Efficiency evaluation and promoter identification of primary health care system in China: an enhanced DEA-Tobit approach.

BACKGROUND: With Primary Health Care (PHC) being a cornerstone of accessible, affordable, and effective healthcare worldwide, its efficiency, especially in developing countries like China, is crucial for achieving Universal Health Coverage (UHC). This study evaluates the efficiency of PHC systems in a southwest China municipality post-healthcare reform, identifying factors influencing efficiency and proposing strategies for improvement. METHODS: Utilising a 10-year provincial panel dataset, this study employs an enhanced Data Envelopment Analysis (DEA) model integrating Slack-Based Measure (SBM) and Directional Distance Function (DDF) with the Global Malmquist-Luenberger (GML) index for efficiency evaluation. Tobit regression analysis identifies efficiency determinants within the context of China's healthcare reforms, focusing on horizontal integration, fiscal spending, urbanisation rates, and workforce optimisation. RESULTS: The study reveals a slight decline in PHC system efficiency across the municipality from 2009 to 2018. However, the highest-performing county achieved a 2.36% increase in Total Factor Productivity (TFP), demonstrating the potential of horizontal integration reforms and strategic fiscal investments in enhancing PHC efficiency. However, an increase in nurse density per 1,000 population negatively correlated with efficiency, indicating the need for a balanced approach to workforce expansion. CONCLUSIONS: Horizontal integration reforms, along with targeted fiscal inputs and urbanisation, are key to improving PHC efficiency in underdeveloped regions. The study underscores the importance of optimising workforce allocation and skillsets over mere expansion, providing valuable insights for policymakers aiming to strengthen PHC systems toward achieving UHC in China and similar contexts.

Cross-efficiency analysis of energy sector using stochastic DEA: Considering pollutant emissions.

Undesirable outputs can be challenging to avoid in the production of goods and services, often overlooked. Pollution is generally regarded as a negative externality and is taken into account during the production process. The novelty of this study lies in introducing CO2 as an economic "bad" in the energy sector's efficiency measure through a stochastic data envelopment analysis (DEA) cross-efficiency model. Unlike pollution and economic goods, where increased production leads to more pollution, CO2 is weakly disposable, meaning that higher CO2 values lead to a decrease in the number of good outputs produced. The study proposes a new stochastic model based on an extension of the cross-efficiency model and applies it to measure the energy efficiency of 32 thermal power plants in Angola in the presence of undesirable outputs. This will help promote better environmental management. The study's findings offer vital policy insights for the energy sector. The introduction of new stochastic models enables more accurate efficiency measurement under uncertain conditions, aiding policymakers in resource allocation decisions. Additionally, the adoption of stochastic cross-efficiency methods enhances performance assessments, facilitating targeted interventions for underperforming units. These findings contribute to evidence-based policymaking, promoting sustainability and competitiveness within the energy sector.

Evaluating the impact of the innovation efficiency of high-tech industry on carbon emissions: a case study of the manufacturing industry in China.

Amid China's economic shift to high-quality development, addressing environmental challenges like greenhouse gas emissions and manufacturing pollution, there is a crucial demand for sustainable and eco-friendly development strategies. This study aims to investigate the impact of innovation efficiency in the high-tech industry on carbon emissions. It seeks to explore regional differences, mechanisms, and the influence of energy consumption structures in achieving sustainable development goals. Utilizing data from 30 provinces spanning 2009 to 2020, the study employs the DEA-Malmquist index model, spatial and temporal classification evaluation, and a panel measurement model to assess the efficiency of innovation and development in high-tech industries and their relationship with carbon emissions. The results indicate several key findings: (1) The overall operational efficiency of high-tech industry innovation and development in China is steadily increasing. However, there are distinct characteristics observed among provinces and cities, reflecting diverse input and output types. (2) High-tech industry innovation efficiency significantly contributes to carbon emission reduction, and there is regional heterogeneity in this impact. The central and western regions exhibit greater effects compared to other provinces and cities. (3) The optimization of the energy structure is identified as a mechanism through which high-tech industry innovation efficiency reduces carbon emissions. Moreover, different intervals of high-tech industry innovation efficiency yield varying effects on carbon emissions. This research underscores the importance of fostering high-tech industry innovation efficiency as a means to reduce carbon emissions. It also identifies key areas for future policy development and resource allocation, emphasizing the support needed for low-carbon technology research and development.

Non-contrast enhanced MRI for efficiency evaluation of high-intensity focused ultrasound in adenomyosis ablation.

