AI Health Care

How Hospitals Use Algorithms to Prioritize COVID-19 Vaccine Distribution

Algorithms prioritize vaccine

Introduction: How Hospitals Use Algorithms to Prioritize COVID-19 Vaccine Distribution

About 51.7% of the global population has at least a single COVID-19 vaccine dose. While just 4.5% of individuals in low-income countries have managed to obtain a dose. Roughly 31.33 million doses are administered on a daily basis as this data shows. Hospitals use algorithms to prioritize vaccine delivery, and use that as a powerful tool in their arsenal. 

To tackle the major logistical issue of distributing vaccines, some states and governments have turned to private companies. All in an effort to create algorithms that would help prioritize shipments. 

Here, we will take a closer look at how some of these algorithms guide vaccine distribution in hospitals and whether they have what it takes to optimize the problems of vaccine distribution. 

What Kinds of Algorithms Are Being Used?

Amid the chaotic rollout of vaccination plans, US healthcare and hospital systems have drafted up plans. These plans would aid with vaccine prioritization according to the CDC’s guidelines. Some use AI (Artificial Intelligence) that would determine who would obtain the first doses. 

Here is how algorithms guide vaccine distribution in different hospitals. Renton city in King County, Washington, relied on an algorithm to settle on the proper distribution strategies. It allowed their caregivers to self-attest to their role and risk. 

Some used questions and a straightforward scoring system to prioritize caregivers into a group of people with a shared characteristic. Other hospitals prefer to stretch their dose allocation. To avoid having a huge portion of clinicians unavailable from adverse reactions at the same time. 

In the UK, experts are using the QCovid calculator.

In 2020, the team behind the tool collected data from over 6 million patients to come up with an algorithm that would predict the outcome of the virus. The research helped find an additional 1.5 million patients suitable for the shielding list at the start of 2021. 

Currently, the data obtained from 6.9 million individuals who got 2 shots provides a prediction of who might be more susceptible to the virus even with vaccination. Algorithms that guide vaccine distribution, such as this one, would help identify those who might need extra treatment or booster shots. 

Some regions in Italy are using a different method. The Italian Federation of General Practitioners is focused on algorithms for efficient prioritization. They adopted ADM systems (automated decision-making) to figure out who would be a priority to get vaccinated. 

The ADM system is meant to maximize vaccine distribution efficiency while prioritizing older and high-risk patients. Particularly those that suffer from more than a single ailment. Experts caution that this approach is not always transparent. Although details are given, methodological complications remain. This paves the way for potential discriminatory results.

Emotion Vs. Data Affect Vaccination Decisions

Right now, vaccination is a very emotional and highly-discussed topic. That’s why it can be a good idea to describe the importance of emotions in healthy communication. The goal of COVID-19 vaccination is to obtain herd immunity and protect the masses. 

So, the act of vaccination could be seen as a social contract. But, carrying it out has come with many challenges. Some algorithms have come under scrutiny, like in the Stanford case in Palo Alto, California. In the winter of 2020, Stanford found itself in a heap of trouble. 

They deployed a faulty SARS‑CoV‑2 vaccine distribution algorithm. But, the fiasco extended well beyond their own doors. As the country prepared to confront the complicated question of who should get a vaccine, when, and why. 

Also Read: Artificial Intelligence and Otolaryngology.

By creating personal software, Stanford prioritized administrators and doctors who work remotely. Rather than residents that made direct contact with infected patients. The tool decided the order in which thousands of medical workers would get a shot. 

People wondered what kind of problems were these algorithms meant to solve? At the start of the debacle, administrators at Stanford blamed the algorithm. What Stanford aimed to do was factor more things, like exposure prevalence, department, and age. 

Experts explained what seemed to go wrong, and it is believed to arise at the intersection of AI and human intuition. But, it turned out to be a human problem from start to finish. Now, the question of one’s vaccination status is more and more relevant – even a condition of employment.

Many workers face mandatory vaccinations to keep their jobs. Many sectors are already urging their employees to get vaccinated. Predominantly those that hold public-facing roles. That includes education, healthcare, travel, finance, hospitality, and technology sectors. 

