Predicting hosts based on early SARS-CoV-2 samples and analyzing the 2020 pandemic.

The SARS-CoV-2 pandemic has raised concerns in the identification of the hosts of the virus since the early stages of the outbreak. To address this problem, we proposed a deep learning method, DeepHoF, based on extracting viral genomic features automatically, to predict the host likelihood scores on five host types, including plant, germ, invertebrate, non-human vertebrate and human, for novel viruses. DeepHoF made up for the lack of an accurate tool, reaching a satisfactory AUC of 0.975 in the five-classification, and could make a reliable prediction for the novel viruses without close neighbors in phylogeny. Additionally, to fill the gap in the efficient inference of host species for SARS-CoV-2 using existing tools, we conducted a deep analysis on the host likelihood profile calculated by DeepHoF. Using the isolates sequenced in the earliest stage of the COVID-19 pandemic, we inferred that minks, bats, dogs and cats were potential hosts of SARS-CoV-2, while minks might be one of the most noteworthy hosts. Several genes of SARS-CoV-2 demonstrated their significance in determining the host range. Furthermore, a large-scale genome analysis, based on DeepHoF's computation for the later pandemic in 2020, disclosed the uniformity of host range among SARS-CoV-2 samples and the strong association of SARS-CoV-2 between humans and minks.

Rapid diagnostic testing for antimicrobial stewardship: Utility in Asia Pacific.

Rapid diagnostic testing (RDT) can provide prompt, accurate identification of infectious organisms and be a key component of antimicrobial stewardship (AMS) programs. However, their use is less widespread in Asia Pacific than western countries. Cost can be prohibitive, particularly in less resource-replete settings. A selective approach is required, possibly focusing on the initiation of antimicrobials, for differentiating bacterial versus viral infections and identifying locally relevant tropical diseases. Across Asia Pacific, more data are needed on RDT use within AMS, focusing on the impact on antimicrobial usage, patient morbidity and mortality, and cost effectiveness. Moreover, in the absence of formal guidelines, regional consensus statements to guide clinical practice are warranted. These will provide a regionally relevant definition for RDT; greater consensus on its role in managing infections; advice on implementation and overcoming barriers; and guidance on optimizing human resource capacity. By addressing these issues, the outcomes of AMS programs should improve.

The potential impact of the COVID-19 pandemic on global antimicrobial and biocide resistance: an AMR Insights global perspective.

The COVID-19 pandemic presents a serious public health challenge in all countries. However, repercussions of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections on future global health are still being investigated, including the pandemic's potential effect on the emergence and spread of global antimicrobial resistance (AMR). Critically ill COVID-19 patients may develop severe complications, which may predispose patients to infection with nosocomial bacterial and/or fungal pathogens, requiring the extensive use of antibiotics. However, antibiotics may also be inappropriately used in milder cases of COVID-19 infection. Further, concerns such as increased biocide use, antimicrobial stewardship/infection control, AMR awareness, the need for diagnostics (including rapid and point-of-care diagnostics) and the usefulness of vaccination could all be components shaping the influence of the COVID-19 pandemic. In this publication, the authors present a brief overview of the COVID-19 pandemic and associated issues that could influence the pandemic's effect on global AMR.