With the aim to improve the level of monitoring and warning as well as the comprehensive control of rice blast disease, and to feasibly reduce the disease threat in Nanchong City, the methods of GPS and GIS, systemati...With the aim to improve the level of monitoring and warning as well as the comprehensive control of rice blast disease, and to feasibly reduce the disease threat in Nanchong City, the methods of GPS and GIS, systematical monitoring and field survey, rice blast resistance identification, physiologic races of rice blast monitoring, and meteorological data analysis were performed to study the occurrence and epidemic region division, precise demarcation and occurrence and epidemic regularity of rice blast in Nanchong City. This study first completed the epidemic region division and precise demarcation; first clarified the initial affection（beginning period） locations, occurrence characteristics, epidemic trends and characteristics; explicated the existence of four epidemic peak periods of rice blast in the field, where the damage areas of first peak period played a decisive role during the blast epidemic years; in late May, the cumulative occurrence areas and annual occurrence areas presented higher positive correlation with the correlation coefficient of 0.817;and established a prediction model of occurrence areas per year based on the disease field rate at the end of boot stages and the diseased plant rate at dough stages. The results of investigation on the impact factors investigation of blast disease in Nanchong in recent years suggested that the internal causes were the decrease or loss of blast resistance of the rice cultivars, as well as the increase of physiological races with strong resistance to rice blast and the emergence of new virulent physiologic varieties; the external causes were suitable temperature, too much rainy, and sunlight shortage. Between 2010 and 2015, the short-term forecast accuracy for rice blast in Nanchong was up to 100%, and medium-and long-term forecast accuracy was also up to 98% and 95%, respectively, which increased by 5-15% than that before 1997, thereby making the control effect of rice blast in Nanchong increased by 15-30%.展开更多
This manuscript introduces the convergence Epidemic Volatility Index(cEVI),a modifi-cation of the recently introduced Epidemic Volatility Index(EVI),as an early warning tool for emerging epidemic waves.cEVI has a simi...This manuscript introduces the convergence Epidemic Volatility Index(cEVI),a modifi-cation of the recently introduced Epidemic Volatility Index(EVI),as an early warning tool for emerging epidemic waves.cEVI has a similar architectural structure as EVI,but with an optimization process inspired by a Geweke diagnostic-type test.Our approach triggers an early warning based on a comparison of the most recently available window of data samples and a window based on the previous time frame.Application of cEVI to data from the COVID-19 pandemic data revealed steady performance in predicting early,intermediate epidemic waves and retaining a warning during an epidemic wave.Furthermore,we present two basic combinations of EVI and cEVI:(1)their disjunction cEVI+that respectively identifies waves earlier than the original index,(2)their conjunction cEVIthat results in higher accuracy.Combination of multiple warning systems could potentially create a surveillance umbrella that would result in early implementation of optimal outbreak interventions.展开更多
In order to realize monitoring and early warning and comprehensive management of wheat stripe rust and to reduce its occurrence in Nanchong City, the occurrence and epidemic regularity of wheat stripe rust in Nanchong...In order to realize monitoring and early warning and comprehensive management of wheat stripe rust and to reduce its occurrence in Nanchong City, the occurrence and epidemic regularity of wheat stripe rust in Nanchong was studied by system monitoring and general survey, resistance identification, physiological race monitoring and meteorological data analysis. The initial occurrence location and spreading pathway of Puccinia striiformis f. sp. tritici （Pst） were first verified; there were two infection peaks of wheat stripe rust in Nanchong and one to three epidemic peaks in fields, in which the occurrence area of the first epidemic peak played a pivotal role in disease prevalence in that year; the cumulative occurrence area in late January was positively correlated with annual occurrence area, with the correlation coefficient of 0.769 ; the prediction model for infected field rate, diseased plant rate and annual occurrence area was established. The internal reason for heavy occurrence and prevalence of wheat stripe rust in Nanchong was the decline or loss of wheat resistance against stripe rust, as well as the appearance of physiological races of Pst, which later became dominant races. Large fluctuation of temperature in warm winter and spring and more fog and dew days were external reasons responsible for prevalence of stripe rust. From 2002 to 2014 ,the accuracy rate of short-term prediction of wheat stripe rust reached 100%, while that of me- dium-term and long-term prediction reached over 98% and 95%, respectively, 5% -15% higher than that of the years before 1998.展开更多
目的/意义系统梳理基于互联网数据的传染病预测模型相关研究,助力实现传染病监测关口前移,为构建传染病智慧化立体防治体系提供参考。方法/过程对Web of Science核心数据库和中国知网收录的近20年基于互联网数据的传染病监测预警研究发...目的/意义系统梳理基于互联网数据的传染病预测模型相关研究,助力实现传染病监测关口前移,为构建传染病智慧化立体防治体系提供参考。方法/过程对Web of Science核心数据库和中国知网收录的近20年基于互联网数据的传染病监测预警研究发展历程及研究方向进行梳理,分析当前主要问题与挑战,总结常见预测模型及其优化方向。结果/结论互联网传染病监测研究呈监测疾病多样化、数据来源精细化和专业化等趋势。由于互联网数据的复杂性和不确定性,现有模型大多仅适用于短时或实时预测。通过构建组合模型、加强多源数据融合、完善关键词与影响因素选择等方式,可进一步优化模型,加强拟合效果和预测能力。展开更多
