%0 Journal Article
%J The Lancet. Infectious diseases
%D 2017
%T The basic reproduction number (R) of measles: a systematic review.
%A Guerra, Fiona M
%A Bolotin, Shelly
%A Lim, Gillian
%A Heffernan, Jane
%A Deeks, Shelley L
%A Li, Ye
%A Crowcroft, Natasha S
%K Disease Transmission, Infectious
%K Humans
%K Measles
%K Models, Biological
%N 12
%P e420-e428
%R 10.1016/S1473-3099(17)30307-9
%V 17
%X The basic reproduction number, R nought (R), is defined as the average number of secondary cases of an infectious disease arising from a typical case in a totally susceptible population, and can be estimated in populations if pre-existing immunity can be accounted for in the calculation. R determines the herd immunity threshold and therefore the immunisation coverage required to achieve elimination of an infectious disease. As R increases, higher immunisation coverage is required to achieve herd immunity. In July, 2010, a panel of experts convened by WHO concluded that measles can and should be eradicated. Despite the existence of an effective vaccine, regions have had varying success in measles control, in part because measles is one of the most contagious infections. For measles, R is often cited to be 12-18, which means that each person with measles would, on average, infect 12-18 other people in a totally susceptible population. We did a systematic review to find studies reporting rigorous estimates and determinants of measles R. Studies were included if they were a primary source of R, addressed pre-existing immunity, and accounted for pre-existing immunity in their calculation of R. A search of key databases was done in January, 2015, and repeated in November, 2016, and yielded 10 883 unique citations. After screening for relevancy and quality, 18 studies met inclusion criteria, providing 58 R estimates. We calculated median measles R values stratified by key covariates. We found that R estimates vary more than the often cited range of 12-18. Our results highlight the importance of countries calculating R using locally derived data or, if this is not possible, using parameter estimates from similar settings. Additional data and agreed review methods are needed to strengthen the evidence base for measles elimination modelling.
%8 2017 Dec