The global response: How cities and provinces around the globe tackled COVID-19 outbreaks in 2021—Authors' reply

Third, regarding the inclusion of RT-PCR and RATs in the laboratory tests, as mentioned in the text (page 9 of manuscript), "All cities/provinces except Tokyo (Table 5), relied on using mass testing strategies comprising both rapid antigen tests and standard RT-PCRs.” The number of laboratory tests was gathered from official websites of relevant national reporting authorities. As mentioned in the footnotes of the table, the WHO "had previously suggested a positivity rate of around 3-12% as a general benchmark of adequate testing, along with recommending that test positivity should remain at 5% or lower for 14 days before regions reopen." The point raised by the Ngo et al., has already been addressed in the manuscript.

SARS-CoV-2 Omicron and its current known unknowns: A narrative review.

The emergence of the SARS-CoV-2 Omicron variant (B.1.1.529) has created great global distress. This variant of concern shows multiple sublineages, importantly B.1.1.529.1 (BA.1), BA.1 + R346K (BA.1.1), and B.1.1.529.2 (BA.2), each with unique properties. However, little is known about this new variant, specifically its sub-variants. A narrative review was conducted to summarise the latest findings on transmissibility, clinical manifestations, diagnosis, and efficacy of current vaccines and treatments. Omicron has shown two times higher transmission rates than Delta and above ten times more infectious than other variants over a similar period. With more than 30 mutations in the spike protein's receptor-binding domain, there is reduced detection by conventional RT-PCR and rapid antigen tests. Moreover, the two-dose vaccine effectiveness against Delta and Omicron variants was found to be approximately 21%, suggesting an urgent need for a booster dose to prevent the possibility of breakthrough infections. However, the current vaccines remain highly efficacious against severe disease, hospitalisation, and mortality. Japanese preliminary lab data elucidated that the Omicron sublineage BA.2 shows a higher illness severity than BA.1. To date, the clinical management of Omicron remains unchanged, except for monoclonal antibodies. Thus far, only Bebtelovimab could sufficiently treat all three sub-variants of Omicron. Further studies are warranted to understand the complexity of Omicron and its sub-variants. Such research is necessary to improve the management and prevention of Omicron infection.

The global response: How cities and provinces around the globe tackled Covid-19 outbreaks in 2021.

Background: Tackling the spread of COVID-19 remains a crucial part of ending the pandemic. Its highly contagious nature and constant evolution coupled with a relative lack of immunity make the virus difficult to control. For this, various strategies have been proposed and adopted including limiting contact, social isolation, vaccination, contact tracing, etc. However, given the heterogeneity in the enforcement of these strategies and constant fluctuations in the strictness levels of these strategies, it becomes challenging to assess the true impact of these strategies in controlling the spread of COVID-19. Methods: In the present study, we evaluated various transmission control measures that were imposed in 10 global urban cities and provinces in 2021- Bangkok, Gauteng, Ho Chi Minh City, Jakarta, London, Manila City, New Delhi, New York City, Singapore, and Tokyo. Findings: Based on our analysis, we herein propose the population-level Swiss cheese model for the failures and pitfalls in various strategies that each of these cities and provinces had. Furthermore, whilst all the evaluated cities and provinces took a different personalized approach to managing the pandemic, what remained common was dynamic enforcement and monitoring of breaches of each barrier of protection. The measures taken to reinforce the barriers were adjusted continuously based on the evolving epidemiological situation. Interpretation: How an individual city or province handled the pandemic profoundly affected and determined how the entire country handled the pandemic since the chain of transmission needs to be broken at the very grassroot level to achieve nationwide control. Funding: The present study did not receive any external funding.

Machine Learning and LPWAN Based Internet of Things Applications in Healthcare Sector during COVID-19 Pandemic

Low power wide area networks (LPWAN) are comprised of small devices having restricted processing resources and limited energy budget. These devices are connected with each other using communication protocols. Considering their available resources, these devices can be used in a number of different Internet of Things (IoT) applications. Another interesting paradigm is machine learning, which can also be integrated with LPWAN technology to embed intelligence into these IoT applications. These machine learning-based applications combine intelligence with LPWAN and prove to be a useful tool. One such IoT application is in the medical field, where they can be used to provide multiple services. In the scenario of the COVID-19 pandemic, the importance of LPWAN-based medical services has gained particular attention. This article describes various COVID-19-related healthcare services, using the the applications of machine learning and LPWAN in improving the medical domain during the current COVID-19 pandemic. We validate our idea with the help of a case study that describes a way to reduce the spread of any pandemic using LPWAN technology and machine learning. The case study compares k-Nearest Neighbors (KNN) and trust-based algorithms for mitigating the flow of virus spread. The simulation results show the effectiveness of KNN for curtailing the COVID-19 spread.