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We investigate the effect of noise in an epidemic system. We have studied dynamics and complexity for both the deterministic and its noise-induced model. We have verified the stochastic sensitivity under the variation of noise strength and changing the initial conditions of the noise-induced system. It confirms that noise can make significant perturbation in the stochastic sensitivity. To quantify the dynamics, phase space analysis is done under both noisy and noise free conditions. The transition between regular and chaotic dynamics has been examined by test. Corresponding complexity analysis is also done using the weighted recurrence entropy method. Numerical results confirm the chaotic dynamics in the noise-induced epidemic system within a larger region of parameters compared to the same in its noise free part.
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http://dx.doi.org/10.1140/epjs/s11734-022-00658-8 | DOI Listing |
BMC Glob Public Health
September 2025
Kenya Medical Research Institute (KEMRI) - Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya.
Background: Between November 2023 and March 2024, coastal Kenya experienced another wave of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections detected through our continued genomic surveillance. Herein, we report the clinical and genomic epidemiology of SARS-CoV-2 infections from 179 individuals (a total of 185 positive samples) residing in the Kilifi Health and Demographic Surveillance System (KHDSS) area (~ 900 km).
Methods: We analyzed genetic, clinical, and epidemiological data from SARS-CoV-2 positive cases across pediatric inpatient, health facility outpatient, and homestead community surveillance platforms.
Genome Biol
September 2025
Department of Evolutionary Genetics, Max-Planck Institute for Evolutionary Biology, Plön, Germany.
Background: Most RNA-seq datasets harbor genes with extreme expression levels in some samples. Such extreme outliers are usually treated as technical errors and are removed from the data before further statistical analysis. Here we focus on the patterns of such outlier gene expression to investigate whether they provide insights into the underlying biology.
View Article and Find Full Text PDFNutr J
September 2025
Department of Life Sciences, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, 412 96, Sweden.
Background: Avenanthramides (AVAs) and Avenacosides (AVEs) are unique to oats (Avena Sativa) and may serve as biomarkers of oat intake. However, information regarding their validity as food intake biomarkers is missing. We aimed to investigate critical validation parameters such as half-lives, dose-response, matrix effects, relative bioavailability under single dose, and in relation to the abundance of Feacalibacterium prausnitzii, and under repeated dosing, to understand the potential applications of AVAs and AVEs as biomarkers of oat intake.
View Article and Find Full Text PDFInfect Dis Poverty
September 2025
Faculty of Medicine and Pharmaceutical Sciences, University of Douala, Douala, Cameroon.
Background: Little is documented on key community-based One Health (OH) approach implementation, pro-activeness and effectiveness of interactions and strategies against Mpox outbreak public health emergency in international concern (PHEIC) in various African countries in order to stamp out the persisting Mpox outbreak threat and burden. Prioritizing critical community-based interventions and lessons learned from previous COVID-19, Mpox, Ebola, COVID-19, Rift Valley Fever and Marburg virus outbreaks revealed critical shortcomings in funding, surveillance, and community engagement that plague public health initiatives across the continent. The article provides critical insights and benefits of community-based One Health approaches implementation against Mpox outbreak management in Africa.
View Article and Find Full Text PDFGenome Biol
September 2025
Center for Genomic Medicine, Cardiovascular Research Center, , Massachusetts General Hospital Simches Research Center, 185 Cambridge Street, CPZN 5.238,, Boston, MA, 02114, USA.
Background: Rare genetic variation provided by whole genome sequence datasets has been relatively less explored for its contributions to human traits. Meta-analysis of sequencing data offers advantages by integrating larger sample sizes from diverse cohorts, thereby increasing the likelihood of discovering novel insights into complex traits. Furthermore, emerging methods in genome-wide rare variant association testing further improve power and interpretability.
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