Epidemiology of bacterial Septicemia among children under five in Mbita Subcounty, South Nyanza, Kenya

Background: Septicaemia is a major cause of mortality and morbidity, especially in sub-Saharan Africa leading to complications marked by bodily inflammation referred as sepsis. This is a systemic disease associated with presence of pathogenic microorganisms (viral, parasitic and bacterial) or their toxins in the blood. Bacterial septicaemia is the most fatal and prevalent in hospitalised cases. Globally, 76% of children under five years die due to septicaemia. In East Africa a mortality rate of 40% have been reported. In Kenya, South Nyanza regions have reported higher morbidity and mortality cases among children. We hypothesis that apart from immunosuppressive diseases, septicaemia could contribute significantly to this prevalence in the region. Methods: Blood samples were obtained from 248 children whose guardian consented and a detailed sociodemographic questionnaire was administered. Bacterial isolation and characterization were done using the automated BACTEC 9240 system. Results: The mean age of the participants was 27.9 (SD ±20.7) months. The majority (30.6%) were aged between 1 to 12 months, 50.8% were males, 58.9% had body temperatures above 37.6 OC while only 8.1% were HIV seropositive. The mean white blood cells (WBC) of the participants were 17720.9 (SD 8929.1) cells/ml with 5.2% had leucopenia. A total of 84 of the 248 (33.9%) of the children had septicaemia with the majority (28.6%) caused by Staphylococcus epidermidis followed by Staphylococcus aureus and Escherichia coli each at 13.1%. Bacteria that were reported singly included Salmonella Paratyphi B, Citrobacter freundii, Gemella morbillorum, Klebsiella pneumoniae, Lactococcus lactis cremoris, Pantoea spp, and Pseudomonas putida. In multivariate regression analysis, female gender (OR 0.6; 95% confidence interval (CI) 0.4 to 0.9), co-infection with malaria (OR 2.7; 95% CI 1.1 to 6.7) and gastrointestinal disorders (OR 2.9, 95% CI 1.3 – 7.3) were independently associated with bacterial septicemia infection. Conclusion: Significantly higher proportion of the children in this region are infected with septicaemia. Majority of the cases were caused by Gram positive bacteria. Age and other c-infection contribute significantly to septicaemia infection in this region. Rapid testing and etiological characterisation of children with suspected symptoms of septicaemia is key in this region in order to institute appropriate treatment and management. Keywords: bacterial Septicemia, Epidemiology, Children under five, South Nyanza, Kenya DOI: 10.7176/JNSR/10-10-06 Publication date:May 31st 202

High Prevalence of Multidrug-Resistant Clostridioides difficile Following Extensive Use of Antimicrobials in Hospitalized Patients in Kenya

Introduction: Clostridioides difficile is a neglected pathogen in many African countries as it is generally not regarded as one of the major contributors toward the diarrheal disease burden in the continent. However, several studies have suggested that C. difficile infection (CDI) may be underreported in many African settings. The aim of this study was to determine the prevalence of CDI in hospitalized patients, evaluate antimicrobial exposure, and detect toxin and antimicrobial resistance profiles of the isolated C. difficile strains. Methods: In this cross-sectional study, 333 hospitalized patients with hospital-onset diarrhoea were selected. The stool samples were collected and cultured on cycloserine-cefoxitin egg yolk agar (CCEY). Isolates were presumptively identified by phenotypic characteristics and Gram stain and confirmed by singleplex real-time PCR (qPCR) assays detecting the species-specific tpi gene, toxin A (tcdA) gene, toxin B (tcdB) gene, and the binary toxin (cdtA/cdtB) genes. Confirmed C. difficile isolates were tested against a panel of eight antimicrobials (vancomycin, metronidazole, rifampicin, ciprofloxacin, tetracycline, clindamycin, erythromycin, and ceftriaxone) using E-test strips. Results: C. difficile was detected in 57 (25%) of diarrheal patients over the age of two, 56 (98.2%) of whom received antimicrobials before the diarrheal episode. Amongst the 71 confirmed isolates, 69 (97.1%) harbored at least one toxin gene. More than half of the toxigenic isolates harbored a truncated tcdA gene. All isolates were sensitive to vancomycin, while three isolates (2.1%) were resistant to metronidazole (MIC \u3e32 mg/L). High levels of resistance were observed to rifampicin (65/71, 91.5%), erythromycin (63/71, 88.7%), ciprofloxacin (59/71, 83.1%), clindamycin (57/71, 80.3%), and ceftriaxone (36/71, 50.7.8%). Among the resistant isolates, 61 (85.9%) were multidrug-resistant. Conclusion: Multidrug-resistant C. difficile strains were a significant cause of healthcare facility-onset C. difficile infections in patients with prior antimicrobial exposure in this Kenyan hospital

A Quantitative Approach For Estimating Intravoxel Incoherent Motion (IVIM) Model Parameters In Diffusion Weighted Magnetic Resonance Imaging

