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Published on: Jul 02, 2021
2 minute read
By: Dr Rakesh Rai

Delta Plus Variant Mystery: What Can Cause The Third Covid Wave?

Delta plus variant mystery: What can cause the third Covid wave?

Things in India are looking to normalize and beginning to reopen after a deadly second wave of Covid-19 infections devastated the country in April and May. There is various thought process from experts who are warning that a third wave could strike in the next few months. The majority of Indians are worried about new variants named delta plus, which is related to the Delta, an existing variant of concern first identified in India last year that was responsible for the deadly second wave.

The million-dollar question is how realistic these fears are. The reality is that future waves are not out of question but their severity and spread depend on several factors. In the past few weeks, the number of average daily cases in India has tapered down to less than 40,000 in recent days which was peak over 420,000 in May. The big drop in numbers has mainly because of strict lockdowns by states.

Many social and political events added to the second wave. If the reopening process are not orchestrated in a controlled fashion the next wave could come sooner than expected.

We are in a very decisive phase and our fate will depend on how we behave. Opening the states in a staggered manner is best. Going aggressive with vaccination and continue with COVID protocols will be the winning strategy. A balanced local and central health protocols could do the magic while severe action on defaulters could be used as a deterrent.

We know that the Delta variant had a killer impact during the second wave. The risk of future mutants in densely populated areas is known and preventive actions should be put in place immediately. There is no clear data around Delta plus but things have changed really fast when the proactive approach is not taken in advance. We need to understand that mutants only emerge when active transmission happening. A lot of research is happening around it take preemptive containment measures by understanding probable sequences.

So far data is indicating that the current vaccine is delivering good results in emerging mutants. India had sequenced 30,000 samples until June, but experts believe more needs to be done because the current vaccine is not a guaranteed long-term solution.

There are multiple cases where vaccinated people have got infected. Some call 3rd wave inevitable and some call it will be a smaller wave but the science is indicating that it will all depend on how effective our existing vaccine is against the new variants.

So, in conclusion, one can say that the key is the vaccinated population in controlling the wave and even allowing it to be formed. The acquired immunity and its efficacy will be crucial in determining the damage the third wave can cause. The required daily dose is upwards of 10 million to get all eligible populations covered by 2021.

The wide range of infection-causing natural antibodies and vaccination combined will provide the ammunition India needs badly to shield against future variants. The problem is the data around it is not very accurate. During the height of infections lot of COVID, infections went unreported. A lot of statisticians around it are guessing the acquired immunity percentage to be around 65%. This number should not be the reason we can take it easy.

Acquired immunity is immunity you develop over time from a vaccine or exposure to the infection.

Conclusively it can be said that “Third wave is only possible if the new variant beats the barriers of acquired immunity.”

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How Artificial Intelligence Is Transforming Patient Care in India

As a clinician working closely with patients across urban clinics and remote teleconsultation setups, I have seen firsthand how delayed diagnosis, fragmented follow-up, and specialist shortages affect outcomes in India. Artificial intelligence is not a futuristic concept in Indian healthcare anymore. It is actively reshaping how we diagnose diseases, monitor patients, and prevent complications.

AI, when used responsibly under clinical supervision, is becoming a critical support system for doctors and a powerful safety net for patients navigating a complex healthcare ecosystem.

Why India’s Healthcare System Needs AI

India’s healthcare challenges are deeply structural. A large population burdened by lifestyle diseases, combined with uneven access to medical expertise, creates gaps that traditional systems struggle to bridge.

In daily practice, we increasingly see patients presenting late with diabetes, hypertension, heart disease, or cancer. Many ask a simple but important question: why was this not detected earlier? The answer often lies in limited screening, overloaded clinicians, and lack of continuous monitoring.

Chronic conditions dominating Indian clinics today include:

Diabetes affecting over 100 million individuals.
Hypertension rising even among young adults.
Cardiovascular disease driven by late detection.
Increasing cancer incidence with delayed diagnosis.

AI matters here because it supports earlier identification of risk patterns, reduces diagnostic delays, and allows clinicians to focus on decision-making rather than data overload.

How AI Is Changing Medical Diagnosis

One common concern patients raise during consultations is whether AI can truly diagnose diseases accurately. In practice, AI does not replace a doctor. It acts as a high-speed analytical assistant.

AI in Imaging and Diagnostics

AI systems can rapidly analyse:

X-rays and CT scans.
MRI images.
Mammograms.
Pathology slides.
Cardiac and neurological imaging.

