In this study, we examined various forms of mathematical models that are relevant for the containment, risk analysis, and features of COVID-19. Greater emphasis was laid on the extension of the Susceptible-Infectious-Recovered (SIR) models for policy relevance in the time of COVID-19. These mathematical models play a significant role in the understanding of COVID-19 transmission mechanisms, structures, and features. Considering that the disease has spread sporadically around the world, causing large scale socioeconomic disruption unwitnessed in contemporary ages since World War II, researchers, stakeholders, government, and the society at large are actively engaged in finding ways to reduce the rate of infection until a cure or vaccination procedure is established. We advanced argument for the various forms of the mathematical model of epidemics and highlighted their relevance in the containment of COVID-19 at the present time. Mathematical models address the need for understanding the transmission dynamics and other significant factors of the disease that would aid policymakers to make accurate decisions and reduce the rate of transmission of the disease.
The study assessed the effect of seasonal variation on enteric bacteria population in water sources of six different communities between April 2017 and March 2018 using conventional microbiological methods. Bacteria belonging to the enteric family were primarily investigated in this study. The bacteriological analyses included total viable bacterial counts and phenotypic characterization. The bacteriological analyses showed that total heterotrophic counts ranged from 1.2 × 104 cfu/ml to 3.0 × 104 cfu/ml and from 1.0 × 104 cfu/ml to 2.0 × 104 cfu/ml during the dry and wet seasons, respectively. One hundred and twenty-two potentially pathogenic species of bacteria representing 10 genera were identified. These included Acinetobacter sp., Enterobacter sp., Escherichia coli, Shigella sp., Salmonella sp., and Proteus sp. Others are Serratia sp., Pseudomonas sp., Yersinia sp., and Klebsiella sp. Results showed that bacteria isolated (10) were higher during the rainy season while Klebsiella sp (24) and Enterobacter sp (30) were the predominant species. It was apparent that water sources investigated in this study were unsafe for domestic use due to the presence of these pathogenic bacteria. So, there is a need for the provision of safe water in these communities to prevent outbreaks of waterborne disease. Key words: microbial, potable water, rural dwellers, seasonal variation
Introduction. The difficulty of managing trash and cleaning up the environment prompted interest in biosurfactants and surface-active proteins made by microbes. The study aims to augment bacterial isolates from agro-industrial wastes targeted for possible mass production of biosurfactants. Methods. Six agro-industrial wastes from Cassava, Palm kernel, and Sawdust from six agro-industrial sites within Ijebu area in Ogun State were collected for standard laboratory analyses in the Biotechnology Unit of the Federal Industrial Institute for Research, Oshodi (FIIRO). Five screening methods; blood hemolysis, lipase activity, blue agar hydrolysis, oil spreading, and emulsification index (EI24) were carried out to confirm biosurfactant production. Isolates with the highest hyper-production were subjected to 16rRNA molecular identification. Results. The study justified efficient biosurfactant production from 4 bacterial isolates out of 26 screened bacterial isolates from hydrocarbon degraders and 29 heterotrophic screened bacterial isolates, making a total of 55 screened bacterial isolates. Screening results reveal the emulsification capacities of identified Pseudomonas putida strain SG1, Acinetobacter baumanii strain MS14413, Bacillus zhangzhouensis strain cdsV18, and Burkholderia cepacia strain 717. Conclusion. Biosurfactant bacteria produced in all agricultural and industrial wastes considered in this study are capable of mass production.
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