Heterogeneity in the Effectiveness of Non-pharmaceutical Interventions During the First SARS-CoV2 Wave in the United States

Background: Attempts to quantify effect sizes of non-pharmaceutical interventions (NPI) to control COVID-19 in the US have not accounted for heterogeneity in social or environmental factors that may influence NPI effectiveness. This study quantifies national and sub-national effect sizes of NPIs during the early months of the pandemic in the US.Methods: Daily county-level COVID-19 cases and deaths during the first wave (January 2020 through phased removal of interventions) were obtained. County-level cases, doubling times, and death rates were compared to four increasingly restrictive NPI levels. Socio-demographic, climate and mobility factors were analyzed to explain and evaluate NPI heterogeneity, with mobility used to approximate NPI compliance. Analyses were conducted separately for the US and for each Census regions (Pacific, Mountain, east/West North Central, East/West South Central, South Atlantic, Middle Atlantic and New England). A stepped-wedge cluster-randomized trial analysis was used, leveraging the phased implementation of policies.Results: Aggressive (level 4) NPIs were associated with slower COVID-19 propagation, particularly in high compliance counties. Longer duration of level 4 NPIs was associated with lower case rates (log beta −0.028, 95% CI −0.04 to −0.02) and longer doubling times (log beta 0.02, 95% CI 0.01–0.03). Effects varied by Census region, for example, level 4 effects on doubling time in Pacific states were opposite to those in Middle Atlantic and New England states. NPI heterogeneity can be explained by differential timing of policy initiation and by variable socio-demographic county characteristics that predict compliance, particularly poverty and racial/ethnic population. Climate exhibits relatively consistent relationships across Census regions, for example, higher minimum temperature and specific humidity were associated with lower doubling times and higher death rates for this period of analysis in South Central, South Atlantic, Middle Atlantic, and New England states.Conclusion and Relevance: Heterogeneity exists in both the effectiveness of NPIs across US Census regions and policy compliance. This county-level variability indicates that control strategies are best designed at community-levels where policies can be tuned based on knowledge of local disparities and compliance with public health ordinances.

Haskap Berry Phenolic Subclasses Differentially Impact Cellular Stress Sensing in Primary and Immortalized Dermal Fibroblasts

It is generally accepted that dietary phenolics from fruits are of significant importance to human health. Unfortunately, there is minimal published data on how differences in phenolic structure(s) impact biological pathways at cellular and molecular levels. We observed that haskap berry extracts isolated with ethanol:formic acid:water or phenolic subclass fractions separated using different concentrations of ethanol (40% and 100%) impacted cell growth in a positive manner. All fractions and extracts significantly increased population doubling times. All extracts and fractions reduced intracellular free radicals; however, there were differences in these effects, indicating different abilities to scavenge free radicals. The extracts and fractions also exhibited differing impacts on transcripts encoding the antioxidant enzymes (CAT, SOD1, GPX1, GSS and HMOX1) and the phosphorylation state of nuclear factor-κB (NF-κB). We further observed that extracts and fractions containing different phenolic structures had divergent impacts on the mammalian target of rapamycin (mTOR) and sirtuin 1 (SIRT1). siRNA-mediated knockdown of SIRT1 transcripts demonstrated that this enzyme is key to eliciting haskap phenolic(s) impact on cells. We postulate that phenolic synergism is of significant importance when evaluating their dietary impact.

Adeno-associated and lentiviral vector production in 2D and 3D formats with adherent cells in chemically defined, blood-free media

Large scale manufacturing of viral vectors or vaccines with adherent cells still relies heavily on the inclusion of fetal bovine serum for the growth and production phases. The inclusion of serum presents numerous problems with the undefined chemical makeup, the undesirable safety profile, and the constraints and limitations on the global supply. Despite these challenges, alternatives to serum for adherent cells have been limited; however, advances in large-scale production of recombinant human proteins have enabled the advancement of blood-free media that can support adherent cell growth. In order to circumvent the need for serum in adherent platforms, we developed a serum and blood-free, chemically defined medium specific for adherent human epithelial kidney cells and evaluated growth kinetics as well as viral vector production with associated adenovirus and lentivirus. We observed doubling times equal to or faster than doubling times observed in serum containing medium. We also demonstrate transfection efficiencies and viral titers that are equivalent to or higher than that of serum. Our results demonstrate that fetal bovine serum is not required for culture of adherent HEK cells, and that a serum-free, blood-free, chemically defined approach can be reliably implemented in the production of viral vectors for gene therapy.

