Modeling seasonal variation in rotavirus hospitalizations for use in evaluating the effect of rotavirus vaccine

Abstract

Every year rotavirus epidemic repeats in cooler months of the year in temperate countries, but the size of the epidemic may often vary. Such seasonal variation needs to be considered when the effect of rotavirus vaccine is predicted before vaccine introduction or it is evaluated after vaccine introduction. A computer program based on a stochastic decision tree model was developed to produce stochastic variation, which was used as a proxy for seasonal variation, in the number of rotavirus hospitalizations. When the model was applied to a hypothetical community with a birth cohort of 1,000 children in Japan, it predicted the occurrence of up to 29% of stochastic variation from the average number of rotavirus hospitalizations. Then, the model was applied for use in evaluating the effect of rotavirus vaccine in two different scenarios regarding vaccine use in the community: a scenario where rotavirus vaccine was introduced only into the private sector, and another where it was incorporated into the universal immunization program. In the former scenario, an average of 23% reduction in the number of rotavirus hospitalizations was predicted, but this level of reduction would be obscured due to seasonal variation. In the latter scenario, an average of 74% reduction was predicted, which would be beyond seasonal variation. This model will be useful to inform stakeholders and policymakers how vaccine introduction will change the burden of rotavirus disease under different scenarios of vaccine implementation.

Impact of Rotavirus Vaccine on Premature Infants

“…Such secular variability was demonstrated in a study of three US hospitals over the same periods (2006-2007 and 2007-2008) (26). In addition, Sato et al showed that the effectiveness of the vaccine against rotavirus may be masked by not including this concept in the analysis (27). This effectiveness has now been observed in other studies that have taken into account the variability of the rotavirus epidemics (15)(16)(17).…”

Burden of Rotavirus Disease: A Population‐Based Study in Eastern Townships, Quebec

“…Other publications in Canada, in which active laboratory surveillance was used, report that rotaviruses contribute to approximately 37% to 71% of hospitalizations, 44% to 47% of ED visits and 18% to 20% of outpatient visits for AGE (3-5). The range of results reported in these studies may be explained by the fact they were conducted during only one epidemic season; it is well known that interyear variations are important in rotavirus AGE (18)(19)(20)(21)(22)(23)(24). The main limitations of the present study are its retrospective design and use of indirect methods of rotavirus-associated AGE estimation.…”

A Retrospective, Hospital-Based Study to Determine the Incidence of Rotavirus Hospitalizations among Children Less than 5 Years of Age over a 10-Year Period (2001^|^ndash;2011) in Akita Prefecture, Japan

“…The exact cause for this considerable variation is unknown, but the degree of observed annual variations exceeded the level of variation predicted by a computer simulation model developed to produce stochastic variations based on parameters obtained from an epidemiological study conducted in this same catchment area. That model predicted up to a 1.79-fold difference between the highest and lowest year (21). Thus, it is likely that other factors such as changes in dominant circulating strains and the immunity formed in the local population may play a role in the seasonal variation of the number of rotavirus hospitalizations.…”

“…The level of annual variations was most appropriately assessed by a computer simulation model precisely developed on the basis of parameters obtained by epidemiological studies conducted in the same catchment area (21). However, this study had some limitations.…”