BackgroundPresence of microorganisms in the circulating blood whether continuously or intermittently is a threat to every organ in the body. Approximately 200,000 cases of bacteraemia occur annually with mortality rates ranging from 20–50%. Early diagnosis and appropriate treatment of these infections can make the difference between life and death. The aim of the present study was to determine the bacterial flora of the blood stream infections and their antibiotic susceptibility pattern.MethodsA cross sectional study was conducted on 260 adult febrile patients in Jimma University Specialized Hospital from 27 October 2009 to 26 March 2010. The positive blood cultures were examined and the organisms were identified as per standard procedures. Antimicrobial testing was performed for all isolates by disk diffusion techniques, according to Clinical Laboratory Standards Institute guide lines. The data was analyzed using SPSS for windows version 16 and Microsoft Office Excel.ResultsFrom the total of two hundred sixty blood specimens only 23(8.8%) were positive to seven different types of bacteria. The isolated bacteria were: Coagulase negative staphylococci 6(26.1%), S. aureus 5 (21.7%), S. pyogens 3 (13.0%), E. coli 4(17.4%), K. pneumoniae 3(13.0%), Salmonella spp. 1(4.3%), and Citrobacter spp. 1(4.3%). The isolates showed high rates of resistance to most antibiotics tested. The range of resistance for gram positive bacteria were 0% to 85.7%, and for gram negative from 0% to 100%. None of the isolates were resistance to ciprofloxacin and ceftriaxone.ConclusionOur study result showed the presence of invasive bacterial pathogens with high rate of resistance to most commonly used antibiotics used to treat bacterial infections. Therefore, timely investigation of bacterial flora of the blood stream infections and monitoring of their antibiotic resistance pattern plays an important role in reduction of the incidence of blood stream infections.

COVID-19 caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originated in Wuhan (Hubei province, China) during late 2019. It has spread across the globe affecting nearly 21 million people with a toll of 0.75 million deaths and restricting the movement of most of the world population during the past 6 months. COVID-19 became the leading health, economic, and humanitarian challenge of the twenty-first century. In addition to the considerable COVID-19 cases, hospitalizations, and deaths in humans, several cases of SARS-CoV-2 infections in animal hosts (dog, cat, tiger, lion, and mink) have been reported. Thus, the concern of pet owners is increasing. Moreover, the dynamics of the disease requires further explanation, mainly concerning the transmission of the virus from humans to animals and vice versa. Therefore, this study aimed to gather information about the reported cases of COVID-19 transmission in animals through a literary review of works published in scientific journals and perform genomic and phylogenetic analyses of SARS-CoV-2 isolated from animal hosts. Although many instances of transmission of the SARS-CoV-2 have been reported, caution and further studies are necessary to avoid the occurrence of maltreatment in animals, and to achieve a better understanding of the dynamics of the disease in the environment, humans, and animals. Future research in the animal–human interface can help formulate and implement preventive measures to combat the further transmission of COVID-19.

This review was focused on global data analysis and risk factors associated with morbidity and mortality of coronavirus disease 2019 from different countries, including Bangladesh, Brazil, China, Central Eastern Europe, Egypt, India, Iran, Pakistan, and South Asia, Africa, Turkey and UAE. Male showed higher confirmed and death cases compared to females in most of the countries. In addition, the case fatality ratio (CFR) for males was higher than for females. This gender variation in COVID-19 cases may be due to males' cultural activities, but similar variations in the number of COVID-19 affected males and females globally. Variations in the immune system can illustrate this divergent risk comparatively higher in males than females. The female immune system may have an edge to detect pathogens slightly earlier. In addition, women show comparatively higher innate and adaptive immune responses than men, which might be explained by the high density of immune-related genes in the X chromosome. Furthermore, SARS-CoV-2 viruses use angiotensin-converting enzyme 2 (ACE2) to enter the host cell, and men contain higher ACE2 than females. Therefore, males may be more vulnerable to COVID-19 than females. In addition, smoking habit also makes men susceptible to COVID-19. Considering the age-wise distribution, children and older adults were less infected than other age groups and the death rate. On the contrary, more death in the older group may be associated with less immune system function. In addition, most of these group have comorbidities like diabetes, high pressure, low lungs and kidney function, and other chronic diseases. Due to the substantial economic losses and the numerous infected people and deaths, research examining the features of the COVID-19 epidemic is essential to gain insight into mitigating its impact in the future and preparedness for any future epidemics.

Context: In the healthcare system, Artificial Intelligence (AI) is emerging as a productive tool. There are instances where AI has done marvels in the diagnosis of various health conditions and the interpretation of complex medical disorders. Although AI is far from human intelligence, it can be used as an effective tool to study the SARS-CoV-2 and its capabilities, virulence, and genome. The progress of the pandemic can be tracked, and the patients can be monitored, thereby speeding up the research for the treatment of COVID-19. In this review article, we highlighted the importance of AI and Machine learning (ML) techniques that can speed up the path to the discovery of a possible cure for COVID-19. We also deal with the interactions between viromics and AI, which can hopefully find a solution to this pandemic. Evidence Acquisition: A review of different articles was conducted using the following databases: MEDLINE/PubMed, SCOPUS, Web of Science, ScienceDirect, and Google Scholar for recent studies regarding the use of AI, seeking the spread of different infectious diseases using relevant MeSH subheadings. Results: After a thorough screening of different articles, 30 articles were considered, and key information was obtained from them. Finally, the scope was broadened to obtain more information. Our findings indicated that AI/ML is a promising approach to drug development. Conclusions:The field of AI has enormous potential to predict the changes that may take place in the environment. If this technology is applied to situations of a pandemic such as COVID-19, breakthroughs could potentially pave the way for new vaccines and antiviral drugs.

Infectious threats to humans are continuously emerging. The 2022 worldwide monkeypox outbreak is the latest of these threats with the virus rapidly spreading to 106 countries by the end of September 2022. The burden of the ongoing monkeypox outbreak is manifested by 68,000 cumulative confirmed cases and 26 deaths. Although monkeypox is usually a self-limited disease, patients can suffer from extremely painful skin lesions and complications can occur with reported mortalities. The antigenic similarity between the smallpox virus (variola virus) and monkeypox virus can be utilized to prevent monkeypox using smallpox vaccines; treatment is also based on antivirals initially designed to treat smallpox. However, further studies are needed to fully decipher the immune response to monkeypox virus and the immune evasion mechanisms. In this review we provide an up-to-date discussion of the current state of knowledge regarding monkeypox virus with a special focus on innate immune response, immune evasion mechanisms and vaccination against the virus.