivax was the predominant species along the border.The number of reported malaria cases and the proportion of vivax infection in the 18 Chinese counties were strongly correlated with those of the 23 Myanmar townships(P<0.05).Conclusions: Malaria elimination is approaching along the China-Myanmar border.However,in order to achieve the malaria elimination in this region and prevent the re-establishment of malaria in China after elimination,continued political,financial and scientific commitment is required.展开更多
Climate change has been known to cause variations in the geographically suitable areas for the schistosome-transmitting Oncomelania hupensis(O.hupensis).The spread of snails not only depends on the degree of warming b...Climate change has been known to cause variations in the geographically suitable areas for the schistosome-transmitting Oncomelania hupensis(O.hupensis).The spread of snails not only depends on the degree of warming but also on the socioeconomic development of the next few decades.Shared socioeconomic pathways(SSPs)published by CMIP6 consider carbon emission pathways as well as influences of distinct types of social development and land use on the regional climate,providing the possibility to accurately evaluate the impact of socioeconomic development and climate variation on the spread of O.hupensis.This study employed SSP126,SSP245,SSP370,and SSP585 and the correlative approach to explore the impacts of climate change and socioeconomic development on the potential diffusion areas for O.hupensis in China.The results exhibited strong evidence that O.hupensis will spread in the north of the middle and lower reaches of the Yangtze River and disappear from a small part of its current southern habitat,whereas in Sichuan and Yunnan,O.hupensis may spread slightly to the southeast.The projection also demonstrated that fossil fuel-driven development(SSP585)will be more conducive to the spread of O.hupensis breeding sites in the 2030s,whereas the continuous increase in snail breeding habitats under the regional rivalry path(SSP370)may lead to great challenges in snail control in the long term(2020-2080).展开更多
Background One Health approach is crucial to tackling complex global public health threats at the interface of humans, animals, and the environment. As outlined in the One Health Joint Plan of Action, the internationa...Background One Health approach is crucial to tackling complex global public health threats at the interface of humans, animals, and the environment. As outlined in the One Health Joint Plan of Action, the international One Health community includes stakeholders from different sectors. Supported by the Bill & Melinda Gates Foundation, an academic community for One Health action has been proposed with the aim of promoting the understanding and real-world implementation of One Health approach and contribution towards the Sustainable Development Goals for a healthy planet.Main text The proposed academic community would contribute to generating high-quality scientific evidence, distilling local experiences as well as fostering an interconnected One Health culture and mindset, among various stakeholders on different levels and in all sectors. The major scope of the community covers One Health governance, zoonotic diseases, food security, antimicrobial resistance, and climate change along with the research agenda to be developed. The academic community will be supported by two committees, including a strategic consultancy committee and a scientific steering committee, composed of influential scientists selected from the One Health information database. A workplan containing activities under six objectives is proposed to provide research support, strengthen local capacity, and enhance global participation.Conclusions The proposed academic community for One Health action is a crucial step towards enhancing communication, coordination, collaboration, and capacity building for the implementation of One Health. By bringing eminent global experts together, the academic community possesses the potential to generate scientific evidence and provide advice to local governments and international organizations, enabling the pursuit of common goals, collaborative policies, and solutions to misaligned interests.展开更多