Diffusion weighted magnetic resonance imaging (DW-MRI) has found numerous clinical applications like tumor classification, recognizing acute ischemic stroke, etc. Tissue perfusion is traditionally evaluated by monitoring MRI signal changes following the administration of contrast agents. However, if tissue diffusion is modeled as consisting of a vascular compartment and a tissue compartment with relatively lower diffusivity (compared to a vascular compartment), then tissue perfusion information can be obtained using DW-MRI without contrast administration. This model is called intra-voxel incoherent motion (IVIM) model of biologic tissue. Despite its promise, the IVIM model has not gained widespread clinical acceptance for three main reasons: (a) IVIM derived perfusion metrics are noisy and lack precision, (b) the lack of in-vitro models that can mimic wide physiological conditions encountered in-vivo, and (c) the dependency of perfusion related IVIM (pr-IVIM) model parameters on acquisition parameters. In this dissertation, I propose a set of solutions to address these limitations. First, I propose and demonstrate via numerical simulations a new approach - analytical segmented (AS) approach- to improve the robustness of estimation of pr-IVIM model parameters. Second, I demonstrate the design and implementation of an in-vitro phantom model with the flexibility to adjust the pr-IVIM model parameters over a wide range of physiological conditions. Third, I propose and demonstrate an extended AS approach - called AS-T2 method- capable of extracting pr-IVIM model parameters with little sensitivity to acquisition parameters such as echo time (TE) (AS-T2 method), and provides a means to extract the T2 relaxation parameter of the fluid compartment (hitherto not described). Fourth, the accuracy, precision, and bias of my proposed analysis approaches are rigorously evaluated using in-silico and in-vitro models. Finally, preliminary in-vivo results in human brain parenchyma show that pr-IVIM model parameters extracted using the proposed approaches have a lower coefficient of variation than conventional methods and are relatively insensitive to changes in TE. In sum, the algorithmic approaches and the in-vitro phantom model described in this dissertation can be used to standardize results from data acquired across different commercial MRI platforms. More extensive clinical trials are necessary to confirm these findings

Epidemiology and Pathogenesis of Providencia alcalifaciens Infections

Providencia alcalifaciens is a member of the family Enterobacteriaceae that has been commonly implicated as a causative agent of diarrheal infection in humans and animals. Recent outbreaks of P. alcalifaciens in both developing and developed countries have raised public health concerns. Several studies have suggested that P. alcalifaciens can cause diarrhea by invading the intestinal mucosa, although its pathogenicity has not been well established. Often routine laboratory investigations that seek etiological agents of diarrhea do not actively pursue P. alcalifaciens detection. Therefore, routine laboratory diagnosis should be given more attention for better understanding the epidemiology and pathogenicity of P. alcalifaciens

Ten Thousand-Fold Higher than Acceptable Bacterial Loads Detected in Kenyan Hospital Environments: Targeted Approaches to Reduce Contamination Levels

Microbial monitoring of hospital surfaces can help identify target areas for improved infection prevention and control (IPCs). This study aimed to determine the levels and variations in the bacterial contamination of high-touch surfaces in five Kenyan hospitals and identify the contributing modifiable risk factors. A total of 559 high-touch surfaces in four departments identified as high risk of hospital-acquired infections were sampled and examined for bacterial levels of contamination using standard bacteriological culture methods. Bacteria were detected in 536/559 (95.9%) surfaces. The median bacterial load on all sampled surfaces was 6.0 × 104 CFU/cm2 (interquartile range (IQR); 8.0 × 103–1.0 × 106). Only 55/559 (9.8%) of the sampled surfaces had acceptable bacterial loads, <5 CFU/cm². Cleaning practices, such as daily washing of patient sheets, incident rate ratio (IRR) = 0.10 [95% CI: 0.04–0.24], providing hand wash stations, IRR = 0.25 [95% CI: 0.02–0.30], having running water, IRR = 0.19 [95% CI: 0.08–0.47] and soap for handwashing IRR = 0.21 [95% CI: 0.12–0.39] each significantly lowered bacterial loads. Transporting dirty linen in a designated container, IRR = 72.11 [95% CI: 20.22–257.14], increased bacterial loads. The study hospitals can best reduce the bacterial loads by improving waste-handling protocols, cleaning high-touch surfaces five times a day and providing soap at the handwash stations

Study samples

Identification of Pseudomonas water reservoirs in 6 sub locations and a hospital in Kisumu county. 297 samples collected 42 Pseudomonas isolates identified among 42 isolates on Vitek 2. Conducted antimicrobial susceptibility testing for the 42 resultant isolates on Vitek 2.</p

Distribution of OTUs that were classified to the bacterial species level per tick genera.

Distribution of OTUs that were classified to the bacterial species level per tick genera.</p

Map of Sampling Sites, Isiolo County (a) Kwale County (b).

These maps were generated using ArcGIS version 10.2.2 for Desktop (Advanced License) courtesy of Samwel Owaka.</p