Metabolic regulatory network kinetic modeling with multiple isotopic tracers for iPSCs.

The rapidly expanding market for regenerative medicines and cell therapies highlights the need to advance the understanding of cellular metabolisms and improve the prediction of cultivation production process for human induced pluripotent stem cells (iPSCs). In this paper, a metabolic kinetic model was developed to characterize the underlying mechanisms of iPSC culture process, which can predict cell response to environmental perturbation and support process control. This model focuses on the central carbon metabolic network, including glycolysis, pentose phosphate pathway, tricarboxylic acid cycle, and amino acid metabolism, which plays a crucial role to support iPSC proliferation. Heterogeneous measures of extracellular metabolites and multiple isotopic tracers collected under multiple conditions were used to learn metabolic regulatory mechanisms. Systematic cross-validation confirmed the model's performance in terms of providing reliable predictions on cellular metabolism and culture process dynamics under various culture conditions. Thus, the developed mechanistic kinetic model can support process control strategies to strategically select optimal cell culture conditions at different times, ensure cell product functionality, and facilitate large-scale manufacturing of regenerative medicines and cell therapies.

A Dynamic Prognostic Model for Identifying Vulnerable COVID-19 Patients at High Risk of Rapid Deterioration.

PURPOSE: We aimed to validate and, if performance was unsatisfactory, update the previously published prognostic model to predict clinical deterioration in patients hospitalized for COVID-19, using data following vaccine availability. METHODS: Using electronic health records of patients ≥18 years, with laboratory-confirmed COVID-19, from a large care-delivery network in Massachusetts, USA, from March 2020 to November 2021, we tested the performance of the previously developed prediction model and updated the prediction model by incorporating data after availability of COVID-19 vaccines. We randomly divided data into development (70%) and validation (30%) cohorts. We built a model predicting worsening in a published severity scale in 24 h by LASSO regression and evaluated performance by c-statistic and Brier score. RESULTS: Our study cohort consisted of 8185 patients (Development: 5730 patients [mean age: 62; 44% female] and Validation: 2455 patients [mean age: 62; 45% female]). The previously published model had suboptimal performance using data after November 2020 (N = 4973, c-statistic = 0.60. Brier score = 0.11). After retraining with the new data, the updated model included 38 predictors including 18 changing biomarkers. Patients hospitalized after Jun 1st, 2021 (when COVID-19 vaccines became widely available in Massachusetts) were younger and had fewer comorbidities than those hospitalized before. The c-statistic and Brier score were 0.77 and 0.13 in the development cohort, and 0.73 and 0.14 in the validation cohort. CONCLUSION: The characteristics of patients hospitalized for COVID-19 differed substantially over time. We developed a new dynamic model for rapid progression with satisfactory performance in the validation set.

"It Takes a Village": Reflections from participants after a Hispanic community-based health promotion program.

BACKGROUND: Physical activity (PA) among Hispanic and other minority adolescents in the U.S. lag behind White, non-Hispanic adolescents. Previous studies have examined the beneficial impact of culturally informed, community-based health programs within the Hispanic community on PA levels. There is a need for longer term follow up to determine the impact on family and individual habits over time. Our study aims to explore the aspects of a two-year PA and nutrition program, Families Inspired Together 4 Youth Empowered to Succeed (FIT4YES), that continue to influence family health habits and child development. METHODS: Community-based focus groups were held in Milwaukee, WI with Hispanic parent participants of the FIT4YES program three years after program conclusion. A semi-structured guide of open-ended questions was used to facilitate the discussion of the lasting impact of FIT4YES. Each group was audio recorded, transcribed, and translated from Spanish when necessary. Four student researchers utilized a grounded theory qualitative approach to identify overarching themes. RESULTS: Three focus groups with 16 total parents (N = 16) spoke about the program. Three overarching themes emerged from the transcripts indicating that cultural exposure, relationships, and self-growth were necessary for families to sustain the healthy behaviors promoted in FIT4YES. Specifically, parents discussed increased comfort levels with their children participating in school sports, the impact of shared experiences with community members, and continued skills initially taught and practiced during active programming. CONCLUSIONS: Our group adapted our previously published model to a "post-program" state that incorporated the major themes and sub-themes with levels of the social-ecological model. Although the FIT4YES program ended, multiple ideals instilled by the program continued, we believe, due to the common themes illustrated by our model. This study utilized a community check-in approach to gain insight into the long-term impacts of the FIT4YES program. We propose three recommendations for consideration in the creation of community-based health programs: utilize dynamic, culturally appropriate components based on the intended community; understand the strength of the program as a whole is dependent on the strength of each individual component; and incorporate an anchor institution for consistency and trust within the community.

