scholarly journals Understanding small Chinese cities as COVID-19 hotspots with an urban epidemic hazard index

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tianyi Li ◽  
Jiawen Luo ◽  
Cunrui Huang
Keyword(s):  
Transportation Network ◽  
Local Population ◽  
Hazard Index ◽  
Northern China ◽  
Small Towns ◽  
Mathematical Explanation ◽  
Model Framework ◽  
Response Planning ◽  
City Population ◽  
Second Wave

AbstractMultiple small- to middle-scale cities, mostly located in northern China, became epidemic hotspots during the second wave of the spread of COVID-19 in early 2021. Despite qualitative discussions of potential social-economic causes, it remains unclear how this unordinary pattern could be substantiated with quantitative explanations. Through the development of an urban epidemic hazard index (EpiRank) for Chinese prefectural districts, we came up with a mathematical explanation for this phenomenon. The index is constructed via epidemic simulations on a multi-layer transportation network interconnecting local SEIR transmission dynamics, which characterizes intra- and inter-city population flow with a granular mathematical description. Essentially, we argue that these highlighted small towns possess greater epidemic hazards due to the combined effect of large local population and small inter-city transportation. The ratio of total population to population outflow could serve as an alternative city-specific indicator of such hazards, but its effectiveness is not as good as EpiRank, where contributions from other cities in determining a specific city’s epidemic hazard are captured via the network approach. Population alone and city GDP are not valid signals for this indication. The proposed index is applicable to different epidemic settings and can be useful for the risk assessment and response planning of urban epidemic hazards in China. The model framework is modularized and the analysis can be extended to other nations.

scholarly journals Green urbanization

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0260393
Author(s):  
Jan Eeckhout ◽  
Christoph Hedtrich
Keyword(s):  
Energy Efficient ◽  
Energy Demand ◽  
Small Towns ◽  
Demand Elasticity ◽  
Total Output ◽  
Waste Generation ◽  
Large Cities ◽  
Economic Output ◽  
City Population ◽  
Percent Increase

Large cities are more productive and generate more output per person. Using data from the UK on energy demand and waste generation, we show that they are also more energy-efficient. Large cities are therefore greener than small towns. The amount of energy demanded and waste generated per person is decreasing in total output produced, that is, energy demand and waste generation scale sublinearly with output. Our research provides the first direct evidence of green urbanization by calculating the rate at which per capita electricity use and waste decrease with city population. The energy demand elasticity with respect to city output is 83%: as the total output of a city increases by one percent, energy demand increases less than one percent, and the Urban Energy Premium is therefore 17%. The energy premium by source of energy demand is from households (13%), transport (20%), and industry (16%). Similarly, we find that the elasticity of waste generation with respect to city output is 90%. For one percent increase in total city output, there is a less than one percent increase in waste, with an Urban Waste Premium of 10%. Because large cities are energy-efficient ways of generating output, energy efficiency can be improved by encouraging urbanization and thus green living. We perform a counterfactual analysis in a spatial equilibrium model that makes income taxes contingent on city population, which attracts more people to big cities. We find that this pro-urbanization counterfactual not only increases economic output but also lowers energy consumption and waste production in the aggregate.

scholarly journals Territorial identity and attitude to their town of the russian provincial youth

2021 ◽  
Author(s):  
Liubov Ostapenko ◽  
Keyword(s):  
Local Population ◽  
Local Environment ◽  
Small Towns ◽  
Rolling Stock ◽  
Considerable Part ◽  
Migration Activity ◽  
Territorial Identity ◽  
Central Russia ◽  
Local Residents ◽  
Academy Of Sciences