Background Chongming Island in China serves as a breeding and shelter point on the East Asian–Australasian Flyway.The resting frequency of migratory birds,abundance of mosquito populations,and the popular domestic po...Background Chongming Island in China serves as a breeding and shelter point on the East Asian–Australasian Flyway.The resting frequency of migratory birds,abundance of mosquito populations,and the popular domestic poultry industry pose a potential risk of mosquito-borne zoonotic diseases.The aim of this study is to explore the role of migratory birds in the spread of mosquito-borne pathogens and their prevalent status on the island.Methods We conducted a mosquito-borne pathogen surveillance in 2021,in Chongming,Shanghai,China.Approxi‑mately 67,800 adult mosquitoes belonging to ten species were collected to investigate the presence of faviviruses,alphaviruses,and orthobunyaviruses by RT-PCR.Genetic and phylogenetic analyses were conducted to explore the virus genotype and potential nature source.Serological survey was performed by ELISA to characterize Tembusu virus(TMUV)infection among domestic poultry.Results Two strains of TMUV and Chaoyang virus(CHAOV)and 47 strains of Quang Binh virus(QBV)were detected in 412 mosquito pools,with the infection rate of 0.16,0.16,and 3.92 per 1000 Culex tritaeniorhynchus,respectively.Fur‑thermore,TMUVs viral RNA was found in serum samples of domestic chickens and faecal samples of migratory birds.Antibodies against TMUV were detected in domestic avian serum samples,generally ranging from 44.07%in pigeons to 55.71%in ducks.Phylogenetic analyses indicated that the TMUV detected in Chongming belonged to Cluster 3,Southeast Asia origin,and most closely related to the CTLN strain,which caused a TMUV outbreak in chickens in Guangdong Province in 2020,but distant from strains obtained previously in Shanghai,which were involved in the 2010 TMUV outbreak in China.Conclusions We speculate that the TMUV was imported to Chongming Island through long-distance spreading by migratory birds from Southeast Asia,followed by spill over and transmission in mosquitoes and domestic avian species,threatening the local domestic poultry.In addition,the expansion and prevalence of insect-specifc favivi‑ruses and its simultaneous circulation with mosquito-borne virus are worthy of close attention and further study.展开更多
Background:The prevalence of schistosomiasis remains a key public health issue in China.Jiangling County in Hubei Province is a typical lake and marshland endemic area.The pattern analysis of schistosomiasis prevalenc...Background:The prevalence of schistosomiasis remains a key public health issue in China.Jiangling County in Hubei Province is a typical lake and marshland endemic area.The pattern analysis of schistosomiasis prevalence in Jiangling County is of significant importance for promoting schistosomiasis surveillance and control in the similar endemic areas.Methods:The dataset was constructed based on the annual schistosomiasis surveillance as well the socio-economic data in Jiangling County covering the years from 2009 to 2013.A village clustering method modified from the K-mean algorithm was used to identify different types of endemic villages.For these identified village clusters,a matrix-based predictive model was developed by means of exploring the one-step backward temporal correlation inference algorithm aiming to estimate the predicative correlations of schistosomiasis prevalence among different years.Field sampling of faeces from domestic animals,as an indicator of potential schistosomiasis prevalence,was carried out and the results were used to validate the results of proposed models and methods.Results:The prevalence of schistosomiasis in Jiangling County declined year by year.The total of 198 endemic villages in Jiangling County can be divided into four clusters with reference to the 5 years’occurrences of schistosomiasis in human,cattle and snail populations.For each identified village cluster,a predictive matrix was generated to characterize the relationships of schistosomiasis prevalence with the historic infection level as well as their associated impact factors.Furthermore,the results of sampling faeces from the front field agreed with the results of the identified clusters of endemic villages.Conclusion:The results of village clusters and the predictive matrix can be regard as the basis to conduct targeted measures for schistosomiasis surveillance and control.Furthermore,the proposed models and methods can be modified to investigate the schistosomiasis prevalence in other regions as well as be used for investigating other parasitic diseases.展开更多