Bibliometric Analysis in the Field of Quantum Technology

The second quantum technological revolution started around 1980 with the control of single quantum particles and their interaction on an individual basis. These experimental achievements enabled physicists, engineers, and computer scientists to utilize long-known quantum features—especially superposition and entanglement of single quantum states—for a whole range of practical applications. We use a publication set of 54,598 papers from Web of Science, published between 1980 and 2018, to investigate the time development of four main subfields of quantum technology in terms of numbers and shares of publications, as well as the occurrence of topics and their relation to the 25 top contributing countries. Three successive time periods are distinguished in the analyses by their short doubling times in relation to the whole Web of Science. The periods can be characterized by the publication of pioneering works, the exploration of research topics, and the maturing of quantum technology, respectively. Compared to the USA, China’s contribution to the worldwide publication output is overproportionate, but not in the segment of highly cited papers.

Adaptation of the Start-Growth-Time Method for High-Throughput Biofilm Quantification

Colony forming unit (CFU) determination by agar plating is still regarded as the gold standard for biofilm quantification despite being time- and resource-consuming. Here, we propose an adaption of the high-throughput Start-Growth-Time (SGT) method from planktonic to biofilm analysis, which indirectly quantifies CFU/mL numbers by evaluating regrowth curves of detached biofilms. For validation, the effect of dalbavancin, rifampicin and gentamicin against mature biofilms of Staphylococcus aureus and Enterococcus faecium was measured by accessing different features of the viability status of the cell, i.e., the cultivability (conventional agar plating), growth behavior (SGT) and metabolic activity (resazurin assay). SGT correlated well with the resazurin assay for all tested antibiotics, but only for gentamicin and rifampicin with conventional agar plating. Dalbavancin treatment-derived growth curves showed a compared to untreated controls significantly slower increase with reduced cell doubling times and reduced metabolic rate, but no change in CFU numbers was observed by conventional agar plating. Here, unspecific binding of dalbavancin to the biofilm interfered with the SGT methodology since the renewed release of dalbavancin during detachment of the biofilms led to an unintended antimicrobial effect. The application of the SGT method for anti-biofilm testing is therefore not suited for antibiotics which stick to the biofilm and/or to the bacterial cell wall. Importantly, the same applies for the well-established resazurin method for anti-biofilm testing. However, for antibiotics which do not bind to the biofilm as seen for gentamicin and rifampicin, the SGT method presents a much less labor-intensive method suited for high-throughput screening of anti-biofilm compounds.

Intuition and exponential growth: bias and the roles of parameterization and complexity

Exponential growth bias is the phenomenon that humans intuitively underestimate exponential growth. This article reports on an experiment where treatments differ in the parameterization of growth: Exponential growth is communicated to one group in terms of growth rates, and in terms of doubling times to the other. Exponential growth bias is much smaller when doubling times are employed. Considering that in many applications, individuals face a choice between different growth rates, rather than between exponential growth and zero growth, we ask a question where growth is reduced from high to low. Subjects vastly underestimate the effect of this reduction, though less so in the parameterization using doubling times. The answers to this question are more severely biased than one would expect from the answers to the exponential growth questions. These biases emerge despite the sample being highly educated and exhibiting awareness of exponential growth bias. Implications for teaching, the usefulness of heuristics, and policy are discussed.

