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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM62215
Volume:
10 |
4 |
April 2026
Pages:
1-7
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Computer Science and Engineering
Lovely Professional University
Department of Computer Science and Engineering
Lovely Professional University
Department of Computer Science and Engineering
Lovely Professional University
Public-health systems in low- and middle-income countries (LMICs) face a persistent dual crisis: a shortage of accessible, trustworthy health information and an overabun- dance of misinformation that fills the resulting gap. Rural and underserved communities bear a disproportionate burden from vaccine-preventable and communicable diseases—malaria, cholera, dengue, tuberculosis, and acute diarrhoeal illness— often compounded by low health literacy and rampant health misinformation circulating via social media and informal net- works. This paper proposes ArogyaBot, an Artificial Intelligence– driven public-health chatbot designed for scalable deployment in resource-constrained settings. The system architecture comprises three core functional modules: (i) the Verified Information Relay (VIR), which grounds every response in authoritative sources including the World Health Organization (WHO), the Centers for Disease Control and Prevention (CDC), the National Health Portal of India (NHP), and the Ministry of Health and Family Welfare (MoHFW); (ii) the Pandemic and Myth Correction (PMC) engine, which detects and debunks circulating health misinformation in real time; and (iii) the Community Action and Referral Engine (CARE), which connects users to nearby government health facilities, emergency services, and community health workers. A mandatory safety filter layer enforces the disclaimer—this tool is not a diagnostic instrument; consult local health authorities—and triggers human-in-the-loop escalation for crisis scenarios. The paper presents system architecture, user- experience design principles (WCAG 2.1 compliant), a phased deployment roadmap, a prospective evaluation framework in- cluding a cluster-randomised pragmatic trial design, and a com- prehensive ethics and privacy compliance analysis under Indian and international regulatory standards. ArogyaBot represents a scalable, evidence-grounded, and governance-aligned digital public-health intervention adaptable to any linguistically and infrastructurally diverse region.
KEYWORDS
This paper has presented ArogyaBot, a modular, ethics- grounded, AI-driven public-health chatbot designed for scal- able deployment in resource-constrained settings. By anchor- ing every response to verified sources (WHO, CDC, NHP, MoHFW) [1]–[4], actively correcting health misinformation via the PMC module, and linking citizens to actionable care pathways via CARE, ArogyaBot directly addresses the dual challenge of the health-information gap and the infodemic that undermines public-health gains in underserved communities [9]. The system’s commitment to data minimisation, DPDPA and MoHFW regulatory compliance, WCAG 2.1 accessibility, and mandatory HITL escalation places ethics and safety at the architecture’s core. Critically, ArogyaBot is not a replacement for qualified healthcare—it is a bridge. It connects a citizen who has a health question with the authoritative information and services they need at the moment they need it. In communities where a significant portion of the population consults informal or unverified sources before seeking formal care, a trusted, acces- sible, multilingual digital health companion has the potential to meaningfully improve health-seeking behaviours, reduce vaccine hesitancy, counter harmful myths, and contribute to a measurable reduction in preventable disease burden [8], [9]. Rigorous evaluation through the proposed cluster-randomised pragmatic trial will generate the real-world evidence needed to guide continuous improvement and responsible scaling across diverse deployment contexts. Final disclaimer: ArogyaBot is not a diagnostic instrument. It does not prescribe medications or dosages. All guidance is for health awareness purposes only. In any medical emergency, call emergency services immediately. Consult local health au- thorities and qualified healthcare professionals for all clinical advice.
1 World Health Organization, “Infodemic Management: A Key Component of the COVID-19 Global Response,” WHO, Geneva, 2021. [Online]. Available: https://www.who.int/health-topics/infodemic 2 Ministry of Health and Family Welfare, Government of India, “National Framework for Malaria Elimination in India 2016–2030,” MoHFW, New Delhi, 2023. [Online]. Available: https://main.mohfw.gov.in 3 National Health Portal of India, “State and District Health Profiles,” NHP India, 2022. [Online]. Available: https://www.nhp.gov.in/state-health- profile 4 Ministry of Health and Family Welfare, “Digital Health Incentive Scheme and National Digital Health Blueprint,” MoHFW / ABDM, New Delhi, 2023. [Online]. Available: https://abdm.gov.in 5 International Institute for Population Sciences, “National Family Health Survey (NFHS-5), 2019–21: India,” IIPS, Mumbai, 2021. [On- line]. Available: http://rchiips.org/nfhs/NFHS-5Reports/NFHS-5 INDIA REPORT.pdf 6 World Health Organization, “Global Tuberculosis Report 2023,” WHO, Geneva, 2023. [Online]. Available: https://www.who.int/teams/global- tuberculosis-programme/tb-reports 7 World Health Organization, “Health Literacy: The Solid Facts,” WHO Europe, 2021. [Online]. Available: https://www.euro.who.int/en/ publications/abstracts/health-literacy.-the-solid-facts 8 E. G. Lattie, S. E. Adkins, N. Winquist, C. Stiles-Shields, R. L. Wafford, and D. C. Mohr, “Digital Mental Health Interventions for Depression, Anxiety, and Enhancement of Psychological Well-Being Among College Students: Systematic Review,” Journal of Medical Internet Research, vol. 21, no. 7, p. e12869, 2019. 10.2196/12869 9 S. M. Abd-Alrazaq, M. Alajlani, A. A. Alalwan, B. Bewick, P. Gardner, and M. Househ, “An Overview of the Features of Chatbots in Mental Health: A Scoping Review,” International Journal of Medical Informatics, vol. 132, p. 103978, 2019. 10.1016/j.ijmedinf.2019.103978 10 Centers for Disease Control and Prevention, “Health Literacy: Accurate, Accessible, and Actionable Health Information,” CDC, Atlanta, 2023. [Online]. Available: https://www.cdc.gov/healthliteracy
Publication Date
5/1/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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