Reproduction Number Research Articles

Impact of COVID-19 pandemic on some fiscal and monetary indicators in the kingdom of Saudi Arabia

PurposeThe purpose of this study is to investigate the impact of COVID-19 on some fiscal and monetary indicators in the Kingdom of Saudi Arabia.Design/methodology/approachThe research relied on data, studies and reports issued by the International Monetary Fund, Arab Monetary Fund, Saudi Central Bank, Investing Website and the World in Data Website.FindingsMany sectors have been affected by the COVID-19 pandemic, which outbreak has been associated with a high cost, in addition to increased inflation and prices, a result that was confirmed by the increase in consumer price indices for different sectors. The general consumer price index for the second period rose above that of the first period, while an upward shift occurred in the curve depicting the Saudi Riyal exchange rate against the United States (US) dollar during the second period above that of the first period, only in slope, due to outbreak of the pandemic. Impact of the number of daily new cases infected with COVID-19 was the highest on the opening and closing price indices of the food retail sector, the pharmaceutical sector and the transportation sector; while impact of the number of daily deaths by COVID-19 was the highest on the opening and closing price indices of the banking sector, the general index and the investment and finance sector. In addition, impact of the daily reproduction rate of COVID-19 was the highest on the opening price indices of the energy sector, the food production sector and the transportation sector.Research limitations/implicationsThe research aims to demonstrate measures taken by the Kingdom of Saudi Arabia through fiscal and monetary policies.Practical implicationsThe COVID-19 pandemic is still an ongoing global pandemic. The virus was first identified in Wuhan City in China at the beginning of December 2019. At the end of January 2020, the World Health Organization (WHO) declared that the outbreak of the virus represented a public health emergency, and later, on March 11, 2020, WHO declared the situation had transformed into a pandemic. Until January 17, 2022, the pandemic had caused more than 328 million cases and 545 million deaths, while 188 million of the cases had recovered. It is worth mentioning that the pandemic caused several social and economic disruptions, including a global economic recession; shortages in goods, supplies and equipment due to consumers' panic and thus tendency to buy; besides causing other disruptions like the negative impacts on health, as well as political, cultural, religious and sport events that influenced economic policies, including both the fiscal and monetary policies of world countries (Wikipedia, 2022).Social implicationsSocial implications steps that taken to reduce the impacts of the COVID-19 pandemic, in addition to measuring the impacts of the COVID-19 pandemic (as the main event next to which other events fade up) on some of the fiscal and monetary indicators for the Kingdom of Saudi Arabia.Originality/valueThe research aims to demonstrate measures taken by the Kingdom of Saudi Arabia through fiscal and monetary policies to mitigate the impacts of the COVID-19 pandemic, in addition to measuring the impacts of the COVID-19 pandemic (as the main event next to which other events fade up) on some of the fiscal and monetary indicators for the Kingdom of Saudi Arabia.

Stability analysis of fractional epidemic model for two infected classes incorporating hospitalization impact

This article presents an epidemic disease propagation mathematical model in fractional order. The epidemiological characteristics are presented based on the susceptible, exposed, unknown infected, known infected, hospitalized population and the population in the secure zone. Both the disease endemic equilibrium and the disease-free equilibrium’s stability characteristics have been examined using the basic reproduction number. Variation of basic reproduction number based on the different sensitive parameters has been discussed. It has been disputed whether the fractional model provides a uniform, reliable solution. An analysis of the time history of unknown and known infected populations, hospitalized populations and recovered populations at different values of various sensitive parameters has been carried out. To support the key theoretical conclusions, some numerical simulations are completed using MATLAB. The impact of various populations on the propagation of the illness has also been investigated, as well as how specific state variables change over time for various fractional order values.

Mathematical Analysis for the Influence of Seasonality on Chikungunya Virus Dynamics

In this article, we discuss a mathematical system modelling Chikungunya virus dynamics in a seasonal environment with general incidence rates. We establish the existence, uniqueness, positivity and boundedness of a periodic orbit. We show that the global dynamics is determined using the basic reproduction number denoted by R0 and calculated using the spectral radius of a linear integral operator. We show the global stability of the disease free periodic solution if R0<1 and we show also the persistence of the disease if R0>1 where the trajectories converge to a periodic orbit. Finally, we display some numerical examples confirming the theoretical findings.

A mathematical model for HIV dynamics with multiple infections: implications for immune escape.