OBJECTIVE: To investigate the value of T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) in evaluating the therapeutic effect of high-intensity focused ultrasound (HIFU) in adenomyosis ablation. MATERIAL AND METHODS: One hundred eighty-nine patients with adenomyosis were treated with HIFU. The ablation areas on T2WI and DWI sequences were classified into different types: type I, relatively ill-defined rim or unrecognizable; subtype IIa, well-defined rim with hyperintensity; subtype IIb, well-defined rim with hypointensity. The volume of ablation areas on T2WI (VT2WI) and DWI (VDWI) was measured and compared with the non-perfused volume (NPV), and linear regression was conducted to analyze their correlation with NPV. RESULTS: The VT2WI of type I and type II (subtype IIa and subtype IIb) were statistically different from the corresponding NPV (p = 0.004 and 0.024, respectively), while no significant difference was found between the VDWI of type I and type II with NPV (p = 0.478 and 0.561, respectively). In the linear regression analysis, both VT2WI and VDWI were positively correlated with NPV, with R2 reaching 0.96 and 0.97, respectively. CONCLUSIONS: Both T2WI and DWI have the potential for efficient evaluation of HIFU treatment in adenomyosis, and DWI can be a replacement for CE-T1WI to some extent.

Non-homogeneity in the efficiency evaluation of health systems.

BACKGROUND: An international comparison of health system performance is a popular tool of health policy analysis. However, the efficiency evaluation of health systems is a practical example of an international comparison in which non-homogeneity is expected. The objective of this paper is to evaluate the efficiency of health systems by models in which a degree of non-homogeneity among countries is considered. METHODS: We study the problem of non-homogeneity of health systems in the theoretical framework of the data envelopment analysis (DEA), which is a popular method of efficiency evaluation with hundreds of applications from various fields. DEA assume the homogeneity of production units and the homogeneity of the environment in which the production units operate. Hence, we compiled a summary of 14 recommendations on how to deal with the non-homogeneity in the DEA models. The analysed sample includes 38 OECD member countries. The data are from the year 2019. RESULTS: As an example, we evaluated the health system efficiency of the Czech Republic. We used the DEA models with the neighbourhood measure of distance and the constraint limiting the comparison of countries with different levels of economic development. The health system inputs were the numbers of physicians, nurses, and hospital beds. In the production of the intermediate outputs (doctor consultations, inpatient care discharges), the Czech Republic should look at Poland, Slovakia and Slovenia. In the production of health outcomes (life expectancy), the peer countries are France, Italy and Switzerland. CONCLUSIONS: The results of the DEA analysis are only indicative because no single analytical method can determine whether a health system is better or worse than others. We need to combine different methods, and DEA is one of them. We consider DEA as an exploratory method, not a method providing definitive answers.

Integrated Cardiomyocyte-Based Biosensing Platform for Electroporation-Triggered Intracellular Recording in Parallel with Delivery Efficiency Evaluation.

Electroporation is a proven technique that can record action potential of cardiomyocytes and serve for biomolecular delivery. To ensure high cell viability, micro-nanodevices cooperating with low-voltage electroporation are frequently utilized in research, and the effectiveness of delivery for intracellular access is typically assessed using an optical imaging approach like flow cytometry. However, the efficiency of in situ biomedical studies is hampered by the intricacy of these analytical approaches. Here, we develop an integrated cardiomyocyte-based biosensing platform to effectively record action potential and evaluate the electroporation quality in terms of viability, delivery efficiency, and mortality. The ITO-MEA device of the platform possesses sensing/stimulating electrodes which combines with the self-developed system to achieve intracellular action potential recording and delivery by electroporation trigger. Moreover, the image acquisition processing system analyzes various parameters effectively to assess delivery performance. Therefore, this platform has the potential for drug delivery therapy and pathology research for cardiology.

The construction efficiency study of China National Ecological Civilization Pilot Zone with network SBM model: a city-based analysis.

