Rotavirus vaccination takes seasonal signature of childhood diarrhea back to pre-sanitation era in Brazil

The burden of rotavirus-associated acute gastroenteritis in the elderly: assessment of the epidemiology in the context of universal childhood vaccination programs

INTRODUCTION

Rotaviruses (RVs) cause acute gastroenteritis (AGE) in infants and young children worldwide and also in older adults (≥60 years), however the burden among this age group is not well understood. Herd immunity through pediatric RV vaccination may reduce the burden of RVGE across all ages, however the impact of pediatric vaccination on burden in older adults is poorly understood.

AREAS COVERED

This systematic review was undertaken to identify studies related to the following objectives: understand the burden of RV in older adults, RV seroprevalence, and the impact of pediatric vaccination on this burden and highlight evidence gaps to guide future research. Of studies identified, 59 studies from two databases were included in this analysis following a review by two reviewers.

EXPERT OPINION

RV is an understudied disease in older adults. We found that 0-62% of patients with AGE tested positive for RV, with results varying by setting, country, and patient age. Results also suggest that pediatric vaccination benefits older adults through herd protection. Several studies showed a reduction in RV incidence after vaccination. However, there was variety in results and lack of consistency in outcomes reported. Further studies targeting older adults are needed to better characterize RV burden.

Prevalence of Cryptosporidium parvum, Giardia intestinalis and molecular characterization of group A rotavirus associated with diarrhea in children below five years old in Gaborone, Botswana

Introduction

Cryptosporidium, Giardia and rotaviruses are amongst the leading causes of acute gastroenteritis in children ≤5 years worldwide. The purpose of this study was to determine the occurrence of Cryptosporidium parvum, Giardia intestinalis and molecular characteristics of rotaviruses after Rotarix® introduction in Botswana.

Methods

in this case study, 200 diarrheic stool specimens and 100 control samples from children under five years old were collected between March and November, 2017. Samples were analyzed by modified Ziehl Neelsen staining technique for cryptosporidium, wet mount procedure for Giardia and negative samples were confirmed by immunochromatographic assay. Specimens were analyzed for rotavirus by ELISA, PAGE, RT-PCR, sequencing of VP7 and VP4 antigen followed by phylogenetic analysis.

Results

prevalence rates of 20.5%, 16.5% and 11.0% in diarrhea cases were observed for Cryptosporidium parvum, Giardia intestinalis and rotavirus, respectively. Four percent of diarrheic specimens had multiple infections. The predominant rotavirus genotype was GIP[8] (7/15) followed by G2P[4] (2/15) and G3P[8] (1/15). Twenty percent of specimens were non-typeable. One mixed strain, G1+G2P[4,8] (2/15), was detected. Phylogenetic analysis of VP4 and VP7 sequences clustered Botswana rotavirus strains within G1 lineages 1 and 2, G3 lineage 1, P[8] lineage 3 and P[4] lineage 5 together with Southern African strains.

Conclusion

this study provides important information on occurrence and demographic risk groups for Cryptosporidium parvum, Giardia intestinalis and rotavirus in young children as well as genetic diversity of rotaviruses after vaccine introduction in Botswana. Constant monitoring of circulating rotavirus strains is essential in assessing effectiveness of current vaccines in Botswana.

Spatio-temporal impact of self-financed rotavirus vaccination on rotavirus and acute gastroenteritis hospitalisations in the Valencia region, Spain

BACKGROUND

Several studies have shown a substantial impact of Rotavirus (RV) vaccination on the burden of RV and all-cause acute gastroenteritis (AGE). However, the results of most impact studies could be confused by a dynamic and complex space-time process. Therefore, there is a need to analyse the impact of RV vaccination on RV and AGE hospitalisations in a space-time framework to detect geographical-time patterns while avoiding the potential confusion caused by population inequalities in the impact estimations.

METHODS

A retrospective population-based study using real-world data from the Valencia Region was performed among children aged less than 3 years old in the period 2005-2016. A Bayesian spatio-temporal model was constructed to analyse RV and AGE hospitalisations and to estimate the vaccination impact measured in averted hospitalisations.

