Transmission Bottleneck Research Articles

Genomic epidemiology reveals the variation and transmission properties of SARS-CoV-2 in a single-source community outbreak.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the coronavirus disease 2019 (COVID-19) pandemic, which is still a global public health concern. During March 2022, a rapid and confined single-source outbreak of SARS-CoV-2 was identified in a community in Nanjing municipal city. Overall, 95 individuals had laboratory-confirmed SARS-CoV-2 infection. The whole genomes of 61 viral samples were obtained, which were all members of the BA.2.2 lineage and clearly demonstrated the presence of one large clade, and all the infections could be traced back to the original index case. The most distant sequence from the index case presented a difference of 4 SNPs, and 118 intrahost single-nucleotide variants (iSNVs) at 74 genomic sites were identified. Some minor iSNVs can be transmitted and subsequently rapidly fixed in the viral population. The minor iSNVs transmission resulted in at least two nucleotide substitutions among all seven SNPs identified in the outbreak, generating genetically diverse populations. We estimated the overall transmission bottleneck size to be 3 using 11 convincing donor-recipient transmission pairs. Our study provides new insights into genomic epidemiology and viral transmission, revealing how iSNVs become fixed in local clusters, followed by viral transmission across the community, which contributes to population diversity.

Ventilation does not affect close-range transmission of influenza virus in a ferret playpen setup

Sustained community spread of influenza viruses relies on efficient person-to-person transmission. Current experimental transmission systems do not mimic environmental conditions (e.g., air exchange rates, flow patterns), host behaviors, or exposure durations relevant to real-world settings. Therefore, results from these traditional systems may not be representative of influenza virus transmission in humans. To address this pitfall, we developed a close-range transmission setup that implements a play-based scenario and used it to investigate the impact of ventilation rates on transmission. In this setup, four immunologically naive recipient ferrets were exposed to a donor ferret infected with a genetically barcoded 2009 H1N1 virus (H1N1pdm09) for 4 h. The ferrets interacted in a shared space that included toys, similar to a childcare setting. Transmission efficiency was assessed under low and high ventilation, with air exchange rates of ~1.3 h-1 and 23 h-1, respectively. Transmission efficiencies observed in three independent replicate studies were similar between ventilation conditions. The presence of infectious virus or viral RNA on surfaces and in air throughout the exposure area was also not impacted by the ventilation rate. While high viral genetic diversity in donor ferret nasal washes was maintained during infection, recipient ferret nasal washes displayed low diversity, revealing a narrow transmission bottleneck regardless of ventilation rate. Examining the frequency and duration of ferret physical touches revealed no link between these interactions and a successful transmission event. Our findings indicate that exposures characterized by frequent, close-range interactions and the presence of fomites can overcome the benefits of increased ventilation.

Channel assisted noise propagation in a two-step cascade.

Signal propagation in biochemical networks is characterized by the inherent randomness in gene expression and fluctuations of the environmental components, commonly known as intrinsic and extrinsic noise, respectively. We present a theoretical framework for noise propagation in a generic two-step cascade (S→X→Y) regarding intrinsic and extrinsic noise. We identify different channels of noise transmission that regulate the individual and the overall noise properties of each component. Our analysis shows that the intrinsic noise of S alleviates the general noise and information transmission capacity along the cascade. On the other hand, the intrinsic noise of X and Y acts as a bottleneck of information transmission. We also show a hierarchical relationship among the intrinsic noise levels of S, X, and Y, with S exhibiting the highest level of intrinsic noise, followed by X and then Y. This hierarchy is preserved within the two-step cascade, facilitating the highest information transmission from S to Y via X.

Modelling of electromechanical coupling dynamics for high-speed EHT system used in HEV and characteristics analysis