Torsional Vibration Analysis Using Rotational Laser Vibrometers.

Torsional vibration is a critical phenomenon in rotor dynamics. It consists of an oscillating movement of the shaft and causes failures in multiple oscillating fields of application. This type of vibration is more difficult to measure than lateral vibration. Torsional vibrometers are generally invasive and require a complicated setup, as well as being inconvenient for field measurements. One of the most reliable, non-invasive, and transportable measuring techniques involves the laser torsional vibrometer. For this research, two laser heads with different measurement capabilities were utilized. An experimental test rig was used to perform a relative calibration of the two laser vibrometers. The frequency of the acting force and the rotation speed of the shaft vary in the same range, which is commonly found in rotating machines. Finally, experimental measurements of torsional vibrations using laser vibrometers were compared with numerical results from a 1D finite element model of the same test rig. The main outcome of this paper is the definition of a reliable measuring procedure to exploit two laser vibrometers for detecting torsional mode-shapes and natural frequencies on real machines. The relative calibration of two different measuring heads is described in detail, and the procedure was fundamental to properly correlate measuring signals in two machine sections. A good correspondence between the numerical and experimental results was found.

The Influence of Nonlinear High-Intensity Dynamic Processes on the Standing Wave Precession of a Non-Ideal Hemispherical Resonator.

The properties of small size, low noise, high performance and no wear-out have made the hemispherical resonator gyroscope a good choice for high-value space missions. To enhance the precision of the hemispherical resonator gyroscope for use in tasks with large angular velocities and angular accelerations, this paper investigates the standing wave precession of a non-ideal hemispherical resonator under nonlinear high-intensity dynamic conditions. Based on the thin shell theory of elasticity, a dynamic model of a hemispherical resonator is established by using Lagrange's second kind equation. Then, the dynamic model is equivalently transformed into a simple harmonic vibration model of a point mass in two-dimensional space, which is analyzed using a method of averaging that separates the slow variables from the fast variables. The results reveal that taking the nonlinear terms about the square of the angular velocity and the angular acceleration in the dynamic equation into account can weaken the influence of the 4th harmonic component of a mass defect on standing wave drift, and the extent of this weakening effect varies with the dimensions of the mass defects, which is very important for steering the development of the high-precision hemispherical resonator gyroscope.

Bioremediation experiments and dynamic model of petroleum hydrocarbon contaminated soil.

