Different forms of superspreading lead to different outcomes: Heterogeneity in infectiousness and contact behavior relevant for the case of SARS-CoV-2

Superspreading events play an important role in the spread of several pathogens, such as SARS-CoV-2. While the basic reproduction number of the original Wuhan SARS-CoV-2 is estimated to be about 3 for Belgium, there is substantial inter-individual variation in the number of secondary cases each infected individual causes—with most infectious individuals generating no or only a few secondary cases, while about 20% of infectious individuals is responsible for 80% of new infections. Multiple factors contribute to the occurrence of superspreading events: heterogeneity in infectiousness, individual variations in susceptibility, differences in contact behavior, and the environment in which transmission takes place. While superspreading has been included in several infectious disease transmission models, research into the effects of different forms of superspreading on the spread of pathogens remains limited. To disentangle the effects of infectiousness-related heterogeneity on the one hand and contact-related heterogeneity on the other, we implemented both forms of superspreading in an individual-based model describing the transmission and spread of SARS-CoV-2 in a synthetic Belgian population. We considered its impact on viral spread as well as on epidemic resurgence after a period of social distancing. We found that the effects of superspreading driven by heterogeneity in infectiousness are different from the effects of superspreading driven by heterogeneity in contact behavior. On the one hand, a higher level of infectiousness-related heterogeneity results in a lower risk of an outbreak persisting following the introduction of one infected individual into the population. Outbreaks that did persist led to fewer total cases and were slower, with a lower peak which occurred at a later point in time, and a lower herd immunity threshold. Finally, the risk of resurgence of an outbreak following a period of lockdown decreased. On the other hand, when contact-related heterogeneity was high, this also led to fewer cases in total during persistent outbreaks, but caused outbreaks to be more explosive in regard to other aspects (such as higher peaks which occurred earlier, and a higher herd immunity threshold). Finally, the risk of resurgence of an outbreak following a period of lockdown increased. We found that these effects were conserved when testing combinations of infectiousness-related and contact-related heterogeneity.     

Characterizing superspreading potential of infectious disease: Decomposition of individual transmissibility

In the context of infectious disease transmission, high heterogeneity in individual infectiousness indicates that a few index cases can generate large numbers of secondary cases, a phenomenon commonly known as superspreading. The potential of disease superspreading can be characterized by describing the distribution of secondary cases (of each seed case) as a negative binomial (NB) distribution with the dispersion parameter, k. Based on the feature of NB distribution, there must be a proportion of individuals with individual reproduction number of almost 0, which appears restricted and unrealistic. To overcome this limitation, we generalized the compound structure of a Poisson rate and included an additional parameter, and divided the reproduction number into independent and additive fixed and variable components. Then, the secondary cases followed a Delaporte distribution. We demonstrated that the Delaporte distribution was important for understanding the characteristics of disease transmission, which generated new insights distinct from the NB model. By using real-world dataset, the Delaporte distribution provides improvements in describing the distributions of COVID-19 and SARS cases compared to the NB distribution. The model selection yielded increasing statistical power with larger sample sizes as well as conservative type I error in detecting the improvement in fitting with the likelihood ratio (LR) test. Numerical simulation revealed that the control strategy-making process may benefit from monitoring the transmission characteristics under the Delaporte framework. Our findings highlighted that for the COVID-19 pandemic, population-wide interventions may control disease transmission on a general scale before recommending the high-risk-specific control strategies.     