Background China is progressing towards the goal of schistosomiasis elimination,but there are still some problems,such as difficult management of infection source and snail control.This study aimed to develop deep lea...Background China is progressing towards the goal of schistosomiasis elimination,but there are still some problems,such as difficult management of infection source and snail control.This study aimed to develop deep learning models with high-resolution remote sensing images for recognizing and monitoring livestock bovine,which is an intermediate source of Schistosoma japonicum infection,and to evaluate the effectiveness of the models for real-world application.Methods The dataset of livestock bovine’s spatial distribution was collected from the Chinese National Platform for Common Geospatial Information Services.The high-resolution remote sensing images were further divided into training data,test data,and validation data for model development.Two recognition models based on deep learning methods(ENVINet5 and Mask R-CNN)were developed with reference to the training datasets.The performance of the developed models was evaluated by the performance metrics of precision,recall,and F1-score.Results A total of 50 typical image areas were selected,1125 bovine objectives were labeled by the ENVINet5 model and 1277 bovine objectives were labeled by the Mask R-CNN model.For the ENVINet5 model,a total of 1598 records of bovine distribution were recognized.The model precision and recall were 81.9%and 80.2%,respectively.The F1 score was 0.81.For the Mask R-CNN mode,1679 records of bovine objectives were identified.The model precision and recall were 87.3%and 85.2%,respectively.The F1 score was 0.87.When applying the developed models to real-world schistosomiasis-endemic regions,there were 63 bovine objectives in the original image,53 records were extracted using the ENVINet5 model,and 57 records were extracted using the Mask R-CNN model.The successful recognition ratios were 84.1%and 90.5%for the respectively developed models.Conclusion The ENVINet5 model is very feasible when the bovine distribution is low in structure with few samples.The Mask R-CNN model has a good framework design and runs highly efficiently.The livestock recognition models developed using deep learning methods with high-resolution remote sensing images accurately recognize the spatial distribution of livestock,which could enable precise control of schistosomiasis.展开更多
基金supported in part by The International Joint Laboratory on Tropical Diseases Control in the Greater Mekong Subregion fund(21410750200)the Science and Technology Commission of Shanghai,China and The Science and Technology Innovation Project fund of the School of Global Health,Shanghai Jiao Tong University School of Medicine(SGHKJCX2021-05,SGHKJCX2021-04),China.
文摘Haemaphysalis ticks are pathogenic vectors that threaten human and animal health and were identified in Chongming,the third largest island in China.To understand the distribution of these ticks and determine their potential invasion risk,this study aimed to identify the habitat suitability of the dominant tick H.flava based on natural environmental factors.Geographic information system(GIS)images were combined with sample points from tick investigations to map the spatial distribution of H.flava.Data on 19 bioclimatic variables,environmental variables,and satellite-based landscapes of Chongming Island were retrieved to create a landcover map related to natural environmental determinants of H.flava.These data included 38 sites associated with the vectors to construct species distribution models with MaxEnt,a model based on the maximum entropy principle,and to predict habitat suitability for H.flava on Chongming Island in 2050 and 2070 under different climate scenarios.The model performed well in predicting the H.flava distribution,with a training area under the curve of 0.84 and a test area under the curve of 0.73.A habitat suitability map of the whole study area was created for H.flava.The resulting map and natural environment analysis highlighted the importance of the normalized difference vegetation index and precipitation in the driest month for the bioecology of H.flava,with 141.61 km^(2)(11.77%),282.94 km^(2)(23.35%),and 405.30 km^(2)(33.69%)of highly,moderately,and poorly suitable habitats,respectively.The distribution decreased by 135.55 km^(2) and 138.82 km^(2) in 2050 and 2070,respectively,under the shared socioeconomic pathway(SSP)1.2.6 climate change scenario.However,under SSP 5.8.5,the total area will decrease by 128.5 km^(2) in 2050 and increase by 151.64 km^(2) in 2070.From a One Health perspective,this study provides good knowledge that will guide tick control efforts to prevent the spread of Haemaphysalis ticks or transmission risk of Haemaphysalis-borne infections at the human-animal-environment interface on the island.
基金The project was supported by China Medical Board(no.20-365)Shanghai Jiao Tong University Integrated Innovation Fund(no.2020-01).