Coronavirus disease 2019(COVID-19)is an emerging infectious disease,and it is important to detect early and monitor the disease trend for policymakers to make informed decisions.We explored the predictive utility of B...Coronavirus disease 2019(COVID-19)is an emerging infectious disease,and it is important to detect early and monitor the disease trend for policymakers to make informed decisions.We explored the predictive utility of Baidu Search Index and Baidu Information Index for early warning of COVID-19 and identified search keywords for further monitoring of epidemic trends in Guangxi.A time-series analysis and Spearman correlation between the daily number of cases and both the Baidu Search Index and Baidu Information Index were performed for seven keywords related to COVID-19 from January 8 to March 9,2020.The time series showed that the temporal distributions of the search terms“coronavirus,”“pneumonia”and“mask”in the Baidu Search Index were consistent and had 2 to 3 days'lead time to the reported cases;the correlation coefficients were higher than 0.81.The Baidu Search Index volume in 14 prefectures of Guangxi was closely related with the number of reported cases;it was not associated with the local GDP.The Baidu Information Index search terms“coronavirus”and“pneumonia”were used as frequently as 192,405.0 and 110,488.6 per million population,respectively,and they were also significantly associated with the number of reported cases(rs>0.6),but they fluctuated more than for the Baidu Search Index and had 0 to 14 days'lag time to the reported cases.The Baidu Search Index with search terms“coronavirus,”“pneumonia”and“mask”can be used for early warning and monitoring of the epidemic trend of COVID-19 in Guangxi,with 2 to 3 days'lead time.展开更多
基金Supported by Notice on the First Batch of National Modern Agricultural Demonstration Zone by the Ministry of Agriculture([2010]22)the Research and Application Project for the Early Warning and Comprehensive Control of the Major Pests and Diseases for Main Grain and Oil Crops(N1997-ZC002)the Fundamental Research Funds for the Central Universities(XDJK2015C060,SWU114046,2362015xk04)~~
文摘With the aim to improve the level of monitoring and warning as well as the comprehensive control of rice blast disease, and to feasibly reduce the disease threat in Nanchong City, the methods of GPS and GIS, systematical monitoring and field survey, rice blast resistance identification, physiologic races of rice blast monitoring, and meteorological data analysis were performed to study the occurrence and epidemic region division, precise demarcation and occurrence and epidemic regularity of rice blast in Nanchong City. This study first completed the epidemic region division and precise demarcation; first clarified the initial affection（beginning period） locations, occurrence characteristics, epidemic trends and characteristics; explicated the existence of four epidemic peak periods of rice blast in the field, where the damage areas of first peak period played a decisive role during the blast epidemic years; in late May, the cumulative occurrence areas and annual occurrence areas presented higher positive correlation with the correlation coefficient of 0.817;and established a prediction model of occurrence areas per year based on the disease field rate at the end of boot stages and the diseased plant rate at dough stages. The results of investigation on the impact factors investigation of blast disease in Nanchong in recent years suggested that the internal causes were the decrease or loss of blast resistance of the rice cultivars, as well as the increase of physiological races with strong resistance to rice blast and the emergence of new virulent physiologic varieties; the external causes were suitable temperature, too much rainy, and sunlight shortage. Between 2010 and 2015, the short-term forecast accuracy for rice blast in Nanchong was up to 100%, and medium-and long-term forecast accuracy was also up to 98% and 95%, respectively, which increased by 5-15% than that before 1997, thereby making the control effect of rice blast in Nanchong increased by 15-30%.
基金funded by COST Action CA18208:HARMONYdNovel tools for test evaluation and disease prevalence estimation(https://harmony-net.eu/).
文摘This manuscript introduces the convergence Epidemic Volatility Index(cEVI),a modifi-cation of the recently introduced Epidemic Volatility Index(EVI),as an early warning tool for emerging epidemic waves.cEVI has a similar architectural structure as EVI,but with an optimization process inspired by a Geweke diagnostic-type test.Our approach triggers an early warning based on a comparison of the most recently available window of data samples and a window based on the previous time frame.Application of cEVI to data from the COVID-19 pandemic data revealed steady performance in predicting early,intermediate epidemic waves and retaining a warning during an epidemic wave.Furthermore,we present two basic combinations of EVI and cEVI:(1)their disjunction cEVI+that respectively identifies waves earlier than the original index,(2)their conjunction cEVIthat results in higher accuracy.Combination of multiple warning systems could potentially create a surveillance umbrella that would result in early implementation of optimal outbreak interventions.
