The outbreak of an epidemic disease may pose significant treats to human beings and may further lead to a global crisis. In order to control the spread of an epidemic, the effective management of rapidly increased medical waste through establishing a temporary reverse logistics system is of vital importance. However, no research has been conducted with the focus on the design of an epidemic reverse logistics network for dealing with medical waste during epidemic outbreaks, which, if improperly treated, may accelerate disease spread and pose a significant risk for both medical staffs and patients. Therefore, this paper proposes a novel multi-objective multi-period mixed integer program for reverse logistics network design in epidemic outbreaks, which aims at determining the best locations of temporary facilities and the transportation strategies for effective management of the exponentially increased medical waste within a very short period. The application of the model is illustrated with a case study based on the outbreak of the coronavirus disease 2019 (COVID-19) in Wuhan, China. Even though the uncertainty of the future COVID-19 spread tendency is very high at the time of this research, several general policy recommendations can still be obtained based on computational experiments and quantitative analyses. Among other insights, the results suggest installing temporary incinerators may be an effective solution for managing the tremendous increase of medical waste during the COVID-19 outbreak in Wuhan, but the location selection of these temporary incinerators is of significant importance. Due to the limitation on available data and knowledge at present stage, more real-world information are needed to assess the effectiveness of the current solution.

In developing nations with an abundance of natural water resources, fishing is a major source of income. When distributing resources between fisheries and other sectors, and preserving competitiveness in the fisheries industry, access to livelihood assets continues to be a key factor. However, vulnerability of livelihood assets and other economic and social variables have been severely affecting fishermen's livelihood. This article examines livelihood income vulnerability in the context of capital assets and the effects on local fishermen's livelihood and well-being. A survey sample size of 532 rural households based on a descriptive research design was used. Financial capital, human capital, social capital, and natural capital all made an enormous contribution to the earnings of fishermen and household heads in the Manchar Lake basin. The use of multiple regression analysis enabled new insights into how the livelihood assets characteristics affected their household income choices. The main objective of this investigation is to see whether access of livelihood capital assets affect local fishermen's livelihood income in the Manchar Lake basin. In the coastal belt of the Manchar Lake basin, resource acquisition plays a critical role in eradicating poverty. For the fishermen in the Manchar Lake basin, the current regime could further prioritize investing in fish trading infrastructure and improving essential facilities like social networks, education, skillsets, improved technology, and credit facilities in order to raise the livelihood income of fishermen and either reduce or alleviate poverty. These findings provide insight into fishermen's entry and exit for those who are planning livelihood shifts, and offer recommendations on how to overcome the constraints faced by the fisheries industry. Furthermore, insight into livelihood sustainability in order to improve the quality of life and income of fishermen domestically and nationally is also suggested.

Green innovation is an important driving force to promote the sustainable development of urban society and economy. This paper constructs an evaluation index system containing social undesirable outputs, and uses the Super-SBM model and the Malmquist-Luenberger index to evaluate green innovation efficiency in 42 cities along the Yangtze River Economic Belt from 2013 to 2017. Additionally, spatial autocorrelation analysis is used to study the spatial correlation of green innovation efficiency. Finally, the coupling coordination degree model is used to study the coupling coordination degree between green innovation efficiency and high-tech industries. The following results were obtained. (1) The average value of green innovation efficiency increased from 1.0446 to 1.0987, and the annual average growth rate of total factor productivity of green innovation was 1.1%. (2) Green innovation efficiency of the Yangtze River Economic Belt had a significant spatial positive correlation, but the types of agglomeration among cities in different sections of the Yangtze River were quite different. (3) The coupling coordination degree between green innovation efficiency and the development level of high-tech industries in the cities of the Yangtze River Economic Belt was in the basic coordination stage. Based on the research results, we suggest that cities in this belt further enhance the interactive relationship between green innovation and economic development and promote the coordinated development of economy and society.