Clarifying the occurrence and morphological characteristics of petroleum hydrocarbons (PHs) in soil can facilitate a comprehensive understanding of their migration and transformation patterns in soil/sediment. Additionally, by establishing the dynamic transformation process of each occurrence state, the ecological impact and environmental risk associated with PHs in soil/sediment can be assessed more precisely. The adsorption experiments and closed static incubation experiments was carried out to explore the PHs degradation and fraction distribution in aged contaminated soil under two remediation scenarios of natural attenuation (NA) and bioaugmentation (BA) by exogenous bacteria through a new sequential extraction method based on Tenax-TA, Hydroxypropyl-ß-cyclodextrin and Rhamnolipid (HPCD/RL), accelerated solvent extractor (ASE) unit and alkaline hydrolysis extraction. The adsorption experiment results illustrated that bioaugmentation could promote the desorption of PHs in the adsorption phase, and the soil-water partition coefficient Kd decreased from 0.153 L/g to 0.092 L/g. The incubation experiment results showed that compared with natural attenuation, bioaugmentation could improve the utilization of PHs in aged soil and promote the generation of non-extractable hydrocarbons. On the 90th day of the experiment, the concentrations of weakly adsorbed hydrocarbons in the natural attenuation and bioaugmentation experimental groups decreased by 46.44% and 87.07%, respectively, while the concentrations of strongly adsorbed hydrocarbons and non-extractable hydrocarbons increased by 77.93%, 182.14%, and 80.91%, and 501.19%, respectively, compared their initial values. We developed a novel dynamic model and inverted the kinetic parameters of the model by the parameter scanning function and the Markov Chain Monte Carlo (MCMC) method based on the Bayesian approach in COMSOL Multiphysics® finite element software combined with experimental data. There was a good linear relationship between experimental interpolation data and model prediction data. The R2 for the concentrations of weakly adsorbed hydrocarbons ranged from 0.9953 to 0.9974, for strongly adsorbed hydrocarbons from 0.9063 to 0.9756, and for non-extractable hydrocarbons from 0.9931 to 0.9982. These extremely high correlation coefficients demonstrate the high accuracy of the parameters calculated using the Bayesian inversion method.

A dynamic one-dimensional model for simulating unsteady air-water stratified flow in sewer pipes.

Ventilation is paramount in sanitary and stormwater sewer systems to mitigate odor problems and avert pressure surges. Existing numerical models have constraints in practical applications in actual sewer systems due to insufficient airflow modeling or suitability only for steady-state conditions. This research endeavors to formulate a mathematical model capable of accurately simulating various operational conditions of sewer systems under the natural ventilation condition. The dynamic water flow is modeled using a shock-capturing MacCormack scheme. The dynamic airflow model amalgamates energy and momentum equations, circumventing laborious pressure iteration computations. This model utilizes friction coefficients at interfaces to enhance the description of the momentum exchange in the airflow and provide a logical explanation for air pressure. A systematic analysis indicates that this model can be easily adapted to include complex boundary conditions, facilitating its use for modeling airflow in real sewer networks. Furthermore, this research uncovers a direct correlation between the air-to-water flow rate ratio and the filling ratio under natural ventilation conditions, and an empirical formula encapsulating this relationship is derived. This finding offers insights for practical engineering applications.

Tools for time-course simulation in systems biology: a brief overview.

Dynamic modeling of biological systems is essential for understanding all properties of a given organism as it allows us to look not only at the static picture of an organism but also at its behavior under various conditions. With the increasing amount of experimental data, the number of tools that enable dynamic analysis also grows. However, various tools are based on different approaches, use different types of data and offer different functions for analyses; so it can be difficult to choose the most suitable tool for a selected type of model. Here, we bring a brief overview containing descriptions of 50 tools for the reconstruction of biological models, their time-course simulation and dynamic analysis. We examined each tool using test data and divided them based on the qualitative and quantitative nature of the mathematical apparatus they use.

Modeling the mechanisms of conifer mortality under seawater exposure.

Relative sea level rise (SLR) increasingly impacts coastal ecosystems through the formation of ghost forests. To predict the future of coastal ecosystems under SLR and changing climate, it is important to understand the physiological mechanisms underlying coastal tree mortality and to integrate this knowledge into dynamic vegetation models. We incorporate the physiological effect of salinity and hypoxia in a dynamic vegetation model in the Earth system land model, and used the model to investigate the mechanisms of mortality of conifer forests on the west and east coast sites of USA, where trees experience different form of sea water exposure. Simulations suggest similar physiological mechanisms can result in different mortality patterns. At the east coast site that experienced severe increases in seawater exposure, trees loose photosynthetic capacity and roots rapidly, and both storage carbon and hydraulic conductance decrease significantly within a year. Over time, further consumption of storage carbon that leads to carbon starvation dominates mortality. At the west coast site that gradually exposed to seawater through SLR, hydraulic failure dominates mortality because root loss impacts on conductance are greater than the degree of storage carbon depletion. Measurements and modeling focused on understanding the physiological mechanisms of mortality is critical to reducing predictive uncertainty.

