Responding to an outbreak of a novel coronavirus agent of coronavirus disease 2019 (COVID-19) in December 2019, China banned travel to and from Wuhan city on 23 January 2020 and implemented a ...national emergency response. We investigated the spread and control of COVID-19 using a data set that included case reports, human movement, and public health interventions. The Wuhan shutdown was associated with the delayed arrival of COVID-19 in other cities by 2.91 days. Cities that implemented control measures preemptively reported fewer cases on average (13.0) in the first week of their outbreaks compared with cities that started control later (20.6). Suspending intracity public transport, closing entertainment venues, and banning public gatherings were associated with reductions in case incidence. The national emergency response appears to have delayed the growth and limited the size of the COVID-19 epidemic in China, averting hundreds of thousands of cases by 19 February (day 50).
The ongoing coronavirus disease 2019 (COVID-19) outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions were undertaken to mitigate the epidemic and prevent ...the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, affected COVID-19 spread in China. We used real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation in transmission in cities across China and to ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was explained well by human mobility data. After the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside of Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19.
We present a new open source, extensible and flexible software platform for Bayesian evolutionary analysis called BEAST 2. This software platform is a re-design of the popular BEAST 1 platform to ...correct structural deficiencies that became evident as the BEAST 1 software evolved. Key among those deficiencies was the lack of post-deployment extensibility. BEAST 2 now has a fully developed package management system that allows third party developers to write additional functionality that can be directly installed to the BEAST 2 analysis platform via a package manager without requiring a new software release of the platform. This package architecture is showcased with a number of recently published new models encompassing birth-death-sampling tree priors, phylodynamics and model averaging for substitution models and site partitioning. A second major improvement is the ability to read/write the entire state of the MCMC chain to/from disk allowing it to be easily shared between multiple instances of the BEAST software. This facilitates checkpointing and better support for multi-processor and high-end computing extensions. Finally, the functionality in new packages can be easily added to the user interface (BEAUti 2) by a simple XML template-based mechanism because BEAST 2 has been re-designed to provide greater integration between the analysis engine and the user interface so that, for example BEAST and BEAUti use exactly the same XML file format.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Phylogeographic methods aim to infer migration trends and the history of sampled lineages from genetic data. Applications of phylogeography are broad, and in the context of pathogens include the ...reconstruction of transmission histories and the origin and emergence of outbreaks. Phylogeographic inference based on bottom-up population genetics models is computationally expensive, and as a result faster alternatives based on the evolution of discrete traits have become popular. In this paper, we show that inference of migration rates and root locations based on discrete trait models is extremely unreliable and sensitive to biased sampling. To address this problem, we introduce BASTA (BAyesian STructured coalescent Approximation), a new approach implemented in BEAST2 that combines the accuracy of methods based on the structured coalescent with the computational efficiency required to handle more than just few populations. We illustrate the potentially severe implications of poor model choice for phylogeographic analyses by investigating the zoonotic transmission of Ebola virus. Whereas the structured coalescent analysis correctly infers that successive human Ebola outbreaks have been seeded by a large unsampled non-human reservoir population, the discrete trait analysis implausibly concludes that undetected human-to-human transmission has allowed the virus to persist over the past four decades. As genomics takes on an increasingly prominent role informing the control and prevention of infectious diseases, it will be vital that phylogeographic inference provides robust insights into transmission history.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Cases of a novel coronavirus were first reported in Wuhan, Hubei province, China, in December 2019 and have since spread across the world. Epidemiological studies have indicated human-to-human ...transmission in China and elsewhere. To aid the analysis and tracking of the COVID-19 epidemic we collected and curated individual-level data from national, provincial, and municipal health reports, as well as additional information from online reports. All data are geo-coded and, where available, include symptoms, key dates (date of onset, admission, and confirmation), and travel history. The generation of detailed, real-time, and robust data for emerging disease outbreaks is important and can help to generate robust evidence that will support and inform public health decision making.
Objective
The objective of this study was to assess the impact of treatment with dexamethasone, remdesivir or both on neurological complications in acute coronavirus diease 2019 (COVID‐19).
