A Machine Learning Application for Raising WASH Awareness in the Times of COVID-19 Pandemic

Abstract

A proactive approach to raise awareness while preventing misinformation is a modern-day challenge in all domains including healthcare. Such awareness and sensitization approaches to prevention and containment are important components of a strong healthcare system, especially in the times of outbreaks such as the ongoing Covid-19 pandemic. However, there is a fine balance between continuous awareness-raising by providing new information and the risk of misinformation. In this work, we address this gap by creating a life-long learning application that delivers authentic information to users in Hindi, the most widely used local language in India. It does this by matching sources of verified and authentic information such as the WHO reports against daily news by using machine learning and natural language processing. It delivers the narrated content in Hindi by using stateof-the-art text to speech engines. Finally, the approach allows user input for continuous improvement of news feed relevance on a daily basis. We demonstrate a focused application of this approach for Water, Sanitation, Hygiene as it is critical in the containment of the currently raging Covid-19 pandemic through the WashKaro android application. Thirteen combinations of pre-processing strategies, word-embeddings, and similarity metrics were evaluated by eight human users via calculation of agreement statistics. The best performing combination achieved a Cohen's Kappa of 0.54 and was deployed in the WashKaro application backend. Interventional studies for evaluating the effectiveness of the WashKaro application for preventing WASH-related diseases are planned to be carried out in the Mohalla clinics that provided 3.5 Million consults in 2019 in Delhi, India. Additionally, the application also features human-curated and vetted information to reach out to the community as audio-visual content in local languages.

Mapping the landscape of Artificial Intelligence applications against COVID-19

“…Efforts are also underway to curate specific news content related to the virus and to perform both manual and automated fact-checking and relevance analysis. For instance, Pandey et al (2020) † have developed a pipeline for assessing the similarity between daily news headlines and WHO recommendations. The pipeline uses word embedding and similarity metrics, such as cosine similarity, to assess the level of relevance between WHO recommendations and news articles.…”

Sentiment Analysis of Lockdown in India During Covid-19 a Case Study

“…Pandey et al [5] addressed the gap between the information and risk of misinformation by developing a lifelong learning model that provides genuine information in Hindi, the most commonly used local language in India. They matched the sources of authentic and genuine info, such as the news provided by WHO by using machine learning and NLP.…”

“…Most of the formidable diseases are generated from unhygienic habits. Hygiene measures and sanitation, such as hand washing, could play an important and cost-effective role in reducing the spread of pandemics, such as the COVID-19 [5]. The disease causes respiratory illness (like the flu) with symptoms such as cough, fever, and in more severe cases, difficulty breathing.…”

COVID-19 and Computer Audition: An Overview on What Speech & Sound Analysis Could Contribute in the SARS-CoV-2 Corona Crisis

“…Broadening up to Spoken Language Processing (SLP), this can also be of help to gather and analyse information from spoken conversations available in individual communications, news or social media. For textual cues, this has already been considered [23]. From a speech analysis perspective, this includes Automatic Speech Recognition (ASR) and Natural Language Processing (NLP).…”