Predicting genotype compositions in norovirus seasons in Japan

Predictive modeling for infectious diarrheal disease in pediatric populations: A systematic review

Introduction

Diarrhea is still a significant global public health problem. There are currently no systematic evaluation of the modeling areas and approaches to predict diarrheal illness outcomes. This paper reviews existing research efforts in predictive modeling of infectious diarrheal illness in pediatric populations.

Methods

We conducted a systematic review via a PubMed search for the period 1990-2021. A comprehensive search query was developed through an iterative process and literature on predictive modeling of diarrhea was retrieved. The following filters were applied to the search results: human subjects, English language, and children (birth to 18 years). We carried out a narrative synthesis of the included publications.

Results

Our literature search returned 2671 articles. After manual evaluation, 38 of these articles were included in this review. The most common research topic among the studies were disease forecasts 14 (36.8%), vaccine-related predictions 9 (23.7%), and disease/pathogen detection 5 (13.2%). Majority of these studies were published between 2011 and 2020, 28 (73.7%). The most common technique used in the modeling was machine learning 12 (31.6%) with various algorithms used for the prediction tasks. With change in the landscape of diarrheal etiology after rotavirus vaccine introduction, many open areas (disease forecasts, disease detection, and strain dynamics) remain for pathogen-specific predictive models among etiological agents that have emerged as important. Additionally, the outcomes of diarrheal illness remain under researched. We also observed lack of consistency in the reporting of results of prediction models despite the available guidelines highlighting the need for common data standards and adherence to guidelines on reporting of predictive models for biomedical research.

Conclusions

Our review identified knowledge gaps and opportunities in predictive modeling for diarrheal illness, and limitations in existing attempts whilst advancing some precursory thoughts on how to address them, aiming to invigorate future research efforts in this sphere.

Predicting Dominant Genotypes in Norovirus Seasons in Japan

Human noroviruses are an etiological agent of acute gastroenteritis. Since multiple genotypes co-circulate every season changing their proportions, it may be desirable to develop multivalent vaccines by formulating genotype composition of seed strains to match that of dominant strains. Here, performances of the models for predicting dominant genotypes, defined as the two most prevalent genotypes, were evaluated using observed genotype frequencies in Japan and genomic sequences for GI and GII strains. In the null model, genotype proportions in the target season were predicted to be the same as those in the immediately preceding season. In the fitness model, genotype proportions were predicted taking into account the acquisition of novel P-types through recombination and genotype-specific proliferation efficiency, as well as herd immunity to VP1 assuming the duration (d) of 0-10 years. The null model performed better in GII than in GI, apparently because dominant genotypes were more stable in the former than in the latter. Performance of the fitness model was similar to that of the null model irrespective of the assumed value of d. However, performance was improved when dominant genotypes were predicted as the union of those predicted with d = 0-10, suggesting that d may vary among individuals.

Norovirus Epidemiology and Genetic Diversity in Leipzig, Germany during 2013-2017

Globally and in all age groups, noroviruses are a main cause of gastroenteritis. To assess their local epidemiology and genetic diversity, stool samples of 7509 inpatients with gastrointestinal complaints from all age groups were analyzed. After detection of norovirus genogroup I and II RNA by real-time RT-PCR, viral capsids were genotyped by partial nucleic acid sequencing. In the case of GII.2 strains, polymerase genotypes were also assessed. Between October 2013 and September 2017, presence of norovirus RNA was shown in 611 samples (8.1%), of which 610 (99.8%) were typed successfully. Norovirus positivity rate was higher in patients aged below five years (14.8%) than in older patients (5.7%). Among the 611 norovirus positive samples, GII.4 (56.6%) strains prevailed, followed by GII.6 (11.3%), GII.3 (11.0%) and GII.2 (9.5%). The most common genogroup I (GGI) genotype was GI.3 (3.6%). In addition, rare genotypes such as GII.13, GII.14 and GII.26 were detected. Interestingly, GII.3 infections were most common in children under the age of five years. Assessment of polymerase genotypes in GII.2 viruses showed a shift from P2 to P16, with higher diversity in P2 sequences. The varying distribution of norovirus genotypes depending on season, age and setting of infection highlights the importance of frequent genotyping as a basis for vaccine development and needful adjustments.

Variation of human norovirus GII genotypes detected in Ibaraki, Japan, during 2012-2018

Background

Human norovirus (HuNoV) is the major cause of viral acute gastroenteritis for all age groups in various countries. HuNoV GII in particular accounted for the majority of norovirus outbreaks, among which GII.4 caused repeated outbreaks for a long time. Besides GII.4, other norovirus genotypes, GII.2, GII.6, and GII.17, have also been prevalent in various contexts in recent years, but few detailed epidemiological studies of them have been performed and are poorly understood. We thus conducted an epidemiological analysis of HuNoV GII in Ibaraki Prefecture, Japan, by performing surveillance in the six seasons from September 2012 to August 2018.

