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Sustainable social development promotes COVID-19 pandemic control.

ABSTRACT: The rapid spread of COVID-19 had a negative impact on public health and economic recovery worldwide. There is a large and growing literature on pandemic prevention and control. However, these existing studies seldom focus on the role of sustainable social development in this process. By setting specifications of fixed-effect models based on the score data of sustainable development goals (SDG) and infection case data from 257 Chinese cities, we evaluate the positive effect of sustainable social development on pandemic control. Our results show that sustainable social development leads to a remarkable improvement in pandemic prevention and control, especially for SDG4 (Quality Education) and SDG5 (Gender Equality). Significant positive effects of sustainable social development still exist in the post-pandemic era. This study highlights the importance of promoting social SDGs by linking them with pandemic prevention and control and suggests region-specific policies based on the heterogeneous analysis results.

SUBMITTER: Feng S

PROVIDER: S-EPMC9188261 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: The world has been unprecedentedly hit by a global pandemic which broke the record of deadly pandemics that faced humanity ever since its existence. Even kids are well-versed in the terminologies and basics of the SARS-CoV-2 virus and COVID-19 now. The vaccination program has been successfully launched in various countries, given that the huge global population of concern is still far behind to be vaccinated. Furthermore, the scarcity of any potential drug against the COVID-19-causing virus forces scientists and clinicians to search for alternative and complementary medicines on a war-footing basis. Aims and Objectives: The present review aims to cover and analyze the etiology and epidemiology of COVID-19, the role of intestinal microbiota and pro-inflammatory markers, and most importantly, the natural products to combat this deadly SARS-CoV-2 virus. Methods: A primary literature search was conducted through PubMed and Google Scholar using relevant keywords. Natural products were searched from January 2020 to November 2020. No timeline limit has been imposed on the search for the biological sources of those phytochemicals. Interactive mapping has been done to analyze the multi-modal and multi-target sources. Results and Discussion: The intestinal microbiota and the pro-inflammatory markers that can serve the prognosis, diagnosis, and treatment of COVID-19 were discussed. The literature search resulted in yielding 70 phytochemicals and ten polyherbal formulations which were scientifically analyzed against the SARS-CoV-2 virus and its targets and found significant. Retrospective analyses led to provide information about 165 biological sources that can also be screened if not done earlier. Conclusion: The interactive analysis mapping of biological sources with phytochemicals and targets as well as that of phytochemical class with phytochemicals and COVID-19 targets yielded insights into the multitarget and multimodal evidence-based complementary medicines.

Project description:In this paper, a new production, allocation, location, inventory holding, distribution, and flow problems for a new sustainable-resilient health care network related to the COVID-19 pandemic under uncertainty is developed that also integrated sustainability aspects and resiliency concepts. Then, a multi-period, multi-product, multi-objective, and multi-echelon mixed-integer linear programming model for the current network is formulated and designed. Formulating a new MILP model to design a sustainable-resilience healthcare network during the COVID-19 pandemic and developing three hybrid meta-heuristic algorithms are among the most important contributions of this research. In order to estimate the values of the required demand for medicines, the simulation approach is employed. To cope with uncertain parameters, stochastic chance-constraint programming is proposed. This paper also proposed three meta-heuristic methods including Multi-Objective Teaching-learning-based optimization (TLBO), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) to find Pareto solutions. Since heuristic approaches are sensitive to input parameters, the Taguchi approach is suggested to control and tune the parameters. A comparison is performed by using eight assessment metrics to validate the quality of the obtained Pareto frontier by the heuristic methods on the experiment problems. To validate the current model, a set of sensitivity analysis on important parameters and a real case study in the United States are provided. Based on the empirical experimental results, computational time and eight assessment metrics proposed methodology seems to work well for the considered problems. The results show that by raising the transportation costs, the total cost and the environmental impacts of sustainability increased steadily and the trend of the social responsibility of staff rose gradually between - 20 and 0%, but, dropped suddenly from 0 to + 20%. Also in terms of the on-resiliency of the proposed network, the trends climbed slightly and steadily. Applications of this paper can be useful for hospitals, pharmacies, distributors, medicine manufacturers and the Ministry of Health.Supplementary informationThe online version contains supplementary material available at 10.1007/s10479-021-04238-2.

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Sustainable social development promotes COVID-19 pandemic control.

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