In recent years,the development trend of passion fruit seedling industry in Qinzhou,Guangxi is good,but on the whole,it is still in its infancy and the development of the industry is fragile.This paper briefly describ...In recent years,the development trend of passion fruit seedling industry in Qinzhou,Guangxi is good,but on the whole,it is still in its infancy and the development of the industry is fragile.This paper briefly described the development status and existing problems of the passion fruit seedling industry in Qinzhou,Guangxi,and put forward reasonable suggestions in order to promote the healthy development of the passion fruit seedling industry,increase farmers’income and prosper rural economy.展开更多
Background At the end of 2022,China adjusted its coronavirus disease 2019(COVID-19)prevention and control strategy.How this adjustment affected the cumulative infection rate is debated,and how second booster dose vacc...Background At the end of 2022,China adjusted its coronavirus disease 2019(COVID-19)prevention and control strategy.How this adjustment affected the cumulative infection rate is debated,and how second booster dose vaccination affected the pandemic remains unclear.Methods We collected COVID-19 case data for China's mainland from December 7,2022,to January 7,2023,reported by the World Health Organization.We also collected cumulative infection rate data from five large-scale population-based surveys.Next,we developed a dynamic transmission compartment model to characterize the COVID-19 pandemic and to estimate the cumulative infection rate.In addition,we estimated the impact of second booster vaccination on the pandemic by examining nine scenarios with different vaccination coverages(0%,20%,and 40%)and vaccine effectiveness(30%,50%,and 70%).Results By January 7,2023,when COVID-19 was classified as a Class B infectious disease,the cumulative infection rate of the Omicron variant nationwide had reached 84.11%(95%confidence interval[CI]:78.13%–90.08%).We estimated that the cumulative infection rates reached 50.50%(95%CI:39.58%–61.43%),56.15%(95%CI:49.05%–67.22%),73.82%(95%CI:64.63%–83.02%),75.76%(95%CI:67.02%–84.50%),and 84.99%(95%CI:79.45%–90.53%)on December 19,20,25,and 26,2022,and on January 15,2023,respectively.These results are similar to those of the population survey conducted on the corresponding dates,that is 46.93%,61%,63.52%,74%,and 84.7%,respectively.In addition,we estimated that by January 7,2023,the cumulative infection rate decreased to 29.55%(64.25%)if vaccination coverage and the effectiveness of second booster vaccination were 40%(20%)and 70%(30%),respectively.Conclusion We estimate that,in late 2022,the cumulative infection rate was approximately 84%and that second booster vaccination before the policy adjustment was effective in reducing this rate.展开更多
Background:Evidence is inefficient about how meteorological factors influence the trends of influenza transmission in different regions of China.Methods:We estimated the time-varying reproduction number(Rt)of influenz...Background:Evidence is inefficient about how meteorological factors influence the trends of influenza transmission in different regions of China.Methods:We estimated the time-varying reproduction number(Rt)of influenza and explored the impact of temperature and relative humidity on Rt using generalized additive quasi-Poisson regression models combined with the distribution lag non-linear model(DLNM).The effect of temperature and humidity interaction on Rt of influenza was explored.The multiple random-meta analysis was used to evaluate region-specific association.The excess risk(ER)index was defined to investigate the correlation between Rt and each meteorological factor with the modification of seasonal and regional characteristics.Results:Low temperature and low relative humidity contributed to influenza epidemics on the national level,while shapes of merged cumulative effect plots were different across regions.Compared to that of median temperature,the merged RR(95%CI)of low tem-perature in northern and southern regions were 1.40(1.24,1.45)and 1.20(1.14,1.27),respectively,while those of high temperature were 1.10(1.03,1.17)and 1.00(0.95,1.04),respectively.There were negative interactions between temperature and relative humidity on national(SI=0.59,95%CI:0.57e0.61),southern(SI=0.49,95%CI:0.17e0.80),and northern regions(SI=0.59,95%CI:0.56,0.62).In general,with the increase of the change of the two meteorological factors,the ER of Rt also gradually increased.Conclusions:Temperature and relative humidity have an effect on the influenza epidemics in China,and there is an interaction between the two meteorological factors,but the effect of each factor is heterogeneous among regions.Meteorological factors may be considered to predict the trend of influenza epidemic.展开更多
基金Supported by Science and Technology Pioneer"Strengthening Farmers and Enriching People"and"Six Ones"Special Action Project(GNKM 202104)Grassroots Agricultural Technology Extension Service Ability Improvement Project of Agriculture and Rural Affairs Department,Guangxi Zhuang Autonomous Region。
文摘In recent years,the development trend of passion fruit seedling industry in Qinzhou,Guangxi is good,but on the whole,it is still in its infancy and the development of the industry is fragile.This paper briefly described the development status and existing problems of the passion fruit seedling industry in Qinzhou,Guangxi,and put forward reasonable suggestions in order to promote the healthy development of the passion fruit seedling industry,increase farmers’income and prosper rural economy.
