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BackgroundHuman rhinovirus (HRV) is the most common cause of the common cold but may also lead to more severe respiratory illness in vulnerable populations. The epidemiology and genetic diversity of HRV within a school setting have not been described.ObjectiveTo characterise HRV molecular epidemiology among children attending primary school in a rural location of Kenya.MethodsBetween May 2017 to April 2018, over three school terms, we collected 1859 nasopharyngeal swabs (NPS) from pupils and teachers with symptoms of acute respiratory infection in a public primary school in Kilifi County, coastal Kenya. The samples were tested for HRV using real-time RT-PCR. HRV positive samples were sequenced in the VP4/VP2 coding region for species and genotype classification.ResultsA total of 307 NPS (16.4%) from 164 individuals were HRV positive, and 253 (82.4%) were successfully sequenced. The proportion of HRV in the lower primary classes was higher (19.8%) than upper primary classes (12.2%), p-value ConclusionHRV was frequently detected among school-going children with mild ARI symptoms, and particularly in the younger age groups (Summary pointsWe describe the molecular epidemiology of human rhinovirus (HRV) within a school setting over one-year in rural coastal Kenya. A high diversity of HRV infections was observed across all classes with evidence of introduction and transmission of 47 different genotypes.

Background Human rhinovirus (HRV) is the most common cause of the common cold but may also lead to more severe respiratory illness in vulnerable populations. The epidemiology and genetic diversity of HRV within a school setting have not been previously described. The objective of this study was to characterize HRV molecular epidemiology in a primary school in a rural location of Kenya. Methods Between May 2017 and April 2018, over 3 school terms, we collected 1859 nasopharyngeal swabs (NPS) from pupils and teachers with symptoms of acute respiratory infection in a public primary school in Kilifi County, coastal Kenya. The samples were tested for HRV using real-time reverse transcription polymerase chain reaction. HRV-positive samples were sequenced in the VP4/VP2 coding region for species and genotype classification. Results A total of 307 NPS (16.4%) from 164 individuals were HRV positive, and 253 (82.4%) were successfully sequenced. The proportion of HRV in the lower primary classes was higher (19.8%) than upper primary classes (12.2%; P < .001). HRV-A was the most common species (134/253; 53.0%), followed by HRV-C (73/253; 28.9%) and HRV-B (46/253; 18.2%). Phylogenetic analysis identified 47 HRV genotypes. The most common genotypes were A2 and B70. Numerous (up to 22 in 1 school term) genotypes circulated simultaneously, there was no individual re-infection with the same genotype, and no genotype was detected in all 3 school terms. Conclusions HRV was frequently detected among school-going children with mild acute respiratory illness symptoms, particularly in the younger age groups (

Background Kenya introduced the monovalent G1P [8] Rotarix® vaccine into the infant immunization schedule in July 2014. We examined trends in rotavirus group A (RVA) genotype distribution pre- (January 2010–June 2014) and post- (July 2014–December 2018) RVA vaccine introduction. Methods Stool samples were collected from children aged Results We genotyped 614 samples in pre-vaccine and 261 in post-vaccine introduction periods. During the pre-vaccine introduction period, the most frequent RVA genotypes were G1P [8] (45.8%), G8P [4] (15.8%), G9P [8] (13.2%), G2P [4] (7.0%) and G3P [6] (3.1%). In the post-vaccine introduction period, the most frequent genotypes were G1P [8] (52.1%), G2P [4] (20.7%) and G3P [8] (16.1%). Predominant genotypes varied by year and site in both pre and post-vaccine periods. Temporal genotype patterns showed an increase in prevalence of vaccine heterotypic genotypes, such as the commonly DS-1-like G2P [4] (7.0 to 20.7%, P P P P Conclusion Genotype prevalence varied from before to after vaccine introduction. Such observations emphasize the need for long-term surveillance to monitor vaccine impact. These changes may represent natural secular variation or possible immuno-epidemiological changes arising from the introduction of the vaccine. Full genome sequencing could provide insights into post-vaccine evolutionary pressures and antigenic diversity.