As the development of hybrid electric vehicle (HEV) to high-speed, heavy-load, the electromechanical coupling vibration becomes the bottleneck in high-speed electromechanical hybrid transmission (EHT) system. To explore the dynamics characteristics and optimization direction for high-speed EHT system, an electromechanical coupling dynamics model under multi-source excitations is established with lumped-distributed parameter method and verified with experiment data. The dynamics model shows higher accuracy in both time and frequency domain analysis. On this basis, firstly, the comparison between lumped-shaft and distributed-shaft model is studied under time and frequency domain. Comparing with the lumped-shaft model, the distributed-shaft model shows higher accuracy, and can better reflect the coupling vibration of multi-stage planetary gears (PGs). Secondly, the inherent vibration model is derived, and the effect of electromechanical coupling and high-speed working conditions on inherent vibration characteristics are studied. Thirdly, a new method called ‘machine-electricity-magnet coupling interface’ is proposed to reveal the coupling vibration phenomenon. In addition, the signal of stator current and electromagnetic torque includes the frequency of PGs, which is a basis on the fault diagnosis and state monitor of EHT system. Last but not the least, the vibration acceleration of EHT system is analysed under variable speed and load working conditions. Rotation speed and gear meshing force is found as the main influencing factor of series EHT system, and the specific optimization direction is also given.

Active Queue Management in L4S with Asynchronous Advantage Actor-Critic: A FreeBSD Networking Stack Perspective

Bufferbloat is one of the leading causes of high data transmission latency and jitter on the Internet, which severely impacts the performance of low-latency interactive applications such as online streaming, cloud-based gaming/applications, Internet of Things (IoT) applications, voice over IP (VoIP), real-time video conferencing, and so forth. There is currently a pressing need for developing Transmission Control Protocol (TCP) congestion control algorithms and bottleneck queue management schemes that can collaboratively control/reduce end-to-end latency, thus ensuring optimal quality of service (QoS) and quality of experience (QoE) for users. This paper introduces a novel solution by experimentally integrate the low latency, low loss, and scalable throughput (L4S) architecture (specified by the IETF in RFC 9330) in FreeBSD framework with the asynchronous advantage actor-critic (A3C) reinforcement learning algorithm. The first phase involves incorporating a modified dual-queue coupled active queue management (AQM) system for L4S into the FreeBSD networking stack, enhancing queue management and mitigating latency and packet loss. The second phase employs A3C to adjust and fine-tune the system performance dynamically. Finally, we evaluate the proposed solution’s effectiveness through comprehensive experiments, comparing it with traditional AQM-based systems. This paper contributes to the advancement of machine learning (ML) for transport protocol research in the field. The experimental implementation and results presented in this paper are made available through our GitHub repositories.

Analysis of Reliable Transmission Performance Optimization Methods for Satellite-to-Ground Laser Communication Links

The satellite-to-ground laser communication link plays a crucial role in addressing the technical bottleneck of high-speed information transmission between satellite and ground networks. However, the impact of atmospheric channel conditions poses challenges to the link performance. To overcome these challenges, this paper presents a comprehensive analysis of the characteristics and influencing factors of the satellite-to-ground laser communication link. It summarizes methods for optimizing the transmission performance of the link and proposes approaches for optimizing, monitoring, and predicting the link performance through factors such as the optimization of ground station quantity and location, link availability, link transmission quality, and adaptive coding and modulation. These methods enable the optimization of the transmission performance of the satellite-to-ground laser communication link, thus significantly contributing to the realization of high-speed and reliable laser communication between satellite and ground networks.

Planning natural gas supply chain pathways for energy system decarbonisation: An Australian case study

The future role of natural gas systems in a deeply decarbonised world is very uncertain. This work seeks to characterise the changes that the clean energy transition is likely to induce in the natural gas chain, across extraction and transmission, distribution networks and gas consumption/use trends, for various scenarios with different demand and supply drivers. First, the results of a least-cost macro-scale energy system planning optimisation are explored to identify future natural gas demand and supply requirements. Second, those findings are used as inputs to a detailed analysis of the full gas supply chain, from extraction to final use, to examine the evolution of i) stored resource levels; ii) transmission and distribution networks operation and financing; and iii) required capacity and siting of gas generation; all, with a realistic account of the related infrastructure. Australia is investigated as a case study that relies on natural gas for both domestic and export purposes. Results project a shift towards a more localised gas consumption to be largely supplied by fewer basins, with associated potential transmission and extraction bottlenecks. They anticipate an overall less utilised, ageing distribution network with potential challenges to asset reliability and financing. Finally, they demonstrate both the scheduled and early retirement of fossil generation assets can allow the siting of considerable amounts of new gas power firming capacity on brownfield sites, thus offering an opportunity to reduce total system costs.

