2019年中国大陆食源性疾病暴发监测资料分析

目的 分析2019年中国大陆食源性疾病暴发事件的流行病学特征,为制定预防措施提供依据。方法 对我国食源性疾病暴发监测系统收集的2019年食源性疾病暴发数据的流行病学特征进行描述性统计学分析。结果 2019年,30个省(自治区、直辖市)和新疆生产建设兵团(除西藏自治区)共上报食源性疾病暴发事件数6 390起,累计发病38 797人,死亡134人。在病因明确的3 572起事件中,微生物性因素导致的发病人数最多,占 52.01%(12 738/24 491);毒蘑菇导致的事件数和死亡人数最多,分别占44.96%(1 606/3 572)和57.60%(72/125);在食源性疾病暴发的场所中,餐饮服务场所的事件数和发病人数最多,分别占49.95%(3 192/6 390)和70.00%(27 156/38 797);家庭的死亡人数最多,占80.60%(108/134)。结论 餐饮服务场所是食源性疾病暴发的主要场所,微生物性因素是主要致病因素,毒蘑菇引起的死亡人数最多;该结果提示应加大食品安全监督管理和健康教育力度,对重点食品、重点场所和主要致病因素采取有效措施并加以控制,降低食源性疾病的负担。     

2015-2020年广西毒蘑菇中毒事件流行病学分析

目的 分析广西毒蘑菇中毒事件流行病学特点,为毒蘑菇中毒的风险预警和预防控制提供科学依据。方法 采用描述流行病学方法,对广西2015—2020年食源性疾病事件监测系统报告的毒蘑菇中毒事件的流行病学特征进行分析。结果 2015—2020年,广西共报告毒蘑菇中毒事件189起,发病人数789人,死亡10人,病死率为1.27%。事件数最多的是2020年,占事件总数的38.10%(72/189);中毒事件主要发生在5～9月,高发地区为桂林市、百色市、梧州市和钦州市;家庭为主要的发生场所,占总事件数的93.65%(177/189),其中农村地区占88.14%(156/177);毒蘑菇中毒的主要原因为误食误用。结论 广西毒蘑菇中毒防控应根据高发季节、高危场所和人群有针对性行预防,加强对农村地区家庭的宣传教育,提高公众防范意识。     

Tangible geospatial modeling for collaborative solutions to invasive species management

Managing landscape-scale environmental problems, such as biological invasions, can be facilitated by integrating realistic geospatial models with user-friendly interfaces that stakeholders can use to make critical management decisions. However, gaps between scientific theory and application have typically limited opportunities for model-based knowledge to reach the stakeholders responsible for problem-solving. To address this challenge, we introduce Tangible Landscape, an open-source participatory modeling tool providing an interactive, shared arena for consensus-building and development of collaborative solutions for landscape-scale problems. Using Tangible Landscape, stakeholders gather around a geographically realistic 3D visualization and explore management scenarios with instant feedback; users direct model simulations with intuitive tangible gestures and compare alternative strategies with an output dashboard. We applied Tangible Landscape to the complex problem of managing the emerging infectious disease, sudden oak death, in California and explored its potential to generate co-learning and collaborative management strategies among actors representing stakeholders with competing management aims.     

Associations between Streptococcus uberis strains from the animal environment and clinical bovine mastitis cases

Bovine clinical mastitis quarter foremilk samples were collected from 15 German dairy farms for the isolation of Streptococcus uberis strains. Samples were also collected from the 8 spots where Streptococcus uberis was most expected in the dairy environment to investigate the transmission behavior of Streptococcus uberis within the farm. The selected environmental spots for sampling were the inner surface of the milking liner, drinking troughs (on pasture and in the barn), exit area of milking parlor, bedding material from the lying area in the barn, passageway to pasture, lying area of soil or vegetation on pasture, and the barn area in front of the milking parlor. We performed pulsed-field gel electrophoresis on 237 Streptococcus uberis isolates to identify environmental strains that matched those from mastitis milk. The same strains were detected on the passageway to the pasture, milking parlor waiting area, in one of the liners, and a drinking trough. Streptococcus uberis strains showed high variability within farms and because identical strains (in mastitis milk and environment) were found in different environmental localizations, its transmission appears to be farm specific. Thus, to establish a farm-specific mastitis control strategy, the main environmental sources of Streptococcus uberis must be analyzed for matching strains. A molecular method such as pulsed-field gel electrophoresis is an important tool that can be used to obtain the necessary information.     

