Abstract
Significant variations in infection, testing, and mortality rates have exposed key differences in the initial COVID-19 response by Indian states. At the onset of the pandemic, states like Gujarat, known for its large economic output, suffered high COVID-19 case fatality rates, a disorganized response, and poor access to healthcare. In contrast, Kerala, a less industrialized state on India’s southwestern coast, experienced low infection rates and fatalities. The low case fatality rate was accompanied by widespread access to care, extensive testing, and an organized response by the state. The emergence of the COVID-19 pandemic provides an opportunity to compare how the Gujarat and Kerala models performed. Since 2000, the Gujarat model has emphasized industrialization and economic development, often at the expense of social development. In contrast, the Kerala model emphasizes social development, often at the expense of economic development. This article analyses the initial response to COVID-19 by Kerala and Gujarat and finds that the Kerala model and its emphasis on social development helped the state respond more effectively to the first wave of the pandemic compared to Gujarat.
Highlights
On 30 January 2020, India reported its first case of COVID-19 in Kerala, a state of 35 million people on the southwestern coast
The same day, the student was administered a COVID-19 test and her sample sent to the National Institute of Virology (NIV) in Pune, Maharashtra (Vaman et al, 2020)
The Kerala model’s focus on inclusive social development and economic growth meant that vulnerable populations were not left out of the government response to COVID-19
Summary
On 30 January 2020, India reported its first case of COVID-19 in Kerala, a state of 35 million people on the southwestern coast. The Kerala model is characterized by large government investment in health and education and a high rate of social mobilization led by strong labour organizations and popular movements resulting in improved living conditions for the poor (Heller et al, 2007; Parwez, 2016: 106).
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