These tools flag abnormalities within seconds, allowing doctors to prioritise critical findings. Clinical studies published in peer-reviewed journals have shown that AI models can match specialist-level accuracy for specific imaging tasks when used correctly.

From a physician’s perspective, the real benefit is not speed alone. It is consistency. AI reduces the risk of missed findings during high-volume diagnostic workflows, especially in resource-constrained settings.

Can AI Monitor Patients Outside Hospitals

Patients managing chronic illness often ask whether technology can help them avoid repeated hospital visits. AI-enabled remote monitoring is one of the most meaningful advances in this area.

AI-Supported Remote Patient Monitoring

AI continuously evaluates trends in:

Blood pressure.
Heart rate variability.
Blood glucose patterns.
Oxygen saturation.
Physical activity and sleep quality.

Rather than reacting to a single abnormal value, AI identifies worsening trends over time. Clinically, this allows early intervention before complications escalate.

Evidence from global health system studies shows that continuous monitoring can significantly reduce avoidable hospital admissions, particularly for diabetes, heart disease, and elderly patients.

Using AI to Predict and Prevent Chronic Diseases

Preventive healthcare remains underdeveloped in India. Most patients seek care after symptoms appear. AI helps shift this model.

By analysing medical history, lifestyle habits, vitals, and environmental factors, predictive models can estimate:

Future heart attack risk.
Progression of diabetes.
Decline in kidney function.
Stroke probability.
Asthma exacerbation triggers.

Patients often ask if AI can really prevent disease. Prevention here means early warnings. When risk patterns are detected early, doctors can adjust treatment plans, recommend lifestyle changes, and prevent irreversible damage.

Personalised Treatment in a Diverse Indian Population

Indian patients differ widely in genetics, diet, stress patterns, and cultural habits. Standardised treatment protocols often fall short.

AI supports personalised care by analysing:

Medication responses.
Dietary intake.
Blood markers.
Sleep and stress trends.
Coexisting medical conditions.

For example:

In diabetes care, AI helps personalise carbohydrate distribution and medication timing.
In hypertension, it identifies sodium sensitivity and stress-related spikes.
In hormonal conditions like PCOS, it aligns nutrition and activity with cycle patterns.

From a clinical standpoint, personalised insights improve adherence and reduce relapse rates.

AI-Enabled Telemedicine and Smarter Consultations

Telemedicine has become an essential part of care delivery in India. Patients frequently ask whether online consultations are as effective as in-person visits.

AI enhances telemedicine by:

Structuring symptom inputs before consultations.
Routing patients to the appropriate specialist.
Generating concise medical summaries for doctors.
Supporting follow-up reminders and medication adherence checks.

When used correctly, AI reduces diagnostic delays and improves consultation efficiency without compromising safety.

Expanding Healthcare Access Beyond Cities

A major question in public health is whether AI can truly improve rural healthcare access. In practice, it already is.

AI enables:

Remote diagnostics supported by portable devices.
Virtual specialist consultations for rural clinics.
Smartphone-based imaging and screening tools.
AI-guided triage in underserved regions.

By reducing dependence on physical proximity to specialists, AI helps bridge longstanding geographical barriers in India’s healthcare system.

Safety, Ethics, and the Role of Doctors in AI Care

Patients rightly express concern about safety, privacy, and over-reliance on technology. These concerns are valid.

Responsible AI use in healthcare requires:

Transparent algorithms.
Explicit patient consent.
High-quality, verified medical datasets.
Strict data privacy safeguards.
Continuous clinical supervision.

In ethical practice, AI outputs never replace medical judgment. Doctors remain accountable for decisions. Human-in-the-loop verification is essential to ensure patient safety and trust.

What This Transformation Means for Indian Patients

Artificial intelligence is fundamentally changing patient care in India by making healthcare more proactive, more precise, and more accessible. From early diagnosis to personalised treatment and continuous monitoring, AI empowers both patients and clinicians with data-backed clarity.

SecondMedic’s patient-first approach integrates AI as a clinical support system, not a replacement for doctors. By combining medical expertise with digital intelligence, the goal remains simple: better outcomes, earlier intervention, and care that adapts to each patient’s real-world needs.

As clinicians, our responsibility is to ensure that technology serves patients ethically and effectively. When used with care and oversight, AI has the potential to redefine healthcare delivery across India in a way that is inclusive, preventive, and sustainable.

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