R0 Values Research Articles

Transgenerational effects of pyriproxyfen in a field strain of Musca domestica L. (Diptera: Muscidae).

Musca domestica L. (Muscidae: Diptera) is a human and livestock pest especially in tropical and sub-tropical areas. Different insecticides have been used to control this pest that pose serious harmful effects on humans and the environment. The current study was planned to investigate the effects of two concentrations (LC25 and LC50) of pyriproxyfen on biological and population parameters of a field strain of M. domestica. The exposed parents (F0) and their progeny (F1) were studied to examine the transgenerational effects. The results indicated that preadult duration was higher in control (13.68 days) compared to LC50 treated individuals (12.44 days). The male and female longevity was relatively lower in the LC25 treated population i.e. 24.62 and 26.62 days, respectively. The adult pre-oviposition period (APOP) and total pre-oviposition period (TPOP) values were higher in the LC25 treated individuals than those of control. Moreover, oviposition days and fecundity were reduced in the treated individuals as compared to the control treatment. A gradual decrease in the net reproductive rate (R0) was observed (8.46-14.07 per day) while the value of R0 was significantly higher in control. The results suggested that pyriproxyfen can be effectively utilized and incorporated in the management programs of M. domestica.

Single-Nucleobase-Resolved Nanoruler Determines the Surface Energy Transfer Radius on the Living Cell Membrane.

Investigations about surface energy transfer radius (r0) are limited to the aqueous solution system, and it is quite limited on experimental values of r0 between dyes and the corresponding gold particle (AuNP) sizes, especially for living cell systems. Hence, the selection of suitable AuNP-dye pairs is restricted when designing nanometal surface energy transfer (NSET) strategies in analytical sciences. Here, we developed a single-nucleobase-resolved NSET strategy to in situ measure the r0 value between a specific dye and different-sized AuNPs on the living cell membrane. Using the aptamer-dye complex (XQ-2d-nTA-FAM) and antiCD71 antibody-coupled AuNP conjugate (Au@antiCD71) as two working elements to bind two different sites on CD71 receptors on living cell membranes, we modified the nTA spacer between FAM and the terminal of aptamer to change the distance (r) from FAM to AuNP center and further adjusted the quenching efficiency (Φ) between them. Different r0 values of various AuNP-FAM pairs in living cells are determined by this in situ detection strategy. Based on this single-nucleobase-resolved NSET strategy, we established a simple and efficient universal method for measuring r0 in the living cell system, which greatly expanded the selection range of AuNP-dye pairs during the construction of the NSET model at the nanoscale.

Bifurcation analysis of a delayed stochastic HBV epidemic model: Cell-to-cell transmission

In the present study, we develop a model for hepatitis B virus (HBV) that integrates cell-to-cell transmission of the virus, CTL immunological response, delay effects, and the effect of fluctuating environmental noise. The inheritance randomness of the system shifting the system from a deterministic to another system consists of stochastic differential equations (SDEs). After model formulation, the dynamical aspects of the model are investigated by using the key threshold quantity R0. If the threshold value R0 is assumed less than unity, then it is proven that the solution trajectories are fluctuating around the disease-free state (DFS) of the associated deterministic model. The fluctuation of the trajectories around the DFS explains the phenomenon of extinction of the stochastic models. It is also proved that the trajectories of the SDE model oscillate around the endemic state of the underlying ODE system when R0s>1 explains the sure persistence theory of the proposed model. One notable finding of the present manuscript is the positive association between the fluctuating amplitude and the intensities of the white noises. This understanding can provide useful control tools for managing the worst dynamic(s) of the infection. The exact value of the parameter for time delay determines the stability of the model under consideration. By analyzing the time-delayed parameter, it was identified that the model is stable by keeping the value of the parameter below the crucial value that causes the Hopf bifurcation. This conclusion is supported by the numerical examples having epidemiological significance. Furthermore, the findings suggest that stochastic environmental disturbance can impact the spread of infectious illnesses. Notably, the high levels of noise can help to slow down the spread of epidemics in the population.

