@article{fdi:010077423,
  title = {{I}mproved inference of time-varying reproduction numbers during infectious disease outbreaks},
  author = {{T}hompson, {R}. {N}. and {S}tockwin, {J}. {E}. and van {G}aalen, {R}. {D}. and {P}olonsky, {J}. {A}. and {K}amvar, {Z}. {N}. and {D}emarsh, {P}. {A}. and {D}ahlqwist, {E}. and {L}i, {S}. and {M}iguel, {E}ve and {J}ombart, {T}. and {L}essler, {J}. and {C}auchemez, {S}. and {C}ori, {A}.},
  editor = {},
  language = {{ENG}},
  abstract = {{A}ccurate estimation of the parameters characterising infectious disease transmission is vital for optimising control interventions during epidemics. {A} valuable metric for assessing the current threat posed by an outbreak is the time-dependent reproduction number, i.e. the expected number of secondary cases caused by each infected individual. {T}his quantity can be estimated using data on the numbers of observed new cases at successive times during an epidemic and the distribution of the serial interval (the time between symptomatic cases in a transmission chain). {S}ome methods for estimating the reproduction number rely on pre-existing estimates of the serial interval distribution and assume that the entire outbreak is driven by local transmission. {H}ere we show that accurate inference of current transmissibility, and the uncertainty associated with this estimate, requires: (i) upto-date observations of the serial interval to be included, and; (ii) cases arising from local transmission to be distinguished from those imported from elsewhere. {W}e demonstrate how pathogen transmissibility can be inferred appropriately using datasets from outbreaks of {H}1{N}1 influenza, {E}bola virus disease and {M}iddle-{E}ast {R}espiratory {S}yndrome. {W}e present a tool for estimating the reproduction number in real-time during infectious disease outbreaks accurately, which is available as an {R} software package ({E}pi{E}stim 2.2). {I}t is also accessible as an interactive, user-friendly online interface ({E}pi{E}stim {A}pp), permitting its use by non-specialists. {O}ur tool is easy to apply for assessing the transmission potential, and hence informing control, during future outbreaks of a wide range of invading pathogens.},
  keywords = {{M}athematical modelling ; {I}nfectious disease epidemiology ; {P}arameter inference ; {R}eproduction number ; {S}erial interval ; {D}isease control},
  booktitle = {},
  journal = {{E}pidemics},
  volume = {29},
  numero = {},
  pages = {art. 100356 [11 p.]},
  ISSN = {1755-4365},
  year = {2019},
  DOI = {10.1016/j.epidem.2019.100356},
  URL = {https://www.documentation.ird.fr/hor/fdi:010077423},
}