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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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AI-Based Disease Detection India: How SecondMedic Is Transforming Early Diagnosis

India’s healthcare landscape is evolving rapidly, with artificial intelligence emerging as one of the most powerful tools for early disease detection. AI-based disease detection India represents a major shift from reactive healthcare to predictive, preventive, and precise medical analysis. Instead of waiting for symptoms to appear, AI enables clinicians and patients to identify risks early through advanced data interpretation.

Rising chronic diseases, increased diagnostic loads, and limited specialist availability make AI essential for early diagnosis in India. The use of AI in medical imaging, risk scoring, and pattern recognition significantly enhances accuracy while reducing time-consuming manual processes. SecondMedic integrates AI-powered diagnostic tools to help individuals detect health conditions in their earliest stages, enabling timely intervention and improved long-term outcomes.

Why India Needs AI-Based Disease Detection

India faces one of the world’s highest burdens of chronic and lifestyle diseases. Many conditions remain undiagnosed until they reach advanced stages, often due to late screenings, limited access to specialists, or lack of early symptoms.

The need for AI-based detection is driven by:

High incidence of silent diseases like diabetes and hypertension
Overloaded healthcare systems
Limited availability of expert radiologists
Rising lifestyle risk factors
Increasing demand for precision diagnostics
Need for faster, more accurate analysis

AI bridges these gaps by providing early alerts, consistent accuracy, and fast interpretations.

How AI Detects Diseases Early

AI-based disease detection uses machine learning models trained on thousands of medical datasets. These models learn to recognize abnormal patterns and subtle changes that the human eye might overlook.

AI analyzes:

Blood test patterns
Vital signs and wearable data
Imaging scans (X-rays, MRIs, CT scans)
Medical history
Genetic predispositions
Lifestyle habits

Through advanced algorithms, AI can identify risks long before symptoms appear, giving patients critical time for prevention and treatment.

AI in Medical Imaging: A Major Breakthrough for India

Medical imaging AI has transformed diagnosis speed and accuracy. In India, where access to radiologists is uneven, AI helps bridge diagnostic gaps.

AI-assisted imaging helps detect:

Lung infections and tuberculosis
Early-stage cancer indicators
Cardiac abnormalities
Brain tumors and neurological issues
Bone fractures and musculoskeletal conditions
Liver and kidney anomalies

SecondMedic uses AI-supported imaging interpretation to enhance precision and reduce reporting delays.

AI for Chronic Disease Prediction

Chronic illnesses often develop silently. By analyzing long-term trends, AI can predict disease progression and alert patients earlier.

AI helps forecast:

Prediabetes to diabetes progression
Heart attack risk
Hypertension development
Chronic kidney disease
Thyroid dysfunction
Metabolic health decline

These predictions allow individuals to take preventive action far in advance.

Personalized Disease Detection with AI

AI enables personalized diagnostics by incorporating each user’s biological and lifestyle data into prediction models.

Personalized AI detection considers:

Age and family history
Diet and activity levels
Sleep patterns
Stress levels
Blood markers
Genetic factors

This creates a highly individualized health risk profile.

SecondMedic’s AI engine creates a personalized risk score for each user, allowing targeted preventive strategies.

AI for Cancer Early Detection

Cancer often goes undiagnosed until it reaches advanced stages. AI helps detect early warning signs by analyzing subtle abnormalities.

AI supports early cancer detection in:

Breast cancer (mammograms)
Cervical cancer (Pap tests and visual scans)
Lung cancer (X-rays and CT scans)
Colon cancer indicators
Skin cancer lesion analysis

This improves survival rates by supporting early diagnosis.

Real-Time Monitoring with AI

Continuous monitoring is essential for early disease detection. AI integrates with wearable devices and digital health tools to track vital parameters in real time.

AI monitors:

Heart rate trends
Oxygen levels
Blood pressure variations
Stress levels
Sleep quality
Blood glucose fluctuations (connected devices)

Real-time alerts notify users of abnormalities that require attention.

AI in Public Health Disease Detection

AI is also used at the population level to identify disease patterns and outbreaks.

AI supports public health by:

Predicting outbreak patterns
Analyzing environmental health impact
Tracking regional disease trends
Supporting government screening programs

This strengthens India’s preventive health strategy.

How SecondMedic Uses AI for Disease Detection

SecondMedic integrates AI tools throughout its digital healthcare ecosystem, helping individuals access early detection and preventive insights.

SecondMedic’s AI capabilities include:

Risk scoring for diseases
AI analysis of medical reports
Predictive analytics dashboards
Early-warning alerts
Integration with wearables
AI-supported doctor consultations

This helps users understand risks clearly and take action early.

Challenges in AI-Based Disease Detection

While AI offers powerful benefits, it must be used responsibly.

Challenges include:

Requirement of high-quality medical data
Need for clinical validation
Maintaining data privacy
Avoiding algorithmic bias
Ensuring user awareness and understanding

SecondMedic follows ethical AI practices aligned with DPDP Act and ABDM standards.

Future of AI-Based Disease Detection in India

AI will continue to redefine diagnostics in India over the next decade.

Future developments include:

Deep AI for full-body scan interpretation
Genomic-based AI predictions
Emotion and mental health detection through AI
AI-assisted virtual triage systems
At-home AI diagnostic kits
National integrated AI health platforms

SecondMedic aims to lead in these innovations by integrating advanced predictive tools.

Conclusion

AI-based disease detection India is shaping a new era of proactive healthcare. By analyzing health patterns, detecting abnormalities early, and providing accurate risk assessment, AI empowers individuals to act before diseases progress. SecondMedic uses AI-driven diagnostic tools to support early detection, preventive care, and long-term health protection.

To explore AI-powered diagnostic support, visit www.secondmedic.com

References

NITI Aayog – AI for Healthcare in India
WHO – AI in Early Disease Detection
ICMR – Chronic Disease Patterns India
IMARC – Indian AI Healthcare Market
FICCI – AI and Precision Medicine India

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