6
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Meningococcal carriage by age in the African meningitis belt: a systematic review and meta-analysis

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Meningococcal carriage dynamics drive patterns of invasive disease. The distribution of carriage by age has been well described in Europe, but not in the African meningitis belt, a region characterised by frequent epidemics of meningitis. We aimed to estimate the age-specific prevalence of meningococcal carriage by season in the African meningitis belt. We searched PubMed, Web of Science, the Cochrane Library and grey literature for papers reporting carriage of Neisseria meningitidis in defined age groups in the African meningitis belt. We used a mixed-effects logistic regression to model meningococcal carriage prevalence as a function of age, adjusting for season, location and year. Carriage prevalence increased from low prevalence in infants (0.595% in the rainy season, 95% CI 0.482–0.852%) to a broad peak at age 10 (1.94%, 95% CI 1.87–2.47%), then decreased in adolescence. The odds of carriage were significantly increased during the dry season (OR 1.5 95% CI 1.4–1.7) and during outbreaks (OR 6.7 95% CI 1.6–29). Meningococcal carriage in the African meningitis belt peaks at a younger age compared to Europe. This is consistent with contact studies in Africa, which show that children 10–14 years have the highest frequency of contacts. Targeting older children in Africa for conjugate vaccination may be effective in reducing meningococcal transmission.

          Related collections

          Most cited references27

          • Record: found
          • Abstract: found
          • Article: not found

          Meningococcal carriage by age: a systematic review and meta-analysis.

          Neisseria meningitidis is an important cause of meningitis and septicaemia, but most infected individuals experience a period of asymptomatic carriage rather than disease. Previous studies have shown that carriage rates vary by age and setting; however, few have assessed carriage across all ages. We aimed to estimate the age-specific prevalence of meningococcal carriage. We searched Embase, Medline, Web of Science, the Cochrane Library, and grey literature for papers reporting carriage of N meningitidis in defined age groups in European countries or in countries with a similar epidemiological pattern (where disease caused by serogroups B and C predominates). We used mixed-effects logistic regression with a natural cubic spline to model carriage prevalence as a function of age for studies that were cross-sectional or serial cross-sectional. The model assessed population type, type of swab used, when swabs were plated, use of preheated plates, and time period (decade of study) as fixed effects, with country and study as nested random effects (random intercept). Carriage prevalence increased through childhood from 4·5% in infants to a peak of 23·7% in 19-year olds and subsequently decreased in adulthood to 7·8% in 50-year olds. The odds of testing positive for carriage decreased if swabs were not plated immediately after being taken compared with if swabs were plated immediately (odds ratio 0·46, 95% CI 0·31-0·68; p = 0·0001). This study provides estimates of carriage prevalence across all ages, which is important for understanding the epidemiology and transmission dynamics of meningococcal infection. None. Copyright © 2010 Elsevier Ltd. All rights reserved.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Better Bootstrap Confidence Intervals

              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              A comparison of observation-level random effect and Beta-Binomial models for modelling overdispersion in Binomial data in ecology & evolution

              Overdispersion is a common feature of models of biological data, but researchers often fail to model the excess variation driving the overdispersion, resulting in biased parameter estimates and standard errors. Quantifying and modeling overdispersion when it is present is therefore critical for robust biological inference. One means to account for overdispersion is to add an observation-level random effect (OLRE) to a model, where each data point receives a unique level of a random effect that can absorb the extra-parametric variation in the data. Although some studies have investigated the utility of OLRE to model overdispersion in Poisson count data, studies doing so for Binomial proportion data are scarce. Here I use a simulation approach to investigate the ability of both OLRE models and Beta-Binomial models to recover unbiased parameter estimates in mixed effects models of Binomial data under various degrees of overdispersion. In addition, as ecologists often fit random intercept terms to models when the random effect sample size is low (<5 levels), I investigate the performance of both model types under a range of random effect sample sizes when overdispersion is present. Simulation results revealed that the efficacy of OLRE depends on the process that generated the overdispersion; OLRE failed to cope with overdispersion generated from a Beta-Binomial mixture model, leading to biased slope and intercept estimates, but performed well for overdispersion generated by adding random noise to the linear predictor. Comparison of parameter estimates from an OLRE model with those from its corresponding Beta-Binomial model readily identified when OLRE were performing poorly due to disagreement between effect sizes, and this strategy should be employed whenever OLRE are used for Binomial data to assess their reliability. Beta-Binomial models performed well across all contexts, but showed a tendency to underestimate effect sizes when modelling non-Beta-Binomial data. Finally, both OLRE and Beta-Binomial models performed poorly when models contained <5 levels of the random intercept term, especially for estimating variance components, and this effect appeared independent of total sample size. These results suggest that OLRE are a useful tool for modelling overdispersion in Binomial data, but that they do not perform well in all circumstances and researchers should take care to verify the robustness of parameter estimates of OLRE models.
                Bookmark

                Author and article information

                Journal
                Epidemiol Infect
                Epidemiol. Infect
                HYG
                Epidemiology and Infection
                Cambridge University Press (Cambridge, UK )
                0950-2688
                1469-4409
                2019
                27 June 2019
                : 147
                : e228
                Affiliations
                [1 ]Disease Dynamics Unit, Department of Veterinary Medicine, University of Cambridge , Madingley Road, Cambridge CB3 0ES, England, UK
                [2 ]WHO Collaborating Center for Reference and Research on Meningococci, Norwegian Institute of Public Health , Oslo, Norway
                [3 ]Population Health Sciences, Bristol Medical School, University of Bristol , Oakfield House, Oakfield Grove, Bristol BS8 2BN, England, UK
                Author notes
                Author for correspondence: Laura V. Cooper, E-mail: lvc32@ 123456cam.ac.uk
                Author information
                https://orcid.org/0000-0002-2942-3627
                Article
                S0950268819001134 00113
                10.1017/S0950268819001134
                6625194
                31364554
                4241c474-5233-4763-8406-fa846b247dc8
                © The Author(s) 2019

                This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence ( http://creativecommons.org/licenses/by-nc-sa/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is included and the original work is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use.

                History
                : 10 February 2019
                : 13 May 2019
                : 29 May 2019
                Page count
                Figures: 3, Tables: 4, References: 36, Pages: 9
                Categories
                Original Paper

                Public health
                infectious disease epidemiology,meningitis-bacterial,meningococcal disease,meta-analysis,pharyngeal carriage

                Comments

                Comment on this article