The Chinese government proposed the establishment of China National Ecological Civilization Pilot Zone in 2016 to further explore the coordinated development of economy and environment. Fujian, Jiangxi, and Guizhou provinces were selected as the first batch of pilot zones. After years of exploration, it is necessary to discuss and summarize the construction progress of the three pilot zones from the perspective of the city. In this study, first, the ecological civilization pilot zone construction system was decomposed into an economic construction subsystem (ECS) and an environmental optimization subsystem (EOS). Then, a two-stage network SBM model was adopted to calculate the efficiencies of the subsystems, and the Kruskal-Wallis test was used to measure the efficiency difference. Finally, a panel data regression model was applied to explore the influencing factors of both subsystems. The results show that the ECS efficiency is higher than that of the EOS, and the ECS efficiency in Fujian is significantly better than that in Jiangxi and Guizhou. However, there is no significant difference in EOS efficiency in the three provinces. Furthermore, industrial structure and population agglomeration have a significant effect on ECS efficiency, environmental regulation has a significant impact on EOS, and the technology level has a significant impact on both subsystems. Based on the results, policy implications for improving the efficiency of the two subsystems were given respectively.

Evaluation of the Impact of Policymakers' Decisions in the Management Capacity of Protected Areas: Efficiency Evidence from Five Countries.

Protected areas play an important role in biodiversity conservation and tourism. Significant efforts have been made to increase the amount of protected lands. A problem of increasing the amount of public protected areas is that governments and other institutions face difficulties in providing the necessary resources for effective management. Accordingly, managers must be as efficient as possible but the lack of comparative methods makes the evaluation of efficiency difficult. Using Data Envelopment Analysis, a non-stochastic and non-parametric approach, information from 29 protected areas in 5 countries was analyzed to compare management efficiency amongst them. The first result found is the level of management efficiency that each park has in comparison with the others parks. The other important result is a prediction of the changes in the outputs if there is a hypothetical budget change. These results allow the generation of information for decision making.

Efficiency Evaluation and Influencing Factors of Green Innovation in Chinese Resource-Based Cities: Based on SBM-Undesirable and Spatial Durbin Model.

Based on data from 64 resource-based cities in China from 2010 to 2019, the efficiency of green innovation is evaluated by using the super-efficiency SBM Model with undesired outputs, while influencing factors of green innovation efficiency are analyzed by the spatial Durbin model. The results are as follows. First, as for the efficiency evaluation, the average green innovation efficiency in 62 resource-based cities from 2010 to 2019 is only 0.5689, while the green innovation efficiency of declining cities is the highest, and the growth type is the lowest in the comprehensive planning cities. Second, based on spatial self-correlation in resource-based cities, the government support, and the influencing factors including the industrial structure and economic development, have positive impacts, while the environmental regulations and opening to the outside world will inhibit the urban green innovation. Therefore, to enhance the green innovation efficiency in resource-based cities, some suggestions include formulating differentiated development strategies, forming regional cooperation mechanisms, increasing government scientific and technological support, determining the reasonable intensity of environmental regulations, setting entry barriers for polluting enterprises, and optimizing industrial structure.

Evaluation and driving factors of land use economic efficiency in China's urban agglomerations under the impact of COVID-19 epidemic.

Land is an indispensable factor of production and the basic support for all social and economic activities. The COVID-19 epidemic has a great impact on China's macro-economy and land market. As a unit with a high concentration of economic entities, urban agglomeration is closely related to its land use economic efficiency. Under the impact of epidemic and the rigid constraints of the relative scarcity of land resources, improving the land use economic efficiency is crucial to the sustainable development of urban agglomerations. Taking the 10 major urban agglomerations in China as a case study, this paper constructs a theoretical and empirical analysis framework for the land use economic efficiency and its driving mechanism of urban agglomerations, and measures the land use economic efficiency of urban agglomerations from the aspects of single factor productivity and total factor productivity. The results show that the COVID-19 epidemic has a great impact on the land market of various cities in China's urban agglomerations. Whether single factor productivity or total factor productivity is used to measure land use economic efficiency of urban agglomerations, the driving effects of industrial agglomeration, industrial structure change, technological progress, and transportation infrastructure are all significant. It is necessary to take a series of measures to reform the market-oriented allocation of land elements, and improve a long-term mechanism for the smooth operation of the land market. It is necessary to improve the land use economic efficiency through a combination of industrial agglomeration, industrial structure adjustment, technological progress, and transportation infrastructure.

Operational efficiency evaluation of urban and rural residents' basic pension insurance system by utilizing a picture fuzzy TOPSIS method based on the cumulative prospect theory.

