The COVID-19 pandemic disrupted health systems and economies throughout the world during 2020 and was particularly devastating for the United States, which experienced the highest numbers of reported ...cases and deaths during 2020
. Many of the epidemiological features responsible for observed rates of morbidity and mortality have been reported
; however, the overall burden and characteristics of COVID-19 in the United States have not been comprehensively quantified. Here we use a data-driven model-inference approach to simulate the pandemic at county-scale in the United States during 2020 and estimate critical, time-varying epidemiological properties underpinning the dynamics of the virus. The pandemic in the United States during 2020 was characterized by national ascertainment rates that increased from 11.3% (95% credible interval (CI): 8.3-15.9%) in March to 24.5% (18.6-32.3%) during December. Population susceptibility at the end of the year was 69.0% (63.6-75.4%), indicating that about one third of the US population had been infected. Community infectious rates, the percentage of people harbouring a contagious infection, increased above 0.8% (0.6-1.0%) before the end of the year, and were as high as 2.4% in some major metropolitan areas. By contrast, the infection fatality rate fell to 0.3% by year's end.
For influenza forecasts generated using dynamical models, forecast inaccuracy is partly attributable to the nonlinear growth of error. As a consequence, quantification of the nonlinear error ...structure in current forecast models is needed so that this growth can be corrected and forecast skill improved. Here, we inspect the error growth of a compartmental influenza model and find that a robust error structure arises naturally from the nonlinear model dynamics. By counteracting these structural errors, diagnosed using error breeding, we develop a new forecast approach that combines dynamical error correction and statistical filtering techniques. In retrospective forecasts of historical influenza outbreaks for 95 US cities from 2003 to 2014, overall forecast accuracy for outbreak peak timing, peak intensity and attack rate, are substantially improved for predicted lead times up to 10 weeks. This error growth correction method can be generalized to improve the forecast accuracy of other infectious disease dynamical models.Inaccuracy of influenza forecasts based on dynamical models is partly due to nonlinear error growth. Here the authors address the error structure of a compartmental influenza model, and develop a new improved forecast approach combining dynamical error correction and statistical filtering techniques.
Abstract
Background
Nonpharmaceutical interventions (NPIs) have been implemented to suppress transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Evidence indicates that NPIs ...against coronavirus disease 2019 (COVID-19) may also have effects on transmission of seasonal influenza.
Methods
In this study, we use an absolute humidity-driven susceptible-infectious-recovered-susceptible (SIRS) model to quantify the reduction of influenza incidence and transmission in the United States and US Department of Health and Human Services regions after implementation of NPIs in 2020. We investigate long-term effect of NPIs on influenza incidence by projecting influenza transmission at the national scale over the next 5 years, using the SIRS model.
Results
We estimate that incidence of influenza A/H1 and B, which circulated in early 2020, was reduced by more than 60% in the United States during the first 10 weeks following implementation of NPIs. The reduction of influenza transmission exhibits clear geographical variation. After the control measures are relaxed, potential accumulation of susceptibility to influenza infection may lead to a large outbreak, the scale of which may be affected by length of the intervention period and duration of immunity to influenza.
Conclusions
Healthcare systems need to prepare for potential influenza patient surges and advocate vaccination and continued precautions.
Incidence of influenza A/H1 and B were reduced by more than 60% in the United States during the first 10 weeks following implementation of NPIs. Potential large outbreaks of influenza may occur after the relaxation of NPIs.
Improved understanding of the effects of meteorological conditions on the transmission of SARS-CoV-2, the causative agent for COVID-19 disease, is needed. Here, we estimate the relationship between ...air temperature, specific humidity, and ultraviolet radiation and SARS-CoV-2 transmission in 2669 U.S. counties with abundant reported cases from March 15 to December 31, 2020. Specifically, we quantify the associations of daily mean temperature, specific humidity, and ultraviolet radiation with daily estimates of the SARS-CoV-2 reproduction number (R
) and calculate the fraction of R
attributable to these meteorological conditions. Lower air temperature (within the 20-40 °C range), lower specific humidity, and lower ultraviolet radiation were significantly associated with increased R
. The fraction of R
attributable to temperature, specific humidity, and ultraviolet radiation were 3.73% (95% empirical confidence interval eCI: 3.66-3.76%), 9.35% (95% eCI: 9.27-9.39%), and 4.44% (95% eCI: 4.38-4.47%), respectively. In total, 17.5% of R
was attributable to meteorological factors. The fractions attributable to meteorological factors generally were higher in northern counties than in southern counties. Our findings indicate that cold and dry weather and low levels of ultraviolet radiation are moderately associated with increased SARS-CoV-2 transmissibility, with humidity playing the largest role.
Estimation of the prevalence and contagiousness of undocumented novel coronavirus severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infections is critical for understanding the overall ...prevalence and pandemic potential of this disease. Here, we use observations of reported infection within China, in conjunction with mobility data, a networked dynamic metapopulation model, and Bayesian inference, to infer critical epidemiological characteristics associated with SARS-CoV-2, including the fraction of undocumented infections and their contagiousness. We estimate that 86% of all infections were undocumented 95% credible interval (CI): 82-90% before the 23 January 2020 travel restrictions. The transmission rate of undocumented infections per person was 55% the transmission rate of documented infections (95% CI: 46-62%), yet, because of their greater numbers, undocumented infections were the source of 79% of the documented cases. These findings explain the rapid geographic spread of SARS-CoV-2 and indicate that containment of this virus will be particularly challenging.
