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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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Healthcare Predictive Analytics India: The Future of Data-Driven Preventive Health

Indian healthcare is experiencing a major transformation as data analytics and artificial intelligence become integral to medical decision-making. Healthcare predictive analytics uses advanced algorithms to analyze medical data, lifestyle patterns, and population health trends to identify risks long before symptoms appear. This shift toward prediction rather than reaction is helping India build a stronger, more preventive healthcare ecosystem.

Predictive analytics supports early diagnosis, reduces medical complications, improves treatment outcomes, and lowers healthcare costs. As India faces rising chronic diseases, urban lifestyle pressures, and limited specialist availability, predictive healthcare has become essential for timely and accurate care. SecondMedic integrates predictive analytics into its digital health platform, enabling individuals and clinicians to make proactive health decisions.

Why Predictive Analytics Matters in India’s Healthcare Landscape

India has one of the highest global burdens of chronic diseases. According to ICMR, non-communicable diseases account for over 60 percent of total deaths in the country. Many of these illnesses develop silently, making early detection difficult without advanced tools.

Predictive analytics helps change this by identifying patterns and generating early risk signals. Key factors driving its adoption include:

Growth of digital medical records
Widespread use of wearables and health trackers
Increased testing and diagnostic data availability
Government-supported digital health initiatives
Higher patient expectations for personalized care

With these enablers in place, predictive analytics is moving from research to everyday clinical use.

How Predictive Analytics Works in Healthcare

Predictive analytics draws from a wide range of data sources to generate meaningful insights. These insights help forecast risks, detect abnormalities, and recommend preventive actions.

Data sources used include:

Electronic medical records
Lab test results
Vital signs and biometric data
Wearable device data
Lifestyle and nutrition patterns
Family and genetic factors
Population health statistics

AI algorithms analyze this data to identify trends that may indicate early risk.

Early Disease Detection Through Predictive Models

One of the most valuable applications of predictive analytics is early detection. Many chronic diseases show minor biological changes long before symptoms appear. Predictive models can analyze these subtle indicators and alert patients and doctors early.

Predictive analytics can help detect:

Diabetes risk and prediabetes
Hypertension and cardiovascular risk
Thyroid dysfunction
Chronic kidney disease
Mental health patterns
Sleep disorders
Respiratory illness likelihood

SecondMedic’s predictive tools evaluate these risk markers and create personalized alerts.

Predictive Analytics for Chronic Disease Management

Chronic conditions require ongoing care, monitoring, and timely intervention. Predictive analytics enhances chronic disease management by identifying when a condition may worsen or require immediate attention.

Predictive tools help with:

Monitoring health trends continuously
Detecting early warning signs
Reducing emergency hospitalizations
Recommending medication adjustments
Forecasting disease progression
Tracking lifestyle impact

SecondMedic integrates these insights with remote monitoring devices to support long-term chronic care.

Personalized Preventive Care Using Predictive Models

Preventive care becomes more precise with predictive analytics. Instead of generalized recommendations, individuals receive personalized plans based on their specific risks and lifestyle patterns.

Predictive analytics supports personalized care by:

Creating customized screening schedules
Suggesting targeted lifestyle improvements
Recommending personalized diet and exercise routines
Providing sleep and stress insights
Helping individuals avoid long-term complications

SecondMedic uses these data-backed insights to deliver tailored preventive plans for each user.

AI-Driven Risk Scoring and Health Forecasting

AI risk scoring is a core part of predictive healthcare. These scores reflect a person’s likelihood of developing certain conditions within a specific timeframe. They help users understand their health trajectory and take necessary steps early.

Risk scores are generated using:

Blood tests
Vitals
Daily activity patterns
Family health history
Behavioral trends
Environmental factors

SecondMedic offers AI-based risk scores that help individuals track their health over time and make informed decisions.

Predictive Analytics for Mental Health and Lifestyle Patterns

Predictive analytics is increasingly used to understand mental health indicators such as stress, burnout, depression risk, or sleep disturbances. Wearables and digital behavior analysis provide a large amount of data for predicting emotional wellbeing.

Predictive models can analyze:

Sleep patterns
Heart rate variability
Stress markers
Digital behavior patterns
Lifestyle routines

SecondMedic integrates these insights into its wellness programs to support mental and emotional wellbeing.

Improving Population Health with Predictive Analytics

Predictive analytics is not limited to individual care. It also plays a critical role in public health planning. By identifying disease clusters, risk trends, and healthcare needs, predictive models help governments and hospitals prepare better.

Population-level benefits include:

Identifying outbreaks early
Predicting disease burden
Allocating healthcare resources effectively
Planning community health programs
Improving screening recommendations

SecondMedic works toward making population health analytics accessible to organizations and communities.

Predictive Analytics and the Future of Indian Healthcare

In the coming years, predictive analytics will be integrated into most healthcare systems and digital platforms. India is moving toward a future where early risk detection becomes standard practice.

Future trends include:

AI-driven clinical decision support
Predictive genomics
Precision nutrition and metabolism modeling
Hospital predictive workflow systems
Predictive triaging for emergency care
Integration with Ayushman Bharat Digital Mission
Nationwide predictive health screening programs

SecondMedic aims to remain at the forefront of this transformation by developing advanced predictive tools for both clinical and personal use.

Conclusion

Healthcare predictive analytics in India is reshaping how diseases are detected, managed, and prevented. By leveraging AI, big data, and continuous monitoring, predictive healthcare empowers individuals to act early and avoid complications. SecondMedic integrates these advanced tools into a unified digital health ecosystem, offering personalized risk scoring, early alerts, and precise preventive care.

To explore predictive health tools and preventive care programs, visit www.secondmedic.com

References

NITI Aayog – Artificial Intelligence in Healthcare India
ICMR – Chronic Disease Burden Report 2024
IMARC – Healthcare Analytics Market India 2025
WHO – Predictive Health Analytics Standards
FICCI – AI and Healthcare Innovation India Report

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