Exploring factors shaping antibiotic resistance patterns in Streptococcus pneumoniae during the 2020 COVID-19 pandemic.

Non-pharmaceutical interventions implemented to block SARS-CoV-2 transmission in early 2020 led to global reductions in the incidence of invasive pneumococcal disease (IPD). By contrast, most European countries reported an increase in antibiotic resistance among invasive Streptococcus pneumoniae isolates from 2019 to 2020, while an increasing number of studies reported stable pneumococcal carriage prevalence over the same period. To disentangle the impacts of the COVID-19 pandemic on pneumococcal epidemiology in the community setting, we propose a mathematical model formalizing simultaneous transmission of SARS-CoV-2 and antibiotic-sensitive and -resistant strains of S. pneumoniae. To test hypotheses underlying these trends five mechanisms were built into the model and examined: (1) a population-wide reduction of antibiotic prescriptions in the community, (2) lockdown effect on pneumococcal transmission, (3) a reduced risk of developing an IPD due to the absence of common respiratory viruses, (4) community azithromycin use in COVID-19 infected individuals, (5) and a longer carriage duration of antibiotic-resistant pneumococcal strains. Among 31 possible pandemic scenarios involving mechanisms individually or in combination, model simulations surprisingly identified only two scenarios that reproduced the reported trends in the general population. They included factors (1), (3), and (4). These scenarios replicated a nearly 50% reduction in annual IPD, and an increase in antibiotic resistance from 20% to 22%, all while maintaining a relatively stable pneumococcal carriage. Exploring further, higher SARS-CoV-2 R0 values and synergistic within-host virus-bacteria interaction mechanisms could have additionally contributed to the observed antibiotic resistance increase. Our work demonstrates the utility of the mathematical modeling approach in unraveling the complex effects of the COVID-19 pandemic responses on AMR dynamics.

Recombinant transmissible vaccines will be intrinsically contained despite the ability to superinfect.

Transmissible vaccines offer a novel approach to suppressing viruses in wildlife populations, with possible applications against viruses that infect humans as zoonoses - Lassa, Ebola, rabies. To ensure safety, current designs propose a recombinant vector platform in which the vector is isolated from the target wildlife population. Because using an endemic vector creates the potential for preexisting immunity to block vaccine transmission, these designs focus on vector viruses capable of superinfection, spreading throughout the host population following vaccination of few individuals. We present original theoretical arguments that, regardless of its R0 value, a recombinant vaccine using a superinfecting vector is not expected to expand its active infection coverage when released into a wildlife population that already carries the vector. However, if superinfection occurs at a high rate such that individuals are repeatedly infected throughout their lives, the immunity footprint in the population can be high despite a low incidence of active vaccine infections. Yet we provide reasons that the above expectation is optimistic. High vaccine coverage will typically require repeated releases or release into a population lacking the vector, but careful attention to vector choice and vaccine engineering should also help improve transmissible vaccine utility.

A fractional modeling approach to a new Hepatitis B model in light of asymptomatic carriers, vaccination and treatment

Hepatitis B virus (HBV) is a much more threatening and prolonged disease than hepatitis A. It can start as an acute disease, but in roughly 5 to 10% of situations, it can progress to a chronic condition that permanently damages the liver. After getting or coming into contact with the Hepatitis B virus (HBV), the said symptoms normally last from 10 days to 6 months. In the present paper, to have a firm understanding of the dynamics of HBV, we derived a new fractional model in the Caputo sense with asymptomatic carriers, vaccination, and treatment classes. We obtain the basic reproduction number R0 for the diagnosis and recurrence of the disease. We determine the stability of the proposed model locally and globally for R0 values less than and greater than 1. We use the Lyapunov function theory in fractional environments to establish the global stability of the fractional Hepatitis B virus (HBV) model. We demonstrate the existence and uniqueness of the fractional-order model. To look at the fractional order model’s solution graphically, we used a useful numerical strategy to get more detailed numerical results for the factors that have a big effect on getting rid of diseases. Additionally, the inclusion of the treatment class in the population allows for the determination of the impact of alternative medicines used to treat infected populations. Numerical simulation of the proposed fractional order (FO) Caputo model is performed, allowing for the analysis of graphical representations and the significance of fractional order derivatives to illustrate the impact of our theoretical findings.