RESULTS

We found important spatio-temporal patterns in RV and AGE hospitalisations, RV vaccination coverage and in their associated adverted hospitalisations. Overall, ~ 1866 hospital admissions for RV were averted by RV vaccination during 2007-2016. Despite the low-medium vaccine coverage (~ 50%) in 2015-2016, relevant 36 and 20% reductions were estimated in RV and AGE hospitalisations respectively.

CONCLUSIONS

The introduction of the RV vaccines has substantially reduced the number of RV hospitalisations, averting ~ 1866 admissions during 2007-2016 which were space and time dependent. This study improves the methodologies commonly used to estimate the RV vaccine impact and their interpretation.

Design characteristics and statistical methods used in interrupted time series studies evaluating public health interventions: a review

OBJECTIVES

Interrupted time series (ITS) designs are frequently used in public health to examine whether an intervention or exposure has influenced health outcomes. Few reviews have been undertaken to examine the design characteristics, statistical methods, and completeness of reporting of published ITS studies.

STUDY DESIGN AND SETTING

We used stratified random sampling to identify 200 ITS studies that evaluated public health interventions or exposures from PubMed (2013-2017). Study characteristics, details of statistical models and estimation methods used, effect metrics, and parameter estimates were extracted. From the 200 studies, 230 time series were examined.

RESULTS

Common statistical methods used were linear regression (31%, 72/230) and autoregressive integrated moving average (19%, 43/230). In 17% (40/230) of the series, we could not determine the statistical method used. Autocorrelation was acknowledged in 63% (145/230) of the series. An estimate of the autocorrelation coefficient was given for only 1% of the series (3/230). Measures of precision were reported for 63% of effect measures (541/852).

CONCLUSION

Many aspects of the design, methods, analysis, and reporting of ITS studies can be improved, particularly description of the statistical methods and approaches to adjust for and estimate autocorrelation. More guidance on the conduct and reporting of ITS studies is needed to improve this study design.

Seasonality of Rotavirus Hospitalizations at Costa Rica's National Children's Hospital in 2010-2015

Rotavirus is a leading cause of acute diarrhea in children worldwide. Costa Rica recently started universal rotavirus vaccinations for infants with a two-dose schedule in February 2019. We aimed to study the seasonality of rotavirus during the pre-vaccination era. We retrospectively studied a six-year period of hospital admissions due to rotavirus gastroenteritis. We estimated seasonal peak timing and relative intensities using trend-adjusted negative binomial regression models with the δ-method. We assessed the relationship between rotavirus cases and weather characteristics and estimated their effects for the current month, one-month prior and two months prior, by using Pearson correlation coefficients. A total of 798 cases were analyzed. Rotavirus cases predominated in the first five months of the year. On average, the peak of admissions occurred between late-February and early-March. During the seasonal peaks, the monthly count tended to increase 2.5-2.75 times above the seasonal nadir. We found the strongest negative association of monthly hospitalizations and joint percentiles of precipitation and minimal temperature at a lag of two months (R = -0.265, p = 0.027) and we detected correlations of -0.218, -0.223, and -0.226 (p < 0.05 for all three estimates) between monthly cases and the percentile of precipitation at lags 0, 1, and 2 months. In the warm tropical climate of Costa Rica, the increase in rotavirus hospitalizations coincided with dry and cold weather conditions with a two-month lag. The findings serve as the base for predictive modeling and estimation of the impact of a nation-wide vaccination campaign on pediatric rotaviral infection morbidity.

Etiology and severity of diarrheal diseases in infants at the semiarid region of Brazil: A case-control study

Background

Diarrheal diseases are an important cause of morbidity and mortality among children in developing countries. We aimed to study the etiology and severity of diarrhea in children living in the low-income semiarid region of Brazil.

Methodology

This is a cross-sectional, age-matched case-control study of diarrhea in children aged 2–36 months from six cities in Brazil’s semiarid region. Clinical, epidemiological, and anthropometric data were matched with fecal samples collected for the identification of enteropathogens.

