TY - JOUR
AU - Biggerstaff, Matthew
AU - Cowling, Benjamin J
AU - Cucunubá, Zulma M.
AU - Dinh, Linh
AU - Ferguson, Neil M.
AU - Gao, Huizhi
AU - Hill, Verity
AU - Imai, Natsuko
AU - Johansson, Michael A.
AU - Kada, Sarah
AU - Morgan, Oliver
AU - Pastore y Piontti, Ana
AU - Polonsky, Jonathan A.
AU - Venkata Prasad, Pragati
AU - Quandelacy, Talia M.
AU - Rambaut, Andrew
AU - Tappero, Jordan W
AU - Vandemaele, Katelijn A.
AU - Vespignani, Alessandro
AU - Warmbrod, K. Lane
AU - Wong, Jessica Y.
PY - 2020
DA - November
TI - Early insights from statistical and mathematical modeling of key epidemiologic parameters of COVID-19
JO - Emerging Infectious Diseases
VL - 26
IS - 11
DO - https://doi.org/10.3201/eid2611.201074
AB - We report key epidemiologic parameter estimates for coronavirus disease identified in peer-reviewed publications, preprint articles, and online reports. Range estimates for incubation period were 1.8–6.9 days, serial interval 4.0–7.5 days, and doubling time 2.3–7.4 days. The effective reproductive number varied widely, with reductions attributable to interventions. Case burden and infection fatality ratios increased with patient age. Implementation of combined interventions could reduce cases and delay epidemic peak up to 1 month. These parameters for transmission, disease severity, and intervention effectiveness are critical for guiding policy decisions. Estimates will likely change as new information becomes available.
PB - US Centers for Disease Control and Prevention
UR - https://www.research.ed.ac.uk/portal/en/publications/early-insights-from-statistical-and-mathematical-modeling-of-key-epidemiologic-parameters-of-covid19(1deaf5c7-271e-4245-9868-a928678ddc13).html
KW - Coronavirus (COVID-19)
KW - Research methods
ER