Experimental determination of reference intensity ratio essential for accurate thickness measurement of HfO2 ultrathin films by XPS

When measuring the thickness of ultrathin overlayer films using X‐ray photoelectron spectroscopy (XPS), accurate values of the reference intensity ratio (R0) and the effective attenuation length (L) are essential. By definition, R0 is the peak intensity ratio for an overlayer and the substrate in “bulk” phases. Two issues need to be addressed in experimental determining R0 for ultrathin films: (i) How might a contamination layer on the sample used for measuring peak intensities impact R0? And (ii) do differences in the structure or chemistry of an ultrathin film make it inappropriate to determine R0 using bulk forms of the overlayer? In this study, we demonstrate the experimental determination of the R0 for an ultrathin HfO2 film on a Si(100) substrate with a 2 nm SiO2 layer. The values of R0 were determined using (i) the bulk materials of the HfO2 film and substrate and (ii) the ultrathin HfO2 films after different cleaning treatments. The results show that the R0 determined by the ultrathin films is higher than that determined by the bulk materials. Also, keeping the same level of carbonaceous contamination on the sample surface by cleaning as much as possible is essential for an accurate experimental determination of R0. In addition, the effective attenuation length was obtained using samples with known thicknesses measured by X‐ray reflectometry. The thicknesses and uncertainty budget of the ultrathin HfO2 films were then evaluated.

A Model of Hepatitis B Viral Dynamics with Delays

Hepatitis B is a liver disease caused by the human hepatitis B virus (HBV). Mathematical models help further the understanding of the processes involved and help make predictions. The basic reproduction number, R0, is an index that predicts whether the disease will be chronic or not. This is the single most-important information that a mathematical model can give. Within-host virus processes involve delays. We study two within-host hepatitis B virus infection models without and with delay. One is a standard one, and the other considering additional processes and with two delays is new. We analyze the basic reproduction number and alternative threshold indices. The values of R0 and the alternative indices change depending on the model. All these indices predict whether the infection will persist or not, but they do not give the same rate of growth of the infection when it is starting. Therefore, the choice of the model is very important in establishing whether the infection is chronic or not and how fast it initially grows. We analyze these indices to see how to decrease their value. We study the effect of adding delays and how the threshold indices depend on how the delays are included. We do this by studying the local asymptotic stability of the disease-free equilibrium or by using an equivalent method. We show that, for some models, the indices do not change by introducing delays, but they change when the delays are introduced differently. Numerical simulations are presented to confirm the results. Finally, some conclusions are presented.

PENYELESAIAN MODEL PENYEBARAN PENYAKIT ISPA DENGAN MENGGUNAKAN METODE RUNGE KUTTA FEHLBERG DI PROVINSI SULAWESI SELATAN

This stud discusses the analysis and simulation of acute respiratory infection (ISPA) in South Sulawesi Province by applying the RLTSM used the Fehlberg’s Runge-Kutta method. The research is an applied research type with the aim of obtaining a model of the spread of acute respiratory infection and knowing the numerical solution of the mpdel in predicting cases future acute respiratory infection. The mathematical model for acute respiratory infection is in the farm of a system of diffrential equations that includes the variables R (Susceptible), L (Exposed), T (Infected), S (Recovered), dan M (Death). The research results obtained in 2023 with h=0,01 years using the Fehlberg’s Runge-Kutta method with initial values of R0 =458.665, L0 = 165.670, T0 = 141.755, S0 = 103.217, M0 = 9 is R100 =681.560, L100 = 107.068, T0 = 141.755, S100 = 167.445, M100 = 25.248, for order 4 results and R100 =681.559, L100 = 107.070, T100 = 57.208, S100 = 167.442, M100 = 25.247, for order 5 results. The rate of the susceptible population has increased, the exposed and infected population has decreased, the recovered population has increased and then decreased, and the death population has increased and then stabilized