Multiple infections enable the recombination of different strains, which may contribute to viral diversity. How multiple infections affect the competition dynamics between the two types of strains, the wild and the immune escape mutant, remains poorly understood. This study develops a novel mathematical model that includes the two strains, two modes of viral infection, and multiple infections. For the representative double-infection case, the reproductive numbers are derived and global stabilities of equilibria are obtained via the Lyapunov direct method and theory of limiting systems. Numerical simulations indicate similar viral dynamics regardless of multiplicities of infections though the competition between the two strains would be the fiercest in the case of quadruple infections. Through sensitivity analysis, we evaluate the effect of parameters on the set-point viral loads in the presence and absence of multiple infections. The model with multiple infections predict that there exists a threshold for cytotoxic T lymphocytes (CTLs) to minimize the overall viral load. Weak or strong CTLs immune response can result in high overall viral load. If the strength of CTLs maintains at an intermediate level, the fitness cost of the mutant is likely to have a significant impact on the evolutionary dynamics of mutant viruses. We further investigate how multiple infections alter the viral dynamics during the combination antiretroviral therapy (cART). The results show that viral loads may be underestimated during cART if multiple-infection is not taken into account.

Traveling waves for a nonlocal delayed reaction-diffusion SIR epidemic model with demography effects

Considering the importance of time delay phenomenon in disease transmission and the interdependence of time delay and spatial location, a reaction-diffusion SIR epidemic model with nonlocal time delay (or time-space time delay) is proposed and the travelling wave solutions are discussed. Specifically, we define the basic reproduction number R 0 and the critical wave speed c ∗ . For every wave speed c ≥ c ∗ , the existence of travelling wave solutions is studied by using the upper–lower solutions, the fixed-point theorem and some limit techniques when R 0 > 1 . The nonexistence of travelling waves when R 0 > 1 for any 0 < c < c ∗ or R 0 < 1 for any c>0 is also proved. Finally, the influence of time-delay on disease propagation, especially the critical wave speed, is discussed through analysis and simulations.

Bayesian inference for the onset time and epidemiological characteristics of emerging infectious diseases

BackgroundEmerging infectious diseases pose a significant threat to global public health. Timely detection and response are crucial in mitigating the spread of such epidemics. Inferring the onset time and epidemiological characteristics is vital for accelerating early interventions, but accurately predicting these parameters in the early stages remains challenging.MethodsWe introduce a Bayesian inference method to fit epidemic models to time series data based on state-space modeling, employing a stochastic Susceptible-Exposed-Infectious-Removed (SEIR) model for transmission dynamics analysis. Our approach uses the particle Markov chain Monte Carlo (PMCMC) method to estimate key epidemiological parameters, including the onset time, the transmission rate, and the recovery rate. The PMCMC algorithm integrates the advantageous aspects of both MCMC and particle filtering methodologies to yield a computationally feasible and effective means of approximating the likelihood function, especially when it is computationally intractable.ResultsTo validate the proposed method, we conduct case studies on COVID-19 outbreaks in Wuhan, Shanghai and Nanjing, China, respectively. Using early-stage case reports, the PMCMC algorithm accurately predicted the onset time, key epidemiological parameters, and the basic reproduction number. These findings are consistent with empirical studies and the literature.ConclusionThis study presents a robust Bayesian inference method for the timely investigation of emerging infectious diseases. By accurately estimating the onset time and essential epidemiological parameters, our approach is versatile and efficient, extending its utility beyond COVID-19.

Control dengue with Wolbachia: Insights from a two-strain vector-host model with larval competition

Due to deficient treatments and vaccines for dengue viruses, dengue control mainly depends on controlling mosquitoes. Suppressing wild mosquito population size by releasing male-only Wolbachia-carrying mosquitoes into the field has become an eco-friendly alternative for traditional mosquito control methods. By assuming an ideal continuous proportional release strategy, we formulate a two-strain vector-host model incorporating larval competition to describe the affected cross-transmission dynamics of two dengue viruses serotypes. Moreover, antibody-dependent enhancement (ADE) and temporal cross-immunity are considered in this model. Theoretical analysis including the well-posedness, the existence and local stability of dengue-free equilibria in terms of the basic reproduction numbers is conducted. Sensitivity analysis indicates that the basic reproduction numbers are most sensitive to the adult female mortality rate and mosquito bite rate. As expected, intensifying larval competition can prevent the spread of dengue viruses. Unexpectedly, increasing the release ratio can delay the peak time while increase the peak level of both primary and secondary infections. To efficiently eliminate dengue outbreaks, other control methods such as spraying larvicides/adult insecticides and avoiding mosquito bites should be employed simultaneously during the time period gained by releasing Wolbachia-carrying males.