6681 PaNDR express times Tee, Pei Sen
Archives of disease in childhood,
08/2024, Letnik:
109, Številka:
Suppl 1
Journal Article
Recenzirano
ObjectivesSick neonates in local neonatal units and special care baby units depend on the expertise of regional neonatal transport teams and efficient systems to ensure their safe and timely transfer ...to a specialised centre. Efficient and timely dispatch of neonatal transport teams to these local units is crucial to guarantee the safe and prompt transport of newborns in need of specialised attention. The Paediatric and Neonatal Decision Support and Retrieval Service (PaNDR) is the neonatal transport service for the East of England. The National Transport Group (NTG) benchmark for time-critical unplanned emergency team dispatch is 60 minutes. This study presents an investigation into the dispatch time of PaNDR neonatal team.MethodsThis is a retrospective audit investigating the dispatch times of PaNDR neonatal team to unplanned emergency transfers during specific months in year 2022; January, April, and October. The timing measurements were derived from two distinct starting points: The time of referral for an unplanned emergency transfer to Emergency Bed Service (EBS) or the time of transition from a decision support case to an emergency transfer. Instances of unplanned emergency transfers that occurred when the neonatal team was not at their base location were excluded from the study.ResultsDuring the three-month period, the PaNDR neonatal team carried out a total of 97 unplanned emergency transfers, out of which 64 occurred while the team was at their base location. The study revealed that one-third (33%) of these transfers were accomplished within 30 minutes and 83% were within 1 hour. The median dispatch time was 45.5 minutes. Table 1 illustrates the dispatch durations for all of these transfers.The exclusion of the months of March and September was deliberate, as these are months when new doctors undergo rotations within the department, potentially impacting the dispatch process.Abstract 6681 Table 1ConclusionThis study highlights a large variation in dispatch times when the neonatal team was stationed at base. It is imperative to address this by scrutinising the dispatch processes when a referral is initiated with the aim to standardise and improve dispatch times. Numerous strategies have been proposed to address this issue, including logging onto computers at the start of the shift and prepacking equipment rucksack. We intend to re-evaluate the impact of these changes through a re-audit in the upcoming year.
Transition metal-catalyzed organic electrochemistry is a rapidly growing research area owing in part to the ability of metal catalysts to alter the selectivity of a given transformation. This ...conversion mainly focuses on transition metal-catalyzed anodic oxidation and cathodic reduction and great progress has been achieved in both areas. Typically, only one of the half-cell reactions is involved in the organic reaction while a sacrificial reaction occurs at the counter electrode, which is inherently wasteful since one electrode is not being used productively. Recently, transition metal-catalyzed paired electrolysis that makes use of both anodic oxidation and cathodic reduction has attracted much attention. This perspective highlights the recent progress of each type of electrochemical reaction and relatively focuses on the transition metal-catalyzed paired electrolysis, showcasing that electrochemical reactions involving transition metal catalysis have advantages over conventional reactions in terms of controlling the reaction activity and selectivity and figuring out that transition metal-catalyzed paired electrolysis is an important direction of organic electrochemistry in the future and offers numerous opportunities for new and improved organic reaction methods.
Transition metal-catalyzed organic electrochemistry is a rapidly growing research area owing in part to the ability of metal catalysts to alter the selectivity of a given transformation.
Influenza-like illness (ILI) is a commonly measured syndromic signal representative of a range of acute respiratory infections. Reliable forecasts of ILI can support better preparation for patient ...surges in healthcare systems. Although ILI is an amalgamation of multiple pathogens with variable seasonal phasing and attack rates, most existing process-based forecasting systems treat ILI as a single infectious agent. Here, using ILI records and virologic surveillance data, we show that ILI signal can be disaggregated into distinct viral components. We generate separate predictions for six contributing pathogens (influenza A/H1, A/H3, B, respiratory syncytial virus, and human parainfluenza virus types 1-2 and 3), and develop a method to forecast ILI by aggregating these predictions. The relative contribution of each pathogen to the total ILI signal is estimated using a Markov Chain Monte Carlo (MCMC) method upon forecast aggregation. We find highly variable overall contributions from influenza type A viruses across seasons, but relatively stable contributions for the other pathogens. Using historical data from 1997 to 2014 at US national and regional levels, the proposed forecasting system generates improved predictions of both seasonal and near-term targets relative to a baseline method that simulates ILI as a single pathogen. The hierarchical forecasting system can generate predictions for each viral component, as well as infer and predict their contributions to ILI, which may additionally help physicians determine the etiological causes of ILI in clinical settings.
A scalable enantioselective nickel-catalyzed electrochemical reductive homocoupling of aryl bromides has been developed, affording enantioenriched axially chiral biaryls in good yield under mild ...conditions using electricity as a reductant in an undivided cell. Common metal reductants such as Mn or Zn powder resulted in significantly lower yields in the absence of electric current under otherwise identical conditions, underscoring the enhanced reactivity provided by the combination of transition metal catalysis and electrochemistry.
A tightly coupled integrated navigation system (TCINS) for hypersonic vehicles is proposed when the satellite signals are disturbed. Firstly, the architecture of the integrated navigation system for ...the hypersonic vehicle is introduced. This system applies fiber SINS, BeiDou satellite receiver (BDS) and System On a Parogrammable Chip (SOPC) missile-born computer. Subsequently, the SINS mechanization for hypersonic vehicle is presented. The J2 model is employed for the normal gravity of the near space. An algorithm for updating the attitude, velocity and position is designed. State equations and measurement equations of SINS/BDS tightly coupled integrated navigation for hypersonic vehicle are given, and a scheme of validity for satellite data is designed. Finally, the SINS/BDS tightly coupled vehicle field tests and hardware-in-the-loop (HWIL) simulation tests are carried out. The vehicle field test and HWIL simulation results show that the heading angle error of tightly coupled integrated navigation is within 0.2°, the pitch and roll angle errors are within 0.05°, the maximum velocity error is 0.3 m/s, and the maximum position error is 10 m.
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