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Published on: Apr 20, 2020
3 minute read
By: Dr Rajan Choudhary

Is Herd Immunity A Valid Strategy For COVID 19?

Yesterday we explained you what Herd Immunity means and how it works, today we will take the discussion further to determine whether it is effective and can be recommended in the current context.

COVID-19 currently does not have a cure or a vaccine. Lockdown is the only strategy that appears to be working. Could implementing policies that encourages herd immunity be used to accelerate immunity in the population without the need for a vaccine?

INFECTIVITY

For the strategy to work we need to know a few things about the virus. How infective is it? In one of our earliest blogs we discussed infectivity at length and determined that the R0 (infectivity) may be between 2 and 3. This means each person with the virus can infect around 2-3 people at a time. Whilst this is not as high as Mumps (10-12) it is much higher than the common flu. The higher the R0 the more people that need to be immunised before herd immunity is achieved. For COVID it is estimated that 70% of the population need to be infected.

This is based off our current testing. Due to shortages in testing kits, only testing those that have a high likelihood of being infected and poorly organised testing infrastructure in some countries, we are likely underestimating. The number of people infected may be much higher as we are missing those that are asymptomatic but still have the disease and are still passing the disease on.

MORTALITY

Secondly, we need to know the mortality from COVID-19. Early estimates of mortality were as high as 10%, as we had little data on how many people were truly infected, but as the number of infected cases rose, and testing amongst the infected and symptomatic population rose, a more accurate mortality has been found to be around 1%. There is a risk we may still be underestimating the true mortality, as some cities have noted a spike in cardiac deaths, and some evidence supports possible cardiac damage due to COVID. But from the data we have, we know its mortality is lower than MERS (34%) and SARS (10%) but more than influenza (0.1%).

estimates of the COVID-19 case fatality rate

Whilst we have some data on who is likely to suffer from severe COVID symptoms (elderly, immunocompromised, people with heart or lung problems) we still cannot accurately determine who will get severe COVID in the “low risk” population. Simply because someone is young and healthy does not mean they will not die from COVID.

LENGTH OF IMMUNITY

Third we need to know how long this immunity will last. Similar coronaviruses responsible for the common cold usually create immunity that lasts for a few months, which is why we often get the cold repeatedly. A virus is also very prone to mutations that can change the structure and functions of its proteins, proteins responsible for tagging, latching on to and entering cells. If the structure of these proteins changes enough, then our antibodies will not be able to bind on, and new types of antibodies will have to be made with a slightly different structure. This effectively means our bodies have to start from step 1 again to create immunity, and we have to make new vaccines. This mutation rate is why we have to make new vaccines every season for the flu.

LONG TERM COMPLICATIONS

Finally, we need to know if there are any long-term implications from a viral infection. Again, this is something we do not know yet, as the virus has only been around for a few months. There may be implications for the cardiovascular system, long term breathing problems or more. And even if the complication rate appears relatively low (say, 1%), if millions of people are allowed to get infected, by definitions thousands or tens of thousands of people will have these complications, complications that can lead to issues later in life or an early death.

CONCLUSION

So, is herd immunity a viable strategy for COVID? Without a safe vaccine the general consensus appears to be no.

We don’t know how infective the virus really is or how many people it has infected

A 1% death rate is still very high. This means for every 100 people to be infected; one will die. This would mean hundreds of thousands of people dead in a country with a population over 10 million. It is unacceptably high.

If the death rate is 1%, then hospitalisation rate is likely higher. Almost all countries do not have capacity to have 1% of the population in hospital. Overwhelming the healthcare system will lead to poorer care, and worse care for those who do not have COVID. Leading to more people coming to serious harm or dying as a result of poor healthcare, not because of COVID.

We don’t know the long-term effects of COVID. By purposefully infecting people instead of waiting for a vaccine we may be causing unnecessary damage to a person’s health that only becomes apparent later in life. But this is speculation as we do not currently know if COVID has long term effects,

We don’t know if all of the risks above will amount to anything. The immunity may not last long enough, leading to another spike in infections and mortality.

Mass vaccination appears to be the safest strategy. And though human clinical trials have started on a number of vaccines, we are still months away from deployment. Until then we should not come out of lockdown prematurely, not until we have received an unbiased assessment from public health officials that states it is safe.

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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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