Novel estimation of African swine fever transmission parameters within smallholder villages in Lao P.D.R

African Swine Fever (ASF) disease transmission parameters are crucial for making response and control decisions when faced with an outbreak, yet they are poorly quantified for smallholder and village contexts within Southeast Asia. Whilst disease-specific factors − such as latent and infectious periods − should remain reasonably consistent, host, environmental and management factors are likely to affect the rate of disease spread. These differences are investigated using Approximate Bayesian Computation with Sequential Monte-Carlo methods to provide disease parameter estimates in four naïve pig populations in villages of Lao People’s Democratic Republic. The villages represent smallholder pig farmers of the Northern province of Oudomxay and the Southern province of Savannakhet, and the model utilised field mortality data to validate the transmission parameter estimates over the course of multiple model generations. The basic reproductive number between-pigs was estimated to range from 3.08 to 7.80, whilst the latent and infectious periods were consistent with those published in the literature for similar genotypes in the region (4.72 to 6.19 days and 2.63 to 5.50 days, respectively). These findings demonstrate that smallholder village pigs interact similarly to commercial pigs, however the spread of disease may occur slightly slower than in commercial study groups. Furthermore, the findings demonstrated that despite diversity across the study groups, the disease behaved in a consistent manner. This data can be used in disease control programs or for future modelling of ASF in smallholder contexts.

Untangling the stranglehold through mathematical modelling of Streptococcus equi subspecies equi transmission

Strangles, a disease caused by infection with Streptococccus equi subspecies equi (S. equi), is endemic worldwide and one of the most frequently diagnosed infectious diseases of horses. Recent work has improved our knowledge of key parameters of transmission dynamics, but important knowledge gaps remain. Our aim was to apply mathematical modelling of S. equi transmission dynamics to prioritise future research areas, and add precision to estimates of transmission parameters thereby improving understanding of S. equi epidemiology and quantifying the control effort required. A compartmental deterministic model was constructed. Parameter values were estimated from current literature wherever possible. We assessed the sensitivity of estimates for the basic reproduction number on the population scale to varying assumptions for the unknown or uncertain parameters of: (mean) duration of carriership (1∕γC), relative infectiousness of carriers (f), proportion of infections that result in carriership (p), and (mean) duration of immunity after natural infection (1∕γR). Available incidence and (sero-)prevalence data were compared to model outputs to improve point estimates and ranges for these currently unknown or uncertain transmission-related parameters. The required vaccination coverage of an ideal vaccine to prevent major outbreaks under a range of control scenarios was estimated, and compared available data on existing vaccines. The relative infectiousness of carriers (as compared to acutely ill horses) and the duration of carriership were identified as key knowledge gaps. Deterministic compartmental simulations, combined with seroprevalence data, suggest that 0.05<fˆ<0.5 and that the duration of protective immunity after infection is likely 4–6 years. The presence of carriers alone may suffice to keep S. equi endemic in a population, implying that carriers cannot be ignored in control efforts. Weekly screening of herds for signs of strangles could be sufficient to ensure R < 1, provided all horses are screened for carriership post-infection. In some of worst-case scenarios, vaccination alone would not suffice to prevent major outbreaks from occurring. A stochastic agent-based model was also constructed and validated, and used to simulate a remount depot, to evaluate whether historical incidence data of recurrence of strangles within individuals could be explained without the assumption that one in four horses fail to mount a lasting immune response. These simulations demonstrated that the observed data could have occurred without that assumption.

The reproductive number of swine viral respiratory diseases: A Systematic review.

Abstract A literature search to aggregate peer-reviewed original research articles on R0 of pig viral respiratory diseases. Information about location, methodology, modeling, and data type were extracted.

Microbiome depletion and recovery in the sea anemone, Exaiptasia diaphana, following antibiotic exposure.