The article is based on materials from a study carried out by employees of the Institute of Ethnology and Anthropology of the Russian Academy of Sciences in 2017–2019. The study was conducted among young people living in two small towns in Central Russia – Belev, Tula region and Staritsa, Tver region. The issues of local-territorial identity of young residents of the Russian province, their attitude to their native city and the local environment are analyzed. An analysis of the sociological survey data made it possible to conclude that at present, territorial identity and love for their city were characteristic of a considerable part of the provincial youth, but these indicators varied markedly. The prevalence of young people’s orientations towards their city decreased in more developed, urbanized, open cities, with a rolling stock of the local population, wider contacts with the ”outside world”, a higher level of education, etc. In less urbanized cities, local-territorial identity and love for their city were more frequent. At the same time, local residents experienced less satisfaction with living conditions and showed more pronounced migration activity.

scholarly journals Clinico-Demographic Profile of Covid-19 Patients Admitted in COVID- HDU and its Association with Conjunctivitis

2021 ◽  
Vol 4 (2) ◽  
pp. 482-484
Author(s):  
Pragya Singh Basnet ◽  
Deepa Sharma ◽  
Shravya Singh Karki ◽  
Sauhaida Karki ◽  
Hira Lal Bhandari ◽  
...  
Keyword(s):  
Clinical Presentation ◽  
Local Population ◽  
Health Crisis ◽  
Ocular Manifestations ◽  
First Case ◽  
Single Center Study ◽  
Common Clinical Presentation ◽  
Epidemiological Profile ◽  
Second Wave ◽  
Center Study

Introduction: The outbreak of coronavirus diseases 2019 (Covid-19) caused by SARS-COV-2 which started in Wuhan china led to an alarming level of spread and severity. In Nepal, the first case of COVID-19 was reported on 23.1.2020 and has become a global health crisis since then. The clinical presentation and outcome of patients with COVID-19 have been variable in different countries and therefore it is important to analyze as well as document the clinical behaviors of this disease in the local population so we have reported the clinic-epidemiological profile, outcome, and its association with conjunctivitis during the second wave of this pandemic which hit Nepal badly hoping this study will be helpful to tackle the future surges of COVID-19 as well. Materials and Methods: This was a prospective, single-center study where the data regarding epidemiology, demography, common clinical presentation as well as management and outcome of COVID-19 Patients were retracted and analyzed. Results: A total of 238 COVID-Positive patients were admitted out of which 60% were male and 39.9% people belonged to Dang valley itself with dyspnea (67.2%) was the commonest symptoms followed by fever in 59.7% of patients. Out of these patients 9 patients presented with ocular symptom conjunctivitis. Conclusions: Mild conjunctivitis manifesting as conjunctival congestion is common and one of the major ocular manifestations in COVID -19 positive patients.

scholarly journals In situ Ground Radiometric Survey and Risk Assessments of Allanite-Bearing Beach Sands in Erawan, Palawan

2021 ◽  
Author(s):  
Reymar Diwa ◽  
Edmundo Vargas ◽  
Estellita Tabora ◽  
Botvinnik Palattao ◽  
Rolando Reyes ◽  
...  
Keyword(s):  
Local Population ◽  
Hazard Index ◽  
The Philippines ◽  
Risk Assessments ◽  
Anthropogenic Sources ◽  
World Average ◽  
Radiometric Survey ◽  
The World ◽  
The Mean

Past exploration for U deposit in the Philippines discovered the mineralization of radioactive allanite in Palawan. The allanite occurs as sand component in the heavily populated beach of Erawan, San Vicente, Palawan. This work assessed the risks associated with the radionuclides in Erawan beach by in situ ground radiometric survey of K, U, and Th in 694 sampling points. Principal component analysis (PCA) and Pearson correlation coefficient were used to determine the similarity between the radionuclides and to identify other probable anthropogenic sources of radionuclides. Our results show that the mean activity concentrations of K (597.8 Bq kg-1) and Th (93.15 Bq kg-1) are equivalent to 1.5 and 3.1 times of the world average natural radioactivity levels in soil, respectively, while the mean U (34.7 Bq kg-1) is similar to the world average. The mean radiological risk assessments like radium equivalent, gamma specific activity index, external hazard index, internal hazard index, absorbed gamma dose rate, annual effective dose equivalent, annual gonadal equivalent dose, and excess lifetime cancer risk are 213.96 Bq kg-1, 0.78, 0.58, 0.67, 97.24 nGy h-1, 119.25 µSv y-1, 684.39 µSv y-1, and 0.42 (10-3), respectively. Th consistently correlated most to the risks. We attribute the occurrence of Th to the presence of allanite, K to fertilizer use for farming, and U to both the allanite and farming. The results of our study can provide important baseline data for future detailed studies or monitoring of the long-term effects of elevated radiation levels to the local population of Erawan.

