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Published on: Apr 04, 2020
3 minute read
By: Dr Rajan Choudhary

Anyone With Flu Like Symptoms Are Now Encouraged

The Bold Strategy the UK has adopted against COVID-19

The UK government had outlined its Coronavirus strategy in three distinct steps. The first stage was to contain the virus. This was implemented when spread of the virus was primarily by infected patients from abroad. Public health advice was provided, campaigns on washing hands, not touching the face, practicing safe hygiene. Potentially infected individuals were informed to self-quarantine for 14 days whilst waiting for symptoms to develop and testing to occur. Now it is evident this is not enough. The virus has spread to enough people that transmission can now occur locally, between people who have never been abroad. Containment is not the aim, mitigation of number of cases to prevent burdening the health services. The second stage aims to reduce the epidemic’s peak, flatten it out so the number of cases do not occur at once.

Anyone with flu like symptoms are now encouraged to stay home for 7 days, and testing will only occur for hospital admissions. Beyond this little appears to have changed. Schools will remain open, social gatherings have not been cut yet (but is expected over the next week) and general life will continue as normal. This is a risky measure, one that suggests the government is not taking the issue seriously. France, Spain and Italy have enacted lockdown measures, Germany has begun cutting social gatherings. So why is the UK not following in step? Are people going to die as a result of this inaction?

DELAY THE SPREAD

The answer is of course complex. PM Boris Johnson has acknowledged that as a result of his decision people may die, especially the elderly who are seen as a very vulnerable population. But this plan has been discussed with multiple scientists, doctors, public health specialists, and there is method in the madness. Currently the UK is in the early stages of the epidemic. The number of infected are expected to rise sharply in 4 weeks, with a peak in 10–14 weeks. Implementing harsh restrictions too early can lead to “self isolation fatigue”, resulting in people not following the restrictions stringently or leaving their homes at the height of the epidemic. Restrictions also come with their own problems, and implementing them may lead to more harm than good. Simple measures such as hand washing and self isolation can itself reduce the peak of cases by 20%.

Schools have not yet been closed because COVID-19 does not appear to affect children as much. Closure of schools would also mean parents having to stay at home to look after their children (after all, nurseries, creches and other forms of childcare would still result in a spread of infection). In some cases these parents are also healthcare professionals, and the UK needs every single doctor, nurse and allied health professional to be on the frontline treating patients.

So what is the strategy? The NHS is currently full of patients due to the winter burden, one that is expected to taper off in the coming months. Slowing the onset of the epidemic’s peak to Summer, spreading it across the next few months so the maximum number of people can be treated in the hospital setting without overburdening. The aim is no longer to prevent the spread of infection but to protect the most vulnerable age groups. This model allows the young and healthy to become infected, almost encourages it.

INFECT YOUR CITIZENS

Now this sentence may sound ridiculous when said out loud. Allow infection. But why? The UK has acknowledged there is no way to stop the infection. Whilst the mortality in the elderly population and those with medical conditions are high, in the young and healthy it manifests as a mild illness with almost all infected cases recovering. More importantly, recovered patients have immunity against the virus, manifesting as antibodies in their blood. Immune patients cannot infect other people, so the more immune patients there are the slower the virus will spread. This is known as herd immunity, and the process is discussed in length in our blog on vaccines. Herd immunity needs to be achieved before the onset of winter in 2020, as winter admissions alongside COVID admissions would result in a disaster.

https://medium.com/@rajneesh.dwivedi/developing-a-vaccine-for-covid-19-part-1-f7263ae9bf88 Rajneesh secondmedic

The strategy is of course risky, and one that has not been implemented before. And since the infection will not be contained people will die. But by spreading the burden of the infection across a longer time period will allow those who require treatment to receive it in a far less burdened health system. And it has received support from health professionals, even those who are fierce critics of the PM and Conservative government. But it has resulted in confusion amongst the population, a population that looks at authoritative action taking place in other countries and not understanding why their own doesn’t follow suit. The issue is these draconian measures are not sustainable, and if implemented correctly the UK strategy may result in far less lasting damage on its health service and the economy.

Dr Rajan Choudhary, London UK

Head Of Products, Second Medic Inc (www.secondmedic.com)

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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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