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Published on: Oct 28, 2020
2 minute read
By: Dr Rajan ( Medical Second Opinion Cell)

COVID: A Reminder To Stay Safe

COVID: A reminder to stay safe

As we approach the second wave of COVID, we need to remain vigilant with our actions to prevent the spread of the virus. We are continuously reminded about wearing a mask in public, maintaining socially distant, and not engaging in risky behavior such as large gatherings. But today we will focus on other forms of transmission. COVID is primarily transmitted by airborne droplets, but spreading the infection through infected surfaces is still feasible. Here we will look at three articles that investigate this mode of transmission.

SARS-COV-2 Survives for 28 days on surfaces

This study by Australian scientists has found that SARS-CoV-2 can survive on surfaces for up to 28 days. The team investigated using the same amounts of virus found on infected individuals, interacting with surfaces such as cotton, paper, stainless steel, glass, and vinyl. Such materials were chosen as they represent commonly touched objects such as mobile phones, ATMs, supermarket checkout regions, items that may not be cleaned regularly enough. Previous research showed the virus could be detected in aerosols for up to three hours, and on plastic and stainless steel surfaces for up to three days.

This study found the virus may survive as long as a week on most surfaces, with enough potency to re-infect. Even after two weeks, there were still plenty of detectable viruses. On other surfaces such as banknotes, the virus could survive as long as a month. The survival of the virus is also potentiated by colder temperatures. The virus is far less likely to survive at 30C than at 6 C, a worrying finding for countries currently approaching winter.

Survival of SARS-CoV 2 on the human skin

We know our skin is host to millions of different bacteria and viruses, but the conditions created by the body alongside the degree of microbial competition actually makes it quite a hostile environment for pathogenic microbes. Hirose et al looked to investigate how well the SARS-CoV-2 virus survives on human skin, using a model. They found that SARS-CoV-2 and the influenza A virus were destroyed more quickly on the skin than other surfaces such as steel, glass, and plastic. However, COVID lasted over 4x longer on skin compared to Influenza A (9 hours vs 1.8 hours).

More importantly, ethanol compounds were found to inactivate SARS-CoV-2 within 15 seconds on human skin. This highlights the importance of regular hand washing, even if with alcohol gel. Taking this in mind, it is useful to keep small bottles of alcohol gel on a person when traveling in public and using it regularly. After all, if you are touching door handles and other items that hundreds of other people may have touched before you, potentially with poor hygiene, it is safer to regularly disinfect.

Low risk of COVID transmission by fomites in real life conditions

Having taken these studies into account, it is quite difficult to quantifiably measure transmission from surface to a person. Knowledge of this transmissibility is quite important, especially to those working in a hospital environment. A review by Mondelli et al published in the prestigious journal The Lancet (Infectious Disease) describes two sequential studies to looking at the possibility of contamination of surfaces in an infectious disease ward of a major Italian hospital, and also whether risk of transmission was higher in emergency rooms and sub-intensive care wards.

These studies found there were very few surfaces in the hospital through which positive swabs could be taken, suggesting contamination was low. Of course the hospitals were running standard cleaning procedures, with regular wipedowns of commonly toughed objects. This again highlights the importance of maintaining hygiene, and how adequate cleanliness can significantly reduce the risk of infection.

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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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