An open-access database of infectious disease transmission trees to explore superspreader epidemiology

Historically, emerging and reemerging infectious diseases have caused large, deadly, and expensive multinational outbreaks. Often outbreak investigations aim to identify who infected whom by reconstructing the outbreak transmission tree, which visualizes transmission between individuals as a network with nodes representing individuals and branches representing transmission from person to person. We compiled a database, called OutbreakTrees, of 382 published, standardized transmission trees consisting of 16 directly transmitted diseases ranging in size from 2 to 286 cases. For each tree and disease, we calculated several key statistics, such as tree size, average number of secondary infections, the dispersion parameter, and the proportion of cases considered superspreaders, and examined how these statistics varied over the course of each outbreak and under different assumptions about the completeness of outbreak investigations. We demonstrated the potential utility of the database through 2 short analyses addressing questions about superspreader epidemiology for a variety of diseases, including Coronavirus Disease 2019 (COVID-19). First, we found that our transmission trees were consistent with theory predicting that intermediate dispersion parameters give rise to the highest proportion of cases causing superspreading events. Additionally, we investigated patterns in how superspreaders are infected. Across trees with more than 1 superspreader, we found preliminary support for the theory that superspreaders generate other superspreaders. In sum, our findings put the role of superspreading in COVID-19 transmission in perspective with that of other diseases and suggest an approach to further research regarding the generation of superspreaders. These data have been made openly available to encourage reuse and further scientific inquiry.

This study compiles and standardizes reported infectious disease transmission trees to analyze trends in superspreader frequency and generation; these data support theories that intermediate dispersion parameters give rise to the highest proportion of cases causing superspreading events, and that superspreaders generate other superspreaders.     

Age‐specific infectious period shapes dynamics of pneumonia in bighorn sheep

Superspreading, the phenomenon where a small proportion of individuals contribute disproportionately to new infections, has profound effects on disease dynamics. Superspreading can arise through variation in contacts, infectiousness or infectious periods. The latter has received little attention, yet it drives the dynamics of many diseases of critical public health, livestock health and conservation concern. Here, we present rare evidence of variation in infectious periods underlying a superspreading phenomenon in a free‐ranging wildlife system. We detected persistent infections of Mycoplasma ovipneumoniae, the primary causative agent of pneumonia in bighorn sheep (Ovis canadensis), in a small number of older individuals that were homozygous at an immunologically relevant genetic locus. Interactions among age‐structure, genetic composition and infectious periods may drive feedbacks in disease dynamics that determine the magnitude of population response to infection. Accordingly, variation in initial conditions may explain divergent population responses to infection that range from recovery to catastrophic decline and extirpation.     

Ab initio protein modeling into CryoEM density maps using EM-Fold

EM-Fold was used to build models for nine proteins in the maps of GroEL (7.7 ? resolution) and ribosome (6.4 ? resolution) in the ab initio modeling category of the 2010 cryo-electron microscopy modeling challenge. EM-Fold assembles predicted secondary structure elements (SSEs) into regions of the density map that were identified to correspond to either α-helices or β-strands. The assembly uses a Monte Carlo algorithm where loop closure, density-SSE length agreement, and strength of connecting density between SSEs are evaluated. Top-scoring models are refined by translating, rotating, and bending SSEs to yield better agreement with the density map. EM-Fold produces models that contain backbone atoms within SSEs only. The RMSD values of the models with respect to native range from 2.4 to 3.5 ? for six of the nine proteins. EM-Fold failed to predict the correct topology in three cases. Subsequently, Rosetta was used to build loops and side chains for the very best scoring models after EM-Fold refinement. The refinement within Rosetta's force field is driven by a density agreement score that calculates a cross-correlation between a density map simulated from the model and the experimental density map. All-atom RMSDs as low as 3.4 ? are achieved in favorable cases. Values above 10.0 ? are observed for two proteins with low overall content of secondary structure and hence particularly complex loop modeling problems. RMSDs over residues in secondary structure elements range from 2.5 to 4.8 ?.     

