  The Covid-19 has presented an unprecedented challenge to public health
worldwide. However, residents in different countries showed diverse levels of
Covid-19 awareness during the outbreak and suffered from uneven health impacts.
This study analyzed the global Twitter data from January 1st to June 30th,
2020, seeking to answer two research questions. What are the linguistic and
geographical disparities of public awareness in the Covid-19 outbreak period
reflected on social media? Can the changing pandemic awareness predict the
Covid-19 outbreak? We established a Twitter data mining framework calculating
the Ratio index to quantify and track the awareness. The lag correlations
between awareness and health impacts were examined at global and country
levels. Results show that users presenting the highest Covid-19 awareness were
mainly those tweeting in the official languages of India and Bangladesh. Asian
countries showed more significant disparities in awareness than European
countries, and awareness in the eastern part of Europe was higher than in
central Europe. Finally, the Ratio index could accurately predict global
mortality rate, global case fatality ratio, and country-level mortality rate,
with 21-30, 35-42, and 17 leading days, respectively. This study yields timely
insights into social media use in understanding human behaviors for public
health research.