Microbial species that comprise host-associated microbiomes play an essential role in maintaining and mediating the health of plants and animals. While defining the role of individual or even complex communities is important toward quantifying the effect of the microbiome on host health, it is often challenging to develop causal studies that link microbial populations to changes in host fitness. Here, we investigated the impacts of reduced microbial load following antibiotic exposure on the fitness of the anemone, Exaiptasia diaphana and subsequent recovery of the host's microbiome. Anemones were exposed to two different types of antibiotic solutions for 3 weeks and subsequently held in sterilized seawater for a 3-week recovery period. Our results revealed that both antibiotic treatments reduced the overall microbial load during and up to 1 week post-treatment. The observed reduction in microbial load was coupled with reduced anemone biomass, halted asexual reproduction rates, and for one of the antibiotic treatments, the partial removal of the anemone's algal symbiont. Finally, our amplicon sequencing results of the 16S rRNA gene revealed that anemone bacterial composition only shifted in treated individuals during the recovery phase of the experiment, where we also observed a significant reduction in the overall diversity of the microbial community. Our work implies that the E. diaphana's microbiome contributes to host fitness and that the recovery of the host's microbiome following disturbance with antibiotics leads to a reduced, but stable microbial state.IMPORTANCEExaiptasia diaphana is an emerging model used to define the cellular and molecular mechanisms of coral-algal symbioses. E. diaphana also houses a diverse microbiome, consisting of hundreds of microbial partners with undefined function. Here, we applied antibiotics to quantify the impact of microbiome removal on host fitness as well as define trajectories in microbiome recovery following disturbance. We showed that reduction of the microbiome leads to negative impacts on host fitness, and that the microbiome does not recover to its original composition while held under aseptic conditions. Rather the microbiome becomes less diverse, but more consistent across individuals. Our work is important because it suggests that anemone microbiomes play a role in maintaining host fitness, that they are susceptible to disturbance events, and that it is possible to generate gnotobiotic individuals that can be leveraged in microbiome manipulation studies to investigate the role of individual species on host health.

SEIR Mathematical Model with the Use of Hand Sanitizers to Prevent the Spread of Covid-19 Disease

The SARS-CoV-2 coronavirus can spread through contact with contaminated surfaces. The use of hand sanitizer is claimed to reduce the risk of transmission. For this reason, this study aims to develop a model of the spread of COVID-19 using the SEIR model with the use of hand sanitizer for infected individuals. The individual population is divided into six compartments, namely two compartments for susceptible individuals who using hand sanitizer and not, one compartment for exposed individuals, two compartments for infected individuals who using hand sanitizer and not, and one compartment for individuals died and recovered. The results obtained two equilibrium points: the disease-free and endemic equilibrium point, and also the basic reproduction number. The existence of a disease-free equilibrium point is unconditional, while the endemic there exist when the basic reproduction number is more than one. Stability analysis of the disease-free equilibrium point is locally asymptotic stable when the basic reproduction number is less than one. Numerical simulations carried out also strengthen them. Finally, the results of basic reproduction number sensitivity analysis show that the basic reproduction number is strongly influenced by contact of the susceptible individuals with exposed and infected individuals, neglecting of hand sanitizer use, mortality and cure rates.

Mathematical Modeling of HIV/AIDS Disease Spread with Public Awareness

This study develops mathematical model for the spread of HIV/AIDS by the population is divided into seven sub-populations, namely the susceptible unaware HIV subpopulation, the susceptible aware HIV sub-population, the infected sub-population, the pre-AIDS sub-population, the ARV treatment sub-population, the AIDS sub-population, and unlikely to be infected with HIV/AIDS sub-population. In this mathematical model, two equilibrium points are obtained, namely the disease-free equilibrium point and the disease-endemic equilibrium point and the basic reproduction number . The stability analysis shows that the disease-free equilibrium point is locally asymptotically stable if and the disease-endemic equilibrium point is locally asymptotically stable if . Numerical simulations of the equilibrium points are carried out to provide an overview of the analyzed results with parameter values from several sources. Based on the sensitivity analysis, the parameters that significantly affect the spread of HIV/AIDS are the contact rate of HIV-unaware individuals with infected individuals and the transmission rate of HIV infection

Effects of Supplemental Diet during Breeding on Fertility, Litter Size, Survival Rate, and Weaning Weight in Mice (Mus musculus).