Methods
...We used observational data from the International Severe Acute and emerging Respiratory Infection Consortium World Health Organization (WHO) Clinical Characterization Protocol, United Kingdom. Hospital inpatients aged ≥18 years with laboratory‐confirmed severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2) infection admitted between January 31, 2020, and June 29, 2021, were included. Treatment allocation was non‐blinded and performed by reporting clinicians. A propensity scoring methodology was used to minimize confounding. Treatment with remdesivir, dexamethasone, or both was assessed against the standard of care. The primary outcome was a neurological complication occurring at the point of death, discharge, or resolution of the COVID‐19 clinical episode.
Results
Out of 89,297 hospital inpatients, 64,088 had severe COVID‐19 and 25,209 had non‐hypoxic COVID‐19. Neurological complications developed in 4.8% and 4.5%, respectively. In both groups, neurological complications were associated with increased mortality, intensive care unit (ICU) admission, worse self‐care on discharge, and time to recovery. In patients with severe COVID‐19, treatment with dexamethasone (n = 21,129), remdesivir (n = 1,428), and both combined (n = 10,846) were associated with a lower frequency of neurological complications: OR = 0.76 (95% confidence interval CI = 0.69–0.83), OR = 0.69 (95% CI = 0.51–0.90), and OR = 0.54 (95% CI = 0.47–0.61), respectively. In patients with non‐hypoxic COVID‐19, dexamethasone (n = 2,580) was associated with less neurological complications (OR = 0.78, 95% CI = 0.62–0.97), whereas the dexamethasone/remdesivir combination (n = 460) showed a similar trend (OR = 0.63, 95% CI = 0.31–1.15).
Interpretation
Treatment with dexamethasone, remdesivir, or both in patients hospitalized with COVID‐19 was associated with a lower frequency of neurological complications in an additive manner, such that the greatest benefit was observed in patients who received both drugs together. ANN NEUROL 2023;93:88–102
Exploiting pathogen genomes to reconstruct transmission represents a powerful tool in the fight against infectious disease. However, their interpretation rests on a number of simplifying assumptions ...that regularly ignore important complexities of real data, in particular within-host evolution and non-sampled patients. Here we propose a new approach to transmission inference called SCOTTI (Structured COalescent Transmission Tree Inference). This method is based on a statistical framework that models each host as a distinct population, and transmissions between hosts as migration events. Our computationally efficient implementation of this model enables the inference of host-to-host transmission while accommodating within-host evolution and non-sampled hosts. SCOTTI is distributed as an open source package for the phylogenetic software BEAST2. We show that SCOTTI can generally infer transmission events even in the presence of considerable within-host variation, can account for the uncertainty associated with the possible presence of non-sampled hosts, and can efficiently use data from multiple samples of the same host, although there is some reduction in accuracy when samples are collected very close to the infection time. We illustrate the features of our approach by investigating transmission from genetic and epidemiological data in a Foot and Mouth Disease Virus (FMDV) veterinary outbreak in England and a Klebsiella pneumoniae outbreak in a Nepali neonatal unit. Transmission histories inferred with SCOTTI will be important in devising effective measures to prevent and halt transmission.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background
Age‐related muscle dysfunctions are common disorders resulting in poor quality of life in the elderly. Probiotic supplementation is a potential strategy for preventing age‐related ...sarcopenia as evidence suggests that probiotics can enhance muscle function via the gut–muscle axis. However, the effects and mechanisms of probiotics in age‐related sarcopenia are currently unknown. In this study, we examined the effects of Lactobacillus casei Shirota (LcS), a probiotic previously reported to improve muscle function in young adult mice.
Methods
We administered LcS (1 × 108 or 1 × 109 CFU/mouse/day) by oral gavage to senescence‐accelerated mouse prone‐8 mice for 12 weeks (16‐ to 28‐week‐old). Sixteen‐week‐old and 28‐week‐old SMAP8 mice were included as non‐aged and aged controls, respectively. Muscle condition was evaluated using dual‐energy X‐ray absorptiometry for muscle mass, holding impulse and grip strength tests for muscle strength, and oxygen consumption rate, gene expressions of mitochondrial biogenesis, and mitochondrial number assays for mitochondria function. Inflammatory cytokines were determined using enzyme‐linked immunosorbent assay. Gas chromatography–mass spectrometry was utilized to measure the short‐chain fatty acid levels. The gut microbiota was analysed based on the data of 16S rRNA gene sequencing of mouse stool.