scholarly journals Optimized Distribution of Beijing Population Based on CA-MAS

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Haoguang Liang ◽  
Zhong Wang
Keyword(s):  
Population Distribution ◽  
Population Based ◽  
Small Towns ◽  
Rapid Expansion ◽  
Mixed Use ◽  
City Population ◽  
Public Resources ◽  
The City ◽  
Resources Planning

In recent years rapid expansion of populations, disruption of ecological environments, and power shortages to areas of high population density in undeveloped areas have appeared in major cities in China. Well-planned population distribution in a city has become one of the key development strategies of urbanization in the country. Taking Beijing as a case-study and using 2010 as the base period, this study simulates city population size and distribution during 2011–2030 using the CA-MAS model. The results showed that (1) the unplanned layout of Beijing’s population is inefficient and will result in the slow agglomeration of populations into surrounding small towns, (2) the suburbanization of the population (while employment opportunities remain centralized) increases the stress of the city commuters, (3) the current policy guiding the distribution of residential and commercial areas is effective, accelerating the formation of small town clusters, which play a role in the city’s radiation and diffusion, contributing to reducing urban commuter stress, and (4) promoting the homogenization of public resources, planning the development of a multicenter urban area, and promoting mixed use (commercial and residential) zoning are the main measures recommended to strengthen the sustainability of Beijing’s urban development and to optimize spatial layout.

scholarly journals Comparison of different exit scenarios from the lock-down for COVID-19 epidemic in the UK and assessing uncertainty of the predictions

2020 ◽  
Author(s):  
Anatoly Zhigljavsky ◽  
Roger Whitaker ◽  
Ivan Fesenko ◽  
Kobi Kremnizer ◽  
Jack Noonan
Keyword(s):  
Local Population ◽  
Population Data ◽  
Current Data ◽  
List Type ◽  
The Public ◽  
Regional Demand ◽  
Vulnerable People ◽  
The Uk ◽  
Second Wave ◽  
Further Development

AbstractWe model further development of the COVID-19 epidemic in the UK given the current data and assuming different scenarios of handling the epidemic. In this research, we further extend the stochastic model suggested in [1] and incorporate in it all available to us knowledge about parameters characterising the behaviour of the virus and the illness induced by it. The models we use are flexible, comprehensive, fast to run and allow us to incorporate the following: time-dependent strategies of handling the epidemic;spatial heterogeneity of the population and heterogeneity of development of epidemic in different areas;special characteristics of particular groups of people, especially people with specific medical pre-histories and elderly.Standard epidemiological models such as SIR and many of its modifications are not flexible enough and hence are not precise enough in the studies that requires the use of the features above. Decision-makers get serious benefits from using better and more flexible models as they can avoid of nuanced lock-downs, better plan the exit strategy based on local population data, different stages of the epidemic in different areas, making specific recommendations to specific groups of people; all this resulting in a lesser impact on economy, improved forecasts of regional demand upon NHS allowing for intelligent resource allocation.In this work, we investigate the sensitivity of the model to all its parameters while considering several realistic scenarios of what is likely to happen with the dynamics of the epidemic after the lock-down, which has started on March 23, is lifted.The main findings from this research are the following very little gain, in terms of the projected hospital bed occupancy and expected numbers of death, of continuing the lock-down beyond April 13, provided the isolation of older and vulnerable people continues and the public carries on some level of isolation in the next 2-3 months, see Section 3.1;in agreement with [1], isolation of the group of vulnerable people during the next 2-3 months should be one of the main priorities, see Section 3.2;it is of high importance that the whole population carries on some level of isolation in the next 2-3 months, see Section 3.5;the timing of the current lock-down seems to be very sensible in areas like London where the epidemic has started to pick up by March 23; in such areas the second wave of epidemic is not expected, see figures in Sections 2.2 and 3;the epidemic should almost completely finish in July, no global second wave should be expected, except areas where the first wave is almost absent, see Section 3.4.

