Remember PREDICT, the research programme funded by the US Agency for International Development and carried out in partnership with EcoHealth Alliance and Metabiota, with the goal of identifying potential emerging pandemic pathogens?

Well, the Centers for Disease Control now propose to take a similar approach to our thoughts. They’ve solicited grant applications from researchers pledging to “develop a public health tool to predict the virality of vaccine misinformation narratives.”

The purpose of this Notice of Funding Opportunity is to support research to develop a predictive forecasting model that identifies new or reemerging misinformation narratives that are likely to disseminate widely and have a high potential for impact on vaccine confidence. The information from this model will then be used to develop a tool that public health agencies could use to predict misinformation trends in the populations served. Finally, the researchers will evaluate the tool's predictive capabilities on both future social media misinformation narratives and real-world events.

The successful applicant will receive a million dollars over two years.

The documentation explains that “vaccine misinformation” leads to “negative public health consequences,” including “delayed vaccination and acquired vaccine-preventable diseases.” Until now, CDC thought police have had to deploy a “reactive approach” to this misinformation. Alas, “new misinformation that may impact vaccine confidence develops regularly,” which makes it “difficult for public health agencies to know the type of misinformation that will spread and be impactful.”

They hope, therefore, that somebody somewhere will do a science and help them predict emerging thought pathogens before they spread:

Regression analyses and machine learning approaches to identifying the future virality of misinformation in the peer-reviewed literature have so far been very limited in their capacity to identify actionable predictors that can be used by public health agencies to identify misinformation that may impact vaccine confidence before it becomes pervasive. More research needs to be conducted to identify ways to predict future misinformation, and to develop identification tools for public health agencies and community partners, so they can proactively mitigate the spread and potential harm caused by misinformation in their communities.

In much the same way, publishers would like to know which books will become bestsellers before they’re published, film studios would like to know which films will become blockbusters before they’re produced, and investors would like to know which stocks will increase in value before they’re traded. If “regression analyses and machine learning approaches” ever become capable of predicting viral trends, vaccinating schoolmarms will be the last to benefit from it.

Still: It’s interesting to consider that the CDC was founded in 1946 as an outgrowth of a malaria eradication programme, and that it took less than three generations for it to metastasise from those small beginnings into the hypervaccinating mass-containing thought-policing pharmaceutical scam-promoting multidimensionally tentacled tumorous vampire squid that it is today. With every crisis, every crusade and every bad flu season, it’s gotten just a little bigger, a little more comprehensive, down to the present moment, in which it’s soliciting an algorithm that will identify opinions it doesn’t like, in advance of anyone even having heard of them.