Analysis of conservation and substitutions of secondary structure elements within protein superfamilies

MOTIVATION: Structural alignments of superfamily members often exhibit insertions and deletions of secondary structure elements (SSEs), yet conserved subsets of SSEs appear to be important for maintaining the fold and facilitating common functionalities. RESULTS: A database of aligned SSEs was constructed from the structure-based alignments of protein superfamily members in the CAMPASS database. SSEs were classified into several types on the basis of their length and solvent accessibility and counts were made for the replacements of SSEs in different types at structurally aligned positions. The results, summarized as log-odds substitution matrices, can be used for two types of comparisons: (1) structure against structure, both with secondary structure assignments; and (2) structure against sequence with predicted secondary structures. The conservation of SSEs at each alignment position was defined as the deviation of observed SSE frequencies from the uniform distribution. This offers a useful resource to define and examine the core of superfamily folds. Even when the structure of only a single member of a superfamily is known, the extended method can be used to predict the conservation of SSEs. Such information will be useful when modelling the structure of other members of a superfamily or identifying structurally and functionally important positions in the fold.     

How a Spatial Arrangement of Secondary Structure Elements Is Dispersed in the Universe of Protein Folds

It has been known that topologically different proteins of the same class sometimes share the same spatial arrangement of secondary structure elements (SSEs). However, the frequency by which topologically different structures share the same spatial arrangement of SSEs is unclear. It is important to estimate this frequency because it provides both a deeper understanding of the geometry of protein folds and a valuable suggestion for predicting protein structures with novel folds. Here we clarified the frequency with which protein folds share the same SSE packing arrangement with other folds, the types of spatial arrangement of SSEs that are frequently observed across different folds, and the diversity of protein folds that share the same spatial arrangement of SSEs with a given fold, using a protein structure alignment program MICAN, which we have been developing. By performing comprehensive structural comparison of SCOP fold representatives, we found that approximately 80% of protein folds share the same spatial arrangement of SSEs with other folds. We also observed that many protein pairs that share the same spatial arrangement of SSEs belong to the different classes, often with an opposing N- to C-terminal direction of the polypeptide chain. The most frequently observed spatial arrangement of SSEs was the 2-layer α/β packing arrangement and it was dispersed among as many as 27% of SCOP fold representatives. These results suggest that the same spatial arrangements of SSEs are adopted by a wide variety of different folds and that the spatial arrangement of SSEs is highly robust against the N- to C-terminal direction of the polypeptide chain.     

A Versatile Sn‐Substituted Argyrodite Sulfide Electrolyte for All‐Solid‐State Li Metal Batteries

Sulfide‐based solid‐state electrolytes (SSEs) for all‐solid‐state Li metal batteries (ASSLMBs) are attracting significant attention due to their high ionic conductivity, inherently soft properties, and decent mechanical strength. However, the poor incompatibility with Li metal and air sensitivity have hindered their application. Herein, the Sn (IV) substitution for P (V) in argyrodite sulfide Li₆PS₅I (LPSI) SSEs is reported, in the preparation of novel LPSI‐xSn SSEs (where x is the Sn substitution percentage). Appropriate aliovalent element substitutions with larger atomic radius (R_<Sn> > R_<P>) provides the optimized LPSI‐20Sn electrolyte with a 125 times higher ionic conductivity compared to that of the LPSI electrolyte. The high ionic conductivity of LPSI‐20Sn enables the rich I‐containing electrolyte to serve as a stabilized interlayer against Li metal in sulfide‐based ASSLMBs with outstanding cycling stability and rate capability. Most importantly, benefiting from the strong Sn–S bonding in Sn‐substituted electrolytes, the LPSI‐20Sn electrolyte shows excellent structural stability and improved air stability after exposure to O₂ and moisture. The versatile Sn substitution in argyrodite LPSI electrolytes is believed to provide a new and effective strategy to achieve Li metal‐compatible and air‐stable sulfide‐based SSEs for large‐scale applications.     

ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike Trains

With the ability to observe the activity from large numbers of neurons simultaneously using modern recording technologies, the chance to identify sub-networks involved in coordinated processing increases. Sequences of synchronous spike events (SSEs) constitute one type of such coordinated spiking that propagates activity in a temporally precise manner. The synfire chain was proposed as one potential model for such network processing. Previous work introduced a method for visualization of SSEs in massively parallel spike trains, based on an intersection matrix that contains in each entry the degree of overlap of active neurons in two corresponding time bins. Repeated SSEs are reflected in the matrix as diagonal structures of high overlap values. The method as such, however, leaves the task of identifying these diagonal structures to visual inspection rather than to a quantitative analysis. Here we present ASSET (Analysis of Sequences of Synchronous EvenTs), an improved, fully automated method which determines diagonal structures in the intersection matrix by a robust mathematical procedure. The method consists of a sequence of steps that i) assess which entries in the matrix potentially belong to a diagonal structure, ii) cluster these entries into individual diagonal structures and iii) determine the neurons composing the associated SSEs. We employ parallel point processes generated by stochastic simulations as test data to demonstrate the performance of the method under a wide range of realistic scenarios, including different types of non-stationarity of the spiking activity and different correlation structures. Finally, the ability of the method to discover SSEs is demonstrated on complex data from large network simulations with embedded synfire chains. Thus, ASSET represents an effective and efficient tool to analyze massively parallel spike data for temporal sequences of synchronous activity.     

Synthetic Spike-in Standards Improve Run-Specific Systematic Error Analysis for DNA and RNA Sequencing

While the importance of random sequencing errors decreases at higher DNA or RNA sequencing depths, systematic sequencing errors (SSEs) dominate at high sequencing depths and can be difficult to distinguish from biological variants. These SSEs can cause base quality scores to underestimate the probability of error at certain genomic positions, resulting in false positive variant calls, particularly in mixtures such as samples with RNA editing, tumors, circulating tumor cells, bacteria, mitochondrial heteroplasmy, or pooled DNA. Most algorithms proposed for correction of SSEs require a data set used to calculate association of SSEs with various features in the reads and sequence context. This data set is typically either from a part of the data set being "recalibrated" (Genome Analysis ToolKit, or GATK) or from a separate data set with special characteristics (SysCall). Here, we combine the advantages of these approaches by adding synthetic RNA spike-in standards to human RNA, and use GATK to recalibrate base quality scores with reads mapped to the spike-in standards. Compared to conventional GATK recalibration that uses reads mapped to the genome, spike-ins improve the accuracy of Illumina base quality scores by a mean of 5 Phred-scaled quality score units, and by as much as 13 units at CpG sites. In addition, since the spike-in data used for recalibration are independent of the genome being sequenced, our method allows run-specific recalibration even for the many species without a comprehensive and accurate SNP database. We also use GATK with the spike-in standards to demonstrate that the Illumina RNA sequencing runs overestimate quality scores for AC, CC, GC, GG, and TC dinucleotides, while SOLiD has less dinucleotide SSEs but more SSEs for certain cycles. We conclude that using these DNA and RNA spike-in standards with GATK improves base quality score recalibration.     

Coinfection can trigger multiple pandemic waves

Sequences of epidemic waves have been observed in past influenza pandemics, such as the Spanish influenza. Possible explanations may be sought either in mechanisms altering the structure of the network of contacts, such as those induced by changes in the rates of movement of people or by public health measures, or in the genetic drift of the influenza virus, since the appearance of new strains can reduce or eliminate herd immunity. The pandemic outbreaks may also be influenced by coinfection with other acute respiratory infections (ARI) that increase transmissibility of influenza virus (by coughing, sneezing, running nose). In fact, some viruses (e.g., Rhinovirus and Adenovirus) have been found to induce “clouds” of bacteria and increase the transmissibility of Staphylococcus aureus. Moreover, Rhinovirus and Adenovirus were detected in patients during past pandemics, and their presence is linked to superspreading events. In this paper, by assuming increased transmissibility in coinfected individuals, we propose and study a model where multiple pandemic waves are triggered by coinfection with ARI. The model agrees well with mortality excess data during the 1918 pandemic influenza, thereby providing indications for potential pandemic mitigation.     

