Author: Metcalf, C.J.E.; Wesolowski, A.; Winter, A. K.; Lessler, J.; Cauchemez, S.; Moss, W. J.; McLean, A. R.; Grenfell, B. T.
                    Title: Using serology to anticipate measles post-honeymoon period outbreaks  Cord-id: ab1hy5z6  Document date: 2020_4_20
                    ID: ab1hy5z6
                    
                    Snippet: Abstract Measles vaccination is a public health ‘best buy’, with the highest cost of illness averted of any vaccine-preventable disease [1]. In the last decades, substantial reductions have been made in the number of measles cases, with an estimated 20 million deaths averted from 2000 to 2017 [2]. Yet, an important feature of epidemic dynamics is that large outbreaks can occur following years of apparently successful control [3]. Such ‘post-honeymoon period’ outbreaks are a result of the
                    
                    
                    
                     
                    
                    
                    
                    
                        
                            
                                Document: Abstract Measles vaccination is a public health ‘best buy’, with the highest cost of illness averted of any vaccine-preventable disease [1]. In the last decades, substantial reductions have been made in the number of measles cases, with an estimated 20 million deaths averted from 2000 to 2017 [2]. Yet, an important feature of epidemic dynamics is that large outbreaks can occur following years of apparently successful control [3]. Such ‘post-honeymoon period’ outbreaks are a result of the non-linear dynamics of epidemics [3]. Anticipating post-honeymoon outbreaks could lead to substantial gains in public health, helping to guide the timing, age-range and location of catch-up vaccination campaigns [4]. Theoretical conditions for such outbreaks are well-understood for measles, yet the information required to make these calculations policy-relevant is largely lacking. We propose that a major extension of serological studies to directly characterize measles susceptibility is a high priority.
 
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