OP-ED

AI can combat vaccine misinformation

vaccine misinformation

Artificial intelligence can allow for real-time analysis of public attitudes and sentiments from social media and Web platforms, giving an opportunity to track changing public sentiments and develop proactive two-way communication strategies

The COVID-19 pandemic brought the world to a standstill, leaving governments, healthcare workers, and citizens struggling to contain the virus’s spread. During the peak of the pandemic, people were exposed to a great deal of information, which, unfortunately, gave rise to another problem: vaccine misinformation. This can take many forms, from outright lies, through unfounded rumors, to information taken out of context. Regardless of the form it takes, vaccine misinformation is a threat to public health.

Vaccine misinformation can lead to a reduction in vaccine uptake, which can have dire consequences for public health. Vaccines are critical tools in preventing the spread of diseases, and when large numbers of people fail to get vaccinated, it can create pockets of vulnerability that allow for outbreaks of preventable diseases, prolonged pandemics, and, in the worst-case scenario, loss of lives. For example, in recent years, the anti-vaccine movement has led to a resurgence of diseases like measles, which had been largely eradicated in developed countries.

Vaccine misinformation can also lead to an increase in vaccine hesitancy, making it harder for public health officials to control the spread of diseases – with serious consequences for public health. Vaccine hesitancy is a reluctance or refusal to get vaccinated despite the availability of vaccines. This is caused by a variety of factors, including misinformation and fear. For example, during the H1N1 flu pandemic in 2009, vaccine hesitancy led to a slow uptake of the vaccine, allowing for a more rapid spread of the virus, and leading to more deaths. This also played out in certain countries during the COVID-19 Pandemic.

vaccine misinformation

One of the many reasons vaccine misinformation spreads so quickly is that health data can be complex and difficult to understand. This complexity can make it challenging for the average person to decipher scientific studies and health reports. Misinformation, which thrives in the absence of easily accessible, credible information, is often presented in a simple, attractive, and straightforward manner, making it more accessible to the public. Therefore, it is essential to simplify health data so that it is more accessible to everyone, achievable using clear language, accurate graphics, and other visual aids that can help people understand complex health data more easily.

Furthermore, the spread of vaccine misinformation is made easier by the rise of social media platforms and other communication technologies. Misinformation can spread quickly through social media platforms, making it difficult for public health officials to counteract false information. In an  Africa Centres for Disease Control and Prevention study, people with high levels of hesitancy were more likely to use social media, half of those surveyed in South Africa believed the virus was linked to 5G technology. A small study in Addis Ababa showed that hesitancy was 3.6 times higher among those who received information from social media than those who relied on television and radio. Misinformation can also be perpetuated by media outlets that sensationalize stories about vaccine injuries or side effects. This can create a climate of fear and mistrust around vaccines, making people hesitate to get vaccinated.

Social media platforms and other communication technologies have indeed become a breeding ground for vaccine misinformation. Tech companies and communication platforms are responsible for preventing the spread of misinformation, which they can do by using such gatekeeping strategies as labeling misleading content, restricting the reach of false information, and de-platforming repeat offenders. Social media platforms can also work with public health organizations to promote accurate information about vaccines and health, as done with the World Health Organisation. However, the responsibility of combating vaccine misinformation is not only that of the health authorities or tech companies. Healthcare information consumers also have a vital role to play. They should verify the information they receive before sharing it with others. 

vaccine misinformation

More so, technology can play a critical role in combating vaccine misinformation. For example, artificial intelligence (AI) can be used to monitor social media platforms for vaccine misinformation.  Artificial intelligence can allow for real-time analysis of public attitudes and sentiments from social media and Web platforms, giving an opportunity to track changing public sentiments and develop proactive two-way communication strategies. In addition, large-scale social media analysis using natural language processing (NLP) and machine learning (ML) can be used to identify trends in public opinion. These techniques used to mine social media data hold significant potential to inform public policy research, and the impact of policies and messaging can be monitored to assess ever-changing public perceptions. 

Vaccine misinformation is a threat to public health and complicates efforts to protect public health. It can lead to reduced vaccine uptake, increased vaccine hesitancy, and the spread of preventable diseases. The responsibility of combating vaccine misinformation is not only that of the health authorities or tech companies but also of healthcare information consumers.

Also Read: Why is it tough to address health misinformation?

Author

  • Ezinne Onwuekwe

    Ezinne coordinates and provides technical expertise to the COVID-19 vaccine data intelligence and visualisation efforts at Africa Centres for Disease Control and Prevention (Africa CDC). She is a Public health expert with industry specialization in data analytics; providing data-driven solutions and valuable insights to a technical and non-technical audience. She has demonstrated experience with visualization Tools (Tableau, Power BI, Google data studio), Excel, Data Mining, Business Intelligence, Predictive Modelling using Python libraries (Pandas, Scikit-Learn, Matplotlib) Data Manipulation (SQL), Statistical Analysis, to extract insight to support decision-making in the healthcare, vaccine-preventable disease outbreaks and supply chain space.

About the author

Ezinne Onwuekwe

Ezinne coordinates and provides technical expertise to the COVID-19 vaccine data intelligence and visualisation efforts at Africa Centres for Disease Control and Prevention (Africa CDC). She is a Public health expert with industry specialization in data analytics; providing data-driven solutions and valuable insights to a technical and non-technical audience. She has demonstrated experience with visualization Tools (Tableau, Power BI, Google data studio), Excel, Data Mining, Business Intelligence, Predictive Modelling using Python libraries (Pandas, Scikit-Learn, Matplotlib) Data Manipulation (SQL), Statistical Analysis, to extract insight to support decision-making in the healthcare, vaccine-preventable disease outbreaks and supply chain space.

Add Comment

Click here to post a comment