简介：AbstractBackground:The ongoing new coronavirus pneumonia (Corona Virus Disease 2019, COVID-19) outbreak is spreading in China, but it has not yet reached its peak. Five million people emigrated from Wuhan before lockdown, potentially representing a source of virus infection. Determining case distribution and its correlation with population emigration from Wuhan in the early stage of the epidemic is of great importance for early warning and for the prevention of future outbreaks.Methods:The official case report on the COVID-19 epidemic was collected as of January 30, 2020. Time and location information on COVID-19 cases was extracted and analyzed using ArcGIS and WinBUGS software. Data on population migration from Wuhan city and Hubei province were extracted from Baidu Qianxi, and their correlation with the number of cases was analyzed.Results:The COVID-19 confirmed and death cases in Hubei province accounted for 59.91% (5806/9692) and 95.77% (204/213) of the total cases in China, respectively. Hot spot provinces included Sichuan and Yunnan, which are adjacent to Hubei. The time risk of Hubei province on the following day was 1.960 times that on the previous day. The number of cases in some cities was relatively low, but the time risk appeared to be continuously rising. The correlation coefficient between the provincial number of cases and emigration from Wuhan was up to 0.943. The lockdown of 17 cities in Hubei province and the implementation of nationwide control measures efficiently prevented an exponential growth in the number of cases.Conclusions:The population that emigrated from Wuhan was the main infection source in other cities and provinces. Some cities with a low number of cases showed a rapid increase in case load. Owing to the upcoming Spring Festival return wave, understanding the risk trends in different regions is crucial to ensure preparedness at both the individual and organization levels and to prevent new outbreaks.

简介：AbstractBackground:Several studies highlighted the impact of community-based interventions whose purpose was to reduce the vectors’ breeding sites. These strategies are particularly interesting in low-and-middle-income countries which may find it difficult to sustainably assume the cost of insecticide-based interventions. In this case study we determine the spatial distribution of a community-based intervention for dengue vector control using different entomological indices. The objective was to evaluate locally where the intervention was most effective, using spatial analysis methods that are too often neglected in impact assessments.Methods:Two neighbourhoods, Tampouy and Juvenat in Ouagadougou, Burkina Faso, were chosen among five after a survey was conducted, as part of an assessment related to the burden of dengue. As part of the community-based intervention conducted in Tampouy between August and early October 2016, an entomological survey was implemented in two phases. The first phase consisted of a baseline entomological characterization of potential breeding sites in the neighbourhood of Tampouy as well as in Juvenat, the control area. This phase was conducted in October 2015 at the end of the rainy season. The mosquito breeding sites were screened in randomly selected houses: 206 in Tampouy and 203 in Juvenat. A second phase took place after the intervention, in October 2016. The mosquito breeding sites were investigated in the same yards as during the baseline phase. We performed several entomological analyses to measure site productivity as well as before and after analysis using multilevel linear regression. We used Local Indicators of Spatial Association (LISAs) to analyse spatial concentrations of larvae.Results:After the intervention, it is noted that LISAs at Tampouy reveal few aggregates of all types and the suppression of those existing before the intervention. The analysis therefore reveals that the intervention made it possible to reduce the number of concentration areas of high and low values of pupae.Conclusions:The contribution of spatial methods for assessing community-based intervention are relevant for monitoring at local levels as a complement to epidemiological analyses conducted within neighbourhoods. They are useful, therefore, not only for assessment but also for establishing interventions. This study shows that spatial analyses also have their place in population health intervention research.

简介：AbstractImportance:Clostridium difficile-associated diarrhea (CDAD) is a severe type of antibiotic-associated diarrhea (AAD). However, the risk factors for CDAD in children with AAD have not yet been clarified.Objective:To investigate the distribution and risk factors for CDAD among hospitalized children in Beijing Children’s Hospital.Methods:Stool samples from 197 children with AAD were tested for the C. difficile pathogenic genes (tcdA, tcdB, tcdC, tcdD, tcdE, cdtA, and cdtB) using polymerase chain reaction between January 2011 and January 2014. Children who tested positive for tcdA or tcdB were included in the CDAD group, and those remaining comprised the non-CDAD group.Results:The rate of CDAD among the 197 children with AAD was 42.6% (84/197). The age distribution was 1-15.6 years, among which the majority of children (54.8%, 46/84) were aged 1-4 years. Differences in the CDAD-positive rates among AAD children belonging to different age groups were not statistically significant. Univariate analysis revealed that the duration of antibiotic therapy, the length of hospitalization prior to diarrhea, and gastrointestinal tract operations were significant risk factors (P < 0.05). Children with CDAD underwent more antibiotic therapy and had longer periods of hospitalization prior to diarrhea onset than children in the non-CDAD group. Using multivariate regression analysis, hospitalization for ≥ 10 days prior to diarrhea was found to be an independent risk factor for CDAD.Interpretation:This study revealed that the length of hospitalization (≥ 10 days) prior to diarrhea was an independent risk factor for CDAD in children with AAD.

简介：摘要: 太阳辐射是地球表层能量的主要来源。就全球平均而言，太阳总辐射只占到达大气上界太阳辐射的45%。总辐射量随纬度升高而减小，随高度升高而增大。根据1981-2010郑州辐射站太阳辐射和日照资料、三门峡四个国家级气象观测站的日照资料，采用气候学方法、线性趋势分析等方法和太阳能资源的丰富程度、利用价值、稳定程度、日最佳利用时段等指标，对三门峡地区太阳能资源进行了计算、分析和评估。结果显示：三门峡地区近30年来相应的年均总辐射大约是4916.9 MJ·m -2·a-1，整体来看呈现逐年下降，下降速率大约是2.659 MJ·m -2·a-1/ 年;相应的年总辐射量大约是卢氏最低，则渑池最高;冬季辐射量相对较低，反之夏季辐射量相对较高，夏季总辐射量在一定程度上是冬季的2倍;月均总辐射量最少的月份是12月 ，其中最丰富的是5月份。近30年来相应的年均日照时数大约是2131小时，整体来看呈现逐年下降。渑池的年日照量大约是2298小时，居于首位，卢氏的年日照量大约是2017.5小时，居于末位;日照时数最少的季节为冬季，最多的季节为夏季多。日照总时数冬季比相应的夏季少24.64%;其中月均日照量最多的月份是5月高达219.3小时，为最多)，月均日照量最少的月份是2月低至141.7小时，为最少。三门峡相应月日照量高于6小时的的天数仅为13.8-20.9天，全年大约共有194-220.5天;其中日照相对较为丰富的月份是5月大约存在19.7天日照时数多于6小时，大致是2月份的1.35倍，从12月到次年2月份都不利于相应的太阳能利用。各县（市、区）相应的太阳能资源可进行开发利用的天数相对较多，太阳能资源呈现出相对稳定的状态，资源较为丰富，具有相对较高的利用价值。