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Published on: Nov 13, 2020
2 minute read
By: Dr Rajan ( Medical Second Opinion Cell)

What Are Some Common Side Effects Of The COVID-19 Vaccine?

COVID Vaccine, the Pfizer update

On Monday Pfizer announced to the world the vaccine, once it has been developing with Germany's BioNTech, was found to be more than 90?fective. If this is substantiated, it may be possible for countries to receive the vaccine before the end of the year.

The Vaccine is an mRNA Vaccine, a novel method that introduces viral RNA into the body via a viral coat. The vaccine is incorporated into the person's cell, where the viral RNA is read and viral proteins are produced, including the coronavirus coat proteins. As the body reads and recognizes these proteins, it produces antibodies against these viral proteins and activates immune T cells against the virus.

The Pfizer results are based of a phase 3 clinical trial with 43, 538 participants with a diverse background. In this trial, the participants were split between those receiving a vaccine, and those who received a placebo with no effect. The vaccine is administered in two parts, with a 90?ficacy obtained 7 days after the second dose. This would mean a person is vaccinated just 28 days after the initial vaccination.

The FDA usually looks for a minimum 50?ficacy in vaccination when approving new vaccines. It may surprise you that the annual flu jab is also estimated to be 50?fective. The data from Pfizer was verified by an external, independent Data Monitoring Committee. It used data from 94 patients enrolled in the trial and subsequently developed COVID. It is from this groupset that 90% of efficacy is obtained. This is not the final data analysis, and further publications are expected in late November, with a potential FDA Emergency Use Authorisation approval if the data continues to show promise.

If approved, Pfizer has the ability to make 50 million shots before the end of the year, and 1.3 billion by the end of 2021. Many countries are clamoring for their fair share of these limited resources; the US has already negotiated 200m shots, UK 50m, and Germany (one of the major financers for the Pfizer vaccine) over 300m for European Countries.

We should emphasize that rapid vaccine development on this scale at this speed was unheard of prior to COVID. Usually, the animal studies for vaccines can take 1-2 years. In that time Pfizer and others have managed phase 1-3 clinical trials in humans, something that usually takes upwards of 10 years.

There are many unanswered questions that remain from this information.

How safe is the vaccine? Whilst safety information was not published, overall the vaccine appears to have minimal side effects. This is particularly difficult to state however since mRNA vaccines have never been used in people before.
Does the vaccine prevent transmission? In theory, yes. If you are immunized the replication of the virus should be limited significantly, so the number of viruses in each cough will be much lower. However, we do not have data to prove that there is no transmission, but that is also because we have very little data overall.
How long does the protection last? This is a very critical question. The 90?fectiveness rate was calculated just 7 days after the second shot, but it is likely this will change as data is collected over the long term. Some studies have suggested the antibody response fades within months following COVID infection. T Cell immunity on the other hand can stay for years, and it may be the effectiveness of creating a T cell immunity that dictates just how good this vaccine will be .

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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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