Impact of combination preventative interventions on hospitalization and death under the pandemic of SARS-CoV-2 Omicron variant in China.

With a large population most susceptible to Omicron and emerging SARS-CoV-2 variants, China faces uncertain scenarios if reopening its border. Thus, we aimed to predict the impact of combination preventative interventions on hospitalization and death. An age-stratified susceptible-infectious-quarantined-hospitalized-removed-susceptible (SIQHRS) model based on the new guidelines of COVID-19 diagnosis and treatment (the ninth edition) was constructed to simulate the transmission dynamics of Omicron within 365 days. At baseline, we assumed no interventions other than 60% booster vaccination in individuals aged ≤60 years and 80% in individuals aged >60 years, quarantine and hospitalization. Oral antiviral medications for COVID-19 and nonpharmaceutical interventions (NPIs) such as social distancing and antigen self-testing were considered in subsequent scenarios. Sensitivity analyses were conducted to reflect different levels of interventions. A total of 0.73 billion cumulative quarantines (95% CI 0.53-0.83), 33.59 million hospitalizations (22.41-39.31), and 0.62 million deaths (0.40-0.75) are expected in 365 days. The case fatality rate with pneumonia symptoms (moderate, severe and critical illness) is expected to be 1.83% (1.68-1.99%) and the infected fatality rate is 0.38‰ (0.33-0.4‰). The highest existing hospitalization and ICU occupations are 3.11 (0.30-3.85) and 20.33 (2.01-25.20) times of capacity, respectively. Sensitivity analysis showed that interventions can be adjusted to meet certain conditions to reduce the total number of infections and deaths. In conclusion, after sufficient respiratory and ICU beds are prepared and the relaxed NPIs are in place, the SARS-CoV-2 Omicron variant would not seriously impact the health system.

Hot-topics cross-propagation and opinion-transfer dynamics in the Chinese Sina-microblog social media: A modeling study.

On social media platforms, hot topics often contain several pieces of related information that can influence internet users, generating either positive or negative opinion orientation. Some of them will choose to retain or change their original opinions after exposure to multiple related messages. To describe the opinion-transfer transient and collective behaviors in this scenario, this paper proposes an opinion-transfer susceptible-forwarding-immunized (OT-SFI) information cross-propagation model. Real multiple information in messages with opinions obtained from the Chinese Sina microblog is used for data fitting to illustrate how model parameters can be estimated and used to predict the accumulative numbers of users with a particular view. The study attempts to relate changes in group views in the network to initial opinion distribution and individuals' opinion choices at the macro level. Furthermore, the model parameters at the micro level are used to measure the probability of "retention" and "reversal" of views in events, as well as the extent to which the masses are influenced by new information views. The result illustrates that the viewpoint distribution of the initial message and the opinion selection of the new message opinion leaders play crucial roles in promoting attention to the topic and driving for a desired collective opinion.

Molecular Composition of Anthropogenic Oxygenated Organic Molecules and Their Contribution to Organic Aerosol in a Coastal City.

Organic aerosols (OA) have gained attention as a substantial component of atmospheric aerosols owing to their impact on atmospheric visibility, climate, and human health. Although oxygenated organic molecules (OOMs) are essential contributors to OA formation, the sources, transformations, and fates of the OOMs are not fully understood. Herein, anthropogenic OOMs (AOOMs), anthropogenic volatile organic compounds (AVOCs), and OA were concurrently measured in Xiamen, a coastal city in southeastern China. Our results show that the AOOMs exhibited a high nitrogen content (76%) and a low oxidation degree. Strong photochemical processes of aromatic VOCs were the predominant sources of AOOMs. Also, NOx concentrations and the occurrence of multigeneration OH radical oxidations were the critical factors that might influence the formation of AOOMs. Finally, the newly developed aerosol dynamic model's results show that more than 35% of the OA mass growth rate is attributed to the gas-particle partitioning of AOOMs. Further sensitivity testing demonstrates that the contribution of AOOMs to OA growth is significantly enhanced during high-particulate-concentration periods, especially under low-temperature conditions. This study emphasizes the vital role of photochemically produced AOOMs derived from AVOCs in OA growth in a coastal urban atmosphere.