文摘Background:A One Health approach has been increasingly mainstreamed by the international community, as it provides for holistic thinking in recognizing the close links and inter-dependence of the health of humans, animals and the environment. However, the dearth of real-world evidence has hampered application of a One Health approach in shaping policies and practice. This study proposes the development of a potential evaluation tool for One Health performance, in order to contribute to the scientific measurement of One Health approach and the identification of gaps where One Health capacity building is most urgently needed.Methods:We describe five steps towards a global One Health index (GOHI), including (i) framework formulation;(ii) indicator selection;(iii) database building;(iv) weight determination;and (v) GOHI scores calculation. A cell-like framework for GOHI is proposed, which comprises an external drivers index (EDI), an intrinsic drivers index (IDI) and a core drivers index (CDI). We construct the indicator scheme for GOHI based on this framework after multiple rounds of panel discussions with our expert advisory committee. A fuzzy analytical hierarchy process is adopted to determine the weights for each of the indicators.Results:The weighted indicator scheme of GOHI comprises three first-level indicators, 13 second-level indicators, and 57 third-level indicators. According to the pilot analysis based on the data from more than 200 countries/territories the GOHI scores overall are far from ideal (the highest score of 65.0 out of a maximum score of 100), and we found considerable variations among different countries/territories (31.8–65.0). The results from the pilot analysis are consistent with the results from a literature review, which suggests that a GOHI as a potential tool for the assessment of One Health performance might be feasible.Conclusions:GOHI—subject to rigorous validation—would represent the world’s first evaluation tool that constructs the conceptual framework from a holistic perspective of One Health. Future application of GOHI might promote a common understanding of a strong One Health approach and provide reference for promoting effective measures to strengthen One Health capacity building. With further adaptations under various scenarios, GOHI, along with its technical protocols and databases, will be updated regularly to address current technical limitations, and capture new knowledge.
文摘Background:Schistosomiasis control is striving forward to transmission interruption and even elimination,evidence-lead control is of vital importance to eliminate the hidden dan gers of schistosomiasis.This study attempts to ide ntify high risk areas of schistosomiasis in China by using in formation value and machine learni ng.
基金This study was supported by the National Special Science and Technology Project for Major Infectious Diseases of China(Grant No.2012ZX10004–220,2016ZX10004222–006)the China-UK Global Health Support Programme(Grant No.GHSP-CS-OP1–01)+1 种基金The Forth Round of Three-Year Public Health Action Plan of Shanghai,China(No.15GWZK0101,GWIV-29)The funders had no role in the study design,data collection and analysis,decision to publish,or preparation of the paper.
文摘Background:Pulmonary tuberculosis(PTB,both smear positive and smear negative)is an airborne infectious disease of major public health concern in China and other parts of the world where PTB endemicity is reported.This study aims at identifying PTB spatio-temporal clusters and associated risk factors in Zhaotong prefecture-level city,located in southwest China,where the PTB notification rate was higher than the average rate in the entire country.Methods:Space-time scan statistics were carried out using PTB registered data in the nationwide TB online registration system from 2011 to 2015,to identify spatial clusters.PTB patients diagnosed between October 2015 and February 2016 were selected and a structured questionnaire was administered to collect a set of variables that includes socio-economic status,behavioural characteristics,local environmental and biological characteristics.Based on the discovery of detailed town-level spatio-temporal PTB clusters,we divided selected subjects into two groups including the cases that resides within and outside identified clusters.Then,logistic regression analysis was applied comparing the results of variables between the two groups.Results:A total of 1508 subjects consented and participated in the survey.Clusters for PTB cases were identified in 38 towns distributed over south-western Zhaotong.Logistic regression analysis showed that history of chronic bronchitis(OR=3.683,95%CI:2.180-6.223),living in an urban area(OR=5.876,95%CI:2.381-14.502)and using coal as the main fuel(OR=9.356,95%CI:5.620-15.576)were independently associated with clustering.While,not smoking(OR=0.340,95%CI:0.137-0.843)is the protection factor of spatial clustering.Conclusions:We found PTB specially clustered in south-western Zhaotong.The strong associated factors influencing the PTB spatial cluster including:the history of chronic bronchitis,living in the urban area,smoking and the use of coal as the main fuel for cooking and heating.Therefore,efforts should be made to curtail these associated factors.