基金Supported by Comprehensive Prevention and Treatment Monitoring Station of Inoculum Source of Wheat Stripe Rust in Nanchong City(NYBNJH[2003]104)Notice of the Ministry of Agriculture on Identification of the First Batch of National Modern Agricultural Demonstration Zone(NJF[2010]22)+2 种基金Occurrence and Epidemic Regularity of Wheat Stripe Rust and Its Integrated Control Technology in Nanchong City(N1998-ZC018)Fundamental Research Funds for the Central Universities(XDJK2015C060,SWU114046,2362015xk04)Open Project Program of State Key Laboratory of Crop Stress Biology for Arid Areas(CSBAA2015009)
文摘In order to realize monitoring and early warning and comprehensive management of wheat stripe rust and to reduce its occurrence in Nanchong City, the occurrence and epidemic regularity of wheat stripe rust in Nanchong was studied by system monitoring and general survey, resistance identification, physiological race monitoring and meteorological data analysis. The initial occurrence location and spreading pathway of Puccinia striiformis f. sp. tritici （Pst） were first verified; there were two infection peaks of wheat stripe rust in Nanchong and one to three epidemic peaks in fields, in which the occurrence area of the first epidemic peak played a pivotal role in disease prevalence in that year; the cumulative occurrence area in late January was positively correlated with annual occurrence area, with the correlation coefficient of 0.769 ; the prediction model for infected field rate, diseased plant rate and annual occurrence area was established. The internal reason for heavy occurrence and prevalence of wheat stripe rust in Nanchong was the decline or loss of wheat resistance against stripe rust, as well as the appearance of physiological races of Pst, which later became dominant races. Large fluctuation of temperature in warm winter and spring and more fog and dew days were external reasons responsible for prevalence of stripe rust. From 2002 to 2014 ,the accuracy rate of short-term prediction of wheat stripe rust reached 100%, while that of me- dium-term and long-term prediction reached over 98% and 95%, respectively, 5% -15% higher than that of the years before 1998.
文摘目的/意义系统梳理基于互联网数据的传染病预测模型相关研究,助力实现传染病监测关口前移,为构建传染病智慧化立体防治体系提供参考。方法/过程对Web of Science核心数据库和中国知网收录的近20年基于互联网数据的传染病监测预警研究发展历程及研究方向进行梳理,分析当前主要问题与挑战,总结常见预测模型及其优化方向。结果/结论互联网传染病监测研究呈监测疾病多样化、数据来源精细化和专业化等趋势。由于互联网数据的复杂性和不确定性,现有模型大多仅适用于短时或实时预测。通过构建组合模型、加强多源数据融合、完善关键词与影响因素选择等方式,可进一步优化模型,加强拟合效果和预测能力。
基金supported by the Health and Emergency Skills Training Center of Guangxi(HESTCG202104)National Natural Science Foundation of China(11971479)Guangxi Bagui Honor Scholarship and Chinese State Key Laboratory of Infectious Disease Prevention and Control.
文摘Coronavirus disease 2019(COVID-19)is an emerging infectious disease,and it is important to detect early and monitor the disease trend for policymakers to make informed decisions.We explored the predictive utility of Baidu Search Index and Baidu Information Index for early warning of COVID-19 and identified search keywords for further monitoring of epidemic trends in Guangxi.A time-series analysis and Spearman correlation between the daily number of cases and both the Baidu Search Index and Baidu Information Index were performed for seven keywords related to COVID-19 from January 8 to March 9,2020.The time series showed that the temporal distributions of the search terms“coronavirus,”“pneumonia”and“mask”in the Baidu Search Index were consistent and had 2 to 3 days'lead time to the reported cases;the correlation coefficients were higher than 0.81.The Baidu Search Index volume in 14 prefectures of Guangxi was closely related with the number of reported cases;it was not associated with the local GDP.The Baidu Information Index search terms“coronavirus”and“pneumonia”were used as frequently as 192,405.0 and 110,488.6 per million population,respectively,and they were also significantly associated with the number of reported cases(rs>0.6),but they fluctuated more than for the Baidu Search Index and had 0 to 14 days'lag time to the reported cases.The Baidu Search Index with search terms“coronavirus,”“pneumonia”and“mask”can be used for early warning and monitoring of the epidemic trend of COVID-19 in Guangxi,with 2 to 3 days'lead time.