Prospective validation of a dynamic prognostic model for identifying COVID-19 patients at high risk of rapid deterioration.

BACKGROUND: We sought to develop and prospectively validate a dynamic model that incorporates changes in biomarkers to predict rapid clinical deterioration in patients hospitalized for COVID-19. METHODS: We established a retrospective cohort of hospitalized patients aged ≥18 years with laboratory-confirmed COVID-19 using electronic health records (EHR) from a large integrated care delivery network in Massachusetts including >40 facilities from March to November 2020. A total of 71 factors, including time-varying vital signs and laboratory findings during hospitalization were screened. We used elastic net regression and tree-based scan statistics for variable selection to predict rapid deterioration, defined as progression by two levels of a published severity scale in the next 24 h. The development cohort included the first 70% of patients identified chronologically in calendar time; the latter 30% served as the validation cohort. A cut-off point was estimated to alert clinicians of high risk of imminent clinical deterioration. RESULTS: Overall, 3706 patients (2587 in the development and 1119 in the validation cohort) met the eligibility criteria with a median of 6 days of follow-up. Twenty-four variables were selected in the final model, including 16 dynamic changes of laboratory results or vital signs. Area under the ROC curve was 0.81 (95% CI, 0.79-0.82) in the development set and 0.74 (95% CI, 0.71-0.78) in the validation set. The model was well calibrated (slope = 0.84 and intercept = -0.07 on the calibration plot in the validation set). The estimated cut-off point, with a positive predictive value of 83%, was 0.78. CONCLUSIONS: Our prospectively validated dynamic prognostic model demonstrated temporal generalizability in a rapidly evolving pandemic and can be used to inform day-to-day treatment and resource allocation decisions based on dynamic changes in biophysiological factors.

"It's about being healthy"; a novel approach to the socio-ecological model using family perspectives within the Latinx community.

BACKGROUND: The Latinx community is at risk for obesity, type 2 diabetes, and other chronic illnesses. Culturally appropriate, community facing physical activity (P.A.) and nutrition programs may provide the basis for families to improve their health status. Our objectives are as follows: 1. To investigate synergistic factors within this type of program that play a role in creating an environment for participants to learn and practice healthy behaviors. 2. To apply factors into a novel model of components that support health and wellness. 3. To design an intervention for future implementation and evaluation. METHODS: A two-year P.A. and nutrition program, Families Inspired Together 4 Youth Empowered to Succeed (FIT 4 YES), took place in Milwaukee, WI. with Hispanic families from 2018 to 2020 through a community-academic partnership. A pair of interviewers spoke with families who provided insight into the impact of the program. A grounded theory qualitative approach to code the transcripts guided the team to identify overarching themes. RESULTS: Twenty-four interviews were conducted. Common themes indicated that children had a stronger belief in their abilities and confidence in peer support. Parents noticed their children increasing self-directed healthy behaviors. All families grew in their implementation of health and wellness. CONCLUSIONS: Three main components of FIT 4 YES contributed to its success: opportunities for engagement, supportive relationships, and the interplay of components that emerged from the interviews. Effective programs could include these components to make their outcomes more cohesive within the family. A novel model emerged that builds on the social-ecological model that emphasizes the dynamic interactions between these main components. Additional research is needed to evaluate the long-term effects and response by the community.

Modeling the economic impacts of mobility scores in dairy cows under Irish spring pasture-based management.