Reconfigurable spintronic logic gate utilizing precessional magnetization switching

In traditional von Neumann computing architecture, the efficiency of the system is often hindered by the data transmission bottleneck between the processor and memory. A prevalent approach to mitigate this limitation is the use of non-volatile memory for in-memory computing, with spin–orbit torque (SOT) magnetic random-access memory (MRAM) being a leading area of research. In this study, we numerically demonstrate that a precise combination of damping-like and field-like spin–orbit torques can facilitate precessional magnetization switching. This mechanism enables the binary memristivity of magnetic tunnel junctions (MTJs) through the modulation of the amplitude and width of input current pulses. Building on this foundation, we have developed a scheme for a reconfigurable spintronic logic gate capable of directly implementing Boolean functions such as AND, OR, and XOR. This work is anticipated to leverage the sub-nanosecond dynamics of SOT-MRAM cells, potentially catalyzing further experimental developments in spintronic devices for in-memory computing.

Barcoded SARS-CoV-2 viruses define the impact of time and route of transmission on the transmission bottleneck in a Syrian hamster model.

The transmission bottleneck, defined as the number of viruses that transmit from one host to infect another, is an important determinant of the rate of virus evolution and the level of immunity required to protect against virus transmission. Despite its importance, SARS-CoV-2's transmission bottleneck remains poorly characterized, in part due to a lack of quantitative measurement tools. To address this, we adapted a SARS-CoV-2 reverse genetics system to generate a pool of >200 isogenic SARS-CoV-2 viruses harboring specific 6-nucleotide barcodes inserted in ORF10, a non-translated ORF. We directly inoculated donor Syrian hamsters intranasally with this barcoded virus pool and exposed a paired naïve contact hamster to each donor. Following exposure, the nasal turbinates, trachea, and lungs were collected, viral titers were measured, and the number of barcodes in each tissue were enumerated to quantify the transmission bottleneck. The duration and route (airborne, direct contact, and fomite) of exposure were varied to assess their impact on the transmission bottleneck. In airborne-exposed hamsters, the transmission bottleneck increased with longer exposure durations. We found that direct contact exposure produced the largest transmission bottleneck (average 27 BCs), followed by airborne exposure (average 16 BCs) then fomite exposure (average 8 BCs). Interestingly, we detected unique BCs in both the upper and lower respiratory tract of contact animals from all routes of exposure, suggesting that SARS-CoV-2 can directly infect hamster lungs. Altogether, these findings highlight the utility of barcoded viruses as tools to rigorously study virus transmission. In the future, barcoded SARS-CoV-2 will strengthen studies of immune factors that influence virus transmission.

Emerging 2D Ferroelectric Devices for In-Sensor and In-Memory Computing.

The quantity of sensor nodes within current computing systems is rapidly increasing in tandem with the sensing data. The presence of a bottleneck in data transmission between the sensors, computing, and memory units obstructs the system's efficiency and speed. To minimize the latency of data transmission between units, novel in-memory and in-sensor computing architectures are proposed as alternatives to the conventional von Neumann architecture, aiming for data-intensive sensing and computing applications. The integration of 2D materials and 2D ferroelectric materials has been expected to build these novel sensing and computing architectures due to the dangling-bond-free surface, ultra-fast polarization flipping, and ultra-low power consumption of the 2D ferroelectrics. Here, the recent progress of 2D ferroelectric devices for in-sensing and in-memory neuromorphic computing is reviewed. Experimental and theoretical progresses on 2D ferroelectric devices, including passive ferroelectrics-integrated 2D devices and active ferroelectrics-integrated 2D devices, are reviewed followed by the integration of perception, memory, and computing application. Notably, 2D ferroelectric devices have been used to simulate synaptic weights, neuronal model functions, and neural networks for image processing. As an emerging device configuration, 2D ferroelectric devices have the potential to expand into the sensor-memory and computing integration application field, leading to new possibilities for modern electronics.

The airborne transmission of viruses causes tight transmission bottlenecks

The transmission bottleneck describes the number of viral particles that initiate an infection in a new host. Previous studies have used genome sequence data to suggest that transmission bottlenecks for influenza and SARS-CoV-2 involve few viral particles, but the general principles of virus transmission are not fully understood. Here we show that, across a broad range of circumstances, tight transmission bottlenecks are a simple consequence of the physical process of airborne viral transmission. We use mathematical modelling to describe the physical process of the emission and inhalation of infectious particles, deriving the result that that the great majority of transmission bottlenecks involve few viral particles. While exceptions to this rule exist, the circumstances needed to create these exceptions are likely very rare. We thus provide a physical explanation for previous inferences of bottleneck size, while predicting that tight transmission bottlenecks prevail more generally in respiratory virus transmission.