Revealing the Short‐Circuiting Mechanism of Garnet‐Based Solid‐State Electrolyte

Garnet‐type solid‐state electrolytes (SSEs) have been widely studied as a promising candidate for Li metal batteries. Despite the common belief that inorganic SSEs can prevent dendrite propagation, garnet SSEs suffer from relatively low critical current density (CCD) at which the SSEs are abruptly short‐circuited by Li dendrites. In this study, the short‐circuiting mechanism of garnet Li₇La_2.75Ca_0.25Zr_1.75Nb_0.25O₁₂ (LLCZN) is investigated. It is found that instead of propagating uniaxially from one electrode to other in a dendritic form, metallic lithium is formed within the SSE. This can be attributed to the fact that electrons combine with Li ions at the grain boundary, which exhibits relatively high electronic conductivity, and then reduce Li⁺ to Li⁰ to cause short circuits. In order to reduce the electronic conductivity at the grain boundary, a thin layer of LiAlO₂ is coated on the grain surface of LLCZN, which results in an improved CCD value. It is also found that under higher external voltages, the electronic conductivity of SSE becomes more significant, which is believed to be the origin of CCD. These findings not only shed light on the short‐circuiting mechanism of garnet‐type SSEs but also offer a novel perspective and useful guidance on their designs and modifications.     

Rules for connectivity of secondary structure elements in protein: Two–layer αβ sandwiches

In protein structures, the fold is described according to the spatial arrangement of secondary structure elements (SSEs: α‐helices and β‐strands) and their connectivity. The connectivity or the pattern of links among SSEs is one of the most important factors for understanding the variety of protein folds. In this study, we introduced the connectivity strings that encode the connectivities by using the types, positions, and connections of SSEs, and computationally enumerated all the connectivities of two‐layer αβ sandwiches. The calculated connectivities were compared with those in natural proteins determined using MICAN, a nonsequential structure comparison method. For 2α‐4β, among 23,000 of all connectivities, only 48 were free from irregular connectivities such as loop crossing. Of these, only 20 were found in natural proteins and the superfamilies were biased toward certain types of connectivities. A similar disproportional distribution was confirmed for most of other spatial arrangements of SSEs in the two‐layer αβ sandwiches. We found two connectivity rules that explain the bias well: the abundances of interlayer connecting loops that bridge SSEs in the distinct layers; and nonlocal β‐strand pairs, two spatially adjacent β‐strands located at discontinuous positions in the amino acid sequence. A two‐dimensional plot of these two properties indicated that the two connectivity rules are not independent, which may be interpreted as a rule for the cooperativity of proteins.     

Finding rigid bodies in protein structures: Application to flexible fitting into cryoEM maps

We present RIBFIND, a method for detecting flexibility in protein structures via the clustering of secondary structural elements (SSEs) into rigid bodies. To test the usefulness of the method in refining atomic structures within cryoEM density we incorporated it into our flexible fitting protocol (Flex-EM). Our benchmark includes 13 pairs of protein structures in two conformations each, one of which is represented by a corresponding cryoEM map. Refining the structures in simulated and experimental maps at the 5–15 Å resolution range using rigid bodies identified by RIBFIND shows a significant improvement over using individual SSEs as rigid bodies. For the 15 Å resolution simulated maps, using RIBFIND-based rigid bodies improves the initial fits by 40.64% on average, as compared to 26.52% when using individual SSEs. Furthermore, for some test cases we show that at the sub-nanometer resolution range the fits can be further improved by applying a two-stage refinement protocol (using RIBFIND-based refinement followed by an SSE-based refinement). The method is stand-alone and could serve as a general interactive tool for guiding flexible fitting into EM maps.     