scholarly journals Approaches in assessing the investment attractiveness of small towns of Russia

2018 ◽  
Vol 212 ◽  
pp. 08020
Author(s):  
A. Emelianovich ◽  
E. Kulyagina ◽  
Yu. Kolozhvari
Keyword(s):  
Methodological Approach ◽  
Local Population ◽  
Small Towns ◽  
Small Scale ◽  
Priority Vector ◽  
Product Increase ◽  
Effective Use ◽  
Further Development ◽  
The Town ◽  
Small And Medium Business

Effective use of the territories’ resources depends on the development of small- and medium-sized business as the basis of high economic activity of the local population. In Russia small and medium-sized business is a priority vector of economic development, a factor of the gross domestic product increase, and of unemployment decline. The article describes a methodological approach to assess the development of small scale and medium-sized enterprises of the territory bearing in mind the adaptation of some known methods to the peculiarities of the regional economy. The authors also assessed the investment potential and investment attractiveness on the example of the town of Barabinsk of the Novosibirsk Region. The article proves that small and medium business has great potential for further development, giving rise to many promising projects; still the paper reveals some actual problems delaying the process of small and medium-sized enterprises expansion. In the conclusion some activities for further promotion and stimulation of small and medium business development in the town of Barabinsk are proposed.

scholarly journals Potential Reduction of Carbon Burden for Senak Seawater Desalination Plant in Malaysia

2020 ◽  
Author(s):  
A.Ghani Latifah ◽  
Ilyani Syazira Nazaran ◽  
Nora'aini Ali ◽  
Marlia Hanafiah
Keyword(s):  
Carbon Footprint ◽  
Environmental Sustainability ◽  
Fossil Fuel ◽  
Salt Water ◽  
Local Population ◽  
Processing System ◽  
Water Desalination ◽  
Potential Contribution ◽  
Model Framework ◽  
Desalination Plant

Abstract PurposeCarbon footprint calculation is one of the approaches available in the Life Cycle Assessment (LCA) system, which can be considered as a decision support tool for environmental sustainability management. Hence, this purpose of this study is to examine the potential contribution of the product, namely water through carbon footprint measurement. Seawater has been selected as the source for clean water transformation in Senak due to its ability to meet the growing demands of the local population and its ability to be recycled in the long term.MethodsIn this study, carbon footprint assessment was used to investigate seawater production systems from a desalination plant in Senok, Kelantan, Malaysia. Three stages of the desalination plant processing system have been investigated and the inventory database has been developed using the relevant model framework. The LCA method, in accordance with ISO14040-43 guidelines has been simplified with working unit selected is 1 per cubic meter of treated water produced from a salt water desalination source.Results and discussionOverall, the results of the study indicate that the Revolutionary Osmotic (RO) technology that has been used in the desalination plant in the study area is one of the best options to meet the demands of the environmental sustainability agenda (SDGs). This is due to a lower carbon dioxide (CO2) emission of about 3.5 × 10−2 kg of CO2 eq per m3/year that has been recorded for the entire operation of the system. The other pollutants involved the emission of NOx and Sox, which were considered to be insignificant. However, if the plant continues to operate completely on fossil fuel for the next 25 years, the emission is expected to affect the health of the community.ConclusionsSeveral factors that influence important errors in carbon footprint decisions such as the lack of EIA reporting data and the literature on carbon footprint in the Malaysian scenario. The total dependency of electrical source for SWRO process of fossil fuel is the most critical factor in the carbon footprint issue in this study. These findings can be used to develop a carbon footprint model that can commercialise carbon tax, carbon economy capital, energy security assurance, and standard carbon regulation and legislation in the context of local desalination projects.