文摘Background:Mosquito-based arbovirus surveillance can serve as an early warning in evaluating the status of mosquito-borne virus prevalence and thus prevent local outbreaks.Although Tengchong County in Yunnan Province-which borders Myanmar-is abundant and diverse in mosquitoes,very few mosquito-based arbovirus investigations have been conducted in the recent decade.Herein,this study aims to evaluate the presence and the diffusion of mosquito-borne pathogens,currently prevalent in this region.
基金This work was supported by the Natural Science Foundation of Shanghai(No.18ZR1443400)the National Important Scientific&Technological Project 2018ZX10101002-002)the Forge Ahead Together for Elimination Towards Malaria free China–Myanmar border and National Malaria Elimination Program of China.
文摘Background: Malaria cases have declined significantly along the China-Myanmar border in the past 10 years and this region is going through a process from control to elimination.The aim of this study is to investigate the epidemiology of malaria along the border,will identify challenges in the progress from control to elimination.Methods:: National reported malaria cases from China and Myanmar,along with the data of 18 Chinese border counties and 23 townships in Myanmar were obtained from a web-based diseases information reporting system in China and the national malaria control program of Myanmar,respectively.Epidemiological data was analyzed,including the number of reported cases,annual parasite index and proportion of vivax infection.Spatial mapping of the annual parasite index(API)at county or township level in 2014 and 2018 was performed by ArcGIS.The relationship of malaria endemicity on both sides of the border was evaluated by regression analysis.Results: The number of reported malaria cases and API declined in the border counties or townships.In 2014,392 malaria cases were reported from 18 Chinese border counties,including 8.4%indigenous cases and 91.6%imported cases,while the highest API(0.11)was occurred in Yingjiang County.There have been no indigenous cases reported since 2017,but 164 imported cases were reported in 2018 and 97.6%were imported from Myanmar.The average API in 2014 in 23 Myanmar townships was significantly greater than that of 18 Chinese counties(P<0.01).However,the API decreased significantly in Myanmar side from 2014 to 2018(P<0.01).The number of townships with an API between 0 and 1 increased to 15 in 2018,compared to only five in 2014,while still four townships had API>10.Plasmodium vivax was the predominant species along the border.The number of reported malaria cases and the proportion of vivax infection in the 18 Chinese counties were strongly correlated with those of the 23 Myanmar townships(P<0.05).Conclusions: Malaria elimination is approaching along the China-Myanmar border.However,in order to achieve the malaria elimination in this region and prevent the re-establishment of malaria in China after elimination,continued political,financial and scientific commitment is required.
基金supported by the Fifth Round of the Three-Year Public Health Action Plan of Shanghai(GWV-10.1-XK13)the National Natural Science Foundation of China(No.32161143036)the National Special Science and Technology Project for Major Infection Diseases of China(2016ZX10004222-004).
文摘Climate change has been known to cause variations in the geographically suitable areas for the schistosome-transmitting Oncomelania hupensis(O.hupensis).The spread of snails not only depends on the degree of warming but also on the socioeconomic development of the next few decades.Shared socioeconomic pathways(SSPs)published by CMIP6 consider carbon emission pathways as well as influences of distinct types of social development and land use on the regional climate,providing the possibility to accurately evaluate the impact of socioeconomic development and climate variation on the spread of O.hupensis.This study employed SSP126,SSP245,SSP370,and SSP585 and the correlative approach to explore the impacts of climate change and socioeconomic development on the potential diffusion areas for O.hupensis in China.The results exhibited strong evidence that O.hupensis will spread in the north of the middle and lower reaches of the Yangtze River and disappear from a small part of its current southern habitat,whereas in Sichuan and Yunnan,O.hupensis may spread slightly to the southeast.The projection also demonstrated that fossil fuel-driven development(SSP585)will be more conducive to the spread of O.hupensis breeding sites in the 2030s,whereas the continuous increase in snail breeding habitats under the regional rivalry path(SSP370)may lead to great challenges in snail control in the long term(2020-2080).