Population aging is the most serious challenge facing the pension insurance system in China in the next few decades. Compared with the employees of civil servants and enterprises and institutions, urban and rural residents are unstable vulnerable groups with less income. In order to deal with the pension risks caused by the growing aging population and solve the security problems of urban and rural residents, our government has carried out a series of constructive works in the pension insurance system: in view of the rural and urban residents, new rural social endowment insurance system and the social endowment insurance system for urban residents have been set up and combined into a unified basic old-age insurance system for urban and rural residents in 2014. With the continuous expansion in the scale of income and expenditure of urban and rural living insurance funds and the size of the insured number, it is of great necessity to evaluate the efficiency of this system. The operational efficiency evaluation of urban and rural residents' basic pension insurance systems is viewed as multi-attribute group decision-making (MAGDM). In this paper, we propose an approach by combining the traditional Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) with cumulative prospect theory (CPT) which can be widely used with vague information. Thus, the main contribution of this study is as follows: (1) the TOPSIS method is extended by picture fuzzy sets (PFSs) with unknown weight information; (2) entropy method to obtain the original weights of attributes; (3) the picture fuzzy-CPT-TOPSIS (PF-CPT-TOPSIS) method is used to deal with the MAGDM problems under PFSs; (4) a numerical instance for operational efficiency evaluation of urban and rural residents' basic pension insurance systems is proposed to testify the effectiveness of new method; and (5) some comparative studies are provided to give effect to the rationality of PF-CPT-TOPSIS approach.

Determining the Efficiency of the Sponge City Construction Pilots in China Based on the DEA-Malmquist Model.

Sponge city construction (SCC) has improved the quality of the urban water ecological environment, and the policy implementation effect of SCC pilots is particularly remarkable. Based on the data envelopment analysis (DEA) model, this study employed the related index factors such as economy, ecology, infrastructure, and the population of the pilot city as the input, and the macro factors of SCC as the output, to scientifically evaluate the relative efficiency between the SCC pilots in China. Eleven representative SCC pilots were selected for analysis from the perspectives of static and dynamic approaches, and comparisons based on the horizontal analysis of the efficiency of SCC pilots were conducted and some targeted policy suggestions are put forward, which provide a reliable theoretical model and data support for the efficiency evaluation of SCC. This paper can be used as a reference for construction by providing a DEA model for efficiency evaluation methods and thus helps public sector decision makers choose the appropriate construction scale for SCC pilots.

Evaluating Effects of Dynamic Interventions to Control COVID-19 Pandemic: A Case Study of Guangdong, China.

The emergence of different virus variants, the rapidly changing epidemic, and demands for economic recovery all require continual adjustment and optimization of COVID-19 intervention policies. For the purpose, it is both important and necessary to evaluate the effectiveness of different policies already in-place, which is the basis for optimization. Although some scholars have used epidemiological models, such as susceptible-exposed-infected-removed (SEIR), to perform evaluation, they might be inaccurate because those models often ignore the time-varying nature of transmission rate. This study proposes a new scheme to evaluate the efficiency of dynamic COVID-19 interventions using a new model named as iLSEIR-DRAM. First, we improved the traditional LSEIR model by adopting a five-parameter logistic function ß(t) to depict the key parameter of transmission rate. Then, we estimated the parameters by using an adaptive Markov Chain Monte Carlo (MCMC) algorithm, which combines delayed rejection and adaptive metropolis samplers (DRAM). Finally, we developed a new quantitative indicator to evaluate the efficiency of COVID-19 interventions, which is based on parameters in ß(t) and considers both the decreasing degree of the transmission rate and the emerging time of the epidemic inflection point. This scheme was applied to seven cities in Guangdong Province. We found that the iLSEIR-DRAM model can retrace the COVID-19 transmission quite well, with the simulation accuracy being over 95% in all cities. The proposed indicator succeeds in evaluating the historical intervention efficiency and makes the efficiency comparable among different cities. The comparison results showed that the intervention policies implemented in Guangzhou is the most efficient, which is consistent with public awareness. The proposed scheme for efficiency evaluation in this study is easy to implement and may promote precise prevention and control of the COVID-19 epidemic.

The Efficiency Evaluation of Municipal-Level Traditional Chinese Medicine Hospitals Using Data Envelopment Analysis After the Implementation of Hierarchical Medical Treatment Policy in Gansu Province, China.

