THE PROBLEM?Outbreaks of infectious diseases from pandemics like COVID-19 to persistent endemics, pose a significant threat to the UK as well as global health and economies. COVID-19, for instance, caused over 100 million infections, millions of deaths, and a crippling 3.5% drop in global GDP in 2020 [1]. In the UK alone, COVID-19 resulted in nearly 60,000 healthcare worker absences, costing the government between £310 billion and £410 billion [2]. This financial burden underscores the urgent need for improved predictive tools in healthcare to prevent future crises. In the short term, pandemics inflated NHS service costs by £4-5 billion annually [3], hindering UK healthcare delivery and economic stability.
The long-term effects are even more concerning, where potential global costs exceeded £12.9 trillion and significant impacts on national GDP and human wellbeing [4]. Source – [Office for Budget Responsibility, 2021].
Tragedy: A report by the Office for National Statistics (ONS) reveals 88 tragic deaths of children under 18 attributed to COVID-19 from March 2020 to October 2022. These children did not have a fair chance at life. Strained healthcare system: The National Health Service (NHS) faces pressure from an aging population, increasing costs, and a backlog of cases. AI can potentially improve efficiency, reduce costs, and support earlier diagnoses. [1]
Focus on innovation: The UK government and Healthcare institutions are actively exploring AI applications in Healthcare. This creates a market for AI-powered tools and services. Serious illnesses, viruses, bacteria, and outbreaks like pandemics and epidemics can strike anyone, regardless of age, race, or physical health. New and old infectious threats are constantly emerging, putting a strain on regions with limited healthcare resources. Vaccine-preventable diseases like meningococcal disease, yellow fever, and cholera can be particularly devastating in these areas where timely detection and response are difficult. SynthoSense wants to make an important contribution to the health and wellbeing of the nation, driving more efficient and effective health for all across the UK.
The COVID-19 pandemic has been an unprecedented challenge. The worst public health emergency for a century has had a profound impact on the NHS. Staff have treated more than half a million COVID-19 patients over the last 18 months in hospital alone. The pandemic has illuminated chronic problems in our health and social care system, and made many of them worse. For instance, when COVID-19 broke out, there were thousands of hospital beds filled with people that could have been better cared for elsewhere. The number of NHS patients waiting for tests, surgery and routine treatment in England is at a record high of 5.5 million and could potentially reach 13 million over the next few years. Health services in other parts of the UK have faced similar challenges. [Building Back Better: Our Plan for Health and Social Care. Presented to Parliament by the Prime Minister by Command of Her Majesty, 2021]
SOLVING THE PROBLEM?
To solve this problem, Artificial Intelligence offers various techniques in applying AI to healthcare, which can considerably change the effect of any pandemic in the UK and/or globally. AI can change our future in healthcare.
By partnering and working alongside The Alan Turing Institute, Imperial College and other AI companies in HealthCare we can build a first of its kind HealthCare Neural Network which would put the United Kingdom at the forefront of HealthCare Technology.
Four Stages of applying AI in HealthCare:
a. Early Detection and Surveillance of data: AI can analyse an immense set of data from medical records in a very short time, social media and news reports and identify patterns and predict disease outbreaks much faster than traditional methods.By analysing these diverse sources, AI can identify patterns and trends that might be missed by traditional methods.
Here's how:
a.1. Real-time analysis: AI can continuously monitor these data streams, allowing for much faster detection of potential outbreaks compared to waiting for official reports. a.2. Pattern recognition: AI algorithms can identify subtle patterns in the data, such as increases in specific keywords on social media or correlations between geography and diagnoses in medical records. a.3. Predictive modelling: AI can be used to build models that predict the potential spread of an outbreak based on historical data and current trends. These capabilities allow AI to provide early warnings of potential outbreaks, giving public health officials a head start in containing them.
b. Diagnosis and Treatment: AI can analyse medical images like X-rays and CT scans to improve accuracy and speed up diagnoses. AI can analyse patient data to recommend personalized treatment and predict potential drug interactions.
c. Resource Allocation and Response: AI in healthcare can model the spread of an epidemic and make predictions of areas most likely to be affected. This can help to allocate resources such as Healthcare Personnel and medical supplies such as vaccines.
d. Drug Discovery and Development: AI can analyse vast datasets of genetic information and chemical compounds to accelerate the development of new drugs and vaccines.