India is dealing with a problem of snakebites. Every year around 50,000 people die from snakebites in India. This is out of about 3 to 4 million snakebite incidents that happen. Sadly India accounts for half of all the snakebite deaths that happen in the whole world (Ministry of Health & Family Welfare, 2024). The real number of deaths from snakebites is probably a lot higher than what the officials are reporting. The official numbers only show a part of the actual deaths from snakebites, in India. Madhya Pradesh had a lot of snakebite deaths from 2020 to 2022. There were 5,728 deaths from snakebites in Madhya Pradesh that were confirmed. This made the government pay out a lot of money to the families of the people who died. The government paid out INR 229.12 crores, which’s about USD 28.2 million. This is not even half of the total number of deaths from snakebites that were expected in Madhya Pradesh. It is 45 percent of the predicted mortality in Madhya Pradesh according to the research done by (Kadam et al., 2025) about snakebite deaths, in Madhya Pradesh. Recognizing this neglected crisis, the Government of India launched the National Action Plan for Prevention and Control of Snakebite Envenoming (NAPSE) in March 2024, with an ambitious vision to “prevent and control snakebite envenoming in order to halve the numbers of deaths and cases of disability that it causes by 2030” (Ministry of Health & Family Welfare, 2024). NAPSE’s success depends critically on integrating artificial intelligence and digital health systems to close gaps in diagnosis, surveillance, treatment access, and antivenom distribution.
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The Diagnostic and Surveillance Crisis
The main issue with snakebites is that it is very complicated. Many people who get bitten by snakes in areas do not know what kind of snake bit them. This means they often get the medicine, which can lead to deaths that could have been prevented. The medicine for snakebites only reaches 60.2 percent of people who are in the hospital because it is not always available and some places are hard to get to. We do not have information, about snakebites because the data is spread out across different states. This makes it difficult to send help to the areas that need it most. Until November 2024 snakebites were not considered a disease that had to be reported in India. The Ministry of Health & Family Welfare mandated integration of snakebite into the Integrated Disease Surveillance Programme (IDSP) on November 27, 2024, enabling real-time case reporting through IDSP-IHIP (Integrated Health Information Platform) across all primary health centers (Ministry of Health & Family Welfare, 2024). This infrastructure now allows automated hotspot mapping and outcome tracking, but only with accurate, timely data entry integrated with hospital systems.
Artificial Intelligence for Species Identification
Knowing the right kind of snake is very important for treatment. This is because different snakes have venom so doctors need to use the right medicine and give the right amount of it. A Vision Transformer-based AI model uses pictures to identify things was trained on a lot of snake pictures. 386,006 pictures of 772 kinds of snakes from 188 countries. This program was able to identify the type of snake 96.0 percent of the time and the group of snake 99.0 percent of the time. This includes all the snakes, in India that can cause harm like the “big four” snakes that cause 90 percent of the bad cases of snake venom poisoning (McCallum et al., 2022). When field workers photograph offending snakes and submit them to AI-enabled mobile apps, identification returns within 30 seconds, allowing immediate antivenom selection and clinical preparation. For NAPSE implementation, governments should mandate deployment of AI snake identification apps in high-burden districts, integrated with hospital electronic medical record systems.
Machine Learning for Outcome Prediction
Machine learning algorithms predict snakebite outcomes—recovery, amputation, or death-based on patient characteristics, bite site, and time-to-treatment. The algorithms look at things like the person who got bitten where the snake bit them. How long it took to get treatment. Some people used a kind of computer program called XGBoost to look at what happened to 1,022 people who got bitten by snakes. They found out that how old the person is, what they do, for work, where the snake bit them and how long it took to get to the hospital are all things to know. This information helps doctors figure out who needs the medicine that fights snake venom the most. They can give it to the people who’re most likely to get very sick or die from the snakebite (McCallum.,2025). In India’s context, ML models trained on NAPSE surveillance data can identify high-risk population, farmers during monsoon season (when 62% of bites occur), tribal communities with limited access, and patients presenting late (>6 hours post-bite), guiding antivenom pre-positioning and targeted interventions. Implementation requires linking hospital management systems with IDSP-IHIP to auto-upload treatment details, enabling continuous model refinement with real-world outcomes data.