Laboratory diagnosis plays a critical role in the containment of a pandemic. Strong laboratory quality management systems (QMS) are essential for laboratory diagnostic services. However, low laboratory capacities in resource-limited countries has made the maintenance of laboratory quality assurance, especially during a pandemic, a daunting task. In this paper, we describe our experience of how we went about providing diagnostic testing services for SARS-CoV-2 through laboratory reorganization, redefining of the laboratory workflow, and training and development of COVID-19 documented procedures, all while maintaining the quality assurance processes during the COVID-19 pandemic at the Kenya Medical Research Institute (KEMRI) Wellcome Trust Research Programme (KWTRP) laboratory. The KWTRP laboratory managed to respond to the COVID-19 outbreak in Kenya by providing diagnostic testing for the coastal region of the country, while maintaining its research standard quality assurance processes. A COVID-19 team comprising of seven sub-teams with assigned specific responsibilities and an organizational chart with established reporting lines were developed. Additionally, a total of four training sessions were conducted for county Rapid Response Teams (RRTs) and laboratory personnel. A total of 11 documented procedures were developed to support the COVID-19 testing processes, with three for the pre-analytical phases, seven for the analytical phase, and one for the post-analytical phase. With the workflow re-organization, the development of appropriate standard operating procedures, and training, research laboratories can effectively respond to pandemic outbreaks while maintaining research standard QMS procedures.

RationalePneumonia is a leading cause of mortality in infants and young children. The mechanisms that lead to mortality in these children are poorly understood. Studies of the cellular immunology of the infant airway have traditionally been hindered by the limited sample volumes available from the young, frail children who are admitted to hospital with pneumonia. This is further compounded by the relatively low frequencies of certain immune cell phenotypes that are thought to be critical to the clinical outcome of pneumonia. To address this, we developed a novel in-silico deconvolution method for inferring the frequencies of immune cell phenotypes in the airway of children with different survival outcomes using proteomic data.MethodsUsing high-resolution mass spectrometry, we identified > 1,000 proteins expressed in the airways of children who were admitted to hospital with clinical pneumonia. 61 of these children were discharged from hospital and survived for more than 365 days after discharge, while 19 died during admission. We used machine learning by random forest to derive protein features that could be used to deconvolve immune cell phenotypes in paediatric airway samples. We applied these phenotype-specific signatures to identify airway-resident immune cell phenotypes that were differentially enriched by survival status and validated the findings using a large retrospective pneumonia cohort.Main ResultsWe identified immune-cell phenotype classification features for 33 immune cell types. Eosinophil-associated features were significantly elevated in airway samples obtained from pneumonia survivors and were downregulated in children who subsequently died. To confirm these results, we analyzed clinical parameters from >10,000 children who had been admitted with pneumonia in the previous 10 years. The results of this retrospective analysis mirrored airway deconvolution data and showed that survivors had significantly elevated eosinophils at admission compared to fatal pneumonia.ConclusionsUsing a proteomics bioinformatics approach, we identify airway eosinophils as a critical factor for pneumonia survival in infants and young children.

RSV infection is typically associated with secondary bacterial infection. We hypothesise that the local airway immune response to RSV has incidental antibacterial effects. Using coordinated proteomics and metagenomics analysis we simultaneously analysed the microbiota and proteomes of the upper airway and determined direct antibacterial activity in airway secretions of RSV-infected children. Here, we report that the airway abundance of Streptococcus was higher in samples collected at the time of RSV infection compared with samples collected one month later. RSV infection is associated with neutrophil influx into the airway and degranulation and is marked by overexpression of proteins with known antibacterial activity including BPI, EPX, MPO and AZU1. Airway secretions of children infected with RSV, have significantly greater antibacterial activity compared to RSV-negative controls. This RSV-associated, neutrophil-mediated antibacterial response in the airway appears to act as a regulatory mechanism that modulates bacterial growth in the airways of RSV-infected children.

RSV infection is typically associated with secondary bacterial infection. We hypothesise that the local airway immune response to RSV has incidental antibacterial effects. Using coordinated proteomics and metagenomics analysis we simultaneously analysed the microbiota and proteomes of the upper airway and determined direct antibacterial activity in airway secretions of RSV-infected children. Here, we report that the airway abundance of Streptococcus was higher in samples collected at the time of RSV infection compared with samples collected one month later. RSV infection is associated with neutrophil influx into the airway and degranulation and is marked by overexpression of proteins with known antibacterial activity including BPI, EPX, MPO and AZU1. Airway secretions of children infected with RSV, have significantly greater antibacterial activity compared to RSV-negative controls. This RSV-associated, neutrophil-mediated antibacterial response in the airway appears to act as a regulatory mechanism that modulates bacterial growth in the airways of RSV-infected children., Respiratory syncytial virus (RSV) can trigger secondary airway bacterial infections. Here, by proteomics and metagenomics analyses of samples from Kenyan children, the authors report that RSV associates with Streptococcus burden and a local upper airway response with direct antibacterial properties.

