Publications by authors named "K L Kotloff"
Poor water, sanitation, and hygiene (WASH) are the primary risks of exposure to enteric viral infection. Our study aimed to describe the role of WASH conditions and practices as risk factors for enteric viral infections in children under 5. Literature on the risk factors associated with all-cause diarrhea masks the taxa-specific drivers of diarrhea from specific pathogens, limiting the application of relevant control strategies.
View Article and Find Full Text PDFPost rotavirus vaccine introduction in Mozambique (September 2015), we documented a decline in rotavirus-associated diarrhoea and genotypes changes in our diarrhoeal surveillance spanning 2008-2021. This study aimed to perform whole-genome sequencing of rotavirus strains from 2009 to 2012 (pre-vaccine) and 2017-2018 (post-vaccine). Rotavirus strains previously detected by conventional PCR as G2P[4], G2P[6], G3P[4], G8P[4], G8P[6], and G9P[6] from children with moderate-to-severe and less-severe diarrhoea and without diarrhoea (healthy community controls) were sequenced using Illumina MiSeq platform and analysed using bioinformatics tools.
View Article and Find Full Text PDFArticle Synopsis
- Serotype 6 is a common cause of moderate to severe diarrhea but remains understudied, prompting research into its genomic and phenotypic characteristics compared to other serotypes.
- Genomic analyses revealed notable similarities among 6 strains across different regions and timeframes, along with the identification of a potential novel virulence factor and unique patterns of antibiotic susceptibility specific to geographic locations.
- Findings suggest that serotype 6 has distinct genetic and phenotypic traits that could enhance vaccine development and diagnostic tools, which is crucial given the rising incidence of shigellosis, particularly in low- and middle-income countries.
Introduction: Malnutrition contributes to 45% of all childhood deaths globally, but these modelled estimates lack direct measurements in countries with high malnutrition and under-5 mortality rates. We investigated malnutrition's role in infant and child deaths in the Child Health and Mortality Prevention Surveillance (CHAMPS) network.
Methods: We analysed CHAMPS data from seven sites (Bangladesh, Ethiopia, Kenya, Mali, Mozambique, Sierra Leone and South Africa) collected between 2016 and 2023.
Article Synopsis
- * A machine learning approach was applied using data from the VIDA and EFGH-Shigella studies in rural Kenya to create predictive models for LGF among children aged 6-35 months, encompassing 65 potential predictors including demographic and health-related factors.
- * The models showed a prevalence of LGF at 16.9% and 22.4% in different cohorts, with the gradient boosting model providing the best prediction accuracy, demonstrating its usefulness in identifying at-risk children for targeted healthcare interventions