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India's pharmaceutical sector has been one of the largest manufacturers of generic drugs globally. During the pandemic, most countries were dependent on imports of generic drugs from India. However, India has been relying on resources from China for Active Pharmaceutical Ingredients (APIs) which are the raw material for preparing generic drugs. We considered, in our analysis, branded product groups of Paracetamol and Amoxicillin due to their extensive use in the treatment of COVID-19. From a thorough market analysis of both the drugs, we conclude that firms have a monopoly over their brands but compete within the same product group and operate in their respective market under varying prices within certain bandwidths which resembles the feature of monopolistic competitive market. We have introduced compensating function a la Helpman (1981) in the pharmaceutical goods market with the assumption that an 'ideal product' exists among the pharmaceutical goods. Given the framework, this paper explores a general equilibrium model set in a monopolistic competitive product market for branded drugs. We concluded through our propositions that expanding the pharmaceutical sector will increase the employment of unskilled labor under no capacity constraint. We will observe an increase in wages of unskilled labor only under full employment conditions wherein we would observe that the expansion of pharmaceutical good will increase wages in the unskilled labor market. However we obtain an intriguing result wherein we obtain that despite instances of limiting trade dependence on China through implementation of policies like 'Aatmanirbhar Bharat' and 'profit linked incentive schemes', yet to maintain the status quo in the global market for generic drugs, India's dependence on China would increase, owing to API imports due to the pandemic crisis. While India can grab the opportunity in the form of increased demand for pharmaceutical goods to increase the employment level of the economy but this improvement in welfare is also dependent on the degree of dependency of API India has on China. The Indian government has recognized the same through the incorporation of 'Covid-Suraksha' and PLI schemes to minimize import dependency, and accelerate the development of APIs and the production of indigenous drugs. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak has led to a substantial loss of human life throughout the world and has a tremendous impact on healthcare services. Industry 4.0 technologies have established effective supply chain management towards the fulfillment of customized demands in the healthcare field. In addition, the internet of things, artificial intelligence, big data analytics, and 3D printing have been extensively used to combat the COVID-19 pandemic and assist in providing value-added services in the healthcare sector. Henceforth, this paper presents a scientometric analysis on the literature of aforementioned Industry 4.0 technologies in the context of COVID-19. It provides extensive insights into co-citation and co-occurrence analysis of high cited publications, participating countries, influential authors, prolific journals, and keywords using the CiteSpace tool. The analyses reveal that China has produced the highest research outputs, although India is the most collaborative country in this field. The current research hotspots include supply chain, 4D printing, and social distancing technologies. Furthermore, it explores emerging trends, intellectual structure of publications, research frontiers, and potential research directions for further work in the Industry 4.0 assisted healthcare domain. [Display omitted] • Industry 4.0 technologies have emerged in the healthcare domain as an area of growing interest in academia and industry discipline. • Artificial intelligence, big data analytics, internet of things and 3D printing have been extensively used to control the COVID-19 spread and assist in providing value-added services in the healthcare sector. • It explores emerging trends, intellectual structure of publications, and potential research directions for further work in the Industry 4.0 assisted healthcare domain. [ABSTRACT FROM AUTHOR]