Rapid evolution of SARS-CoV-2 challenges human defenses.

The race between pathogens and their hosts is a major evolutionary driver, where both reshuffle their genomes to overcome and reorganize the defenses for infection, respectively. Evolutionary theory helps formulate predictions on the future evolutionary dynamics of SARS-CoV-2, which can be monitored through unprecedented real-time tracking of SARS-CoV-2 population genomics at the global scale. Here we quantify the accelerating evolution of SARS-CoV-2 by tracking the SARS-CoV-2 mutation globally, with a focus on the Receptor Binding Domain (RBD) of the spike protein determining infection success. We estimate that the > 820 million people that had been infected by October 5, 2021, produced up to 1021 copies of the virus, with 12 new effective RBD variants appearing, on average, daily. Doubling of the number of RBD variants every 89 days, followed by selection of the most infective variants challenges our defenses and calls for a shift to anticipatory, rather than reactive tactics involving collaborative global sequencing and vaccination.

Ten new insights in climate science 2021: a horizon scan

Non-technical summaryWe summarize some of the past year's most important findings within climate change-related research. New research has improved our understanding about the remaining options to achieve the Paris Agreement goals, through overcoming political barriers to carbon pricing, taking into account non-CO2 factors, a well-designed implementation of demand-side and nature-based solutions, resilience building of ecosystems and the recognition that climate change mitigation costs can be justified by benefits to the health of humans and nature alone. We consider new insights about what to expect if we fail to include a new dimension of fire extremes and the prospect of cascading climate tipping elements.Technical summaryA synthesis is made of 10 topics within climate research, where there have been significant advances since January 2020. The insights are based on input from an international open call with broad disciplinary scope. Findings include: (1) the options to still keep global warming below 1.5 °C;(2) the impact of non-CO2 factors in global warming;(3) a new dimension of fire extremes forced by climate change;(4) the increasing pressure on interconnected climate tipping elements;(5) the dimensions of climate justice;(6) political challenges impeding the effectiveness of carbon pricing;(7) demand-side solutions as vehicles of climate mitigation;(8) the potentials and caveats of nature-based solutions;(9) how building resilience of marine ecosystems is possible;and (10) that the costs of climate change mitigation policies can be more than justified by the benefits to the health of humans and nature.Social media summaryHow do we limit global warming to 1.5 °C and why is it crucial? See highlights of latest climate science.

Detection of SARS-CoV-2 variants requires urgent global coordination.

OBJECTIVES: To assess the efforts deployed by different nations and territories in sequencing SARS-CoV-2 isolates, thus enabling detection of variants, known and novel, of concern. METHODS: The sources of over one million full genome sequences of SARS-CoV-2 virus available in the COVID-19 virus Mutation Tracker (CovMT) were analyzed to determine the number of variants in the RBD region of the genome determining infectivity detected in the various nations and territories. RESULTS: The number of detected variants increased as the square root of sequencing effort by nations. Eight nations have contributed 79% of all SARS-CoV-2 isolates that have been sequenced, with two-thirds of all unique variants, adding to 1118 RBD variants, reported by five nations. The median number of sequenced isolates required to detect, on average, one novel RBD variant is 24.05, which is a threshold achieved by 70 nations. CONCLUSIONS: Many developing nations have not contributed any sequences due to lack of capacity. This poses a risk of dangerous virus variants in these under-sampled regions spreading globally before being detected. A collaborative program to sequence SARS-CoV-2 isolates, and other pathogens of concern, is needed to monitor, track, and control the pandemic.

Rise and fall of the global conversation and shifting sentiments during the COVID-19 pandemic

Social media (e.g., Twitter) has been an extremely popular tool for public health surveillance. The novel coronavirus disease 2019 (COVID-19) is the first pandemic experienced by a world connected through the internet. We analyzed 105+ million tweets collected between March 1 and May 15, 2020, and Weibo messages compiled between January 20 and May 15, 2020, covering six languages (English, Spanish, Arabic, French, Italian, and Chinese) and represented an estimated 2.4 billion citizens worldwide. To examine fine-grained emotions during a pandemic, we built machine learning classification models based on deep learning language models to identify emotions in social media conversations about COVID-19, including positive expressions (optimistic, thankful, and empathetic), negative expressions (pessimistic, anxious, sad, annoyed, and denial), and a complicated expression, joking, which has not been explored before. Our analysis indicates a rapid increase and a slow decline in the volume of social media conversations regarding the pandemic in all six languages. The upsurge was triggered by a combination of economic collapse and confinement measures across the regions to which all the six languages belonged except for Chinese, where only the latter drove conversations. Tweets in all analyzed languages conveyed remarkably similar emotional states as the epidemic was elevated to pandemic status, including feelings dominated by a mixture of joking with anxious/pessimistic/annoyed as the volume of conversation surged and shifted to a general increase in positive states (optimistic, thankful, and empathetic), the strongest being expressed in Arabic tweets, as the pandemic came under control.

Assessing the age- and gender-dependence of the severity and case fatality rates of COVID-19 disease in Spain.

Background: The assessment of the severity and case fatality rates of coronavirus disease 2019 (COVID-19) and the determinants of its variation is essential for planning health resources and responding to the pandemic. The interpretation of case fatality rates (CFRs) remains a challenge due to different biases associated with surveillance and reporting. For example, rates may be affected by preferential ascertainment of severe cases and time delay from disease onset to death. Using data from Spain, we demonstrate how some of these biases may be corrected when estimating severity and case fatality rates by age group and gender, and identify issues that may affect the correct interpretation of the results. Methods: Crude CFRs are estimated by dividing the total number of deaths by the total number of confirmed cases. CFRs adjusted for preferential ascertainment of severe cases are obtained by assuming a uniform attack rate in all population groups, and using demography-adjusted under-ascertainment rates. CFRs adjusted for the delay between disease onset and death are estimated by using as denominator the number of cases that could have a clinical outcome by the time rates are calculated. A sensitivity analysis is carried out to compare CFRs obtained using different levels of ascertainment and different distributions for the time from disease onset to death. Results: COVID-19 outcomes are highly influenced by age and gender. Different assumptions yield different CFR values but in all scenarios CFRs are higher in old ages and males. Conclusions: The procedures used to obtain the CFR estimates require strong assumptions and although the interpretation of their magnitude should be treated with caution, the differences observed by age and gender are fundamental underpinnings to inform decision-making.

