scholarly journals Simulation-based power and sample size calculation for designing interrupted time series analyses of count outcomes in evaluation of health policy interventions

2020 ◽  
Vol 17 ◽  
pp. 100474 ◽  
Author(s):  
Wei Liu ◽  
Shangyuan Ye ◽  
Bruce A. Barton ◽  
Melissa A. Fischer ◽  
Colleen Lawrence ◽  
...  
2021 ◽  
Author(s):  
Jakob Manthey ◽  
Domantas Jasilionis ◽  
Huan Jiang ◽  
Olga Mesceriakova-Veliuliene ◽  
Janina Petkeviciene ◽  
...  

Introduction Alcohol use is a major risk factor for mortality. Previous studies suggest that the alcohol-attributable mortality burden is higher in lower socioeconomic strata. This project will test the hypothesis, that the 2017 increase of alcohol excise taxes for beer and wine, which was linked to lower all-cause mortality rates in previous analyses, will reduce socioeconomic mortality inequalities. Methods and analysis Data on all causes of deaths will be obtained from Statistics Lithuania. Record linkage will be implemented using personal identifiers combining data from 1) the 2011 whole-population census, 2) death records between March 1, 2011 (census date) and December 31, 2019, and 3) emigration records, for individuals aged 30 to 70 years. The analyses will be performed separately for all-cause and for alcohol-attributable deaths. Monthly age-standardized mortality rates will be calculated by sex, education, and three measures of socioeconomic status. Inequalities in mortality will be assessed using absolute and relative indicators between low and high SES groups. We will perform interrupted time series analyses, and test the impact of the 2017 rise in alcohol excise taxation using generalized additive mixed models. In these models, we will control for secular trends for economic development. Ethics and dissemination This work is part of project grant 1R01AA028224-01 by the National Institute on Alcohol Abuse and Alcoholism. It has been granted research ethics approval 050/2020 by CAMH Research Ethics Board on April 17, 2020, renewed on March 30, 2021.


2021 ◽  
Author(s):  
Zhicheng Wang ◽  
Hong Xiao ◽  
Leesa Lin ◽  
Kun Tang ◽  
Joseph Unger

Abstract The emergence of the COVID-19 virus and the subsequent official announcement of human-to-human transmission of COVID-19 alarmed the public and initiated the uptake of preventive measures. We conducted interrupted time-series analyses using Baidu Search Index from Jan 1, 2017 to Mar 15, 2021 to investigate how information seeking changed over time and how changes in information seeking varied across regions in China. Our findings show that changes in the patterns of search interest in COVID-19 in each province of China occurred in a synchronous fashion during the first wave of the COVID-19 pandemic and subsequent local outbreaks, irrespective of the location and severity of each outbreak. However, inequalities in the magnitude of public response to and awareness of COVID-19 were evident, with lower-levels of information seeking regarding COVID-19 in less developed areas compared with developed areas.


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