This study examines the economic impact and public sentiment surrounding COVID-19 in ten South Asian countries, utilizing diverse analytical approaches including epidemiological analysis, demographic profiling, and climatic examination. Analyzing the data from reliable sources, the research employs advanced techniques such as the Long Short-Term Memory (LSTM) neural network model and Multiple Criteria decision-making (MCDM) methodologies to discern trends and patterns in the data. The analysis reveals insights into the epidemiological dynamics, demographic vulnerabilities, and climatic influences shaping COVID-19 progression. The present study’s multi-faceted analytical framework underscores the importance of understanding the pandemic’s complexities. The findings can inform evidence-based policy interventions and strategic decision-making processes to mitigate the pandemic’s impact and facilitate regional recovery efforts. Overall, this research aims to provide a thorough understanding of the COVID-19 situation in South Asia and elucidate the effectiveness of different analytical approaches in displaying the complexities of the pandemic.