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      Determinants of Rotavirus Transmission : A Lag Nonlinear Time Series Analysis

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          Abstract

          Rotavirus is a common viral infection among young children. As in many countries, the infection dynamics of rotavirus in the Netherlands are characterized by an annual winter peak, which was notably low in 2014. Previous study suggested an association between weather factors and both rotavirus transmission and incidence. From epidemic theory, we know that the proportion of susceptible individuals can affect disease transmission. We investigated how these factors are associated with rotavirus transmission in the Netherlands, and their impact on rotavirus transmission in 2014. We used available data on birth rates and rotavirus laboratory reports to estimate rotavirus transmission and the proportion of individuals susceptible to primary infection. Weather data were directly available from a central meteorological station. We developed an approach for detecting determinants of seasonal rotavirus transmission by assessing nonlinear, delayed associations between each factor and rotavirus transmission. We explored relationships by applying a distributed lag nonlinear regression model with seasonal terms. We corrected for residual serial correlation using autoregressive moving average errors. We inferred the relationship between different factors and the effective reproduction number from the most parsimonious model with low residual autocorrelation. Higher proportions of susceptible individuals and lower temperatures were associated with increases in rotavirus transmission. For 2014, our findings suggest that relatively mild temperatures combined with the low proportion of susceptible individuals contributed to lower rotavirus transmission in the Netherlands. However, our model, which overestimated the magnitude of the peak, suggested that other factors were likely instrumental in reducing the incidence that year.

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          Bayesian computing with INLA: New features

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            Rotavirus infections in infants as protection against subsequent infections.

            Rotavirus is the leading cause of severe diarrhea in infants. To provide a base line for assessing the efficacy of rotavirus vaccines, we evaluated the protection that is conferred by natural rotavirus infection. We monitored 200 Mexican infants from birth to two years of age by weekly home visits and stool collections. A physician assessed the severity of any episodes of diarrhea and collected additional stool specimens for testing by enzyme immunoassay and typing of strains. Serum collected during the first week of life and every four months thereafter was tested for antirotavirus IgA and IgG. A total of 316 rotavirus infections were detected on the basis of the fecal excretion of virus (56 percent) or a serologic response (77 percent), of which 52 percent were first and 48 percent repeated infections. Children with one, two, or three previous infections had progressively lower risks of both subsequent rotavirus infection (adjusted relative risk, 0.62, 0.40, and 0.34, respectively) and diarrhea (adjusted relative risk, 0.23, 0.17, and 0.08) than children who had no previous infections. No child had moderate-to-severe diarrhea after two infections, whether symptomatic or asymptomatic. Subsequent infections were significantly less severe than first infections (P=0.024), and second infections were more likely to be caused by another G type (P=0.054). In infants, natural rotavirus infection confers protection against subsequent infection. This protection increases with each new infection and reduces the severity of the diarrhea.
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              Noisy clockwork: time series analysis of population fluctuations in animals.

              Both biotic interactions and abiotic random forcing are crucial influences on population dynamics. This frequently leads to roughly equal importance of deterministic and stochastic forces. The resulting tension between noise and determinism makes ecological dynamics unique, with conceptual and methodological challenges distinctive from those in other dynamical systems. The theory for stochastic, nonlinear ecological dynamics has been developed alongside methods to test models. A range of dynamical components has been considered-density dependence, environmental and demographic stochasticity, and climatic forcing-as well as their often complex interactions. We discuss recent advances in understanding ecological dynamics and testing theory using long-term data and review how dynamical forces interact to generate some central field and laboratory time series.
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                Author and article information

                Journal
                Epidemiology
                Epidemiology
                EDE
                Epidemiology (Cambridge, Mass.)
                Lippincott Williams & Wilkins
                1044-3983
                1531-5487
                July 2017
                01 June 2017
                : 28
                : 4
                : 503-513
                Affiliations
                From the [a ]Center for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands; [b ]Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands; and [c ]Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands.
                Author notes
                Correspondence: Rolina D. van Gaalen, RIVM, EPI Postbak 75, P.O. Box 1, 3720BA Bilthoven, The Netherlands. E-mail: rolina.van.gaalen@ 123456rivm.nl .
                Article
                00006
                10.1097/EDE.0000000000000654
                5457827
                28333764
                56687d24-9de7-490d-b26d-b41bf87e10d4
                Copyright © 2017 The Author(s). Published by Wolters Kluwer Health, Inc.

                This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

                History
                : 19 April 2016
                : 14 March 2017
                Categories
                Infectious Diseases
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