THE POTALA PALACE REOPENS

Visitors head for the Potala Palace in Lhasa, capital city of Tibet Autonomous Region in southwest China, on June 3, the first day of its reopening.The number of visitors per day is restricted, and advance online reservation is required. The 1,300-year-old palace had been closed since January 27 due to the novel coronavirus lockdown.

Sichuan Tourism Reopens

A tourist snaps a picture of the Sanxingdui Museum, situated near an archaeological site dating back more than 5,000 years in Sichuan Province.

Breast Imaging Experiences at Academic Medical Centers during COVID-19: Restructuring, Reopening, and Preparing for Possible Resurgence

Severe acute respiratory syndrome coronavirus 2 has thoroughly reshaped the medical landscape. Much has been written and discussed of the adaptations required by this pandemic, particularly in the realm of elective medical care. While some areas of the country have, in recent weeks, seen a plateau or even a decrease in coronavirus 2019 case-burden, others remain face-to-face with significant ongoing morbidity and mortality. Furthermore, given eased restrictions across numerous states and municipalities, a widespread resurgence of the disease is not precluded. To that end, we have attempted to summarize experiences and best practices in the handling of breast imaging against the backdrop of the novel coronavirus, and we consider future directions.

COVID-19 Times: Impact on Information Generation and Data Sharing

At the beginning of 2020, human activities were interrupted by a new virus, identified as SARS-CoV-2, which causes COVID-19 disease. The scientific area was no exception: for a certain period, researchers around the world were forced to leave their laboratories and work remotely. There was a global necessity for finding alternatives focused on generating knowledge and publishing data, so repositories of scientific information, such as databases, represented strong support. In the specific case of life sciences, different strategies allowed rapid compilation of data and its sharing worldwide. Therefore, in this work, the impact of the SARS-CoV-2 pandemic on the amount of peer-reviewed and published papers during COVID-19 times was analyzed along with the role of databases. Our results pointed out that an increase in the number of papers belonging to different knowledge fields took place, with the medical field being the most significant. On the other hand, the complete genome of the new virus was sequenced, and repositories were created with sufficient data for monitoring, preventing, and controlling its dissemination. This was the case for the generation of vaccines in addition to potential candidates for drugs against COVID-19. However, although in 2021, vaccines allowed us to gradually return to our activities, databases and the generation of other repositories remain a key point for facing new strains and adapting to a new reality. Finally, this paper discusses joint efforts to tackle the obstacles of the pandemic, not only from a medical but also from the point of view regarding the fight against misinformation.

Social distancing and testing as optimal strategies against the spread of COVID-19 in the Rio Grande Valley of Texas

At the beginning of August 2020,the Rio Grande Valley(RGV)of Texas experienced a rapid increase of coronavirus disease 2019(abbreviated as COVID-19)cases and deaths.This study aims to determine the optimal levels of effective social distancing and testing to slow the virus spread at the outset of the pandemic.We use an age-stratified eight compartment epidemiological model to depict COVID-19 transmission in the community and within households.With a simulated 120-day outbreak period data we obtain a post 180-days period optimal control strategy solution.Our results show that easing social distancing between adults by the end of the 180-day period requires very strict testing a month later and then daily testing rates of 5%followed by isolation of positive cases.Relaxing social distancing rates in adults from 50%to 25%requires both children and seniors to maintain social distancing rates of 50%for nearly the entire period while maintaining maximum testing rates of children and seniors for 150 of the 180 days considered in this model.Children have higher contact rates which leads to transmission based on our model,emphasizing the need for caution when considering school reopenings.

Impact of school reopening on pandemic spread: A case study using an agent-based model for COVID-19

This article examines the impact of partial/full reopening of school/college campuses on the spread of a pandemic using COVID-19 as a case study.The study uses an agent-based simulation model that replicates community spread in an urban region of U.S.A.via daily social mixing of susceptible and infected individuals.Data representing population demographics,SARS-CoV-2 epidemiology,and social interventions guides the model's behavior,which is calibrated and validated using data reported by the government.The model indicates a modest but significant increase(8.15%)in the total number of reported cases in the region for a complete(100%)reopening compared to keeping schools and colleges fully virtual.For partial returns of 75%and 50%,the percent increases in the number of reported cases are shown to be small(2.87%and 1.26%,respectively)and statistically insignificant.The AB model also predicts that relaxing the stringency of the school safety protocol for sanitizing,use of mask,social distancing,testing,and quarantining and thus allowing the school transmission coefficient to double may result in a small increase in the number of reported infected cases(2.14%).Hence for pandemic outbreaks from viruses with similar characteristics as for SARS-CoV-2,keeping the schools and colleges open with a modest campus safety protocol and in-person attendance below a certain threshold may be advisable.

Assessing effects of reopening policies on COVID-19 pandemic in Texas with a data-driven transmission model

While the Coronavirus Disease 2019(COVID-19)pandemic continues to threaten public health and safety,every state has strategically reopened the business in the United States.It is urgent to evaluate the effect of reopening policies on the COVID-19 pandemic to help with the decision-making on the control measures and medical resource allocations.In this study,a novel SEIR model was developed to evaluate the effect of reopening policies based on the real-world reported COVID-19 data in Texas.The earlier reported data before the reopening were used to develop the SEIR model;data after the reopening were used for evaluation.The simulation results show that if continuing the“stay-at-home order”without reopening the business,the COVID-19 pandemic could end in December 2020 in Texas.On the other hand,the pandemic could be controlled similarly as the case of noreopening only if the contact rate was low and additional high magnitude of control measures could be implemented.If the control measures are only slightly enhanced after reopening,it could flatten the curve of the COVID-19 epidemic with reduced numbers of infections and deaths,but it might make the epidemic last longer.Based on the reported data up to July 2020 in Texas,the real-world epidemic pattern is between the cases of the low and high magnitude of control measures with a medium risk of contact rate after reopening.In this case,the pandemic might last until summer 2021 to February 2022 with a total of 4-10 million infected cases and 20,080e58,604 deaths.