Background: Efficiency evaluation is an integral part of new medical reform and is necessary to solve the problem of limited and unbalanced medical resources. This study evaluated the efficiency of municipal-level Traditional Chinese Medicine hospitals by Data Envelopment Analysis application after a hierarchical medical treatment policy was implemented. We propose solutions to the problems existing in hospital operations and promote the utilization efficiency of medical resources in those hospitals. Methods: The sample included all municipal-level TCM hospitals in Gansu province from 2017 to 2019. The DEA-BCC model was employed to evaluate the relative efficiency of hospital operations, and the Manny-Whitney test was used to compare the input and output variables of technical efficiency efficient and inefficient hospitals. Results: From 2017 to 2019, the growth in the number of staff in secondary hospitals (25.88%) was lower than that in tertiary hospitals (31.98%). However, the increase in the number of beds (16.52%) in secondary hospitals was higher than that in tertiary hospitals (-0.30%). 5 (38.46%) achieved DEA efficient in secondary hospitals and 2 (40.00%) in tertiary hospitals. The means of technical efficiency, pure technical efficiency, and scale efficiency in secondary hospitals were 0.812, 0.887, and 0.908, respectively. The means in tertiary hospitals were 0.868, 0.926, and 0.935, respectively. The hospital areas were statistically different between the TE efficient and inefficient hospitals (P<0.05) in secondary hospitals. However, the number of outpatients between the two groups was statistically different (P<0.05) in tertiary hospitals. Conclusion: In this study, the medical and health services of municipal TCM hospitals in Gansu Province have made great progress. Due to the backward economy of Gansu Province, the classification of diagnosis and treatment of diseases was still based on Western medicine, resulting in the slow medical development of some municipal TCM hospitals. TCM hospitals should improve management efficiency, optimize hospital operation scale, improve the utilization efficiency of medical resources and promote efficient hospital development.

Changes in efficiency of tertiary public general hospitals during the reform of public hospitals in Beijing, China.

BACKGROUND: In March 2009, the Chinese government formally launched a new round of healthcare reform. As the city with the highest concentration of high-quality medical resources in China, in the past 10 years, Beijing has also been exploring medical reforms. This article studied the performance and development of the 10 tertiary general public hospitals managed by Beijing Municipal Hospital Management Centre to provide policy basis for further deepening Beijing public hospital reform and improving hospital efficiency. METHODS: The 2011, 2015 and 2018 'Beijing Health Work Statistics' were used to evaluate the performance of Beijing's tertiary public general hospitals, based on the Pabon Lasso model and the data envelopment analysis (DEA) model. RESULTS: Based on the Pabon Lasso model, 60%, 70% and 70% of the hospitals were entirely efficient (zone 3) in 2011, 2015 and 2018. It shows that among the 10 general public hospitals in Beijing, efficient hospitals accounted for the majority and further increased during the reform period. The DEA model further illustrates this point and shows more effective hospitals (80%) than the Pabon Lasso model, showing the efficiency of these hospitals to be improved during the reform period. CONCLUSIONS: The efficiency of the 10 hospitals has gradually improved during the reform period, and the difficulty of seeing a doctor in Beijing at a national medical centre has been relieved to a certain extent. Combining the Pabon Lasso model and the DEA model can analyse hospital efficiency more comprehensively, and can prompt initial information for improving hospital efficiency, but the results also reflect some problems.

A proposed multistage evaluation approach for Higher Education Institutions based on network Data envelopment analysis: A Brazilian experience.

The evaluation of Higher Education Institutions (HEIs) is a challenging task, due to the complexity inherent in the context in which they are inserted, the different institutional profiles, the variety of resources used and the results offered in the performance of their mission. In this way, the present study proposes an evaluative approach that aims to measure efficiency taking into account the diverse activities characteristic of university institutions. To this end, a data envelopment analysis (DEA) approach, known as Network DEA, is used, which encompasses the different processes and subprocesses that take place within these institutions. In all, the evaluation considers eleven variables organized in three distinct stages, which reflect the performance of the HEIs in different perspectives: financial, undergraduate level and graduate level (student training and scientific production and innovation). Finally, the model was applied at 45 Brazilian federal universities. This case study allows a comprehensive efficiency analysis to be carried out for the set of institutions considered, from each perspective taken into account in the approach.

Preliminary Safety and Potential Effect of 6B11-OCIK Adoptive Cell Therapy Against Platinum-Resistant Recurrent or Refractory Ovarian Cancer.

