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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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Machine Learning in Healthcare India: A New Era of Predictive and Personalized Care

Machine learning is driving one of the biggest transformations in Indian healthcare. Machine learning in healthcare India is improving diagnostics, predicting diseases early, and enabling personalized treatment plans based on large volumes of medical data. India’s enormous population, diverse health patterns, and rising burden of lifestyle diseases make ML an essential technology for improving care outcomes.

SecondMedic integrates machine learning across diagnostics, risk scoring, preventive care, and remote monitoring to create intelligent, data-driven healthcare experiences.

Why Machine Learning Is Crucial for India’s Healthcare

India faces major challenges: increasing chronic diseases, low doctor-to-patient ratio, and gaps in early diagnosis. Machine learning helps overcome these limitations through automated analysis and predictive insights.

ML supports:

Accurate disease prediction
Faster diagnosis
Personalized treatment
Proactive health management
Population-level insights

These benefits significantly improve care outcomes.

Machine Learning in Diagnostics

ML excels at interpreting complex medical data faster than traditional methods.

ML improves diagnostics by:

Identifying abnormal patterns
Analyzing imaging scans
Interpreting lab values
Comparing historical trends
Supporting clinical decisions

This reduces misdiagnosis and saves time.

Predictive Healthcare with Machine Learning

Predictive analytics is one of the most powerful ML applications.

ML predicts risks for:

Heart disease
Diabetes
Kidney disorders
Thyroid imbalances
Mental health issues
Respiratory disorders

SecondMedic provides predictive scoring for early detection.

Personalized Treatment Planning

Machine learning tailors treatment to individual needs.

ML personalizes care based on:

Age and genetics
Lifestyle patterns
Vitals and wearable data
Sleep and stress levels
Previous medical history

This ensures more accurate and effective treatment.

ML in Remote Patient Monitoring

With the rise of home healthcare, ML analyzes continuous vitals data.

ML monitors:

Heart rate
Blood oxygen
Blood sugar
Blood pressure
Sleep cycles

AI-generated alerts support timely intervention.

ML in Medical Imaging

ML enhances imaging interpretation by detecting subtle visual patterns.

Applications include:

Lung infections
Cancer markers
Cardiac abnormalities
Brain lesions
Kidney anomalies

This improves radiology accuracy and speed.

ML for Population Health in India

ML identifies health trends at a large scale, helping policymakers and hospitals plan resources.

ML provides:

Outbreak prediction
Disease burden patterns
Community health insights
Regional risk mapping

These tools help improve national healthcare planning.

Challenges in ML Healthcare Adoption

While ML is powerful, challenges include:

Data quality issues
Need for clinical validation
Privacy concerns
Infrastructure limitations
Need for skilled professionals

SecondMedic follows ethical ML standards and ensures secure data practices.

Future of Machine Learning in Indian Healthcare

Upcoming innovations include:

Deep learning diagnostics
Digital health twins
Fully AI-driven preventive dashboards
ML-based robotic treatments
Genomic ML predictions

SecondMedic is committed to building future-ready ML healthcare solutions.

Conclusion

Machine learning in healthcare India is transforming medical care through predictive analytics, personalized treatment, and early disease detection. SecondMedic uses machine learning across its digital ecosystem to deliver accurate, efficient, and patient-centered care.

To explore ML-powered healthcare tools, visit www.secondmedic.com

References

NITI Aayog – AI & ML in Indian Healthcare
WHO – Machine Learning in Clinical Practice
ICMR – India Chronic Disease Data
IMARC – AI & ML Healthcare India
FICCI – Emerging Health Technologies India

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