Results
The LcS supplementation reduced age‐related declines in muscle mass (>94.6%, P < 0.04), strength (>66% in holding impulse and >96.3% in grip strength, P < 0.05), and mitochondrial function (P < 0.05). The concentration of short‐chain fatty acids (acetic, isobutyric, butyric, penic, and hexanoic acid) was recovered by LcS (>65.9% in the mice given high dose of LcS, P < 0.05) in the aged mice, and LcS attenuated age‐related increases in inflammation (P < 0.05) and reactive oxygen species (>89.4%, P < 0.001). The high dose of LcS supplementation was also associated with distinct microbiota composition as indicated by the separation of groups in the beta‐diversity analysis (P = 0.027). LcS supplementation altered predicted bacterial functions based on the gut microbiota. Apoptosis (P = 0.026), p53 signalling (P = 0.017), and non‐homologous end‐joining (P = 0.031) were significantly reduced, whereas DNA repair and recombination proteins (P = 0.043), RNA polymerase (P = 0.008), and aminoacyl‐tRNA biosynthesis (P = 0.003) were increased. Finally, the genera enriched by high‐dose LcS linear discriminant analysis (LDA) score > 2.0 were positively correlated with healthy muscle and physiological condition (P < 0.05), while the genera enriched in aged control mice (LDA score > 2.0) were negatively associated with healthy muscle and physiological condition (P < 0.05).
Conclusions
Lactobacillus casei Shirota represents an active modulator that regulates the onset and progression of age‐related muscle impairment potentially via the gut–muscle axis.
People with chronic obstructive pulmonary disease, cardiovascular disease, or hypertension have a high risk of developing severe coronavirus disease 2019 (COVID-19) and of COVID-19 mortality. ...However, the association between long-term exposure to air pollutants, which increases cardiopulmonary damage, and vulnerability to COVID-19 has not yet been fully established. We collected data of confirmed COVID-19 cases during the first wave of the epidemic in mainland China. We fitted a generalized linear model using city-level COVID-19 cases and severe cases as the outcome, and long-term average air pollutant levels as the exposure. Our analysis was adjusted using several variables, including a mobile phone dataset, covering human movement from Wuhan before the travel ban and movements within each city during the period of the emergency response. Other variables included smoking prevalence, climate data, socioeconomic data, education level, and number of hospital beds for 324 cities in China. After adjusting for human mobility and socioeconomic factors, we found an increase of 37.8% (95% confidence interval CI: 23.8%–52.0%), 32.3% (95% CI: 22.5%–42.4%), and 14.2% (7.9%–20.5%) in the number of COVID-19 cases for every 10-μg/m3 increase in long-term exposure to NO2, PM2.5, and PM10, respectively. However, when stratifying the data according to population size, the association became non-significant. The present results are derived from a large, newly compiled and geocoded repository of population and epidemiological data relevant to COVID-19. The findings suggested that air pollution may be related to population vulnerability to COVID-19 infection, although the extent to which this relationship is confounded by city population density needs further exploration.
Display omitted
•Long-term exposure to NO2, PM2.5 or PM10 corresponded to COVID-19 case numbers.•This study focused on the period in the first wave of China.•The nationwide COVID-19 cases and severe infections in 324 cities of China were included.•The association may be confounded by city population size and density.
This research reported a national-level association with long-term exposure to air pollutants and COVID-19 cases covering 324 cities in China.
Evolutionary dynamics of language systems Greenhill, Simon J.; Wu, Chieh-Hsi; Hua, Xia ...
Proceedings of the National Academy of Sciences - PNAS,
10/2017, Letnik:
114, Številka:
42
Journal Article
Recenzirano
Odprti dostop
Understanding how and why language subsystems differ in their evolutionary dynamics is a fundamental question for historical and comparative linguistics. One key dynamic is the rate of language ...change. While it is commonly thought that the rapid rate of change hampers the reconstruction of deep language relationships beyond 6,000–10,000 y, there are suggestions that grammatical structures might retainmore signal over time than other subsystems, such as basic vocabulary. In this study, we use a Dirichlet process mixture model to infer the rates of change in lexical and grammatical data from 81 Austronesian languages. We show that, on average, most grammatical features actually change faster than items of basic vocabulary. The grammatical data show less schismogenesis, higher rates of homoplasy, and more bursts of contact-induced change than the basic vocabulary data. However, there is a core of grammatical and lexical features that are highly stable. These findings suggest that different subsystems of language have differing dynamics and that careful, nuanced models of language change will be needed to extract deeper signal from the noise of parallel evolution, areal readaptation, and contact.
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