Ovarian cancer is a leading cause of death among gynecological malignancies, and novel therapies are urgently needed. Here we report preliminary findings on the potential safety and efficacy of 6B11-OCIK, an adoptive cell therapy of autologous T cells induced by the humanized anti-idiotypic antibody 6B11 minibody plus dendritic cells and cytokines, against platinum-resistant recurrent or refractory ovarian cancer in three patients. We found that 6B11-OCIK treatment was safe and well tolerated after five cycles of intravenous infusion with an initial dose of 1-2×109 cells and a dose-climbing strategy. Hemoglobin, platelets, white cell count, creatinine or liver enzyme values, coagulation function, kidney and heart function were not significantly affected over the duration of therapy. Two of the three enrolled patients showed potentially drug-related grade 1 and 2 weakness, and no other adverse events were observed. Of the three enrolled patients, one had stable disease and two showed disease progression. The patient with favorable clinical efficacy had better immune response as measured by 6B11-OCIK proliferation capacity, activation ability of CD3+CD8+ tumor-specific cytotoxic T lymphocytes and CD3+CD56+ cytokine-induced killer cells, and tumor cell killing efficiency. Changes in circulating tumor cells after treatment were consistent with serum level CA125 in the patient with stable disease (both decreased), while differences were observed in the two patients with disease progression (increased CA125 in both and decreased CTC in the patient with better immune response), suggesting that variation of circulating tumor cells was more consistent with immune response and reflected efficacy directly. This preliminary study suggested that autologous 6B11-OCIK treatment was safe and had potential clinical efficacy against ovarian cancer. Patients with better immune response had more favorable efficacy. In addition to imaging, CA125 and immunophenotypes, CTC monitoring may represent a potential indicator of immunotherapy response.

Evaluation of the eco-efficiency of waste treatment facilities in Korea.

As waste treatment facilities become old, their operation and maintenance costs could increase, which translates to higher treatment costs and environmental burden. This study applies the concept of eco-efficiency to evaluate waste treatment facilities considering the various conditions of waste treatment operations based on the case of Korea. In Korea, waste treatment methods were largely divided into five categories, and facilities for each treatment method were chosen based on their size, location, and waste properties for data collection. The method for evaluating the facilities' eco-efficiencies were developed using the concepts of environmental and economic performances. The results of the eco-efficiency evaluation showed that landfills were most environmentally efficient, followed by the organic waste biogasification facilities, food waste recycling facilities, incineration facilities, and, lastly, combustible waste-to-fuel facilities. The results of the eco-efficiency evaluation were further reviewed in terms of three factors which assess the status of existing facilities as well as to identify the environmental and economic indicators which significantly affect the eco-efficiency of waste treatment facilities by treatment method and propose strategic policies for promoting better waste treatment operations.

Analysis of China's Industrial Green Development Efficiency and Driving Factors: Research Based on MGWR.

With increasingly severe constraints on resources and the environment, it is the mainstream trend of economic development to reduce industrial pollution emissions and promote green industrial development. In this paper, a super-efficiency slacks-based measure (SBM) model is adopted to measure the industrial green development efficiency (IGDE) of 289 cities in China from 2008 to 2018. Moreover, we analyze their spatiotemporal differentiation pattern. On this basis, the multiscale geographical weighted regression (MGWR) model is used to analyze the scale differences and spatial differences of the driving factors. The results show that the IGDE is still at a low level in China. From 2008 to 2018, the overall polarization of IGDE was relatively serious. The number of high- and low-efficiency cities increased, while that of medium-efficiency cities greatly decreased. Secondly, the IGDE presented an obvious spatial positive correlation. MGWR regression results show that the technological innovation, government regulation, and consumption level belonged to the global scale, and there was almost no spatial heterogeneity. Other driving factors were urbanization, industrial structure, economic development, and population density according to their spatial scale. Lastly, the influence of economic development and technological innovation had a certain circular structure in space; the influence of population size mainly occurred in the cities of the southeast coast and northeast provinces; the influence of urbanization was more obvious in the most northern provinces of the Yangtze River, while that of industrial structure was mainly concentrated in the most southern cities of the Yangtze River Economic Belt (YREB). Spatially, the influence of consumption was manifested as a distribution trend of decreasing from north to south, and the government regulation was manifested as increasing from west to east and then to northeast.

A close look at 2019 novel coronavirus (COVID 19) infections in Turkey using time series analysis & efficiency analysis.

2019 novel coronavirus (COVID 19) infections detected as the first official records of the disease in Wuhan, China, affected almost all countries worldwide, including Turkey. Due to the number of infected cases, Turkey is one of the most affected countries in the world. Thus, an examination of the pandemic data of Turkey is a critical issue to understand the shape of the spread of the virus and its effects. In this study, we have a close look at the data of Turkey in terms of the variables commonly used during the pandemic to set an example for possible future pandemics. Both time series modeling and popular efficiency measurement methods are used to evaluate the data and enrich the results. It is believed that the results and discussions are useful and can contribute to the language of numbers for pandemic researchers working on the elimination of possible future pandemics.