Results

We enrolled 1,200 children, 596 cases and 604 controls. By univariate analysis, eight enteropathogens were associated with diarrhea: Norovirus GII (OR 5.08, 95% CI 2.10, 12.30), Adenovirus (OR 3.79, 95% CI 1.41, 10.23), typical enteropathogenic Escherichia coli (tEPEC), (OR 3.28, 95% CI 1.39, 7.73), enterotoxigenic E. coli (ETEC LT and ST producing toxins), (OR 2.58, 95% CI 0.99, 6.69), rotavirus (OR 1.91, 95% CI 1.20, 3.02), shiga toxin-producing E. coli (STEC; OR 1.77, 95% CI 1.16, 2.69), enteroaggregative E. coli (EAEC), (OR 1.45, 95% CI 1.16, 1.83) and Giardia spp. (OR 1.39, 95% CI 1.05, 1.84). By logistic regression of all enteropathogens, the best predictors of diarrhea were norovirus, adenovirus, rotavirus, STEC, Giardia spp. and EAEC. A high diarrhea severity score was associated with EAEC.

Conclusions

Six enteropathogens: Norovirus, Adenovirus, Rotavirus, STEC, Giardia spp., and EAEC were associated with diarrhea in children from Brazil’s semiarid region. EAEC was associated with increased diarrhea severity.

Most childhood diarrheal diseases studies focus on children from health centers or emergency hospitals that contribute to a lack of understanding of the etiology of community diarrhea. We aimed to investigate the etiology and severity of diarrheal diseases in children living in Brazil’s low-income, semiarid region communities. We used a case-control study of diarrhea (1,200 children, 596 cases and 604 controls) and showed that six enteropathogens (norovirus, adenovirus, rotavirus, STEC, Giardia and EAEC) are associated with diarrhea in these communities. Furthermore, enteroaggregative E. coli (EAEC) was associated with a high diarrhea clinical severity score. These findings help further the understanding of diarrheal disease etiology of previously unevaluated children from Brazil’s low-income semiarid region. This study contributes new information that expands our knowledge of diarrheal etiology in non-hospitalized children from developing countries. Moreover, we believe this work will support further research on specific enteropathogens, with special attention to the role of EAEC in severe cases of diarrhea and guide public health policies and physicians in the management of diarrheal diseases in Brazil’s low-income semiarid region.

Design characteristics and statistical methods used in interrupted time series studies evaluating public health interventions: protocol for a review

INTRODUCTION

An interrupted time series (ITS) design is an important observational design used to examine the effects of an intervention or exposure. This design has particular utility in public health where it may be impracticable or infeasible to use a randomised trial to evaluate health system-wide policies, or examine the impact of exposures (such as earthquakes). There have been relatively few studies examining the design characteristics and statistical methods used to analyse ITS designs. Further, there is a lack of guidance to inform the design and analysis of ITS studies.This is the first study in a larger project that aims to provide tools and guidance for researchers in the design and analysis of ITS studies. The objectives of this study are to (1) examine and report the design characteristics and statistical methods used in a random sample of contemporary ITS studies examining public health interventions or exposures that impact on health-related outcomes, and (2) create a repository of time series data extracted from ITS studies. Results from this study will inform the remainder of the project which will investigate the performance of a range of commonly used statistical methods, and create a repository of input parameters required for sample size calculation.

METHODS AND ANALYSIS

We will collate 200 ITS studies evaluating public health interventions or the impact of exposures. ITS studies will be identified from a search of the bibliometric database PubMed between the years 2013 and 2017, combined with stratified random sampling. From eligible studies, we will extract study characteristics, details of the statistical models and estimation methods, effect metrics and parameter estimates. Further, we will extract the time series data when available. We will use systematic review methods in the screening, application of inclusion and exclusion criteria, and extraction of data. Descriptive statistics will be used to summarise the data.

ETHICS AND DISSEMINATION

Ethics approval is not required since information will only be extracted from published studies. Dissemination of the results will be through peer-reviewed publications and presentations at conferences. A repository of data extracted from the published ITS studies will be made publicly available.