Aims / Objectives: Typhoid fever is a threat to human race and perhaps not much research is conducted towards mitigating it menace in Yobe State. A classical epidemic model SIR is deployed into GLEaMviz software to simulate typhoid spread and spatially analysed the trend. Study Design: Computational modeling and simulation. Place and Duration of Study: Computational Laboratory, Department of Mathematics and Statistics Yobe State University, Damaturu, Nigeria. The duration of the study is between May 2021 and December 2021. Methodology: SIR epidemic model was used to simulate typhoid spread and time series model was explored to investigate the disease trend. Results: The model predicts mild seasonal fluctuations in the trend which coincides with rainy season. The agents causing the disease transmission is possibly being transported through flowing water. Conclusion: A mild seasonality is present in the fluctuations of the trend of typhoid, hence the pattern shows strong evidence of perennial tendency with likelihood of high cases during rainy season. Further work is needed to validate this findings by using real data.

SARS-CoV-2 is a novel coronavirus responsible for the current COVID-19 pandemic. It is the seventh coronavirus known to infect humans (the previous human coronaviruses are HCoV-OC43, HCoV-229E, HCoV-HKU1, HCoV-NL63, SARS-CoV and MERS-CoV) and the third human coronavirus known to cause severe illness in human after SARS-CoV and MERS-CoV. These three coronaviruses have caused three different severe respiratory diseases outbreaks within the last two decades: SARS in 2002-2003, MERS in 2012 and COVID-19 in 2020. The aim of this review was to summarize information on the genome and structure of SARS-CoV-2. SARS-CoV-2 is an enveloped positive-sense single-stranded RNA virus with a crown-like appearance due to the presence of spike glycoprotein on the envelope. The nonsegmented genome of SARS-CoV-2 of approximately 30kb encodes two large polyproteins, four main structural proteins namely spike, membrane, envelope and nucleocapsid proteins as well as several accessory proteins. Analysis of SARS-CoV-2 genome shows that it is highly related to coronavirus from the bat (96%), pangolin (91%) and SARS-CoV (80%). Variants of SARS-CoV-2 have evolved continuously as a result of genetic mutations and are circulating worldwide. These variants have varying degrees of transmissibility, disease severity, susceptibility to therapeutics and detection by diagnostic tools. Understanding the structure and genome of SARS-CoV-2 is important in the control, management, diagnosis and treatment of COVID-19 as well as vaccine development.

The COVID-19 pandemic is considered the most crucial global health problem of the 21st century and the greatest challenge that affects humans globally. In late December 2019, a new infectious respiratory disease emerged from Wuhan city of Hubei province in China. Since then, it has since spread around the world, thus declared a pandemic on 11th March 2020 by the World Health Organisation. The outbreak of the novel coronavirus has become a clinical threat to the common population and healthcare workers worldwide. The intensity and speed with which it struck were almost unimaginable as it turns out to have infected over 327,793,472 people and caused more than 5,539,108 deaths globally as of the 17th of January 2022. Likewise, in Nigeria, as of 17th of January 2022; 250,929 confirmed cases, 3,103 deaths, and 224,052 recovered had been reported by NCDC, 2022. At the time of writing this review, no approved antiviral chemotherapy is available instead, use of some recommended vaccines by WHO. Therefore, nonpharmaceutical interventions are adopted by the national government as possible preventive measures to mitigate the spread of the virus globally. These measures include total lockdown, wearing of face mask in public, regular handwashing with soap and water, use of alcohol-based hand sanitizers, maintaining social and physical distance and coughing or sneezing into the elbow, and general enlightenment.

Multidrug resistance among Escherichia coli causing urinary tract infections (UTIs) and diarrhea are major public health problem worldwide which cause difficulty in treating the infections caused by Escherichia coli due to the high resistances. The study is aimed to determine the phenotypic and molecular detection of multidrug resistant E. coli isolated from clinical samples of patients attending selected Hospitals in Damaturu, Yobe State-Nigeria. Methods: Two hundred (200) clinical samples were collected aseptically from patient diagnosed with (100 stool samples) and UTI’s (100 urine samples) using sterile universal container. The samples were processed using standard microbiological methods for identification of E. coli. Samples were cultured on MacConkey agar (stool) and Cystine lactose electrolyte deficient agar (urine). The resulting colonies of isolates were further subculture on Eosin methylene blue agar for confirmatory and followed by gram stain, biochemical identification at Microbiology laboratory unit of Yobe State Specialist and Yobe State Teaching Hospital respectively. The antimicrobial susceptibility patterns were determined using Kirby-Bauer disc diffusion techniques and the phenotypic expression of extended spectrum beta-lactamases (ESBLs) were determined using modified double disc synergy test (MDDST) and also the three (3) resistance genes (blaTEM, accC1 and qnrA) were detected using polymerase chain reaction. Results: One hundred and twenty-two (122) isolates were resistant to antibiotics. The highest level of resistance was against amoxicillin (90.2%) while the least resistance was against sparfloxacin (24.3%). Thirty-seven (37) E. coli isolates shows MDR; the highest MDR was (24.3%) while least MDR was (5.4%). The PCR amplification of resistant genes (blaTEM, accC1 and qnrA) were detected on E. coli that shows positive ESBL and the bands were separated using agarose gel electrophoresis. Conclusion: The findings of this study show augmentin, ciprofloxacin and sparfloxacin are the most effective antibiotics against E. coli isolated from patients attending the two hospitals in Damaturu; who are diagnose with UTI and diarrheic infection. The resistant genes include; blaTEM, accC1 and qnrA coding for beta-lactam, aminoglycoside and quinolones were present in E. coli isolated from patients attending selected Hospitals in Yobe State, Nigeria. Keywords: Multidrug resistant, Escherichia coli, extended spectrum beta lactamase, resistance-associated genes, urinary tract infections, diarrheic.