Using power system modelling outputs to identify weather-induced extreme events in highly renewable systems

In highly renewable power systems the increased weather dependence can result in new resilience challenges, such as renewable energy droughts, or a lack of sufficient renewable generation at times of high demand. The weather conditions responsible for these challenges have been well-studied in the literature. However, in reality multi-day resilience challenges are triggered by complex interactions between high demand, low renewable availability, electricity transmission constraints and storage dynamics. We show these challenges cannot be rigorously understood from an exclusively power systems, or meteorological, perspective. We propose a new method that uses electricity shadow prices—obtained by a European power system model based on 40 years of reanalysis data—to identify the most difficult periods driving system investments. Such difficult periods are driven by large-scale weather conditions such as low wind and cold temperature periods of various lengths associated with stationary high pressure over Europe. However, purely meteorological approaches fail to identify which events lead to the largest system stress over the multi-decadal study period due to the influence of subtle transmission bottlenecks and storage issues across multiple regions. These extreme events also do not relate strongly to traditional weather patterns (such as Euro-Atlantic weather regimes or the North Atlantic Oscillation index). We therefore compile a new set of weather patterns to define energy system stress events which include the impacts of electricity storage and large-scale interconnection. Without interdisciplinary studies combining state-of-the-art energy meteorology and modelling, further strive for adequate renewable power systems will be hampered.

Modelling transmission dynamics and genomic diversity in a recombining parasite population.

The genomic diversity of a parasite population is shaped by its transmission dynamics but superinfection, cotranmission and recombination make this relationship complex and hard to analyse. This paper aims to simplify the problem by introducing the concept of a genomic transmission graph with three basic parameters: the effective number of hosts, the quantum of transmission and the crossing rate of transmission chains. This enables rapid simulation of coalescence times in a recombining parasite population with superinfection and cotransmission, and it also provides a mathematical framework for analysis of within-host variation. Taking malaria as an example, we use this theoretical model to examine how transmission dynamics and migration affect parasite genomic diversity, including the effective recombination rate and haplotypic metrics of recent common ancestry. We show how key transmission parameters can be inferred from deep sequencing data and as a proof of concept we estimate the Plasmodium falciparum transmission bottleneck. Finally we discuss the potential applications of this novel inferential framework in genomic surveillance for malaria control and elimination. Online tools for exploring the genomic transmission graph are available at d-kwiat.github.io/gtg.

Genomic Diversity in the Endosymbiotic Bacteria of Human Head Lice.

Insects have repeatedly forged symbioses with heritable microbes, gaining novel traits. For the microbe, the transition to symbioses can lead to the degeneration of the symbiont's genome through transmission bottlenecks, isolation, and the loss of DNA repair enzymes. However, some insect-microbial symbioses have persisted for millions of years, suggesting that natural selection slows genetic drift and maintains functional consistency between symbiont populations. By sampling in multiple countries, we examine genomic diversity within a symbiont species, a heritable symbiotic bacterium found only in human head lice. We find that human head louse symbionts contain genetic diversity that appears to have arisen contemporaneously with the appearance of anatomically modern humans within Africa and/or during the colonization of Eurasia by humans. We predict that the observed genetic diversity underlies functional differences in extant symbiont lineages, through the inactivation of genes involved in symbiont membrane construction. Furthermore, we find evidence of additional gene losses prior to the appearance of modern humans, also impacting the symbiont membrane. From this, we conclude that symbiont genome degeneration is proceeding, via gene inactivation and subsequent loss, in human head louse symbionts, while genomic diversity is maintained. Collectively, our results provide a look into the genomic diversity within a single symbiont species and highlight the shared evolutionary history of humans, lice, and bacteria.

