In Search of an Alternative to "Strict Lockdown"; Data-driven Policies in the Face of COVID-19 Pandemic

The world noticed an emerging virus in the Chinese city of Wuhan, in early January. At first, no one was concerned – officials said it was not infectious – so on Chinese New Year, it was considered a local problem that was published coincidentally. Today, after about 300 days of lockout, which is limited to the coronavirus outbreak's epicenter, it has spread all over the world, with every aspect of life, including the ruin of companies. Some countries faced the crisis preferring the use of big data governance over just maximum physical isolation. Notably, some Southeast Asian countries, such as Taiwan, South Korea, Japan, and Singapore, have adopted a set of smart strategies based on data science and disruptive techs to enhance the crisis management process. Past work indicates a major difference in terms of results and overall efficacy between the smart data-driven approach and the strict lockdown policy. This point of view attempts to address these gaps by making distinctions based on knowledge obtained from two approaches. Therefore, it holds a critical position on the extent of progress for each nation, which is the embeddedness of such an integrated strategy in both socio-cultural and political contexts. The paper investigates Iranian experiences of data-driven responses to COVID-19, namely Mask application and the Ministry of Health and Medical Education's online self-assessment, regarding their contribution to the crisis management process. Thus, it seems that integrating success around the problem mentioned above, threatening human existence, requires a cohesive governance strategy that allows people of the digital age to be mobilized for a public interest, social security, and public health.