Cyclic secondary somatic embryogenesis and efficient plant regeneration in mountain ash (Sorbus pohuashanensis)

An efficient protocol for secondary somatic embryogenesis in mountain ash is reported. Secondary somatic embryos (SSEs), initially obtained from primary embryos, were proliferated and maintained for more than 2?years via cyclic secondary somatic embryogenesis. SSEs were produced on the surfaces of cotyledons and radicles of maternal somatic embryos. Histological observations of the various stages of SSE development revealed four typical stages: globular, heart-shaped, torpedo, and cotyledon. Addition of a low concentration of naphthaleneacetic acid (NAA) to Murashige and Skoog (MS) medium resulted in the induction of SSEs, but addition of 2,4-dichlorophenoxyacetic acid (2,4-d) to MS medium decreased SSE formation. Addition of casein hydrolysate (CH) to MS medium promoted induction of SSEs. Cotyledonary SSEs were cultured on MS medium with 20?C60?g?L^?1 sucrose under light for 1?month until maturation. After transferred to MS medium containing either 0.06???M NAA or 0.15???M indole-3-butyric acid in the light, over 50?% of the mature SSEs developed into plantlets. Addition of 1.0?g?L^?1 activated charcoal was beneficial for SSE germination (over 60?%). At 18?°C, over 90?% of the germinated SSEs converted to plantlets on ? MS (half-strength of MS macroelements) with 1.8???M NAA under light. Plantlets acclimatized successfully to ex vitro conditions and field plants developed with normal phenotypes.     

Universal Soldering of Lithium and Sodium Alloys on Various Substrates for Batteries

The high theoretical specific capacity of lithium (Li) metal and the nonflammability of solid‐state electrolytes (SSEs) make the solid‐state Li metal battery a promising option to develop safe batteries with high energy density. To make the switch from liquid to solid‐state electrolyte, the high interfacial resistance resulting from the poor solid–solid contacts between Li metal and SSEs needs to be addressed. Herein, a one‐step soldering technique to quickly coat molten Li onto different substrates including metals, ceramics, and polymers is presented. It is deduced that the surface energy and viscosity of the molten Li can be tuned by adding alloy elements, which improves the wettability against various substrates. When soldered onto the surface of garnet‐based SSEs, the Li alloys exhibit significantly improved contact, which leads to an interface resistance as low as ≈7 Ω cm². While cycling under high loads, the newly plated Li still maintains tight contact with the garnet surface and demonstrates excellent electrochemical stability. Several Li binary alloys as well as sodium (Na) binary alloys are successfully tested on various substrates to demonstrate the versatility of this soldering technique for potential battery applications.     

Interfacial Incompatibility and Internal Stresses in All‐Solid‐State Lithium Ion Batteries

Rechargeable Li‐ion batteries (LIBs) are electrochemical storage device widely applied in electric vehicles, mobile electronic devices, etc. However, traditional LIBs containing liquid electrolytes suffer from flammability, poor electrochemical stability, and limited operational temperature range. Replacement of the liquid electrolytes with inorganic solid‐state electrolytes (SSEs) would solve this problem. However, several critical issues, such as poor interfacial compatibility, low ionic conductivity at ambient temperatures, etc., need to be surmounted before the commercialization of all‐solid‐state Li‐ion batteries (ASSLIBs). In this review, a brief historical context for the inorganic SSEs is described first. Then, two critical issues in the ASSLIBs are highlighted: interfacial incompatibility of the electrodes and SSEs and internal stresses. For the interfacial incompatibility, the discussion is focused on the dynamic characterization of the electrode/SSE interfaces, the origin and evolution of the interfacial resistance, and interface engineering to minimize the interfacial resistance. The internal stresses in the ASSLIBs are another major concern because rigid contacts are introduced. Stress generation, stress evolution during battery cycling, stress measurement/simulation, and ways to alleviate the stresses are outlined in detail. Finally, current challenges and perspectives for future development of the inorganic SSEs and ASSLIBs are outlined.     

SARS流行病传染动力学研究

Logistic确定型增长模型可被用来描述严重急性呼吸道综合症（SARS）的流行规律,通过对部分国家、地区及中国内地部分省市的数据进行拟合,及其对拟合结果的分析,揭示了各个地区SARS传染力不均匀的现象,以及在控制措施上的差异所带来的不同效果.同时,还对超级传播现象（SSEs）等问题进行了讨论.