ABSTRACT
Accurate prediction of the temporal and spatial characteristics of COVID-19 infection can provide favorable guidance for epidemic prevention and control. We first introduce individual antibody dynamics into an agent-based model. Antibody dynamics model can well explain the antibody fading effects through time. Based on this model, we further developed an agent-based approach which considers the dynamic behaviors of each individual antibodies. The method can effectively reflect the dynamic interaction between the antibody and the virus in each host body in the overall population. Using this method, we can accurately predict the temporal and spatial characteristics of the epidemic. It can quantitatively calculate the number and spatial distribution of infected persons with different symptoms at different times. At the same time, our model can predict the prevention and control effect of different prevention and control measures. At present, Chinas dynamic zero strategies mainly include large-scale nucleic acid test, isolation of positive infected persons and their close contacts. Our model demonstrates that for a less infectious and more virulent variant, this approach can achieve good preventive effect. The effect of reducing social contacts and quarantining only positive infected persons is relatively weaker on epidemic control. This can explain why Chinas targeted epidemic-control measures had an excellent performance in 2020 and 2021. However, our model also warns that for the highly infectious and less virulent variant, targeted epidemic-control measures can no longer achieve effective control of the epidemic. Therefore, we must choose to quarantine potential infected groups in a wider range (such as the quarantine of secondary close contact and tertiary close contact) or coexist with the virus. Furthermore, our model has a strong traceability ability, which can effectively conduct epidemiological investigation to unearth patient number zero based on the early epidemic distribution. In the end, our model expands the traditional approaches of epidemiological simulation and provides an alternative in epidemic modeling. Major findingsFirst, a method was developed to integrate the characteristics of individual antibody dynamics into epidemic prediction; Second, this model can effectively predict the spatiotemporal characteristics of patients with different symptoms (including asymptomatic patients, mild and severe patients, etc.); Thirdly, this model proves that Chinas dynamic zero strategy which include the quarantine of close contact people is more efficient than just isolating positive cases; Fourth: This model also reflects the limitations of targeted epidemic-control strategies and warns that for the highly infectious and less virulent variant, targeted epidemic-control measures can no longer achieve effective control of the epidemic; Fifth, this model can help epidemiological research and find out patient zero according to the early incidence of the epidemic.
ABSTRACT
SARS-CoV-2 has caused tremendous deaths world wild. It is of great value to predict the evolutionary direction of SARS-CoV-2. In this paper, we proposed a novel mathematical model that could predict the evolutionary trend of SARS-CoV-2. We focus on the mutational effects on viral assembly capacity. A robust coarse-grained mathematical model is constructed to simulate the virus dynamics in the host body. Both virulence and transmissibility can be quantified in this model. The relationship between virulence and transmissibility can be simulated. A delicate equilibrium point that optimizing the transmissibility can be numerically obtained. Based on this model, we predict the virulence of SARS-CoV-2 might further decrease, accompanied by an enhancement of transmissibility. However, this trend is not continuous; its virulence will not disappear but remains at a relatively stable range. We can also explain the cross-species transmission phenomenon of certain RNA virus based on this model. A small-scale model which simulates the virus packing process is also proposed. It can be explained why a small number of mutations would lead to a significant divergence in clinical performance, both in the overall particle formation quantity and virulence. This research provides a mathematical attempt to elucidate the evolutionary driving force in RNA virus evolution.
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There is a dose effect in the infection process, that is, different initial virus invasion loads will lead to nonlinear changes in infection probability. Experiments already proved that there was a sigmoid functional relationship between virus infection probability and inoculum dose. By means of mathematical simulation of stochastic process, we theoretically demonstrate that there is a sigmoid function relationship between them. At the same time, our model found three factors that influence the severity of infection symptoms, those are virus toxicity, virus invasion dose and host immunity respectively. Therefore, the mortality rate cannot directly reflect the change of virus toxicity, but is the result of the comprehensive action of these three factors. Protective measures such as masks can effectively reduce the severity of infection while reducing the probability of infection. Based on the sigmoid function relationship between virus infection probability and initial virus invasion dose, we deduce that for highly infectious viruses, such as SARS-COV-2, the evolution of its toxicity is closely related to the host population density, and its toxicity will first increase and then decrease with the increase of host population density. That is to say, on the basis of extremely low host population density, increasing population density is beneficial to the development of virus towards strong toxicity. However, this trend is not sustainable, and there is a turning point of population density. Beyond this turning point, increasing population density will be beneficial to the development of virus towards weak toxicity. This theory can well explain the differences of mortality in Covid-19 in different countries. Countries with high population density and extremely low population density often correspond to lower mortality, while countries with population density in the range of 20-100/km2 often have higher mortality. At the same time, we propose that social distance and masks can effectively accelerate the evolution of virus towards low toxicity, so we should not give up simple and effective protection measures while emphasizing vaccination. HighlightsThrough mathematical simulation of random process, we prove the sigmoid function relationship between virus infection probability and initial virus invasion dose theoretically. Our model found three factors that influence the severity of infection symptoms: virus toxicity, virus invasion dose and host immunity. This can help explain why the average infection age was declining as the epidemic went through. With the increase of host population density, virus toxicity will increase at first and then decrease, which will explain the difference of mortality in different population density areas. From the mathematical level, social distance, masks and other protective measures were proved to be positive in promoting the virus evolving into the less toxicity one. Vaccination could also promote virus virulence attenuation.