How can we improve foodborne disease surveillance systems: A comparison through EU and US systems

Foodborne diseases remain a major threat to global public health. Problems in detecting the threats at early stages in the supply chain due to defects in surveillance systems cannot be ignored. The primary goal of this article is to evaluate the capabilities of foodborne disease surveillance systems known for their effectiveness and functionality in order to highlight solutions for preventing and managing the outbreaks more effectively. For this purpose, early detection, notification and monitoring systems of the European Union (EU) and the United States were compared in terms of capability gaps and critical needs via an in-depth examination of two standout outbreaks.     

Molecular and phylogenetic approaches for assessing sources of Cryptosporidium contamination in water

The high sequence diversity and heterogeneity observed within species or genotypes of Cryptosporidium requires phylogenetic approaches for the identification of novel sequences obtained from the environment. A long-term study on Cryptosporidium in the agriculturally-intensive South Nation River watershed in Ontario, Canada was undertaken, in which 60 sequence types were detected. Of these sequence types 33 were considered novel with no identical matches in GenBank. Detailed phylogenetic analysis identified that most sequences belonged to 17 previously described species: Cryptosporidium andersoni, Cryptosporidium baileyi, Cryptosporidium hominis, Cryptosporidium parvum, Cryptosporidium ubiquitum, Cryptosporidium meleagridis, muskrat I, muskrat II, deer mouse II, fox, vole, skunk, shrew, W12, W18, W19 and W25 genotypes. In addition, two new genotypes were identified, W27 and W28. C. andersoni and the muskrat II genotype were most frequently detected in the water samples. Species associated with livestock made up 39% of the total molecular detections, while wildlife associated species and genotypes accounted for 55% of the Cryptosporidium identified. The human pathogenic species C. hominis and C. parvum had an overall prevalence of 1.6% in the environment, indicating a small risk to humans from the Cryptosporidium present in the watershed. Phylogenetic analysis and knowledge of host-parasite relationships are fundamental in using Cryptosporidium as a source-tracking or human health risk assessment tool.     

Human diffusion and city influence

Cities are characterized by concentrating population, economic activity and services. However, not all cities are equal and a natural hierarchy at local, regional or global scales spontaneously emerges. In this work, we introduce a method to quantify city influence using geolocated tweets to characterize human mobility. Rome and Paris appear consistently as the cities attracting most diverse visitors. The ratio between locals and non-local visitors turns out to be fundamental for a city to truly be global. Focusing only on urban residents'' mobility flows, a city-to-city network can be constructed. This network allows us to analyse centrality measures at different scales. New York and London play a central role on the global scale, while urban rankings suffer substantial changes if the focus is set at a regional level.     

Range and severity of a plant disease increased by global warming.

Climate change affects plants in natural and agricultural ecosystems throughout the world but little work has been done on the effects of climate change on plant disease epidemics. To illustrate such effects, a weather-based disease forecasting model was combined with a climate change model predicting UK temperature and rainfall under high- and low-carbon emissions for the 2020s and 2050s. Multi-site data collected over a 15-year period were used to develop and validate a weather-based model forecasting severity of phoma stem canker epidemics on oilseed rape across the UK. This was combined with climate change scenarios to predict that epidemics will not only increase in severity but also spread northwards by the 2020s. These results provide a stimulus to develop models to predict the effects of climate change on other plant diseases, especially in delicately balanced agricultural or natural ecosystems. Such predictions can be used to guide policy and practice in adapting to effects of climate change on food security and wildlife.     

Assessing the risk of bluetongue to UK livestock: uncertainty and sensitivity analyses of a temperature-dependent model for the basic reproduction number.

Since 1998 bluetongue virus (BTV), which causes bluetongue, a non-contagious, insect-borne infectious disease of ruminants, has expanded northwards in Europe in an unprecedented series of incursions, suggesting that there is a risk to the large and valuable British livestock industry. The basic reproduction number, R(0), provides a powerful tool with which to assess the level of risk posed by a disease. In this paper, we compute R(0) for BTV in a population comprising two host species, cattle and sheep. Estimates for each parameter which influences R(0) were obtained from the published literature, using those applicable to the UK situation wherever possible. Moreover, explicit temperature dependence was included for those parameters for which it had been quantified. Uncertainty and sensitivity analyses based on Latin hypercube sampling and partial rank correlation coefficients identified temperature, the probability of transmission from host to vector and the vector to host ratio as being most important in determining the magnitude of R(0). The importance of temperature reflects the fact that it influences many processes involved in the transmission of BTV and, in particular, the biting rate, the extrinsic incubation period and the vector mortality rate.