The online competition between pro- and anti-vaccination views.

Distrust in scientific expertise1-14 is dangerous. Opposition to vaccination with a future vaccine against SARS-CoV-2, the causal agent of COVID-19, for example, could amplify outbreaks2-4, as happened for measles in 20195,6. Homemade remedies7,8 and falsehoods are being shared widely on the Internet, as well as dismissals of expert advice9-11. There is a lack of understanding about how this distrust evolves at the system level13,14. Here we provide a map of the contention surrounding vaccines that has emerged from the global pool of around three billion Facebook users. Its core reveals a multi-sided landscape of unprecedented intricacy that involves nearly 100 million individuals partitioned into highly dynamic, interconnected clusters across cities, countries, continents and languages. Although smaller in overall size, anti-vaccination clusters manage to become highly entangled with undecided clusters in the main online network, whereas pro-vaccination clusters are more peripheral. Our theoretical framework reproduces the recent explosive growth in anti-vaccination views, and predicts that these views will dominate in a decade. Insights provided by this framework can inform new policies and approaches to interrupt this shift to negative views. Our results challenge the conventional thinking about undecided individuals in issues of contention surrounding health, shed light on other issues of contention such as climate change11, and highlight the key role of network cluster dynamics in multi-species ecologies15.

Shockwavelike Behavior across Social Media.

Online communities featuring "anti-X" hate and extremism, somehow thrive online despite moderator pressure. We present a first-principles theory of their dynamics, which accounts for the fact that the online population comprises diverse individuals and evolves in time. The resulting equation represents a novel generalization of nonlinear fluid physics and explains the observed behavior across scales. Its shockwavelike solutions explain how, why, and when such activity rises from "out-of-nowhere," and show how it can be delayed, reshaped, and even prevented by adjusting the online collective chemistry. This theory and findings should also be applicable to anti-X activity in next-generation ecosystems featuring blockchain platforms and Metaverses.

Automated Detection and Classification of Corneal Haze Using Optical Coherence Tomography in Patients With Keratoconus After Cross-Linking.

PURPOSE: To evaluate a proposed technology for offering objective grading and mapping of corneal haze as detected by corneal spectral domain optical coherence tomography after corneal cross-linking. METHODS: This was a retrospective study to evaluate corneal optical coherence tomography images performed on 44 eyes of 44 patients who underwent corneal cross-linking between January 2014 and May 2015, at the American University of Beirut Medical Center. RESULTS: Overall average brightness of the cornea was markedly increased from 43.4% (±6.0) at baseline to 50.2% (±4.4) at 1 month, 47.9% (±4.4) at 3 months, and 46.4% (±5.7) at 6 months with P <0.001, <0.001, and 0.005, respectively. In the anterior stroma, the average brightness significantly increased at 1, 3, and 6 months with values of 54.8% (±3.9), 52.5% (±5.2), and 49.7% (±6.9) with P <0.001, <0.001, and 0.003, respectively. In the mid stroma, the change was clinically significant at 1 and 3 months, whereas in the posterior stroma, it was only significant at 1 month compared with baseline (P = 0.003). Overall, haze was mostly present at 1 month after surgery in all regions, especially in the anterior (32.1%; ±19.2) and mid stromal regions (9.1%; ±18.8), P <0.001 and 0.001, respectively. In contrast, haze in the posterior stromal region peaks at 3 and 6 months after surgery. CONCLUSIONS: Anterior stromal haze was the greatest in intensity and area and it was present for a longer time span than mid and posterior stromal haze. At 12 months, the anterior stroma had still more haze intensity than preoperatively. This image-based software can provide objective and valuable quantitative measurements of corneal haze, which may impact clinical decision-making after different corneal surgeries.