RESUMEN
Background: COVID-19 was initially detected in China's Wuhan, the capital of Hubei Province, in December 2019, and has since spread throughout the world, including Ethiopia. Long-term epidemics will overwhelm the capacity of hospitals and the health system as a whole, with dire consequences for the developing world's damaged health systems. Focusing on COVID-19-related activities while continuing to provide essential services such as emergency and essential surgical care is critical not only to maintaining public trust in the health system but also to reducing morbidity and mortality from other illnesses. The goal of this study was to see how COVID-19 affected essential and emergency surgical care in Gedeo and Sidama zone hospitals. Method: ology: A cross-sectional study was carried out in ten (10) hospitals in the Gedeo and Sidama zone. The information was gathered with the help of the world health organization (WHO) situational analysis tool for determining emergency and essential surgical care (EESC) capability. Infrastructure, human resources, interventions, and EESC equipment and supplies were used to assess the hospitals' capacity. Result: 54.3% of the 35 fundamental therapies indicated in the instrument were available before COVID-19 at all sites, while 25.2 percent were available after the COVID-19 pandemic. During the COVID-19 pandemic, there was a sharing of resources for treatment centers, such as a scarcity of oxygen and anesthesia machines, and emergency surgery was postponed. Before admission, the average distance traveled was 58 km. Conclusion: The COVID-19 pandemic, as well as existing disparities in infrastructure, human resources, service provision, and essential equipment and supplies, reveal significant gaps in hospitals' capacity to provide emergency and essential surgical services and effectively address the growing surgical burden of disease and injury in Gedeo and Sidama zone primary, general, and referral hospitals.
RESUMEN
Recent infectious disease outbreaks, such as COVID-19 and Ebola, have highlighted the need for rapid and accurate diagnosis to initiate treatment and curb transmission. Successful diagnostic strategies critically depend on the efficiency of biological sampling and timely analysis. However, current diagnostic techniques are invasive/intrusive and present a severe bottleneck by requiring specialist equipment and trained personnel. Moreover, centralised test facilities are poorly accessible and the requirement to travel may increase disease transmission. Self-administrable, point-of-care (PoC) microneedle diagnostic devices could provide a viable solution to these problems. These miniature needle arrays can detect biomarkers in/from the skin in a minimally invasive manner to provide (near-) real-time diagnosis. Few microneedle devices have been developed specifically for infectious disease diagnosis, though similar technologies are well established in other fields and generally adaptable for infectious disease diagnosis. These include microneedles for biofluid extraction, microneedle sensors and analyte-capturing microneedles, or combinations thereof. Analyte sampling/detection from both blood and dermal interstitial fluid is possible. These technologies are in their early stages of development for infectious disease diagnostics, and there is a vast scope for further development. In this review, we discuss the utility and future outlook of these microneedle technologies in infectious disease diagnosis.
RESUMEN
The current life-threatening and tenacious pandemic eruption of coronavirus disease in 2019 (COVID-19) has posed a significant global hazard concerning high mortality rate, economic meltdown, and everyday life distress. The rapid spread of COVID-19 demands countermeasures to combat this deadly virus. Currently, there are no drugs approved by the FDA to treat COVID-19. Therefore, discovering small molecule therapeutics for treating COVID-19 infection is essential. So far, only a few small molecule inhibitors are reported for coronaviruses. There is a need to expand the small chemical space of coronaviruses inhibitors by adding potent and selective scaffolds with anti-COVID activity. In this context, the huge antiviral chemical space already available can be analysed using cheminformatic and machine learning to unearth new scaffolds. We created three specific datasets called "antiviral dataset" (N = 38,428) "drug-like antiviral dataset" (N = 20,963) and "anticorona dataset" (N = 433) for this purpose. We analyzed the 433 molecules of "anticorona dataset" for their scaffold diversity, physicochemical distributions, principal component analysis, activity cliffs, R-group decomposition, and scaffold mapping. The scaffold diversity of the "anticorona dataset" in terms of Murcko scaffold analysis demonstrates a thorough representation of diverse chemical scaffolds. However, physicochemical descriptor analysis and principal component analysis demonstrated negligible drug-like features for the "anticorona dataset" molecules. The "antiviral dataset" and "drug-like antiviral dataset" showed low scaffold diversity as measured by the Gini coefficient. The hierarchical clustering of the "antiviral dataset" against the "anticorona dataset" demonstrated little molecular similarity. We generated a library of frequent fragments and polypharmacological ligands targeting various essential viral proteins such as main protease, helicase, papain-like protease, and replicase polyprotein 1ab. Further structural and chemical features of the "anticorona dataset" were compared with SARS-CoV-2 repurposed drugs, FDA-approved drugs, natural products, and drugs currently in clinical trials. Using machine learning tool DCA (DMax Chemistry Assistant), we converted the "anticorona dataset" into an elegant hypothesis with significant functional biological relevance. Machine learning analysis uncovered that FDA approved drugs, Tizanidine HCl, Cefazolin, Raltegravir, Azilsartan, Acalabrutinib, Luliconazole, Sitagliptin, Meloxicam (Mobic), Succinyl sulfathiazole, Fluconazole, and Pranlukast could be repurposed as effective drugs for COVID-19. Fragment-based scaffold analysis and R-group decomposition uncovered pyrrolidine and the indole molecular scaffolds as the potent fragments for designing and synthesizing the novel drug-like molecules for targeting SARS-CoV-2. This comprehensive and systematic assessment of small-molecule viral therapeutics' entire chemical space realised critical insights to potentially privileged scaffolds that could aid in enrichment and rapid discovery of efficacious antiviral drugs for COVID-19.