Digital Health Apps and Telemedicine
A 2025 scoping review identified 16 mobile apps for snakebite management globally, with 11 (69%) from India (JMIR Publications, 2025). These apps provide snake identification, hospital locating, first-aid guidance (prohibiting harmful practices like tourniquets applied in 90% of some cases), and telemedicine consultations linking patients to snakebite specialists. However, significant barriers persist: less than 40% internet connectivity in tribal-majority districts, rural digital literacy at 65% vs. 95% urban, and most apps available only in English or unavailable offline (Yellapu & Rajkumar, 2024). Solutions require developing open-source, government-supported apps in 15+ Indian languages with offline functionality, distributing low-cost smartphones to all primary health centers in high-burden states, and conducting intensive training for frontline workers. State health departments should subsidize app access through National Health Mission funding.
Addressing the Antivenom Supply Crisis
Although antivenom cannot be produced by technology, AI significantly enhances quality control and distribution. The Central Bureau of Health Intelligence (CBHI) reports average annual frequencies of about 3 lakh snakebite cases with about 2,000 deaths (CBHI, 2016–2020), indicating supply-demand mismatches, despite the fact that India’s antivenom demand reaches about 3–4 million vials nationwide. By taking into account seasonal trends and occupational risk, machine learning models trained on NAPSE surveillance data can forecast monthly antivenom requirements by district. With real-time monitoring, IoT sensors integrated into cold-chain vehicles keep supply pipelines at -20°C. In order to lessen reliance on a single government facility, NAPSE should set aside a budget for improving cold-chain infrastructure, installing demand-forecasting machine learning software at state secretariats, and setting up five to eight regional venom centers with AI-integrated quality control. (Haffkine Institute, Mumbai)
Implementation Roadmap
Short Term (2024–25): Operationalize snakebite surveillance through IDSP-IHIP across high-burden states (Uttar Pradesh, Rajasthan, Odisha, West Bengal, Madhya Pradesh); deploy AI snake identification apps in 5 pilot districts; equip 200 PHCs with tablets and train 1,500 health workers; pilot IoT temperature monitoring in 20 cold-chain vehicles.
Medium-term (2025–27): Scale surveillance to 100% of PHCs in high-burden states; deploy identification apps to 1,000 PHCs; integrate AI outcome-prediction algorithms into 30 secondary/tertiary care hospitals; establish telemedicine links between PHCs and venom centers; upgrade cold-chain infrastructure in 100 district hospitals; operationalize demand-forecasting for antivenom allocation; train 5,000 health workers.
Long-term (2027–30): Achieve universal digital surveillance with <24-hour reporting latency; integrate AI decision-support into all hospital EMR systems; establish 5–8 fully operational regional venom centers; deploy AI-chatbots for community prevention in 15+ languages; measure outcomes: 50% mortality reduction (from 50,000 to 25,000 annual deaths) and 75% reduction in preventable deaths.
Overcoming Implementation Barriers
Digital health integration must confront three critical barriers:
a) Digital literacy and infrastructure: Rural populace, particularly tribal communities where snakebite burden is highest, have limited digital literacy and internet access.
Solution: Develop offline-capable apps; provide government-subsidized smartphones and internet data plans to all PHCs in high-burden districts; conduct intensive 2-week training programs for frontline workers.
b) Data privacy: Integration of snakebite surveillance with electronic systems raises patient privacy concerns.
Solution: Implement anonymization protocols separating patient identifiers from clinical data; encrypt all data in transit and at rest; establish state-level data governance boards.
c) Technology adoption resistance: In some rural and tribal areas, traditional healers are consulted first (64% of cases in some tribal zones) with delayed hospital presentation.
Solution: Engage traditional healers as technology partners; frame technology as supporting, not replacing, traditional knowledge; involve community leaders in rollout.
Conclusion:
Through quick species identification, outcome prediction, efficient supply chains, and evidence-based prevention, artificial intelligence and digital health technologies present previously unheard-of chances to lower India’s snakebite burden. For NAPSE to be successful by 2030, an investment roughly INR 1.50 per capita annually is needed, a small portion of health spending for transformative impact. The integrated pathway consists of digital health infrastructure that links rural PHCs to specialized networks, AI-powered identification at point-of-care, predictive logistics that optimizes antivenom distribution, and universal digital surveillance that records incidence and outcomes in real-time. Now is the time to take action before another 500,000 avoidable deaths take place.
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References:
1. Central Bureau of Health Intelligence (CBHI). (2016–2020). Average annual frequency of snakebite cases in India. Ministry of Health & Family Welfare Report.
2. Chandra, A., Union Health Secretary. (2024, March). National Action Plan for Prevention and Control of Snakebite Envenoming (NAPSE). Press Information Bureau, Government of India. https://www.pib.gov.in/PressReleasePage.aspx?PRID=2013803
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