How to tackle dis/misinformation to contain vaccine hesitancy?
By Kamesh Shekar
India has seen two waves of COVID-19 surges (with the second wave being highly tragic) in the past one and half years amid an under performing healthcare system with a shortage of oxygen, hospital beds, etc. While India is predicted to be moving towards yet another COVID-19 surge (third wave), experts believe expediating the vaccination process could help us from ill effects. However, it has been observed that only 4% of the Indians been vaccinated, with a significant proposition population hesitant to take the vaccine. According to the Facebook COVID-19 Symptoms Survey (CSS), about 29% of Indians surveyed are hesitant to take the vaccine (around 12% said "Definitely not", and 16% said "Probably not").
Within a vaccine standpoint spectrum, there are three sorts of people (i) who are pro-vaccine, (ii) swing people (who are not entirely sure of getting vaccinated), (iii) towards the other end entirely anti-vaccine people. While it is difficult to intervene at the anti-vaccine level, we should be targeting swing people for a start such that they move towards the pro-vaccine side, eventually followed by the anti-vaccine people. While there can be various reasons for different standpoints on vaccination such as fear, beliefs, value systems and history dispositions, but in most cases, the information consumed by people firms up their intent. But unfortunately, the information landscape is filled with dis/misinformation on the vaccine. Therefore, to have swing people (later anti-vaccine people) move towards the pro-vaccine, it is crucial to tackle dis/misinformation, which spreads faster. Besides, Facebook CSS (as it is for people who have internet access) and a study published by Cambridge shows that people who have internet access are more sceptical towards the vaccine, as dis/misinformation spreads significantly through social media platforms. In India, 410 million users access Facebook, 15 million users access Twitter, and about a half billion people use WhatsApp. But, as the trickle-down effect kicks in, dis/misinformation disseminate faster into the real world.
While disinformation is intentional, the misinformation happens predominately due to two reasons a) users' incapability in differentiating between a factual and wrong set of information b) users pre-existing biases. Although various ex-post measures are taken to demystify the myths by having community members and doctors speak to the people, it is essential to have some ex-ante measure (at least henceforth) and behavioral change models to control the ill effects of dis/misinformation which concertises/causes hesitancy.
Ex-ante and Ex-post measures to tackle dis/misinformation
Are we doing enough in terms of tackling dis/misinformation on vaccination that causes the hesitancy? This is the question to be answered; experts have flagged that the government is not doing enough to tackle hesitancy as it has various other problems to tackle, such as lack of vaccine availability and fiscal stress of providing free vaccines. Therefore, if Indian truly needs to move towards inclusive immunisation of its citizen, it has to make robust vaccine hesitancy policies, where tackling dis/misinformation, especially on social media, should be a significant part. Below are some of the ex-ante and ex-post measures to be taken by various stakeholders to tackle vaccine-related dis/misinformation.
Ex-ante measures: The government have been indulging in communication strategies, especially through social media, to advocate vaccine and curb dis/misinformation. While that is a step in the right direction, it is also important to package the factual content effectively and not in a misleading way. For instance, the concept of herd immunity can be misleading, where people might think that they would like to be the part of indirect protection as the rest takes the vaccine. Besides, a lot of information on vaccination is generic, which leaves a void filled with various interpretations and manipulation; therefore, it is important to have case-by-case context-relevant information as part of the communication strategy. For instance, there is no concrete information on vaccination for co-morbid patients and patients on medication. At the same time, it is prescribed to consult the doctor before taking the vaccination; this might not be the right way to communicate.
Besides, the social media platforms must institute a prevalence-based gradation matrix for Covid vaccine-related information to formulate proportional measures according to the prevalence of the information. In addition, the ex-ante standards should also include provisions on the appropriate use of algorithms by social media platforms to recommend vaccine-related information to each user. This is important because our biases are reinforced by these algorithm-driven recommendations and keep us away from content that does not fit our ideology. This information ‘filter bubble' could block counterarguments from reaching us, including fact-checks.
Ex-post measures: As the dis/information on the vaccine has already been spread out like forest fire, it is essential to ramp up the ex-post measures in addition to other measures such as fact-checking, flagging the information, spreading awareness etc.
While we have a lot of information revolving around adverse events (which is 0.18%) and dis/misinformation on seemingly serious/discriminative effects of the vaccine, we don't have much information circulated on less to no side-effects stories. While it might be too vanilla to cover or spread, it could still positively impact people as they see for themselves. This will act as the counter speech and social proof helping to balance the existing dis/misinformation.
Although government and organisations are trying to burst the bubble of dis/misinformation by asking doctors, community service members and healthcare providers to speak to the community, this might not be a high impact measure due to existing historical disposition. The marginalised community feel a dichotomy in terms of "us" (marginalised community) vs "others" (State, healthcare providers etc.). Therefore, it is important to have demographic level data to show the percentage of people from their socio-economic group who had vaccinated across the country (only if it is a fair number). At least to tackle gender-based dis/misinformation (such as it affects women's menstrual cycle), it is crucial to have sex-disaggregated data as part of the communication for target groups. In addition, it is important to have testimonials of these people to bolster the effort. These efforts will try to weed out the effects of dis/misinformation consumed by the targeted community and might push them towards a pro-vaccine standpoint. Besides, this information can be part of the social media flagging of dis/misinformation.
Tackling the issue through addressing user behaviour
It has been noted that misinformation such as vaccine effects the menstrual cycle was circulated through WhatsApp. While there is a forward message limit on WhatsApp, less can be done in terms of information as the messages are end-end encrypted (breaking end-end can’t be a solution as it is vital to secure user privacy and various other harms). Therefore, as the mis/disinformation on the vaccine could fall through the cracks, as users, we should introspect whether the information we are about to share complies with our intent. If it does, we have to take one step backwards and cross-check the integrity of the information by referencing multiple credible sources.
According to microeconomics, as the benefit exceeds the cost, it leads to transaction. Modifying the statement, here, if the benefits exceed the intent, this might lead people to vaccinate. It is fundamentally crucial to tackle the intent level, which can be due to pre-existing fears, value systems, historic disposition, etc., yet firmed by the dis/misinformation. It is difficult to intervene at the intent level, therefore borrowing the idea from behavioral change models, government and organisations must identify and bucket the target population for which it would want to increase vaccine uptake and try to change the "Proximate" behavior (behavior that might influence the "ultimate" behavior) to achieve the same. One of the Proximate behaviors could be the response to benefits/incentives. Therefore, it is important to have positive reinforcement for people to get vaccinated, such as popularising #vaccinated on social media to post their vaccination (this has proven to work for elections, where more people turned out to vote), certificates, target population-specific incentives.
Ergo, vaccine hesitancy could be caused by various reasons and causes. But various literature points out that the dis/misinformation does play a significant role in firming up the intent and, in some places, acting as a root cause. Therefore, future research should devote more efforts towards understanding the extent to which dis/misinformation cause/firms up vaccine hesitancy so that more targeted interventions can be instituted to tackle the same. In addition, it is also important to analyse to what extent social media platforms play a role within this dis/misinformation discourse.
The author is currently pursuing PGP in Public Policy from the Takshashila Institution. Views are personal and do not represent Takshashila’s policy recommendations