Mathematical Modeling for a CHIKV Transmission Under the Influence of Periodic Environment

We studied a simple mathematical model for the chikungunya virus (CHIKV) spread under the influence of a seasonal environment with two routes of infection. We investigated the existence and the uniqueness of a bounded positive solution, and we showed that the system admits a global attractor set. We calculated the basic reproduction number R0 for the both cases, the fixed and seasonal environment which permits us to characterise both, the extinction and the persistence of the disease with regard to the values of R0. We proved that the virus-free equilibrium point is globally asymptotically stable if R0≤1, while the disease will persist if R0>1. Finally, we gave some numerical examples confirming the theoretical findings.

Additive multiple contacts and saturation phenomena in epidemiological models are not detected by R0

Many infections are transmitted by direct contacts. Usually, one single direct contact is needed to transmit the required minimum infectious load. Most models describe contagions by single contacts using a term of the type mass action law. However, modelling infections that are transmitted after the susceptible individual had contact with several sources of infection requires more than mass action law terms. We call additive multiple contacts those that do not produce infection by themselves, but can produce infection if they happen simultaneously. We are interested in understanding the role played by R0 missing the mark in infections in which the minimum infectious load is reached not only by single contacts but also by additive multiple contacts. We propose different mathematical models describing not only infections by one single contact but also by additive multiple contacts. We show that all models have the same value of R0, but correspond to different epidemiological mechanisms. Two models show contagions by additive multiple contacts and a third one shows reduction of infections by some saturation process which is not captured by R0. This shows that trying to control the epidemics by controlling R0 could be unsufficient or, in some cases, waste resources.

Modeling and Analysis of Fasciola Hepatica Disease Transmission

In this paper, a mathematical model for the transmission dynamics of Fasciola hepatica in cattle and snail populations is formulated and analyzed. The snail mortality rate (μs) is the most important factor that indirectly impacts the basic reproduction number (R0). A 50% change, either an increase or decrease, in the snail mortality rate will result in an approximate 50% change in the opposite direction in the value of R0. The model shows a forward bifurcation at R0 = 1, indicating that the disease dynamics undergo a critical transition at this threshold. This change signifies a transition from a disease‐free state to a persistent infection, highlighting the possibility of a continuous disease presence given specific epidemiological conditions. Simulations show that reducing miracidia, metacercariae, and snail populations, improving treatment, and lowering pathogen transfer between cattle and snails significantly decrease disease prevalence in cattle. To control the disease, transmission rates for cattle and snails must be reduced below γc = 1.4338 × 10−7 and γs = 1.1473 × 10−8, respectively. Current treatments are insufficient, and a combination of improved treatments reduced transmission rates, and increased snail mortality is recommended for better disease control.

Mathematical model of tuberculosis with seasonality, detection, and treatment

In this study, we use a modified SEIR compartmental model to investigate the transmission dynamics of tuberculosis as well as its detection and treatment. The construction of this model is based on the hypothesis that the total population can be divided into seven compartments: susceptible, vaccinated, latently infected, diagnosed infected, undiagnosed infected, treated individuals, delayed treated individuals, and recovered individuals with a nonautonomous system. The effective reproduction number shows that the amplitude of the effective reproduction number decreases with the increasing vaccination rate and increases with the increase in the degree of seasonality of TB. The stability analyses of the model show that the value of the basic reproduction number R0 acts as a threshold between disease-free and endemic equilibrium. The model is found to be locally and globally asymptotically stable at the disease-free equilibrium when R0<1. On the contrary, the model is found to be locally and globally asymptotically at the endemic equilibrium when R0>1. The sensitivity of the parameters of the corresponding autonomous system is examined using the partial rank correlation coefficients (PRCC) analysis, which demonstrates that identification has a positive index and treatment has a negative index. The model is simulated using the RK-45 numerical method, and the parameter values for the model are taken from the available literature. Finally, the model outcome was compared with the real field data and found to be consistent.