基金supported by the National Natural Science Foundation of China(82320108018,12171387)National Key R&D Program of China(2023YFC2306004,2022YFC2304000,2022YFC2505100).
文摘Background At the end of 2022,China adjusted its coronavirus disease 2019(COVID-19)prevention and control strategy.How this adjustment affected the cumulative infection rate is debated,and how second booster dose vaccination affected the pandemic remains unclear.Methods We collected COVID-19 case data for China's mainland from December 7,2022,to January 7,2023,reported by the World Health Organization.We also collected cumulative infection rate data from five large-scale population-based surveys.Next,we developed a dynamic transmission compartment model to characterize the COVID-19 pandemic and to estimate the cumulative infection rate.In addition,we estimated the impact of second booster vaccination on the pandemic by examining nine scenarios with different vaccination coverages(0%,20%,and 40%)and vaccine effectiveness(30%,50%,and 70%).Results By January 7,2023,when COVID-19 was classified as a Class B infectious disease,the cumulative infection rate of the Omicron variant nationwide had reached 84.11%(95%confidence interval[CI]:78.13%–90.08%).We estimated that the cumulative infection rates reached 50.50%(95%CI:39.58%–61.43%),56.15%(95%CI:49.05%–67.22%),73.82%(95%CI:64.63%–83.02%),75.76%(95%CI:67.02%–84.50%),and 84.99%(95%CI:79.45%–90.53%)on December 19,20,25,and 26,2022,and on January 15,2023,respectively.These results are similar to those of the population survey conducted on the corresponding dates,that is 46.93%,61%,63.52%,74%,and 84.7%,respectively.In addition,we estimated that by January 7,2023,the cumulative infection rate decreased to 29.55%(64.25%)if vaccination coverage and the effectiveness of second booster vaccination were 40%(20%)and 70%(30%),respectively.Conclusion We estimate that,in late 2022,the cumulative infection rate was approximately 84%and that second booster vaccination before the policy adjustment was effective in reducing this rate.
基金supported by the National Natural Science Foundation of China(82073673)National Key R&D Program of China(2022YFC2304000).
文摘Background:Evidence is inefficient about how meteorological factors influence the trends of influenza transmission in different regions of China.Methods:We estimated the time-varying reproduction number(Rt)of influenza and explored the impact of temperature and relative humidity on Rt using generalized additive quasi-Poisson regression models combined with the distribution lag non-linear model(DLNM).The effect of temperature and humidity interaction on Rt of influenza was explored.The multiple random-meta analysis was used to evaluate region-specific association.The excess risk(ER)index was defined to investigate the correlation between Rt and each meteorological factor with the modification of seasonal and regional characteristics.Results:Low temperature and low relative humidity contributed to influenza epidemics on the national level,while shapes of merged cumulative effect plots were different across regions.Compared to that of median temperature,the merged RR(95%CI)of low tem-perature in northern and southern regions were 1.40(1.24,1.45)and 1.20(1.14,1.27),respectively,while those of high temperature were 1.10(1.03,1.17)and 1.00(0.95,1.04),respectively.There were negative interactions between temperature and relative humidity on national(SI=0.59,95%CI:0.57e0.61),southern(SI=0.49,95%CI:0.17e0.80),and northern regions(SI=0.59,95%CI:0.56,0.62).In general,with the increase of the change of the two meteorological factors,the ER of Rt also gradually increased.Conclusions:Temperature and relative humidity have an effect on the influenza epidemics in China,and there is an interaction between the two meteorological factors,but the effect of each factor is heterogeneous among regions.Meteorological factors may be considered to predict the trend of influenza epidemic.