Moderate to severe forms of suboptimal mobility on dairy cows are associated with yield losses, whereas mild forms of suboptimal mobility are associated with elevated somatic cell count and an increased risk to be culled. Although the economic consequences of severe forms of suboptimal mobility (also referred as clinical lameness) have been studied extensively, the mild forms are generally ignored. Therefore, the aim of the current study was to determine the economic consequences associated with varying prevalence and forms of suboptimal mobility within spring calving, pasture-based dairy herds. A new submodel predicting mobility scores was developed and integrated within an existing pastured-based herd dynamic model. Using a daily timestep, this model simulates claw disorders, and the consequent mobility score of individual cows. The impact of a cow having varying forms of suboptimal mobility on production and reproduction was simulated. The economic impact was simulated including treatment costs, as well as the production and reproductive impacts of varying levels of suboptimal mobility. Furthermore, different genetic predispositions for mobility issues and their interaction with herd-level management associated with each level of suboptimal mobility were simulated. Overall, 13 scenarios were simulated, representing a typical spring calving, pasture-based dairy herd with 100 cows. The first scenario represents a perfect herd wherein 100% of the cows had mobility score 0 (optimal mobility) throughout the lactation. The remaining 12 scenarios represent a combination of (1) 3 different herd-management levels, and (2) 4 different levels of a genetic predisposition for suboptimal mobility. The analysis showed that a 17% decrease in farm net profit was achieved in the worst outcome (wherein just 5% of the herd had optimal mobility) compared with the perfect herd. This was due to reduced milk yield, increased culling, and increased treatment costs for mobility issues compared the ideal scenario.

Non Linear Control System for Humanoid Robot to Perform Body Language Movements.

In social robotics, especially with regard to direct interactions between robots and humans, the robotic movements of the body, arms and head must make an adequate displacement to guarantee an adequate interaction, both from a functional and social point of view. To achieve this, the use of closed-loop control techniques that consider the complex nonlinear dynamics and disturbances inherent in these systems is required. In this paper, an implementation of a nonlinear controller for the tracking of trajectories and a profile of speeds that execute the movements of the arms and head of a humanoid robot based on the mathematical model is proposed. First, the design and implementation of the arms and head are initially presented, then the mathematical model via kinematic and dynamic analysis was performed. With the above, the design of nonlinear controllers such as nonlinear proportional derivative control with gravity compensation, Backstepping control, Sliding Mode control and the application of each of them to the robotic system are presented. A comparative analysis based on a frequency analysis, the efficiency in polynomial trajectories and the implementation requirements allowed selecting the non-linear Backstepping control technique to be implemented. Then, for the implementation, a centralized control architecture is considered, which uses a central microcontroller in the external loop and an internal microcontroller (as internal loop) for each of the actuators. With the above, the selected controller was validated through experiments performed in real time on the implemented humanoid robot, demonstrating proper path tracking of established trajectories for performing body language movements.

Construction and influencing factors of an early warning system for marine ranching ecological security: Experience from China's coastal areas.

Marine ranching has been widely considered as a new mode of marine fishery production. Marine ranching ecological security (MRES) is the basis and premise to ensure the sustainable utilization of marine ranching functions. In this study, an MRES early warning system was constructed based on comprehensive marine ranching ecological security index (CMRESI) and system dynamic model to reveal the main factors affecting the development of marine ranching and explore the changes in MRES under different future development scenarios in China's coastal areas from 2011 to 2035. The results showed that (1) the mean CMRESI of China was only 0.3265 and spatial heterogeneity was significant, showing a general security state; (2) coupling and coordination degree of MRES subsystems was high in Jiangsu, Fujian, Shandong, and Guangdong, and resources was a major constraint on the coordinated development of MRES in the study area (63.6%); (3) Under the ecological priority development scenario, the CMRESI will be the highest in 2035; however, 27% of MRES (in Jiangsu, Fujian, and Hainan) will continue to issue serious early warnings. This study could provide a reference for construction planning, management maintenance, and decision-making of marine ranching.

Comparative evaluation of static and dynamic simulated digestion models.