No Evidence for Temperature-Dependence of the COVID-19 Epidemic.

The pandemic of the COVID-19 extended from China across the north-temperate zone, and more recently to the tropics and southern hemisphere. The hypothesis that COVID-19 spread is temperature-dependent was tested based on data derived from nations across the world and provinces in China. No evidence of a pattern between spread rates and ambient temperature was found, suggesting that the SARS-CoV-2 is unlikely to behave as a seasonal respiratory virus.

Functional Pangenome Analysis Shows Key Features of E Protein Are Preserved in SARS and SARS-CoV-2.

The spread of the novel coronavirus (SARS-CoV-2) has triggered a global emergency, that demands urgent solutions for detection and therapy to prevent escalating health, social, and economic impacts. The spike protein (S) of this virus enables binding to the human receptor ACE2, and hence presents a prime target for vaccines preventing viral entry into host cells. The S proteins from SARS and SARS-CoV-2 are similar, but structural differences in the receptor binding domain (RBD) preclude the use of SARS-specific neutralizing antibodies to inhibit SARS-CoV-2. Here we used comparative pangenomic analysis of all sequenced reference Betacoronaviruses, complemented with functional and structural analyses. This analysis reveals that, among all core gene clusters present in these viruses, the envelope protein E shows a variant cluster shared by SARS and SARS-CoV-2 with two completely-conserved key functional features, namely an ion-channel, and a PDZ-binding motif (PBM). These features play a key role in the activation of the inflammasome causing the acute respiratory distress syndrome, the leading cause of death in SARS and SARS-CoV-2 infections. Together with functional pangenomic analysis, mutation tracking, and previous evidence, on E protein as a determinant of pathogenicity in SARS, we suggest E protein as an alternative therapeutic target to be considered for further studies to reduce complications of SARS-CoV-2 infections in COVID-19.

Comparative infection modeling and control of COVID-19 transmission patterns in China, South Korea, Italy and Iran.

The COVID-19 has become a pandemic. The timing and nature of the COVID-19 pandemic response and control varied among the regions and from one country to the other, and their role in affecting the spread of the disease has been debated. The focus of this work is on the early phase of the disease when control measures can be most effective. We proposed a modified susceptible-exposed-infected-removed model (SEIR) model based on temporal moving windows to quantify COVID-19 transmission patterns and compare the temporal progress of disease spread in six representative regions worldwide: three Chinese regions (Zhejiang, Guangdong and Xinjiang) vs. three countries (South Korea, Italy and Iran). It was found that in the early phase of COVID-19 spread the disease follows a certain empirical law that is common in all regions considered. Simulations of the imposition of strong social distancing measures were used to evaluate the impact that these measures might have had on the duration and severity of COVID-19 outbreaks in the three countries. Measure-dependent transmission rates followed a modified normal distribution (empirical law) in the three Chinese regions. These rates responded quickly to the launch of the 1st-level Response to Major Public Health Emergency in each region, peaking after 1-2 days, reaching their inflection points after 10-19 days, and dropping to zero after 11-18 days since the 1st-level response was launched. By March 29th, the mortality rates were 0.08% (Zhejiang), 0.54% (Guangdong) and 3.95% (Xinjiang). Subsequent modeling simulations were based on the working assumption that similar infection transmission control measures were taken in South Korea as in Zhejiang on February 25th, in Italy as in Guangdong on February 25th, and in Iran as in Xinjiang on March 8th. The results showed that by June 15th the accumulated infection cases could have been reduced by 32.49% (South Korea), 98.16% (Italy) and 85.73% (Iran). The surface air temperature showed stronger association with transmission rate of COVID-19 than surface relative humidity. On the basis of these findings, disease control measures were shown to be particularly effective in flattening and shrinking the COVID-10 case curve, which could effectively reduce the severity of the disease and mitigate medical burden. The proposed empirical law and the SEIR-temporal moving window model can also be used to study infectious disease outbreaks worldwide.

COVID-19 pandemic and associated lockdown as a "Global Human Confinement Experiment" to investigate biodiversity conservation.

Efforts to curtail the spread of the novel coronavirus (SARS-CoV2) have led to the unprecedented concurrent confinement of nearly two-thirds of the global population. The large human lockdown and its eventual relaxation can be viewed as a Global Human Confinement Experiment. This experiment is a unique opportunity to identify positive and negative effects of human presence and mobility on a range of natural systems, including wildlife, and protected areas, and to study processes regulating biodiversity and ecosystems. We encourage ecologists, environmental scientists, and resource managers to contribute their observations to efforts aiming to build comprehensive global understanding based on multiple data streams, including anecdotal observations, systematic assessments and quantitative monitoring. We argue that the collective power of combining diverse data will transcend the limited value of the individual data sets and produce unexpected insights. We can also consider the confinement experiment as a "stress test" to evaluate the strengths and weaknesses in the adequacy of existing networks to detect human impacts on natural systems. Doing so will provide evidence for the value of the conservation strategies that are presently in place, and create future networks, observatories and policies that are more adept in protecting biological diversity across the world.