Effect of an epidemic on trade and migration

Abstract

With the recent outbreak of Coronavirus, which has affected India's trade and migration and has affected the whole economy globally, this opens up an avenue to dig a little deeper and understand the dynamics. Epidemics have been quite frequent in humanity's history, to even the extent that some theories say that epidemics have occurred even before humans' existencein the dinosaur era. One of the reasons for the disappearance of the same is credited to an Epidemic. Recent Human History is full of examples of breakthrough epidemics like – cholera, measles, smallpox, bird-flu, and the very recent one being Coronavirus. Talking of this most recent Epidemic, there is already a noise about how much economic impact this outbreak has on trade. According to a Reuters poll of economists, China's economic growth expected to slow to 4.5% in the first quarter of 2020 – the slowest pace since the financial crisis. The International Energy Agency says, "Global oil demand has been hit hard by the novel coronavirus." Factory shutdowns are slowing the flow of products and parts from China, affecting companies worldwide, including Apple and Nissan. All these are significant enough to imply the profound repercussions such outbreaks have on trade. There were expected to be 3 billion journeys by the people living in mainland China on their Lunar new year. Such Mass Migration during this time of Epidemics is bound to increase the chances of dispersion of this disease. These are just some of the superficial aspects of the Epidemic on trade and migration. And that too of only one episode in the history. We aim to understand if mathematically, we can find out this relationship between Epidemic and Trade, if not for the whole world, but at least the country of origin and its trading partners. Thus, we started with understanding the significant epidemics in the world and which attributes of the economy affected the most. We then narrowed down and defined our problem statement to focus on two major epidemics in the recent era on the pretext of data availability. Followed next was applying suitable methodologies in mathematics to understand the association. This was supplemented by secondary research on the epidemic episodes. Finally, we have concluded the result we obtained from our analysis, mentioning the limitations.