scholarly journals Demographic development of Zachodniopomorskie voivodship in the years 2000-2012 in the light of transportation network accessibility

2016 ◽  
Vol 32 (32) ◽  
pp. 61-72
Author(s):  
Elżbieta Chądzyńska
Keyword(s):  
Network Traffic ◽  
Transportation Network ◽  
Small Towns ◽  
Traffic Volume ◽  
Nordic Countries ◽  
Demographic Development ◽  
Capital Region ◽  
Close Vicinity ◽  
Regional Capital ◽  
Intervening Opportunities

Abstract The area of Zachodniopomorskie voivodship is characterized by specific features, resulting from its position in space. The location of the regional capital Szczecin at the mouth of the River Odra and near the Polish-German border, in the close vicinity of well-developed Nordic countries, and on the outskirts of the region creates special conditions for development. At the same time, the considerable remoteness of most small towns from the capital region and the inadequate network of connections in a natural North-South direction make it difficult to work with the assets of larger centres of development like Szczecin and Koszalin. The present approach is based on Webb’s typology for the gminas of Zachodniopomorskie voivodship compared with the analysis of the characteristics of the transportation network. Traffic volume of real transportation network was simulated by using a model based on the idea of intervening opportunities. Two categories of movements were analysed: movements to work and, due to the specificity of the region, tourists’ movements.

scholarly journals Threatening second wave of COVID-19 is imminent: A deep learning perspective

2020 ◽  
Author(s):  
Khondoker Nazmoon Nabi ◽  
Md Toki Tahmid ◽  
Abdur Rafi ◽  
Muhammad Ehsanul Kader ◽  
Md. Asif Haider
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Learning Models ◽  
Government Officials ◽  
Response Planning ◽  
The Future ◽  
The Government ◽  
Second Wave

AbstractWhen the entire world is waiting restlessly for a safe and effective COVID-19 vaccine that could soon become a reality, numerous countries around the globe are grappling with unprecedented surges of new COVID-19 cases. As the number of new cases is skyrocketing, pandemic fatigue and public apathy towards different intervention strategies are posing new challenges to the government officials to combat the pandemic. Henceforth, it is indispensable for the government officials to understand the future dynamics of COVID-19 flawlessly in order to develop strategic preparedness and resilient response planning. In light of the above circumstances, probable future outbreak scenarios in Bangladesh, Brazil, India, Russia and the United kingdom have been sketched in this study with the help of four deep learning models: long short term memory (LSTM), gated recurrent unit (GRU), convolutional neural network (CNN) and multivariate convolutional neural network (MCNN). In our analysis, CNN algorithm has outperformed other deep learning models in terms of validation accuracy and forecasting consistency. Importantly, CNN model showed clear indications of imminent second wave of COVID-19 in the above-mentioned countries. It has been unearthed in our study that CNN can provide robust long term forecasting results in time series analysis due to its capability of essential features learning, distortion invariance and temporal dependence learning. However, the prediction accuracy of LSTM algorithm has been found to be poor as it tries to discover seasonality and periodic intervals from any time series dataset, which were absent in our studied countries. Our results enlighten some surprising results that the studied countries are going to witness dreadful consequences of second wave of COVID-19 in near future. Quick responses from government officials and public health experts are required in order to mitigate the future burden of the pandemic in the above-mentioned countries.

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