Project description:This work examines the impact of various non-pharmaceutical control measures (government and personal) on the population dynamics of the novel coronavirus disease 2019 (COVID-19) in Lagos, Nigeria, using an appropriately formulated mathematical model. Using the available data, since its first reported case on 16 March 2020, we seek to develop a predicative tool for the cumulative number of reported cases and the number of active cases in Lagos; we also estimate the basic reproduction number of the disease outbreak in the aforementioned State in Nigeria. Using numerical simulations, we show the effect of control measures, specifically the common social distancing, use of face mask and case detection (via contact tracing and subsequent testings) on the dynamics of COVID-19. We also provide forecasts for the cumulative number of reported cases and active cases for different levels of the control measures being implemented. Numerical simulations of the model show that if at least 55% of the population comply with the social distancing regulation with about 55% of the population effectively making use of face masks while in public, the disease will eventually die out in the population and that, if we can step up the case detection rate for symptomatic individuals to about 0.8 per day, with about 55% of the population complying with the social distancing regulations, it will lead to a great decrease in the incidence (and prevalence) of COVID-19.

2024-09-02 | BIOMD0000000991 | BioModels

sediment metagenome

Project description:Heavy Metal Pollution Index, Community Structure and Diversity of Mercury-Resistant Bacteria in Sediment of Industrial Effluent Receiving Hydrosphere in Lagos Nigeria

| PRJDB4999 | ENA

Project description:Vibrio spp. and Enterobacteriaceae with ESBL genes from recreational beaches in Lagos, Nigeria

| PRJNA670054 | ENA

Project description:Genome analysis of Vibrio metschnikovii strain MSAJ1-NIMR isolated from Lagos lagoon, Nigeria

| PRJNA1177791 | ENA

Project description:anaerobic treatment of animal wastewater

| PRJNA650545 | ENA

Sewage Protein Information Mining: Discovery of Large Biomolecules as Biomarkers of Population and Industrial Activities.

Project description:Wastewater-based epidemiology has been revealed as a powerful approach for the survey of the population's health and lifestyle. In this context, proteins have been proposed as potential biomarkers that complement the information provided by those used up to now (small exogenous molecules, metabolites, and genomic material). However, few is known about the range of molecular species and dynamics of proteins in wastewater and the information hidden in these protein profiles is still to be uncovered. In previous research, we have described for the first time the proteome of wastewater using polymer probes immersed in wastewater at the entrance of a wastewater treatment plant (WWTP). Here, we studied the protein composition of wastewater from municipalities with diverse population and industrial activities. For this purpose, we collected water samples at the inlet of 10 different WWTPs in Catalonia at three different times of the year and the soluble fraction of this material was then analyzed by Liquid Chromatography High-resolution Tandem Mass Spectrometry using a shotgun proteomics approach. The complete proteomic profiles, the distribution among different organisms, and the semiquantitative analysis of the main constituents are described. Excreta (urine and feces) from humans, and blood and other residues from livestock were identified as the two main protein sources. Significant differences between the proteomes in the soluble phase and the particulate material, respectively dominated by eukaryote and bacterial proteins, were observed. Our findings provide new insights into the characterization of wastewater proteomics that allow proposing specific bioindicators for wastewater-based environmental monitoring, including human and animal population monitoring, most notably, for rodent pest control (immunoglobulins, amylases), and livestock processing industry monitoring (albumins).

2023-07-25 | PXD038781 | Pride

Nitrile-metabolizing Bacteria

Project description:Two nitrile-metabolizing bacteria isolated from two major landfills in Lagos, Nigeria Genome sequencing and assembly

| PRJNA1043449 | ENA

Solid waste leachates

Project description:Metagenomic Analysis Displaying the Diverse Microbial Community of Two Major Waste Disposing Systems in Lagos, Nigeria

| PRJNA849224 | ENA