Audio and Data Transmission using LIFI

Li-Fi stands for Light-Fidelity. LIFI technology is very new and was proposed by the German physicist Harald Haas in 2011. Light based communication system is the backbone of the future of the communication system. Li-Fi is a wireless technology that uses light emitting diodes (LEDs) for transmission of data. The development of the wireless communication leads to advance research in Li-Fi technology. The term Li-Fi states to visible light communication (VLC) technology that uses as medium to deliver high-speed communication in a fashion similar to Wi-Fi. Li-Fi comprises a wide range of frequencies and wavelengths, from the Infrared through visible and down to the Ultraviolet spectrum. The immense use of Li-Fi may solve some bottleneck of data transmission in Wi-Fi technology. With the innovation in technology and the number of users, the existing radio-wave spectrum fails to accommodate this need. To resolve the issues of scalability, availability and security, we have come up with the concept of transmitting data wirelessly through light using visible light communication (VLC) technology. The objective is to study and describe the Li-Fi technology. The improvement of the wireless communication leads to advance research in Li-Fi technology through Visible Light Communications (VLC) Technology.

Role for gene conversion in the evolution of cell-surface antigens of the malaria parasite Plasmodium falciparum.

While the malaria parasite Plasmodium falciparum has low average genome-wide diversity levels, likely due to its recent introduction from a gorilla-infecting ancestor (approximately 10,000 to 50,000 years ago), some genes display extremely high diversity levels. In particular, certain proteins expressed on the surface of human red blood cell-infecting merozoites (merozoite surface proteins (MSPs)) possess exactly 2 deeply diverged lineages that have seemingly not recombined. While of considerable interest, the evolutionary origin of this phenomenon remains unknown. In this study, we analysed the genetic diversity of 2 of the most variable MSPs, DBLMSP and DBLMSP2, which are paralogs (descended from an ancestral duplication). Despite thousands of available Illumina WGS datasets from malaria-endemic countries, diversity in these genes has been hard to characterise as reads containing highly diverged alleles completely fail to align to the reference genome. To solve this, we developed a pipeline leveraging genome graphs, enabling us to genotype them at high accuracy and completeness. Using our newly- resolved sequences, we found that both genes exhibit 2 deeply diverged lineages in a specific protein domain (DBL) and that one of the 2 lineages is shared across the genes. We identified clear evidence of nonallelic gene conversion between the 2 genes as the likely mechanism behind sharing, leading us to propose that gene conversion between diverged paralogs, and not recombination suppression, can generate this surprising genealogy; a model that is furthermore consistent with high diversity levels in these 2 genes despite the strong historical P. falciparum transmission bottleneck.

Electrolyte‐Gated Transistor Array (20 × 20) with Low‐Programming Interference Based on Coplanar Gate Structure for Unsupervised Learning

Compute‐in‐memory (CIM) is a pioneering approach using parallel data processing to eliminate traditional data transmission bottlenecks for faster, energy‐efficient data handling. Crossbar arrays with two‐terminal devices such as memristors and phase‐change memory are commonly employed in CIM, but they encounter challenges such as leakage current and increased power usage. Three‐terminal transistor arrays have potential solutions, yet large‐scale electrolyte‐gated transistors (EGTs) demonstrations are uncommon due to compatibility issues with existing photolithography processes. Herein, a 20 × 20 EGTs array is designed using indium‐gallium‐zinc‐oxide as the semiconductor channel and polyacrylonitrile (PAN) doped with C2F6LiNO4S2 as the electrolyte. Each transistor unit in the array can serve as a synapse, exhibiting a large conductance range, low energy consumption (6.984 fJ) for read–write operations, excellent repeatability, and quasilinear update characteristics. It has been confirmed that the EGTs array not only enables precise device programming but also virtually eliminates signal interference between neighboring devices during the programming process. Using 54 transistors in the EGTs array, unsupervised learning with a winner‐takes‐all neural network is successfully demonstrated. After 50 training iterations, the neural network achieves perfect 100% accuracy in classifying test‐set letters. The work demonstrates the potential of EGTs for constructing large‐scale integration synaptic array toward efficient computing architectures.

