Publication Type : Journal Article
Publisher : Global Transitions
Source : Global Transitions, Volume 2, p.202-220 (2020)
Url : https://www.sciencedirect.com/science/article/pii/S2589791820300190
Keywords : Covid-19, Emerging Infectious Diseases, Novel Corona Virus-19, Total Interpretive Structural Modeling, Wild Life Trade, Zoonotic Diseases
Campus : Coimbatore
School : School of Business
Department : Department of Management
Year : 2020
Abstract : The global risks report of 2020 stated, climate-related issues dominate all of the top-five long-term critical global risks burning the planet and according to the report, "as existing health risks resurge and new ones emerge, humanity's past successes in overcoming health challenges are no guarantee of future results." Over the last few decades, the world has experienced several pandemic outbreaks of various pathogens and the frequency of the emergence of novel strains of infectious organisms has increased in recent decades. As per expert opinion, rapidly mutating viruses, emergence and re-emergence of epidemics with increasing frequencies, climate-sensitive vector-borne diseases are likely to be increasing over the years and the trends will continue and intensify. Susceptible disease hosts, anthropogenic activities and environmental changes contribute and trigger the 'adaptive evolution' of infectious agents to thrive and spread into different ecological niches and to adapt to new hosts. The overarching objective of this paper is to provide insight into the human actions which should be strictly regulated to help to sustain life on earth. To identify and categorize the triggering factors that contribute to disease ecology, especially repeated emergence of disease pandemics, a theory building approach, 'Total Interpretive Structural Modeling' (TISM) was used; also the tool, 'Impact Matrix Cross-Reference Multiplication Applied to a Classification' analysis (MICMAC) was applied to rank the risk factors based on their impacts on other factors and on the interdependence among them. This mathematical modeling tool clearly explains the strength, position and interconnectedness of each anthropogenic factor that contributes to the evolution of pathogens and to the frequent emergence of pandemics which needs to be addressed with immediate priority. As we are least prepared for another pandemic outbreak, significant policy attention must be focused on the causative factors to limit emerging outbreaks like COVID 19 in the future.
Cite this Research Publication : L. S Priyadarsini, Dr. Suresh M., and Huisingh, D., “What can we learn from previous pandemics to reduce the frequency of emerging infectious diseases like COVID-19?”, Global Transitions, vol. 2, pp. 202-220, 2020.