In high-income countries, the problems of having accessible vaccinations are much easier to tackle. That’s why employers are encouraging their staff to get immunized. But, for the remaining sections of non-immunized society, like adolescents, it can be difficult for them to land a job or get employed. 

Countries are pressuring private employers to boost vaccination rates. They also mandate the shots for healthcare workers, federal employees, and contractors. Since the FDA approved the Pfizer vaccine on August 23, more employers required their workers to get completely immunized. 

For instance, the percentage of job postings asking for vaccination in August in the administrative assistance sector went up by 219%. In the legal sector, it jumped 210%, in education, it was up 146%. And communication and media industry increased 180%.

The United States is not the only country tightening its take on vaccinations. The United Kingdom has also taken matters into its own hands, stating that all home care workers must get fully immunized from November. Other countries, like Greece and France, have taken similar measures for workers in the public sector. 

A German survey published in May 2021 studied the willingness to get vaccinated. Based on their results, roughly 70% of adults would get vaccinated if a shot for COVID-19 without side effects was available. 

About half are against it, and half of the residents in Germany are in favor of mandatory vaccination. This study showed that herd immunity could be achieved without a mandatory policy. But, such policy would also be acceptable where it is deemed necessary.

Nuances in Vaccine Distribution for Low-Income Countries

People tend to underestimate the disease. It may not be a hazard for everyone, but COVID has had a significant impact on a major portion of the population. Some of the consequences are complications such as organ failure, pneumonia, septic shock, and death. 

Vaccine inequity doesn’t just hold back poverty-stricken regions – it’s holding the entire world back, stated Henrietta Fore, the executive director of UNICEF. The goal is to get herd immunity so that more people would have a better chance at coping with the pandemic. 

Countries in Africa are still without proper access to vaccines. Fewer than 5% of the African population has been completely immunized. Meaning that other countries are still at risk of a further outbreak. The already fragile healthcare systems make it harder to manage the pandemic. 

African states rely on a combination of donation, bilateral deals, and a vaccine-sharing scheme. The situation improved in August and July. With further promises being made when the United States stated it would donate an extra 500 million, Pfizer dozes. On top of what was already pledged. 

But, there are still some vaccine shortages in the African region. At the current rate, the continent could reach the 40% target before the end of March 2022. Also, there are some worries about vaccine hesitancy in certain regions. So, it’s difficult to conclude the type of impact they will have on the population as a whole. 

Also Read: AI global arms race.

Human Expertise – Trust in Science and Vaccine Confidence

People tend to appraise the risk of a disease based on their own feelings and emotions. When it comes to vaccination, some are afraid because of the side effects it can carry, rather than the disease itself. Although the objectively judged risk of the effects of the ailment is more serious, the appraisal of the vaccine’s side effects is weighted more heavily. 

Countries with a high consensus level regarding the trustworthiness of scientists have better trust in science. Compared to the countries where social consensus is significantly weaker. Many minorities across different countries might refuse to get a vaccine. 

A cross-national survey indicated that 19% of the American public stated they would definitely or probably not get vaccinated. With the corresponding figures of 24% in France, 23% in Germany, and 14% in the United Kingdom. 

These figures can represent a broad spectrum of resistance. And public skepticism of the mass inoculation programs. If the global endeavor of immunization against COVID-19 is to succeed, it’s crucial that we understand the economic, societal, and psychological factors that encourage people to avoid the vaccine. 

Findings suggest that in regions where trust in science is relatively high, people are more confident about getting a vaccine. A key avenue for potential research would be to identify the factors that would help build trust. And develop effective communication strategies about current vaccination programs. 

Also Read: The role of AI in vaccine distribution.

Conclusion: How Hospitals Use Algorithms to Prioritize COVID-19 Vaccine Distribution

There is much that we still don’t understand about COVID-19. But, one thing is for sure – the world can’t return to normality, unless a comprehensive and efficient global vaccination program is successfully carried out. Right now, intense international efforts are underway, urging more people to get vaccinated. 

Despite these efforts, global population immunization has plenty of hurdles to overcome. Particularly in low-income countries, where there are vaccine shortages. Plus, vaccination hesitancy is rampant, making it difficult to attain herd immunity. I think algorithms can be used to prioritize the vaccine distribution.

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