BACKGROUND: The digestion behavior of lipids plays a crucial role in their nutritional values. Currently, the complex dynamic variations of human gastrointestinal conditions are considered in simulated digestion models. The present study compared the digestion behavior of glycerol trilaurate (GTL), glycerol tripalmitate (GTP) and glycerol tristearate (GTS) in a static in vitro digestion model and a dynamic in vitro digestion model. In the dynamic digestion model, the parameters of gastric juice secretion, the rate of gastric emptying, the secretion of intestinal juice and the pH variations were estimated. RESULTS: The dynamic digestion model showed a certain extent of gastric lipase hydrolysis, while almost no lipolysis happened in the gastric phase of the static digestion model. A smoother digestive behavior was observed in the dynamic model than that in the static model. In the static model, the particle size distribution in gastric and intestinal phase changed rapidly in all triacylglycerol (TAG) groups. The change of particle size during the whole digestion period in GTL is more moderate than GTP and GTS. In addition, the final free fatty acids release degree was 58.558%, 54.36%, and 52.97% for GTL, GTP, and GTS, respectively. CONCLUSION: This study illustrated the different digestion profiles of TAGs in two digestion models and the results will contribute to a better understanding of different in vitro digestion models in lipid digestion. © 2023 Society of Chemical Industry.

Effects of baloxavir and oseltamivir antiviral therapy on the transmission of seasonal influenza in China: A mathematical modeling analysis.

New antiviral influenza treatments can effectively alleviate illness while reducing viral shedding. However, how such effects can translate into lower population infections of seasonal influenza in China remains unknown. To shed light on the public health impacts of novel antiviral agents for influenza, we constructed a dynamic transmission model to simulate the seasonal influenza epidemics in China. Two antivirus treatments, baloxavir and oseltamivir, were evaluated by estimating their impacts on the incidences of influenza infection in a single flu season. In the base-case analysis of a 10% antiviral treatment uptake rate, 2760 and 3420 per 10 000 persons contracted influenza under the treatment of baloxavir and oseltamivir, respectively. These incidence rates amounted to an 18.90% relative risk reduction (RRR) of infection associated with baloxavir in relation to oseltamivir. The corresponding RRR was 82.16% when the antiviral treatment uptake rate was increased to 35%. In addition, the peak of the prevalence of infected individuals per 10 000 persons under the baloxavir treatment was 177 (range: 93-274) fewer than that of oseltamivir. Our analyses suggest that the baloxavir treatment strategy reduces the incidence of influenza in China compared with oseltamivir in the setting of a seasonal flu epidemic. Also, increasing the uptake rate of antiviral treatment can potentially prevent millions of infections during a single flu season.

Vaccination strategy for preventing the spread of SARS-CoV-2 in the limited supply condition: A mathematical modeling study.

To mitigate SARS-CoV-2 transmission, vaccines have been urgently approved. With their limited availability, it is critical to distribute the vaccines reasonably. We simulated the SARS-CoV-2 transmission for 365 days over four intervention periods: free transmission, structural mitigation, personal mitigation, and vaccination. Sensitivity analyses were performed to obtain robust results. We further evaluated two proposed vaccination allocations, including one-dose-high-coverage and two-doses-low-coverage, when the supply was low. 33.35% (infection rate, 2.68 in 10 million people) and 40.54% (2.36) of confirmed cases could be avoided as the nonpharmaceutical interventions (NPIs) adherence rate rose from 50% to 70%. As the vaccination coverage reached 60% and 80%, the total infections could be reduced by 32.72% and 41.19%, compared to the number without vaccination. When the durations of immunity were 90 and 120 days, the infection rates were 2.67 and 2.38. As the asymptomatic infection rate rose from 30% to 50%, the infection rate increased 0.92 (SD, 0.16) times. Conditioned on 70% adherence rate, with the same amount of limited available vaccines, the 20% and 40% vaccination coverage of one-dose-high-coverage, the infection rates were 2.70 and 2.35; corresponding to the two-doses-low-coverage with 10% and 20% vaccination coverage, the infection rates were 3.22 and 2.92. Our results indicated as the duration of immunity prolonged, the second wave of SARS-CoV-2 would be delayed and the scale would be declined. On average, the total infections in two-doses-low-coverage was 1.48 times (SD, 0.24) as high as that in one-dose-high-coverage. It is crucial to encourage people in order to improve vaccination coverage and establish immune barriers. Particularly when the supply is limited, a wiser strategy to prevent SARS-CoV-2 is equally distributing doses to the same number of individuals. Besides vaccination, NPIs are equally critical to the prevention of widespread of SARS-CoV-2.