Continuous timely monitoring of core temperature with two wearable devices in pediatric patients undergoing chemotherapy for cancer – a comparison study

PurposePediatric patients with cancer often develop chemotherapy-induced fever in neutropenia (FN), requiring emergency broad-spectrum antibiotics. Continuous temperature monitoring can lead to earlier FN detection and therapy with improved outcomes. We aimed to compare the feasibility of continuous core temperature monitoring with timely data availability between two wearable devices (WDs) in pediatric oncology patients undergoing chemotherapy.MethodsIn this prospective observational two-center study, 20 patients (median age: 8 years) undergoing chemotherapy simultaneously wore two WDs (CORE®, Everion®) for 14 days. The predefined goal was core temperature recorded in sufficient quality and available within ≤ 30 min during ≥ 18/24 h for ≥ 7/14 days in more than 15 patients.ResultsMore patients reached the goal with CORE® (n = 13) versus Everion® (n = 3) (difference, 50% p < 0.001). After correcting for the transmission bottleneck caused by two WDs transmitting via one gateway, these numbers increased (n = 15 versus n = 14; difference, 5%; p = 0.69). CORE® measurements corresponded better to ear temperatures (n = 528; mean bias, − 0.07 °C; mean absolute difference, 0.35 °C) than Everion® measurements (n = 532; − 1.06 °C; 1.10 °C). Acceptance rates for the WDs were 95% for CORE® and 89% for Everion®.ConclusionThe CORE® fulfilled the predefined feasibility criterion (15 of 20 patients) after correction for transmission bottleneck, and the Everion® nearly fulfilled it. Continuous core temperature recording of good quality and with timely data availability was feasible from preschool to adolescent patients undergoing chemotherapy for cancer. These results encourage the design of randomized controlled trials on continuously monitored core temperature in pediatric patients.Trial registration.ClinicalTrials.gov (NCT04914702) on June 7, 2021.

Latitude-Adaptive Integer Bit Allocation for Quantization of Omnidirectional Images

Omnidirectional images have gained significant popularity and drawn great attention nowadays, which poses challenges to omnidirectional image processing in solving the bottleneck of storage and transmission. Projecting onto a two-dimensional image plane is generally used to compress an omnidirectional image. However, the most commonly used projection format, the equirectangular projection (ERP), results in a significant amount of redundant samples in the polar areas, thus incurring extra bitrate and geometric distortion. We derive the optimal latitude-adaptive bit allocation for each image tile. Subsequently, we propose a greedy algorithm for non-negative integer bit allocation (NNIBA) for non-uniform quantization under an omnidirectional image quality metric WMSE. In our experiment, we design quantization tables based on JPEG and compare our approach with other sampling-related methods. Our method achieves an average bit saving of 7.9% compared with JPEG while outperforming other sampling-related methods. Besides, we compare our non-uniform quantization approach with two proposed bit allocation methods, achieving an average improvement of 0.35 dB and 2.66 dB under WS-PSNR, respectively. The visual quality assessment also confirms the superiority of our method.

Within-host evolution of SARS-CoV-2: how often are de novo mutations transmitted from symptomatic infections?

Despite a relatively low mutation rate, the large number of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections has allowed for substantial genetic change, leading to a multitude of emerging variants. Using a recently determined mutation rate (per site replication), as well as within-host parameter estimates for symptomatic SARS-CoV-2 infection, we apply a stochastic transmission-bottleneck model to describe the survival probability of de novo SARS-CoV-2 mutations as a function of bottleneck size and selection coefficient. For narrow bottlenecks, we find that mutations affecting per-target-cell attachment rate (with phenotypes associated with fusogenicity and ACE2 binding) have similar transmission probabilities to mutations affecting viral load clearance (with phenotypes associated with humoral evasion). We further find that mutations affecting the eclipse rate (with phenotypes associated with reorganization of cellular metabolic processes and synthesis of viral budding precursor material) are highly favoured relative to all other traits examined. We find that mutations leading to reduced removal rates of infected cells (with phenotypes associated with innate immune evasion) have limited transmission advantage relative to mutations leading to humoral evasion. Predicted transmission probabilities, however, for mutations affecting innate immune evasion are more consistent with the range of clinically estimated household transmission probabilities for de novo mutations. This result suggests that although mutations affecting humoral evasion are more easily transmitted when they occur, mutations affecting innate immune evasion may occur more readily. We examine our predictions in the context of a number of previously characterized mutations in circulating strains of SARS-CoV-2. Our work offers both a null model for SARS-CoV-2 mutation rates and predicts which aspects of viral life history are most likely to successfully evolve, despite low mutation rates and repeated transmission bottlenecks.