A Novel Coronavirus and a Broad Range of Viruses in Kenyan Cave Bats.

BACKGROUND AND METHODS: To investigate virus diversity in hot zones of probable pathogen spillover, 54 oral-fecal swabs were processed from five bat species collected from three cave systems in Kenya, using metagenome sequencing. RESULTS: Viruses belonging to the Astroviridae, Circoviridae, Coronaviridae, Dicistroviridae, Herpesviridae and Retroviridae were detected, with unclassified viruses. Retroviral sequences were prevalent; 74.1% of all samples were positive, with distinct correlations between virus, site and host bat species. Detected retroviruses comprised Myotis myotis, Myotis ricketti, Myotis daubentonii and Galidia endogenous retroviruses, murine leukemia virus-related virus and Rhinolophus ferrumequinum retrovirus (RFRV). A near-complete genome of a local RFRV strain with identical genome organization and 2.8% nucleotide divergence from the prototype isolate was characterized. Bat coronavirus sequences were detected with a prevalence of 24.1%, where analyses on the ORF1ab region revealed a novel alphacoronavirus lineage. Astrovirus sequences were detected in 25.9%of all samples, with considerable diversity. In 9.2% of the samples, other viruses including Actinidia yellowing virus 2, bat betaherpesvirus, Bole tick virus 4, Cyclovirus and Rhopalosiphum padi virus were identified. CONCLUSIONS: Further monitoring of bats across Kenya is essential to facilitate early recognition of possibly emergent zoonotic viruses.

Capacity indicators for disaster preparedness in hospitals within Nairobi County, Kenya.

The goal of this study was to assess hospital capacity for disaster preparedness within Nairobi County. This information would be valuable to institutional strategists to resolve weaknesses and reinforce strengths in hospital capacity hence ensure efficient and effective service delivery during disasters. Analytical cross-sectional research design was used. Indicator variables for capacity were hospital equipment, hospital infrastructure, surrounding hospital environment, training, drills, staff knowledge and staff capabilities. Thirty two hospitals were studied of which nine of them were public hospitals. Data analysis was done using SPSS and presented in the form of frequency tables at p < 0.05. Study results indicated that hospital capacity to disaster preparedness in Nairobi County existed in 22 (68.88%) hospitals, in 6 (64.95%) public hospitals and 16 (69.64%) private hospitals. The difference in capacity between public and private hospitals within the County was less than 5%. This showed that both public and private hospitals were relatively at par, with regard to the capacity to handle disaster cases. Study findings also revealed that the surrounding hospital environment was the most highly rated indicator while inter hospital training and drills were the least rated. Although existent in hospitals within Nairobi County, for maximum hospital capacity and disaster preparedness within Nairobi County to be achieved, the existent gap in inter hospital training and inter hospital drills, both of which fall under the finance health systems pillar, required addressing.