BackgroundDespite the considerable progress that has been achieved in the development of vaccines, infectious diseases continue to be the major cause of morbidity and mortality in developing countries. The first year of life remains the time of greatest risk with more than half of all deaths caused by infectious diseases in children under the age of five years occurring during this period. For most infections, antibodies are the strongest immune correlate of protective immunity and characterizing the breadth of the antibody repertoire against infectious diseases in early life is key to profiling individual disease risk.MethodsIn order to comprehensively profile the antibody repertoire against infectious diseases in early life, we developed a synthetic peptide-based microarray to simultaneously measure antibodies against forty one common infectious diseases. 82 empirically-validated linear B-cell epitopes were selected from the Immune Epitope Database (IEBD), expressed as synthetic peptides and printed onto microarray glass slides (microarray chip). The chip was used to simultaneously measure antigen-specific IgG and IgA in serum and mucosal samples from thirty eight infants and young children presenting to hospital with different illnesses. We also used the data from the microarray to estimate antibody decay kinetics for the five most frequently detected antigens during the first year of life.ResultsA synthetic peptide microarray to measure antibodies against forty one infectious diseases was successfully developed. Although the combination of antigens that were recognized were different for each child, antigens derived from Epstein-Barr virus, poliovirus,Streptococcus pneumoniae, plasmodium falciparum and varicella zoster were recognized by most study participants. While the combination of antigens recognized in serum was generally similar as those recognized in mucosal samples, antibodies to antigens such as herpesvirus, rubella and echinococcus were more predominant in either serum or mucosal samples. With the exception of the pneumococcus, we observed a progressive decline in serum IgG specific to all the infections above in the first six months of life. Pneumococcal IgG in serum exhibited a continuous rise in the first six months of life.ConclusionsWe successfully developed a synthetic peptide microarray and used it to profile the diversity of systemic and mucosal antibody against multiple infectious diseases in children. The data from the slide provide a snapshot overview of the breadth and kinetics of infectious disease antibodies early in life and opens the opportunity for conducting in-depth multi, multi-target serological studies of infectious diseases in future.

Background: Human rhinovirus (HRV) is the predominant cause of upper respiratory tract infections, resulting in a significant public health burden. The virus circulates as many different types (~160), each generating strong homologous, but weak heterotypic, immunity. The influence of these features on transmission patterns of HRV in the community is understudied. Methods: Nasopharyngeal swabs were collected from patients with symptoms of acute respiratory infection (ARI) at nine out-patient facilities across a Health and Demographic Surveillance System between December 2015 and November 2016. HRV was diagnosed by real-time RT-PCR, and the VP4/VP2 genomic region of the positive samples sequenced. Phylogenetic analysis was used to determine the HRV types. Classification models and G-test statistic were used to investigate HRV type spatial distribution. Demographic characteristics and clinical features of ARI were also compared. Results: Of 5,744 NPS samples collected, HRV was detected in 1057 (18.4%), of which 817 (77.3%) were successfully sequenced. HRV species A, B and C were identified in 360 (44.1%), 67 (8.2%) and 390 (47.7%) samples, respectively. In total, 87 types were determined: 39, 10 and 38 occurred within species A, B and C, respectively. HRV types presented heterogeneous temporal patterns of persistence. Spatially, identical types occurred over a wide distance at similar times, but there was statistically significant evidence for clustering of types between health facilities in close proximity or linked by major road networks. Conclusion: This study records a high prevalence of HRV in out-patient presentations exhibiting high type diversity. Patterns of occurrence suggest frequent and independent community invasion of different types. Temporal differences of persistence between types may reflect variation in type-specific population immunity. Spatial patterns suggest either rapid spread or multiple invasions of the same type, but evidence of similar types amongst close health facilities, or along road systems, indicate type partitioning structured by local spread.