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Previously submitted to: Journal of Medical Internet Research (no longer under consideration since Feb 22, 2021)

Date Submitted: Oct 30, 2020

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

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

  • Rohan Pandey; 
  • Vaibhav Gautam; 
  • Ridam Pal; 
  • Harsh Bandhey; 
  • Lovedeep Singh Dhingra; 
  • Himanshu Sharma; 
  • Chirag Jain; 
  • Kanav Bhagat; 
  • Arushi Arushi; 
  • Lajjaben Patel; 
  • Mudit Agarwal; 
  • Samprati Agrawal; 
  • Rishabh Jalan; 
  • Ayush Garg; 
  • Akshat Wadhwa; 
  • Vihaan Misra; 
  • Yashwin Agrawal; 
  • Bhavika Rana; 
  • Ponnurangam Kumaraguru; 
  • Tavpritesh Sethi

ABSTRACT

Background:

The COVID-19 pandemic has uncovered the potential of digital misinformation in shaping the health of nations. The deluge of unverified information that spreads faster than the epidemic itself is an unprecedented phenomenon that has put millions of lives in danger. Mitigating this ‘Infodemic’ requires strong health messaging systems that are engaging, vernacular, scalable, effective and continuously learn the new patterns of misinformation.

Objective:

We created WashKaro, a multi-pronged intervention for mitigating misinformation through conversational AI, machine translation and natural language processing. WashKaro provides the right information matched against WHO guidelines through AI, and delivers it in the right format in local languages.

Methods:

We theorize (i) an NLP based AI engine that could continuously incorporate user feedback to improve relevance of information, (ii) bite sized audio in the local language to improve penetrance in a country with skewed gender literacy ratios, and (iii) conversational but interactive AI engagement with users towards an increased health awareness in the community.

Results:

A total of 5026 people who downloaded the app during the study window, among those 1545 were active users. Our study shows that 3.4 times more females engaged with the App in Hindi as compared to males, the relevance of AI-filtered news content doubled within 45 days of continuous machine learning, and the prudence of integrated AI chatbot “Satya” increased thus proving the usefulness of an mHealth platform to mitigate health misinformation.

Conclusions:

We conclude that a multi-pronged machine learning application delivering vernacular bite-sized audios and conversational AI is an effective approach to mitigate health misinformation. Clinical Trial: Not Applicable


 Citation

Please cite as:

Pandey R, Gautam V, Pal R, Bandhey H, Dhingra LS, Sharma H, Jain C, Bhagat K, Arushi A, Patel L, Agarwal M, Agrawal S, Jalan R, Garg A, Wadhwa A, Misra V, Agrawal Y, Rana B, Kumaraguru P, Sethi T

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

JMIR Preprints. 30/10/2020:25320

DOI: 10.2196/preprints.25320

URL: https://preprints.jmir.org/preprint/25320

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