Generalities on a Delayed Spatiotemporal Host–Pathogen Infection Model with Distinct Dispersal Rates

We propose a general model to investigate the effect of the distinct dispersal coefficients infected and susceptible hosts in the pathogen dynamics. The mathematical challenge lies in the fact that the investigated model is partially degenerate and the solution map is not compact. The spatial heterogeneity of the model parameters and the distinct diffusion coefficients induce infection in the low-risk regions. In fact, as infection dispersal increases, the reproduction of the pathogen particles decreases. The dynamics of the investigated model is governed by the value of the basic reproduction number R0. If R0 ≤ 1, then the pathogen particles extinct, and for R0 &gt; 1 the pathogen particles persist, and there is at least one positive steady state. The asymptotic profile of the positive steady state is shown in the case when one or both diffusion coefficients for the host tends to zero or infinity.

A new method for identifying the parameters of the Li-ion battery PNGV model

The article delves into modeling the Li-ion cell and the prerequisites for identifying system parameters. Initially, we construct a model that encapsulates the nonlinearity of our cell, employing a PNGV model encompassing dynamic parameters like state of charge (SOC), open-circuit voltage OCV, Cb, R0, R1 and C1. Subsequent to this, pertinent battery discharge tests are conducted to discern the model parameters.Commencing with establishing the relationship between state of charge (SOC) and the variable open-circuit voltage (OCV) using the least squares method, we progressed. Following determining thise relationship, cell discharge tests were employed to ascertain the values of R0, R1 and C1. Once the various parameters of the PNGV Model are identified, validation of this established battery model is performed via experimental discharge tests. The resulting error indicates a mean absolute error (MAE) of 0.0176V for modeling, alongside a root mean square error (RMSE) of 0.0232V. These outcomes underscore the remarkable accuracy of our cell model.

Spatial analysis of Dengue through the reproduction numbers relating to socioeconomic features: Case studies on two Brazilian urban centers

The study of the propagation of infectious diseases in urban centers finds a close connection with their population's social characteristics and behavior. This work performs a spatial analysis of dengue cases in urban centers based on the basic reproduction numbers, R0, and incidence by planning areas (PAs), as well as their correlations with the Human Development Index (HDI) and the number of trips. We analyzed dengue epidemics in 2002 at two Brazilian urban centers, Belo Horizonte (BH) and Rio de Janeiro (RJ), using PAs as spatial units. Our results reveal heterogeneous spatial scenarios for both cities, with very weak correlations between R0 and both the number of trips and the HDI; in BH, the values of R0 show a less spatial heterogeneous pattern than in RJ. For BH, there are moderate correlations between incidence and both the number of trips and the HDI; meanwhile, they weakly correlate for RJ. Finally, the absence of strong correlations between the considered measures indicates that the transmission process should be treated considering the city as a whole.

Analysis of Stability, Sensitivity Index and Hopf Bifurcation of Eco-Epidemiological SIR Model under Pesticide Application

In this paper, a deterministic SIR plant mathematical model is proposed and analysed with the application of pesticides as a control measure. The primary purpose of this model is to study the role of pesticides in controlling disease prevalence in plant populations. The total plant population is subdivided into three categories: susceptible, infected, and recovered. Pesticides are considered to be applied to both susceptible and infected populations to prevent the spread of infection to unaffected plant populations. It is considered that plant populations can be recovered only through the use of pesticides. To ensure the biological validity and well-defined nature of the model, the positivity, boundedness, uniqueness and existence of solutions are analysed. The basic reproduction number (R0) of the infection is determined and observed that the disease-free equilibrium state is locally asymptotically stable whenever (R0) is less than unity and unstable otherwise. The sensitivity analysis of the basic reproduction number is carried out, and it is observed that the value of R0 decreases as the value of the death rate and the recovery rate of plants increases. Moreover, it is revealed that above a critical parameter value of the infective induce rate, the population starts oscillating periodically, and the endemic equilibrium state becomes unstable. Finally, numerical simulations are conducted in MATLAB software to compare the analytical findings. Overall, the results obtained from this analysis are both novel and significant, making them an intriguing and potentially valuable contribution to the field of theoretical ecology.

