  The spread of the global COVID-19 pandemic affected Sri Lanka similar to how
it affected other countries across the globe. The Sri Lankan government took
many preventive measures to suppress the pandemic spread. To aid policy makers
in taking these preventive measures, we propose a novel district-wise
clustering based approach. Using freely available data from the Epidemiological
Department of Sri Lanka, a cluster analysis was carried out based on the
COVID-19 data and the demographic data of districts. K-Means clustering and
spectral clustering models were the selected clustering techniques in this
study. From the many district-wise socio-economic factors, population,
population density, monthly expenditure and the education level were identified
as the demographic variables that exhibit a high similarity with COVID-19
clusters. This approach will positively impact the preventive measures
suggested by the relevant policy making parties of the Sri Lankan government.