Rapid transmission of coronavirus disease 2019 within a religious sect in South Korea: a mathematical modeling study

Rapid transmission of coronavirus disease 2019 (COVID-19) was observed in the Shincheonji Church of Jesus, a religious sect in South Korea. The index case was confirmed on February 18, 2020 in Daegu City, and within two weeks, 3,081 connected cases were identified. Doubling times during the initial stages of the outbreak were less than 2 days. A stochastic model fitted to the time series of confirmed cases suggests that the basic reproduction number (R0) of 18 COVID-19 was 8.5 [95% credible interval (CrI): 6.3, 10.9] among the church members, whereas R0 = 1.9 [95% CrI: 0.4, 4.4] in the rest of the population of Daegu City. The model also suggests that there were 4 [95% CrI: 2, 11] undetected cases when the first case reported symptoms on February 7. The Shincheonji Church cluster is likely to be emblematic of other outbreak-prone populations where R0 of COVID-19 is higher. Understanding and subsequently limiting the risk of transmission in such high-risk places is key to effective control.

Extraordinarily rapid proliferation of cultured muscle satellite cells from migratory birds

Migratory birds experience bouts of muscle growth and depletion as they prepare for, and undertake prolonged flight. Our studies of migratory bird muscle physiology in vitro led to the discovery that sanderling ( Calidris alba ) muscle satellite cells proliferate more rapidly than other normal cell lines. Here we determined the proliferation rate of muscle satellite cells isolated from five migratory species (sanderling; ruff, Calidris pugnax ; western sandpiper, Calidris mauri ; yellow-rumped warbler, Setophaga coronata ; Swainson's thrush, Catharus ustulatus ) from two families (shorebirds and songbirds) and with different migratory strategies. Ruff and sanderling satellite cells exhibited rapid proliferation, with population doubling times of 9.3 ± 1.3 and 11.4 ± 2 h, whereas the remaining species' cell doubling times were greater than or equal to 24 h. The results indicate that the rapid proliferation of satellite cells is not associated with total migration distance but may be related to flight bout duration and interact with lifespan.

Macro-Level Drivers of SARS-CoV-2 Transmission: A Data-Driven Analysis of Factors Contributing to Epidemic Growth During the First Wave of outbreaks in the United States

Many questions remain unanswered about how SARS-CoV-2 transmission is influenced by aspects of the economy, environment, and health. A better understanding of how these factors interact can help us to design early health prevention and control strategies, and develop better predictive models for public health risk management of SARS-CoV-2. This study examines the associations between COVID-19 epidemic growth and macro-level determinants of transmission such as climate, socio-economic factors, demographic factors, and population health, during the first wave of outbreaks in the United States. A spatial-temporal data-set was created by collating information from a variety of data sources including the Johns Hopkins University's Centre for Systems Science and Engineering, the United States Census Bureau, the USDA Economic Research Service, the United States EPA, the National Climatic Data Center, the CDC and the Oxford COVID-19 Government Response Tracker (OxCGRT). A unique data-driven study design was implemented that allows us to assess the relationship between COVID-19 case and death epidemic doubling times and explanatory variables using a Generalized Additive Model (GAM). The main factors associated with case doubling times are higher population density, home overcrowding, manufacturing, and recreation industries. Poverty was also an important predictor of faster epidemic growth perhaps because of factors associated with in-work poverty-related conditions, although poverty is also a predictor of poor population health which is likely driving case and death reporting. Air pollution and diabetes were other important drivers of case reporting. Warmer temperatures are associated with slower epidemic growth, which is most likely explained by human behaviors associated with warmer locations i.e ventilating homes and workplaces. and socializing outdoors. The main factors associated with death doubling times were population density, poverty older age, diabetes, and air pollution. Temperature was also slightly significant slowing death doubling times. Such findings help underpin current understanding of the disease epidemiology and also support current policy and advice recommending ventilation of homes, work-spaces, and schools, along with social distancing and mask-wearing. The results also suggest that states which adopted more stringent containment measures early on did have some success suppressing the virus. We can presume that if this was replicated at a federal level, much better outcomes would have been observed across the United States.