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Analysis of the spatial and temporal variation patterns of surface evapotranspiration is important for understanding global climate change, promoting scientific deployment of regional water resources, and improving crop yield and water productivity. Based on Landsat 8 OIL_TIRS data and remote sensing image data of the lower Yangtze River urban cluster for the same period of 2016–2021, combined with soil and meteorological data of the study area, this paper constructed a multiple linear regression (MLR) model and an extreme learning machine (ELM) inversion model with evapotranspiration as the target and, based on the model inversion, quantitatively and qualitatively analyzed the spatial and temporal variability in surface evapotranspiration in the study area in the past six years. The results show that both models based on feature factors and spectral indices obtained a good inversion accuracy, with the fusion of feature factors effectively improving the inversion ability of the model for ET. The best model for ET in 2016, 2017, and 2021 was MLR, with an R2 greater than 0.8; the best model for ET in 2018–2019 was ELM, with an R2 of 0.83 and 0.62, respectively. The inter-annual ET in the study area showed a "double-peak" dynamic variation, with peaks in 2018 and 2020; the intra-annual ET showed a single-peak cycle, with peaks in July–August. Seasonal differences were obvious, and spatially high-ET areas were mainly found in rural areas north of the Yangtze River and central and western China where agricultural land is concentrated. The net solar radiation, soil heat flux, soil temperature and humidity, and fractional vegetation cover all had significant positive effects on ET, with correlation coefficients ranging from 0.39 to 0.94. This study can provide methodological and scientific support for the quantitative and qualitative estimation of regional ET. [ABSTRACT FROM AUTHOR]

Hypertension is the most common chronic disease and the primary risk factor for cardiovascular diseases. Prehypertension is closely related to a variety of cardiovascular disease risk factors during the development of hypertension. The objective of this study was to explore the relationship between dietary patterns and hypertension in Jiangsu Province. Specifically, we included the participants from 2007 and then followed up in 2014 in the Jiangsu Province of China and collected information from food frequency questionnaires, anthropometric measurements, and disease self-reports. A total of 1762 women and men were included in the final analysis. We extracted four dietary patterns using factor analysis, calculated the pattern-specific factor scores, and divided the scores into quartiles, which increased from Q1 to Q4. Compared with participants in Q1, an increased risk of high diastolic blood pressure was found in Q4 of the snack dietary pattern. Additionally, participants in Q2-Q4 of the frugal dietary pattern were found to have a positive association with abnormal blood pressure. However, the results found in the frugal dietary pattern vanished after adjusting more confounders in Q4 of high systolic blood pressure. We found that some food items were associated with hypertension and prehypertension. The overconsumption of salt and alcohol are risk factors for both prehypertension and hypertension. Added sugar and saturated fatty acids are risk factors for hypertension, which may provide suggestions for the residents in China to change dietary habits to prevent prehypertension and hypertension.

Objective: To evaluate epidemiological characteristics and transmission dynamics of COVID-19 outbreak resurged in Beijing and to assess the effects of three non-pharmaceutical interventions., Design: Descriptive and modelling study based on surveillance data of COVID-19 in Beijing., Setting: Outbreak in Beijing., Participants: The database included 335 confirmed cases of COVID-19., Methods: To conduct spatiotemporal analyses of the outbreak, we collected individual records on laboratory-confirmed cases of COVID-19 from 11 June 2020 to 5 July 2020 in Beijing, and visitor flow and products transportation data of Xinfadi Wholesale Market. We also built a modified susceptible-exposed-infected-removed model to investigate the effect of interventions deployed in Beijing., Results: We found that the staff working in the market (52.2%) and the people around 10 km to this epicentre (72.5%) were most affected, and the population mobility entering-exiting Xinfadi Wholesale Market significantly contributed to the spread of COVID-19 (p=0.021), but goods flow of the market had little impact on the virus spread (p=0.184). The prompt identification of Xinfadi Wholesale Market as the infection source could have avoided a total of 25 708 (95% CI 13 657 to 40 625) cases if unnoticed transmission lasted for a month. Based on the model, we found that active screening on targeted population by nucleic acid testing alone had the most significant effect., Conclusions: The non-pharmaceutical interventions deployed in Beijing, including localised lockdown, close-contact tracing and community-based testing, were proved to be effective enough to contain the outbreak. Beijing has achieved an optimal balance between epidemic containment and economic protection., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Haemaphysalis longicornis, a vector of various pathogens with medical and veterinary importance, is native to eastern Asia, and recently reached the USA as an emerging disease threat. In this study, we aimed to identify the geographical distribution, hosts, and associated pathogens of H longicornis., Methods: Data were collected from multiple sources, including a field survey, reference book, literature review, and related websites. The thematic maps showing geographical distribution of H longicornis and associated pathogens were produced by ArcGIS. Hosts of H longicornis and positive rates for H longicornis-associated pathogens were estimated by meta-analysis. Ecological niche modelling was used to predict potential global distribution of H longicornis., Findings: H longicornis was found to be present in ten countries, predominantly in eastern Asia, the USA, Australia, and New Zealand. The tick was known to feed on a variety of domestic and wild animals, and humans. At least 30 human pathogens were associated with H longicornis, including seven species of spotted fever group rickettsiae, seven species in the family of Anaplasmataceae, four genospecies in the complex Borrelia burgdorferi sensu lato, two Babesia species, six species of virus, and Francisella, Bartonella, Coxiella, and Toxoplasma, which were mainly reported in eastern Asia. The predictive modelling revealed that H longicornis might affect more extensive regions, including Europe, South America, and Africa, where the tick has never been recorded before., Interpretation: H longicornis is relatively common in the world, and is associated with various human and animal pathogens. Authorities and health-care workers should be aware of the threat of the tick species to public health and veterinary medicine. Surveillance and further investigations should be enhanced globally., Funding: National Natural Science Foundation of China and National Key Research and Development Program of China., (Copyright © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)