Molecular epidemiology of human rhinovirus from one-year surveillance within a school setting in rural coastal Kenya

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. Objective To characterise HRV molecular epidemiology in primary school in a rural location of Kenya. Methods Between 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. 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-value &0.001. 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 one school term) genotypes circulated simultaneously, there was no individual re-infection with the same genotype, and no genotype was detected in all three school terms. Conclusion HRV was frequently detected among school-going children with mild ARI symptoms, and particularly in the younger age groups (&5-year-olds). Multiple HRV introductions were observed characterised by the considerable genotype diversity

Methods for the sampling and analysis of marine aerosols: results from the 2008 GEOTRACES aerosol intercalibration experiment

Atmospheric deposition of trace elements and isotopes (TEI) is an important source of trace metals to the open ocean, impacting TEI budgets and distributions, stimulating oceanic primary productivity, and influencing biological community structure and function. Thus, accurate sampling of aerosol TEIs is a vital component of ongoing GEOTRACES cruises, and standardized aerosol TEI sampling and analysis procedures allow the comparison of data from different sites and investigators. Here, we report the results of an aerosol analysis intercalibration study by seventeen laboratories for select GEOTRACES-relevant aerosol species (Al, Fe, Ti, V, Zn, Pb, Hg, NO3-, and SO42-) for samples collected in September 2008. The collection equipment and filter substrates are appropriate for the GEOTRACES program, as evidenced by low blanks and detection limits relative to analyte concentrations. Analysis of bulk aerosol sample replicates were in better agreement when the processing protocol was constrained (+/- 9% RSD or better on replicate analyses by a single lab, n = 7) than when it was not (generally 20% RSD or worse among laboratories using different methodologies), suggesting that the observed variability was mainly due to methodological differences rather than sample heterogeneity. Much greater variability was observed for fractional solubility of aerosol trace elements and major anions, due to differing extraction methods. Accuracy is difficult to establish without an SRM representative of aerosols, and we are developing an SRM for this purpose. Based on these findings, we provide recommendations for the GEOTRACES program to and macro-nutrients to the open ocean (Okin et al. 2011) and is a key component of the international GEOTRACES program (GEOTRACES Planning Group 2006). A priority of the GEOTRACES program is to quantify both major and trace elements (e. g., Al, Fe, Ti, V, Zn, Pb, and Hg) and species such as nitrate and sulfate in marine aerosols. Therefore, marine aerosol samples collected during GEOTRACES cruises must follow sampling protocols that permit the collection and analysis of as many elements and compounds as possible, while meeting the constraints associated with basin-wide oceanographic cruises (e. g., space limitations, high-frequency sampling, etc.)

Surveillance of respiratory viruses in the outpatient setting in rural coastal Kenya : baseline epidemiological observations

Background Endemic and seasonally recurring respiratory viruses are a major cause of disease and death globally. The burden is particularly severe in developing countries. Improved understanding of the source of infection, pathways of spread and persistence in communities would be of benefit in devising intervention strategies. Methods We report epidemiological data obtained through surveillance of respiratory viruses at nine outpatient health facilities within the Kilifi Health and Demographic Surveillance System, Kilifi County, coastal Kenya, between January and December 2016. Nasopharyngeal swabs were collected from individuals of all ages presenting with acute respiratory infection (ARI) symptoms (up to 15 swabs per week per facility) and screened for 15 respiratory viruses using real-time PCR. Paediatric inpatient surveillance at Kilifi County Hospital for respiratory viruses provided comparative data. Results Over the year, 5,647 participants were sampled, of which 3,029 (53.7%) were aged <5 years. At least one target respiratory virus was detected in 2,380 (42.2%) of the samples; the most common being rhinovirus 18.6% (1,050), influenza virus 6.9% (390), coronavirus 6.8% (387), parainfluenza virus 6.6% (371), respiratory syncytial virus (RSV) 3.9% (219) and adenovirus 2.7% (155). Virus detections were higher among <5-year-olds compared to older children and adults (50.3% vs 32.7%, respectively; χ2(1) =177.3, P=0.0001). Frequency of viruses did not differ significantly by facility (χ2(8) =13.38, P=0.072). However, prevalence was significantly higher among inpatients than outpatients in <5-year-olds for RSV (22.1% vs 6.0%; χ2(1) = 159.4, P=0.0001), and adenovirus (12.4% vs 4.4%, χ2(1) =56.6, P=0.0001). Conclusions Respiratory virus infections are common amongst ARI outpatients in this coastal Kenya setting, particularly in young children. Rhinovirus predominance warrants further studies on the health and socio-economic implications. RSV and adenovirus were more commonly associated with severe disease. Further analysis will explore epidemiological transmission patterns with the addition of virus sequence data

Replication Data for: Influenza B virus genomic diversity across a single epidemic season in coastal Kenya

The data used in this analysis arises from a larger study to characterize the transmission pathways of viral respiratory infections in Kilifi County. Two sets of samples were utilized in this study: (1) Data collected from patients presenting in 9 out-patient health facilities within the KHDSS area with symptoms of respiratory infection. The main study was conducted from December 2015 to June 2017. (2) Samples collected from children (under 5 years of age) admitted to the Kilifi County Hospital (KCH) presenting with severe or very severe pneumonia between September 2011 and August 2016. However, this dataset includes samples collected between January 2016 and December 2016 that tested positive for influenza B virus.</p

The Childhood Acute Illness and Nutrition (CHAIN) network nested case-cohort study protocol: a multi-omics approach to understanding mortality among children in sub-Saharan Africa and South Asia.

Introduction: Many acutely ill children in low- and middle-income settings have a high risk of mortality both during and after hospitalisation despite guideline-based care. Understanding the biological mechanisms underpinning mortality may suggest optimal pathways to target for interventions to further reduce mortality. The Childhood Acute Illness and Nutrition (CHAIN) Network ( www.chainnnetwork.org) Nested Case-Cohort Study (CNCC) aims to investigate biological mechanisms leading to inpatient and post-discharge mortality through an integrated multi-omic approach. Methods and analysis; The CNCC comprises a subset of participants from the CHAIN cohort (1278/3101 hospitalised participants, including 350 children who died and 658 survivors, and 270/1140 well community children of similar age and household location) from nine sites in six countries across sub-Saharan Africa and South Asia. Systemic proteome, metabolome, lipidome, lipopolysaccharides, haemoglobin variants, toxins, pathogens, intestinal microbiome and biomarkers of enteropathy will be determined. Computational systems biology analysis will include machine learning and multivariate predictive modelling with stacked generalization approaches accounting for the different characteristics of each biological modality. This systems approach is anticipated to yield mechanistic insights, show interactions and behaviours of the components of biological entities, and help develop interventions to reduce mortality among acutely ill children. Ethics and dissemination. The CHAIN Network cohort and CNCC was approved by institutional review boards of all partner sites. Results will be published in open access, peer reviewed scientific journals and presented to academic and policy stakeholders. Data will be made publicly available, including uploading to recognised omics databases. Trial registration NCT03208725