Effects of varied building solid wastes, particle sizes and substitution ratios on the performance and impedance spectrum of recycled fine aggregate mortar and the feasibility of developing a prediction method

In this study, three solid waste materials (sintered bricks (SB), aerated blocks (AB) and cementitious mortar (CM)) were studied to analysis the influence on the impedance characteristics and mechanical properties of recycled sand mortar. Mortar containing recycled sand obtained similar or even higher compressive strengths as to the control group at 15% substitution rate. The density of the mortar decreased with the substitution rate of recycled sand. The porosity increased by 18% compared to the control group with an inclusion of 45% of SB. The bulk density of recycled mortar was found to be related to the particle size of the recycled sand, for instance, the bulk density of ABCS45 was 6% less than ABFS45. The AC impedance spectrum results showed that the high-frequency arc was the smallest for AB and the largest for CM. The R1 values of AB were 0.27 and 0.14 times that of SB and CM, respectively. The high-frequency arc of the mortar increased with hydration, consuming OH− ions and raising R0 values, while the compacting matrix led to a rise in R1 values. After 28 days curing, mortars containing SB and CM sands displayed higher R1 values, with CMCS45 being approximately 50% higher than the control group. Through analyzing the physical, mechanical, and impedance properties, it revealed a correlation coefficient −0.88 between porosity and R0 values, with bulk density and compressive strength demonstrating stronger correlation with R1 values. These findings offer valuable guidance for utilizing and nondestructively testing recycled materials.

Research on mathematical algorithm to determine the chemical diffusion coefficient of hydrogen in CaZrO3 based proton conductor at high temperature

To study hydrogen diffusion properties is of importance in design of new proton conductors. In the past, the chemical diffusion coefficient of hydrogen in proton conductor was usually obtained by the manual calculation method that largely depends on judgment ability of researchers, so calculation accuracy is difficult to control. To solve this problem, a mathematical algorithm and C language computer program were designed to calculate the chemical diffusion coefficient based on Fick's second law and Romberg numerical integral, in which the chemical diffusion coefficient is obtained by fitting measured electrical resistance relaxation curve based on. In addition, the algorithm can be extended to calculate the chemical diffusion coefficient in some special cases with incomplete measured electrical resistance relaxation curve or inaccurate measured values of R0 and R∞ based on modified algorithm of R0 and R∞, what cannot be handled by the manual calculation method. The chemical diffusion coefficient of self-synthesized Yb doped CaZrO3 proton conductor were calculated by using the algorithm and compared with the manual calculation method. The results show that the algorithm has the advantages of high precision and powerful computing function. The new algorithm is potential to be widely applied to the calculation of the chemical diffusion coefficient for hydrogen in proton conductors to replace the manual calculation method.

Seaqir Covid -19 Mathematical Modell

This research discusses the mathematical model of Covid-19 disease. The model formed consists of 6 components, namely Susceptible (S), Exposed (E), Asymptotically Infected (A), Quarantined (Q), Symptomatic Infected (S), and Recovered (R). This research aims to determine the local stability analysis of the model formed. Apart from that, the R0 value of the model is also looked for. The model stability analysis was carried out in disease-free and endemic settings by showing asymptotic stability. Based on the analysis results obtained. The primary reproduction number for disease-free and endemic simulations is greater than 1. The interpretation of the COVID-19 mathematical model from the stability analysis shows that COVID-19 will still exist for a specific time and will not disappear.