文摘Background One Health approach is crucial to tackling complex global public health threats at the interface of humans, animals, and the environment. As outlined in the One Health Joint Plan of Action, the international One Health community includes stakeholders from different sectors. Supported by the Bill & Melinda Gates Foundation, an academic community for One Health action has been proposed with the aim of promoting the understanding and real-world implementation of One Health approach and contribution towards the Sustainable Development Goals for a healthy planet.Main text The proposed academic community would contribute to generating high-quality scientific evidence, distilling local experiences as well as fostering an interconnected One Health culture and mindset, among various stakeholders on different levels and in all sectors. The major scope of the community covers One Health governance, zoonotic diseases, food security, antimicrobial resistance, and climate change along with the research agenda to be developed. The academic community will be supported by two committees, including a strategic consultancy committee and a scientific steering committee, composed of influential scientists selected from the One Health information database. A workplan containing activities under six objectives is proposed to provide research support, strengthen local capacity, and enhance global participation.Conclusions The proposed academic community for One Health action is a crucial step towards enhancing communication, coordination, collaboration, and capacity building for the implementation of One Health. By bringing eminent global experts together, the academic community possesses the potential to generate scientific evidence and provide advice to local governments and international organizations, enabling the pursuit of common goals, collaborative policies, and solutions to misaligned interests.
文摘Background Chongming Island in China serves as a breeding and shelter point on the East Asian–Australasian Flyway.The resting frequency of migratory birds,abundance of mosquito populations,and the popular domestic poultry industry pose a potential risk of mosquito-borne zoonotic diseases.The aim of this study is to explore the role of migratory birds in the spread of mosquito-borne pathogens and their prevalent status on the island.Methods We conducted a mosquito-borne pathogen surveillance in 2021,in Chongming,Shanghai,China.Approxi‑mately 67,800 adult mosquitoes belonging to ten species were collected to investigate the presence of faviviruses,alphaviruses,and orthobunyaviruses by RT-PCR.Genetic and phylogenetic analyses were conducted to explore the virus genotype and potential nature source.Serological survey was performed by ELISA to characterize Tembusu virus(TMUV)infection among domestic poultry.Results Two strains of TMUV and Chaoyang virus(CHAOV)and 47 strains of Quang Binh virus(QBV)were detected in 412 mosquito pools,with the infection rate of 0.16,0.16,and 3.92 per 1000 Culex tritaeniorhynchus,respectively.Fur‑thermore,TMUVs viral RNA was found in serum samples of domestic chickens and faecal samples of migratory birds.Antibodies against TMUV were detected in domestic avian serum samples,generally ranging from 44.07%in pigeons to 55.71%in ducks.Phylogenetic analyses indicated that the TMUV detected in Chongming belonged to Cluster 3,Southeast Asia origin,and most closely related to the CTLN strain,which caused a TMUV outbreak in chickens in Guangdong Province in 2020,but distant from strains obtained previously in Shanghai,which were involved in the 2010 TMUV outbreak in China.Conclusions We speculate that the TMUV was imported to Chongming Island through long-distance spreading by migratory birds from Southeast Asia,followed by spill over and transmission in mosquitoes and domestic avian species,threatening the local domestic poultry.In addition,the expansion and prevalence of insect-specifc favivi‑ruses and its simultaneous circulation with mosquito-borne virus are worthy of close attention and further study.
基金This work was supported by the National Natural Science Foundation of China(No.81101280)by the National Special Science and Technology Project for Major Infectious Diseases of China(Grant Nos.2012ZX10004-220,2016ZX10004222-004)+3 种基金the China UK Global Health Support Programme(GHSP-CS-OP101)the Forth Round of Three-Year Public Health Action Plan of Shanghai,China(No.15GWZK0101,GWIV-29)High Resolution Remote Sensing Monitoring Progect(No.10-Y30B11-9001-14/16)The open project from Key Laboratory of Parasite and Vector Biology,Ministry of Health.The funders had no role in study design,data collection and analysis,decision to publish,or preparation of the manuscript.
