Echo chambers and opinion dynamics explain the occurrence of vaccination hesitancy.
    
    
        
    
    
        
        R. Soc. Open Sci. 9:220367 (2022)
    
    
    
		
		
			
				Vaccination hesitancy is a major obstacle to achieving and maintaining herd immunity. Therefore, public health authorities need to understand the dynamics of an anti-vaccine opinion in the population. We introduce a spatially structured mathematical model of opinion dynamics with reinforcement. The model allows as an emergent property for the occurrence of echo chambers, i.e. opinion bubbles in which information that is incompatible with one's entrenched worldview, is probably disregarded. We scale the model both to a deterministic limit and to a weak-effects limit, and obtain bifurcations, phase transitions and the invariant measure. Fitting the model to measles and meningococci vaccination coverage across Germany, reveals that the emergence of echo chambers dynamics explains the occurrence and persistence of the anti-vaccination opinion in allowing anti-vaxxers to isolate and to ignore pro-vaccination facts. We predict and compare the effectiveness of different policies aimed at influencing opinion dynamics in order to increase vaccination uptake. According to our model, measures aiming at reducing the salience of partisan anti-vaccine information sources would have the largest effect on enhancing vaccination uptake. By contrast, measures aiming at reducing the reinforcement of vaccination deniers are predicted to have the smallest impact.
			
			
				
			
		 
		
			
				
					
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        Publikationstyp
        Artikel: Journalartikel
    
 
    
        Dokumenttyp
        Wissenschaftlicher Artikel
    
 
    
        Typ der Hochschulschrift
        
    
 
    
        Herausgeber
        
    
    
        Schlagwörter
        Data Analysis ; Opinion Dynamics ; Reinforcement Model ; Vaccination Hesitancy; Self-interest; Polarization; Measles; Economics; Behavior; Systems; Policy; Model
    
 
    
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        Sprache
        englisch
    
 
    
        Veröffentlichungsjahr
        2022
    
 
    
        Prepublished im Jahr 
        0
    
 
    
        HGF-Berichtsjahr
        2022
    
 
    
    
        ISSN (print) / ISBN
        2054-5703
    
 
    
        e-ISSN
        2054-5703
    
 
    
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	    Band: 9,  
	    Heft: 10,  
	    Seiten: ,  
	    Artikelnummer: 220367 
	    Supplement: ,  
	
    
 
  
        
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            Verlag
            Royal Society of London
        
 
        
            Verlagsort
            6-9 Carlton House Terrace, London Sw1y 5ag, England
        
 
	
        
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        Begutachtungsstatus
        Peer reviewed
    
 
     
    
        POF Topic(s)
        30205 - Bioengineering and Digital Health
    
 
    
        Forschungsfeld(er)
        Enabling and Novel Technologies
    
 
    
        PSP-Element(e)
        G-503800-001
    
 
    
        Förderungen
        International Graduate School of Science and Engineering
Deutsche Forschungsgemeinschaft
IGGSE
    
 
    
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        Erfassungsdatum
        2022-11-29