The mechanism shaping the logistic growth of mutation proportion in epidemics at population scale

Virus evolution is a common process of pathogen adaption to host population and environment.Frequently,a small but important fraction of virus mutations are reported to contribute to higher risks of host infection,which is one of the major determinants of infectious diseases outbreaks at population scale.The key mutations contributing to transmission advantage of a genetic variant often grow and reach fixation rapidly.Based on classic epidemiology theories of disease transmission,we proposed a mechanistic explanation of the process that between-host transmission advantage may shape the observed logistic curve of the mutation proportion in population.The logistic growth of mutation is further generalized by incorporating time-varying selective pressure to account for impacts of external factors on pathogen adaptiveness.The proposed model is implemented in real-world data of COVID-19 to capture the emerging trends and changing dynamics of the B.1.1.7 strains of SARS-CoV-2 in England.The model characterizes and establishes the underlying theoretical mechanism that shapes the logistic growth of mutation in population.

Stationary distribution and probability density function of a stochastic waterborne pathogen model with logistic growth

Waterborne disease threatens public health globally.Previous studies mainly consider that the birth of pathogens in water sources arises solely by the shedding of infected individuals,However,for free-living pathogens,intrinsic growth without the presence of hosts in environment could be possible.In this paper,a stochastic waterborne disease model with a logistic growth of pathogens is investigated.We obtain the sufficient conditions for the extinction of disease and also the existence and uniqueness of an ergodic stationary distribution if the threshold R_(0)^(s)>1.By solving the Fokker-Planck equation,an exact expression of probability density function near the quasi-endemic equilibrium is obtained.Results suggest that the intrinsic growth in bacteria population induces a large reproduction number to determine the disease dynamics.Finally,theoretical results are validated by numerical examples.

EXISTENCE AND GLOBAL ATTRACTIVITY OF POSITIVE PERIODIC SOLUTION OF A LOGISTIC GROWTH SYSTEM WITH FEEDBACK CONTROL AND DEVIATING ARGUMENTS

In this paper, we study the existence and global attractivity of positive peri- odic solutions of a Logistic growth system with feedback control and deviating arguments. A sufficient condition is derived for the existence of a unique peri- odic solution with strictly positive components which is globally asymptotically stable by using the method of coincidence degree and Liapunov functional. Some new results are obtained. The known results are improved and generalized.

Rapid estimation of an earthquake impact area using a spatial logistic growth model based on social media data

Rapid estimates of impact areas following large earthquakes constitute the cornerstone of emergency response scenarios.However,collecting information through traditional practices usually requires a large amount of manpower and material resources,slowing the response time.Social media has emerged as a source of real-time‘citizen-sensor data’for disasters and can thus contribute to the rapid acquisition of disaster information.This paper proposes an approach to quickly estimate the impact area following a large earthquake via social media.Specifically,a spatial logistic growth model(SLGM)is proposed to describe the spatial growth of citizen-sensor data influenced by the earthquake impact strength after an earthquake;a framework is then developed to estimate the earthquake impact area by combining social media data and other auxiliary data based on the SLGM.The reliability of our approach is demonstrated in two earthquake cases by comparing the detected areas with official intensity maps,and the time sensitivity of the social media data in the SLGM is discussed.The results illustrate that our approach can effectively estimate the earthquake impact area.We verify the external validity of our model across other earthquake events and provide further insights into extracting more valuable earthquake information using social media.