Results

HuNoV GI occurred almost sporadically for all genotypes; however, each genotype of GII exhibited its typical epidemiological characteristics. Although the number of outbreaks of GII.4 decreased season by season, it reemerged in 2017/2018 season. The timing of the epidemic peak in terms of number of cases for GII.17 differed from that for the other genotypes. The patients age with GII.2 and GII.6 were younger and outbreak of GII.17 occurred frequently as food poisoning. Namely, the primarily infected outbreak group differed for each genotype of HuNoV GII. Moreover, the viral load of patients differed according to the genotype.

Conclusions

Various HuNoV genotypes including GII.2, GII.4, GII.6, and GII.17 were shown to be associated with various types of outbreak sites (at childcare and educational facilities, involving cases of food poisoning, and at elderly nursing homes) in this study. These genotypes emerged in recent years, and their prevalence patterns differed from each other. Moreover, differences in outbreak sites and viral load of patients among the genotypes were identified.

Predicting Directions of Changes in Genotype Proportions Between Norovirus Seasons in Japan

The norovirus forecasting system (NOROCAST) has been developed for predicting directions of changes in genotype proportions between human norovirus (HuNoV) seasons in Japan through modeling herd immunity to structural protein 1 (VP1). Here 404 nearly complete genomic sequences of HuNoV were analyzed to examine whether the performance of NOROCAST could be improved by modeling herd immunity to VP2 and non-structural proteins (NS) in addition to VP1. It was found that the applicability of NOROCAST may be extended by compensating for unavailable sequence data and observed genotype proportions of 0 in each season. Incorporation of herd immunity to VP2 and NS did not appear to improve the performance of NOROCAST, suggesting that VP1 may be a suitable target of vaccines.

Molecular Evolution of the VP1 Gene in Human Norovirus GII.4 Variants in 1974-2015

Human norovirus (HuNoV) is a leading cause of viral gastroenteritis worldwide, of which GII.4 is the most predominant genotype. Unlike other genotypes, GII.4 has created various variants that escaped from previously acquired immunity of the host and caused repeated epidemics. However, the molecular evolutionary differences among all GII.4 variants, including recently discovered strains, have not been elucidated. Thus, we conducted a series of bioinformatic analyses using numerous, globally collected, full-length GII.4 major capsid (VP1) gene sequences (466 strains) to compare the evolutionary patterns among GII.4 variants. The time-scaled phylogenetic tree constructed using the Bayesian Markov chain Monte Carlo (MCMC) method showed that the common ancestor of the GII.4 VP1 gene diverged from GII.20 in 1840. The GII.4 genotype emerged in 1932, and then formed seven clusters including 14 known variants after 1980. The evolutionary rate of GII.4 strains was estimated to be 7.68 × 10⁻³ substitutions/site/year. The evolutionary rates probably differed among variants as well as domains [protruding 1 (P1), shell, and P2 domains]. The Osaka 2007 variant strains probably contained more nucleotide substitutions than any other variant. Few conformational epitopes were located in the shell and P1 domains, although most were contained in the P2 domain, which, as previously established, is associated with attachment to host factors and antigenicity. We found that positive selection sites for the whole GII.4 genotype existed in the shell and P1 domains, while Den Haag 2006b, New Orleans 2009, and Sydney 2012 variants were under positive selection in the P2 domain. Amino acid substitutions overlapped with putative epitopes or were located around the epitopes in the P2 domain. The effective population sizes of the present strains increased stepwise for Den Haag 2006b, New Orleans 2009, and Sydney 2012 variants. These results suggest that HuNoV GII.4 rapidly evolved in a few decades, created various variants, and altered its evolutionary rate and antigenicity.

Ice-associated norovirus outbreak predominantly caused by GII.17 in Taiwan, 2015

Background

On 5 March 2015, Taiwan Centers for Disease Control was notified of more than 200 students with gastroenteritis at a senior high school during excursion to Kenting. We conducted an outbreak investigation to identify the causative agent and possible vehicle of the pathogen.

Methods

We conducted a retrospective cohort study by using a structured questionnaire to interview all students for consumed food items during their stay at the resort. Students were defined as a gastroenteritis case while having vomiting or diarrhea after the breakfast on 4 March. We inspected the environment to identify possible contamination route. We collected stool or vomitus samples from ill students, food handlers and environmental specimens for bacterial culture for common enteropathogens, reverse transcription polymerase chain reaction (RT-PCR) for norovirus and enzyme-linked immunosorbent assay (ELISA) for rotavirus. Norovirus PCR-positive products were then sequenced and genotyped.

Results

Of 267 students enrolled, 144 (54%) met our case definition. Regression analysis revealed elevated risk associated with iced tea, which was made from tea powder mixed with hot water and self-made ice (risk ratio 1.54, 95% confidence interval 1.22–1.98). Ice used for beverages, water before and after water filter of the ice machine and 16 stool and vomitus samples from ill students were tested positive for norovirus; Multiple genotypes were identified including GI.2, GI.4 and GII.17. GII.17 was the predominant genotype and phylogenetic analyses showed that noroviruses identified in ice, water and human samples were clustered into the same genotypes. Environmental investigation revealed the ice was made by inadequate-filtered and un-boiled water.

Conclusions

We identified the ice made by norovirus-contaminated un-boiled water caused the outbreak and the predominant genotype was GII.17. Adequately filtered or boiled water should be strongly recommended for making ice to avoid possible contamination.