Isolation and characterization of Escherichia colipathotypes and factors associated with well and boreholes water contamination in Mombasa County

Introduction: Safe water for human consumption is important, but there is a limited supply. Mombasa County has water shortages making residences rely on other sources of water including boreholes and wells. Microbiological evaluation of drinking water is important to reduce exposure to water borne enteric diseases. This cross sectional study aimed at determining the frequency and characterization of Escherichia coli (E. coli) pathotypes from water samples collected from wells and boreholes in Mombasa County. Methods: One hundred and fifty seven (157) water samples were collected from four divisions of the county and a questionnaire administered. The samples were inoculated to double strength MacConkey broth and incubated at 370C for up to 48 hours. Positive results were compared to the 3 tube McCrady MPN table. The E. coli were confirmed by Eijkman's test and antibiotic susceptibility carried out. Using polymerase chain reaction (PCR), the E. coli were characterized to establish pathotypes. Results: One hundred and thirty one (n=131; 83.4%) samples had coliform bacteria with only 79 (60.3%) samples having E. coli. Significant values (<0.05) were noted when coliforms were compared to variables with E. Coli showing no significance when compared to similar variables. E. coli (n = 77; 100%) tested were sensitive to Gentamicin, while all (n = 77; 100%) isolates were resistant to Ampicillin. PCR typed isolates as enteroinvasive E. Coli (EIEC). Conclusion: Findings suggest that coliforms and E. coli are major contaminants of wells and boreholes in Mombasa County. The isolates have a variety of resistant and sensitivity patterns to commonly used antibiotics.Pan African Medical Journal 2016; 2

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Genetic diversity and evolutionary analysis of human respirovirus type 3 strains isolated in Kenya using complete hemagglutinin-neuraminidase (HN) gene.

Human respirovirus type 3 (HRV3) is a leading etiology of lower respiratory tract infections in young children and ranks only second to the human respiratory syncytial virus (HRSV). Despite the public health importance of HRV3, there is limited information about the genetic characteristics and diversity of these viruses in Kenya. To begin to address this gap, we analyzed 35 complete hemagglutinin-neuraminidase (HN) sequences of HRV3 strains isolated in Kenya between 2010 and 2013. Viral RNA was extracted from the isolates, and the entire HN gene amplified by RT-PCR followed by nucleotide sequencing. Phylogenetic analyses of the sequences revealed that all the Kenyan isolates grouped into genetic Cluster C; sub-clusters C1a, C2, and C3a. The majority (54%) of isolates belonged to sub-cluster C3a, followed by C2 (43%) and C1a (2.9%). Sequence analysis revealed high identities between the Kenyan isolates and the HRV3 prototype strain both at the amino acid (96.5-97.9%) and nucleotide (94.3-95.6%) levels. No amino acid variations affecting the catalytic/active sites of the HN glycoprotein were observed among the Kenyan isolates. Selection pressure analyses showed that the HN glycoprotein was evolving under positive selection. Evolutionary analyses revealed that the mean TMRCA for the HN sequence dataset was 1942 (95% HPD: 1928-1957), while the mean evolutionary rate was 4.65x10-4 nucleotide substitutions/site/year (95% HPD: 2.99x10-4 to 6.35x10-4). Overall, our results demonstrate the co-circulation of strains of cluster C HRV3 variants in Kenya during the study period. This is the first study to describe the genetic and molecular evolutionary aspects of HRV3 in Kenya using the complete HN gene