Open AccessIncorporating Information on Control Diseases Across Space and Time to Improve Estimation of the Population-level Impact of Vaccines
Author(s) -
Kayoko Shioda,
Jiachen Cai,
Joshua L. Warren,
Daniel M Weinberger
Publication year - 2021
Publication title -
epidemiology
Language(s) - English
Resource type - Journals
eISSN - 1531-5487
pISSN - 1044-3983
DOI - 10.1097/ede.0000000000001341
Subject(s) - computer science , estimation , pneumococcal conjugate vaccine , control (management) , aggregate (composite) , medicine , statistics , aggregate data , population , econometrics , mathematics , artificial intelligence , biology , engineering , environmental health , streptococcus pneumoniae , materials science , systems engineering , bacteria , composite material , genetics
The synthetic control method evaluates the impact of vaccines while adjusting for a set of control time series representing diseases that are unaffected by the vaccine. However, noise in control time series, particularly in areas with small counts, can obscure the association with the outcome, preventing proper adjustments. To overcome this issue, we investigated the use of temporal and spatial aggregation methods to smooth the controls and allow for adjustment of underlying trends.