Periodic regression models originally developed for monitoring and measuring the impact of seasonal epidemic and pandemic influenza (3134) were used to estimate seasonal baseline patterns of diarrheal syndrome ED visits and to quantify epidemic period excess visits as a proxy for RVGE. To determine the magnitude of excess diarrheal syndrome ED visits during documented peak rotavirus periods, models were fit to weekly time series of the proportion of diarrheal syndrome ED visits during baseline periods, defined as the consecutive weeks between predominant rotavirus circulation periods, with the remaining upper-quartile weeks removed before model fitting. The periodic regression models included secular trend and annual (52-week) and semiannual (26-week) harmonic terms to approximate seasonal baseline patterns expected in the absence of winter seasonal epidemic increases, as routinely used with surveillance data for monitoring influenza-like syndrome ED visits in New York City (33) and diarrheal syndrome clinic visits in the French Sentinel Network (34).

The periodic regression models were fit to data for each age group. Rotavirus epidemic periods were defined as consecutive weeks during peak rotavirus circulation when observed diarrheal ED visits exceeded the all-ages periodic regression threshold. Weekly rotavirus epidemic period excess diarrheal syndrome ED visit estimates were calculated as the observed minus expected proportions multiplied by the observed weekly total of ED visits for each group. Average seasonal rotavirus epidemic period excess diarrheal ED visits for 2003 to 2006, before widespread vaccine use, were compared to each postvaccine season from 2008 to 2016 as the ratio of the seasonal excess diarrheal ED visit rate for each postvaccine epidemic to the average epidemic prevaccine excess diarrheal ED visit rate by age group. Age-specific excess diarrheal ED visit rate ratios were calculated to determine the relative change by season in each age group.

Note: The content above has been extracted from a research article, so it may not display correctly.

Please log in to submit your questions online.
Your question will be posted on the Bio-101 website. We will send your questions to the authors of this protocol and Bio-protocol community members who are experienced with this method. you will be informed using the email address associated with your Bio-protocol account.

We use cookies on this site to enhance your user experience. By using our website, you are agreeing to allow the storage of cookies on your computer.