  The COVID-19 pandemic has put immense pressure on health systems which are
further strained due to the misinformation surrounding it. Under such a
situation, providing the right information at the right time is crucial. There
is a growing demand for the management of information spread using Artificial
Intelligence. Hence, we have exploited the potential of Natural Language
Processing for identifying relevant information that needs to be disseminated
amongst the masses. In this work, we present a novel Cross-lingual Natural
Language Processing framework to provide relevant information by matching daily
news with trusted guidelines from the World Health Organization. The proposed
pipeline deploys various techniques of NLP such as summarizers, word
embeddings, and similarity metrics to provide users with news articles along
with a corresponding healthcare guideline. A total of 36 models were evaluated
and a combination of LexRank based summarizer on Word2Vec embedding with Word
Mover distance metric outperformed all other models. This novel open-source
approach can be used as a template for proactive dissemination of relevant
healthcare information in the midst of misinformation spread associated with
epidemics.