A Logistic-growth-equation-based Intensity Prediction Scheme for Western North Pacific Tropical Cyclones

Accurate prediction of tropical cyclone(TC)intensity remains a challenge due to the complex physical processes involved in TC intensity changes.A seven-day TC intensity prediction scheme based on the logistic growth equation(LGE)for the western North Pacific(WNP)has been developed using the observed and reanalysis data.In the LGE,TC intensity change is determined by a growth term and a decay term.These two terms are comprised of four free parameters which include a time-dependent growth rate,a maximum potential intensity(MPI),and two constants.Using 33 years of training samples,optimal predictors are selected first,and then the two constants are determined based on the least square method,forcing the regressed growth rate from the optimal predictors to be as close to the observed as possible.The estimation of the growth rate is further refined based on a step-wise regression(SWR)method and a machine learning(ML)method for the period 1982−2014.Using the LGE-based scheme,a total of 80 TCs during 2015−17 are used to make independent forecasts.Results show that the root mean square errors of the LGE-based scheme are much smaller than those of the official intensity forecasts from the China Meteorological Administration(CMA),especially for TCs in the coastal regions of East Asia.Moreover,the scheme based on ML demonstrates better forecast skill than that based on SWR.The new prediction scheme offers strong potential for both improving the forecasts for rapid intensification and weakening of TCs as well as for extending the 5-day forecasts currently issued by the CMA to 7-day forecasts.

Monitoring the impact of Movement Control Order (MCO) in flattening the cummulative daily cases curve of Covid-19 in Malaysia: A generalized logistic growth modeling approach

Introduction:COVID-19 has affected almost every country in the world,which causing many negative implications in terms of education,economy and mental health.Worryingly,the trend of second or third wave of the pandemic has been noted in multiple regions despite early success of flattening the curve,such as in the case of Malaysia,post Sabah state election in September 2020.Hence,it is imperative to predict ongoing trend of COVID-19 to assist crucial policymaking in curbing the transmission.Method:Generalized logistic growth modelling(GLM)approach was adopted to make prediction of growth of cases according to each state in Malaysia.The data was obtained from official Ministry of Health Malaysia daily report,starting from 26 September 2020 until 1 January 2021.Result:Sabah,Johor,Selangor and Kuala Lumpur are predicted to exceed 10,000 cumulative cases by 2 February 2021.Nationally,the growth factor has been shown to range between 0.25 to a peak of 3.1 throughout the current Movement Control Order(MCO).The growth factor range for Sabah ranged from 1.00 to 1.25,while Selangor,the state which has the highest case,has a mean growth factor ranging from 1.22 to 1.52.The highest growth rates reported were inWP Labuan for the time periods of 22 Nov-5 Dec 2020 with growth rates of 4.77.States with higher population densities were predicted to have higher cases of COVID-19.Conclusion:GLM is helpful to provide governments and policymakers with accurate and helpful forecasts on magnitude of epidemic and peak time.This forecast could assist government in devising short-and long-term plan to tackle the ongoing pandemic.

Cold Chain Logistics Display Tremendous Growth Momentum

China’s market demands for cold chain logistics services have been increasing in recent years.At the press conference of the Fourth China(Chingpo Lake)International Agricultural Product Cold Chain Logistics Summit,Cui Zhongfu,deputy chairman and

Effects of non-Gaussian noise on the dynamical properties of a logistic system

The dynamical properties of a tumor cell growth system described by the logistic system with coupling between non- Gaussian and Gaussian noise terms are investigated. The effects of the nonextensive index q on the stationary properties and the transient properties are discussed, respectively. The results show that the nonextensive index q can induce the tumor cell numbers to decrease greatly in the case of q 〉 1. Moreover, the switch from the steady stable state to the extinct state is speeded up as the increases of q, and the tumor cell numbers can be more obviously restrained for a large value of q. The numerical results are found to be in basic agreement with the theoretical predictions.