ABSTRACT
It is of great theoretical and application value to accurately forecast the spreading dynamics of COVID-19 epidemic. We first proposed and established a Bayesian model to predict the epidemic spreading behavior. In this model, the infection probability matrix is estimated according to the individual contact frequency in certain population group. This infection probability matrix is highly correlated with population geographic distribution, population age structure and so on. This model can effectively avoid the prediction malfunction by using the traditional ordinary differential equation methods such as SIR (susceptible, infectious and recovered) model and so on. Meanwhile, it would forecast the epidemic distribution and predict the epidemic hot spots geographically at different time. According to the results revealed by Bayesian model, the effect of population geographical distribution should be considered in the prediction of epidemic situation, and there is no simple derivation relationship between the threshold of group immunity and the virus reproduction number R0. If we further consider the virus mutation effect and the antibody attenuation effect, with a large global population spatial distribution, it will be difficult for us to eliminate Covid-19 in a short time even with vaccination endeavor. Covid-19 may exist in human society for a long time, and the epidemic caused by re-infection is characterized by a wild-geometric && low-probability distribution with no epidemic hotspots.
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<p><b>BACKGROUND</b>Due to racial differences in the morphology of the knee joint and due to most prostheses available in the market being designed using measurements from Caucasians, the objective of this study was to provide the morphometric data of the patella for the southern Chinese population for total knee arthroplasty (TKA), patellar resurfacing, and prostheses design.</p><p><b>METHODS</b>The CT slices of the knee joint were obtained from both knees of 40 Chinese volunteers (20 females, 20 males, and age from 20-25 years) by performing a computer tomographic scan. A 3D model was reconstructed by Mimics software based on the computed tomography images. Six metrical characteristics were measured by digital ruler. Statistical analysis was performed with the SPSS statistical program.</p><p><b>RESULTS</b>The mean, standard deviation and P values of measurements and ratios were calculated using SPSS. All dimensions showed a significant gender difference with P < 0.05, but the six variables of the left and right knees had no statistical significance with P > 0.05. In addition, we studied the relationship between six couples (H-W, H-T, H-HAF, W-T, W-HAF, T-HAF) of the four variables (H: height, W: width, T: thickness and HAF: height of articulating facet) that were measured, which showed a significant correlation.</p><p><b>CONCLUSIONS</b>Examination of the southern Chinese population revealed that males have larger patellae than women. In both genders, comparing data between left and right knees shows no statistically significant difference. Compared with Westerners in previous studies, the patella in our study was thin and small. There was a good linear regression correlation between measurements of the patella. The indirect measurement method on 3D models makes it easy to obtain anatomical data, and the results can provide a region and gender specific database for morphometric measurements of the patella, and can be helpful for designing implants suited for southern Chinese patients.</p>
Subject(s)
Adult , Female , Humans , Male , Young Adult , Arthroplasty, Replacement, Knee , China , Patella , Diagnostic Imaging , Tomography, X-Ray ComputedABSTRACT
Objective To explore the metastasis rules of the lymph node in the colorectal cancer.Method Analyze the metastasis of the lymph node in 94 cases after D 3 radical resection.Results The lymph node metastasis of colorectal cancer was related with the position of tumor,the depth of tumor invasion and the differentiation of tumor cells,but not with patients's sex,age and the size of the tumor.The metastasis rate of the lymph node in rectal cancer was higher than that in colon cancer (P
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The shortage of human hearts has brought the current research focus on finding an animal source as substitute hearts.The immunological barriers to cardiac xenotransplantation are now more clearly defined,allowing retrospective interpretation of past clinical experience in humans.Due to physiological compatibilities as well as ethical and infectious considerations,pigs have now emerged as the most likely source of future xenografts.With the introduction of transgenic pigs expressing human complement regulatory proteins and new immunosuppressive strategies have shown early promise in the laboratory,cardiac xenotransplantation has been the social focus.This article explores ethical issues that surround developments in this field.