文摘Background:The prevalence of schistosomiasis remains a key public health issue in China.Jiangling County in Hubei Province is a typical lake and marshland endemic area.The pattern analysis of schistosomiasis prevalence in Jiangling County is of significant importance for promoting schistosomiasis surveillance and control in the similar endemic areas.Methods:The dataset was constructed based on the annual schistosomiasis surveillance as well the socio-economic data in Jiangling County covering the years from 2009 to 2013.A village clustering method modified from the K-mean algorithm was used to identify different types of endemic villages.For these identified village clusters,a matrix-based predictive model was developed by means of exploring the one-step backward temporal correlation inference algorithm aiming to estimate the predicative correlations of schistosomiasis prevalence among different years.Field sampling of faeces from domestic animals,as an indicator of potential schistosomiasis prevalence,was carried out and the results were used to validate the results of proposed models and methods.Results:The prevalence of schistosomiasis in Jiangling County declined year by year.The total of 198 endemic villages in Jiangling County can be divided into four clusters with reference to the 5 years’occurrences of schistosomiasis in human,cattle and snail populations.For each identified village cluster,a predictive matrix was generated to characterize the relationships of schistosomiasis prevalence with the historic infection level as well as their associated impact factors.Furthermore,the results of sampling faeces from the front field agreed with the results of the identified clusters of endemic villages.Conclusion:The results of village clusters and the predictive matrix can be regard as the basis to conduct targeted measures for schistosomiasis surveillance and control.Furthermore,the proposed models and methods can be modified to investigate the schistosomiasis prevalence in other regions as well as be used for investigating other parasitic diseases.
基金National Natural Science Foundation of China(No.32161143036,No.82173633,No.81960374)Science and Technology research project of Shanghai Municipal Health Commission(No.20194Y0359)National Key Research and Development Program of China(No.2021YFC2300800,2021YFC2300803)
文摘Background China is progressing towards the goal of schistosomiasis elimination,but there are still some problems,such as difficult management of infection source and snail control.This study aimed to develop deep learning models with high-resolution remote sensing images for recognizing and monitoring livestock bovine,which is an intermediate source of Schistosoma japonicum infection,and to evaluate the effectiveness of the models for real-world application.Methods The dataset of livestock bovine’s spatial distribution was collected from the Chinese National Platform for Common Geospatial Information Services.The high-resolution remote sensing images were further divided into training data,test data,and validation data for model development.Two recognition models based on deep learning methods(ENVINet5 and Mask R-CNN)were developed with reference to the training datasets.The performance of the developed models was evaluated by the performance metrics of precision,recall,and F1-score.Results A total of 50 typical image areas were selected,1125 bovine objectives were labeled by the ENVINet5 model and 1277 bovine objectives were labeled by the Mask R-CNN model.For the ENVINet5 model,a total of 1598 records of bovine distribution were recognized.The model precision and recall were 81.9%and 80.2%,respectively.The F1 score was 0.81.For the Mask R-CNN mode,1679 records of bovine objectives were identified.The model precision and recall were 87.3%and 85.2%,respectively.The F1 score was 0.87.When applying the developed models to real-world schistosomiasis-endemic regions,there were 63 bovine objectives in the original image,53 records were extracted using the ENVINet5 model,and 57 records were extracted using the Mask R-CNN model.The successful recognition ratios were 84.1%and 90.5%for the respectively developed models.Conclusion The ENVINet5 model is very feasible when the bovine distribution is low in structure with few samples.The Mask R-CNN model has a good framework design and runs highly efficiently.The livestock recognition models developed using deep learning methods with high-resolution remote sensing images accurately recognize the spatial distribution of livestock,which could enable precise control of schistosomiasis.