基于共生理论的黑龙江国有林区林业产业结构优化研究

利用2006-2017年黑龙江国有林区40个林业局的面板数据进行线性回归求得共生度与共生系数的方法,判断黑龙江国有林区林业产业间共生关系,结果表明:①黑龙江国有林区林业第一、二、三产业之间呈现非对称互惠共生关系,整体看林业第一产业正向影响林业第二、三产业发展较大;②停伐政策后,林业第一、三产业间向对称互惠共生关系进化发展,第一、二产业间却出现些许共生退化现象,第二、三产业间共生关系较稳定。从优化共生单元、改善共生环境角度提出合理的建议。

华中地区畜牧业温室气体排放特征分析与预测

采用IPCC推荐的温室气体清单计算方法,从温室气体排放总量、排放强度等方面分析了华中地区畜牧业温室气体排放现状;根据不同牲畜饲养数量,采用Logistic growth model、Gompertz curve model等非线性时间序列模型模拟2030年华中地区牲畜数量,并计算畜牧业温室气体排放量.结果显示,2015年华中地区温室气体排放为6289.09万t CO2-eq,单位GDP温室气体排放量为1.13万t CO2-eq/亿元,单位肉类产量排放强度为3.73t CO2-eq/t;2030年华中地区畜牧业温室气体排放总量约为4990.06(温室气体排放预测1)~5932.74万tCO2-eq(温室气体排放预测2).应当进一步优化畜牧业饲养技术及条件来提高产业温室气体排放效率,科学合理的规划不同牲畜的饲养规模,优化牲畜饲养结构来降低畜牧业温室气体排放量.

A Novel Parameter-Free Filled Function and Its Application in Least Square Method

The filled function algorithm is an important method to solve global optimization problems.In this paper,a parameter-free filled function is proposed for solving general global optimization problem,discuss the theoretical properties of this function and give the corresponding algorithm.The numerical experiments on some typical test problems using the algorithm and the numerical results show that the algorithm is effective.Applying the filled function method to the parameter solving problem in the logical population growth model,and then can be effectively applied to Chinese population prediction.The experimental results show that the algorithm has good practicability in practical application.

Adequacy of Logistic models for describing the dynamics of COVID-19 pandemic

Logistic models have been widely used for modelling the ongoing COVID-19 pandemic.This study used the data for Kuwait to assess the adequacy of the two most commonly used logistic models(Verhulst and Richards models)for describing the dynamics COVID-19.Specifically,the study assessed the predictive performance of these two models and the practical identifiability of their parameters.Two model calibration approaches were adopted.In the first approach,all the data was used to fit the models as per the heuristic model fitting method.In the second approach,only the first half of the data was used for calibrating the models,while the other half was left for validating the models.Analysis of the obtained calibration and validation results have indicated that parameters of the two models cannot be identified with high certainty from COVID-19 data.Further,the models shown to have structural problems as they could not predict reasonably the validation data.Therefore,they should not be used for long-term predictions of COVID-19.Suggestion have been made for improving the performances of the models.

Mathematical analysis of pulse vaccination in controlling the dynamics of measles transmission

Although the incidence of measles has been significantly reduced through vaccination,it remains an important public health problem.In this paper,a measles model with pulse vaccination is formulated to investigate the influential pulse vaccination on the period of time for the extinction of the disease.The threshold value of the formulated model,called the control reproduction number and denoted by R^(*),is derived.It is found that the disease-free periodic solution of the model exists and is globally attractivity whenever R^(*)<1 in the sense that measles is eliminated.If R^(*)>1,the positive solution of the model exists and is permanent which indicates the disease persists in the community.Theoretical conditions for disease eradication under various constraints are given.The effect of pulse vaccination is explored using data from Thailand.The results obtained can guide policymakers in deciding on the optimal scheduling in order to achieve the strategic plan of measles elimination by vaccination.

A new approach of proration-injection allocation for water-flooding mature oilfields

This paper presents a new method of injection-production allocation estimation for water-flooding mature oilfields.The suggested approach is based on logistic growth rate functions and several type-curve matching methods.Using the relationship between these equations,oil production and water injection rate as well as injection-production ratio can be easily forecasted.The calculation procedure developed and outlined in this paper requires very few production data and is easily implemented.Furthermore,an oilfield case has been analyzed.The synthetic and field cases validate the calculation procedure,so it can be accurately used in forecasting production data,and it is important to optimize the whole injection-production system.