The addition of supplemental diets to laboratory animals, specifically rodents, is a common practice for the provision of additional nutritional support. We set out to investigate whether the use of commercially available supplemental diets during breeding affected fertility rate, litter size, pup health, and pup survival. Genetically modified female breeding mice with a C57BL/6 background were divided into 3 groups (n = 16 per group) that received standard rodent chow alone or standard rodent chow with one of 2 commercially available supplemental diets: Love Mash (Bio-Serv) extruded pellet or Nutra-Gel (Bio-Serv) diet gel. Male and female mice began receiving the supplemental diet 1 wk before being paired with a partner of the same supplemental group. The mice were allowed to breed for 1 wk before separation from the male. The dams were continued on the diet until all pups were weaned. Overall, breeding dams supplemented with the Love Mash diet experienced significantly greater reproductive success rates and pup survivability compared with the standard diet control group. Dams supplemented with either of the 2 supplemental diets supported significantly larger litters compared with the standard diet control group. Furthermore, Love Mash supplemented diet groups produced significantly larger pups compared with the Nutra-Gel supplemented groups. This study demonstrates that supplemental diets given 1 wk before breeding and continued throughout gestation, parturition, and weaning significantly improved reproductive success, increased litter sizes, and supported pup health and survival.

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 coefficient {for the} infected and susceptible hosts on 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 $R_0$. {If $R_0\leq1$, then the} pathogen particles extinct, and for $R_0&gt;1$ the pathogen particles persist, and we guarantees of the existence of 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.

How to quantify the regional effects of ocean temperature rise due to climate change: implications of Octopus maya ecophysiology on food security of the Yucatan shelf artisanal fishermen

The vital survival, maturation, and reproduction rates of Octopus maya were formulated according to the thermal preferences in each stage (juvenile and adult) and the bottom temperature of the Yucatan shelf projected from different shared socioeconomic pathways (SSPs): SSP1-5, to describe the species population growth in shallow waters. The dispersion of each individual in the population and the spread of the offshore population were incorporated with an integrodifference equation. For each SSP, the food security of the artisanal fishermen in the Western, Central, and Eastern Yucatan shelf region was analyzed based on the proposed availability, access, and utilization indices of Octopus maya as food. The analysis was complemented with an average monthly protein and income poverty indicators that this species’ shallow water fishery would have the capacity to supply by the year 2100. Although the proportion of the legally O. maya catchable population may be favored with the gradual increase in temperature in the coming years, this increase may not translate into greater food security for the artisanal fishermen who catch this species in shallow waters. Moreover, this fishery alone may not have the capacity to supply the average annual intake of 10.6 kg of protein per person recommended and maintain fishermen and their families above the income poverty line by 2100.

Finite Difference Method for Infection Model of HPV with Cervical Cancer under Caputo Operator

In this paper, a fractional model in the Caputo sense is used to characterize the dynamics of HPV with cervical cancer. Generalized mean value theorem has been used to examine whether the infection model has a unique positive solution. The model has two equilibrium points: the disease-free point and the endemic point. The examination of the system’s local and global stability is provided in terms of the basic reproductive number Rp°. The global stability analysis has been carried out using an appropriate Lyapunov function and the LaSalle invariant principle. The results demonstrate that in the infection model, if Rp°&lt;1, then the solution converges to the disease-free equilibrium, which is both locally and globally asymptotically stable. Whilst Rp°&gt;1, the endemic equilibrium is considered to exist. Simulations are implemented via a finite difference method with Grünwald-Letnikov discretization approach for Caputo derivative operator to define how changes in parameters impact the dynamic behavior of the system using Matlab.

Asymptotic profiles of a nonlocal dispersal SIS epidemic model with saturated incidence

Infection mechanism plays a significant role in epidemic models. To investigate the influence of saturation effect, a nonlocal (convolution) dispersal susceptible-infected-susceptible epidemic model with saturated incidence is considered. We first study the impact of dispersal rates and total population size on the basic reproduction number. Yang, Li and Ruan (J. Differ. Equ. 267 (2019) 2011–2051) obtained the limit of basic reproduction number as the dispersal rate tends to zero or infinity under the condition that a corresponding weighted eigenvalue problem has a unique positive principal eigenvalue. We remove this additional condition by a different method, which enables us to reduce the problem on the limiting profile of the basic reproduction number into that of the spectral bound of the corresponding operator. Then we establish the existence and uniqueness of endemic steady states by a equivalent equation and finally investigate the asymptotic profiles of the endemic steady states for small and large diffusion rates to provide reference for disease prevention and control, in which the lack of regularity of the endemic steady state and Harnack inequality makes the limit function of the sequence of the endemic steady state hard to get. Finally, we find whether lowing the movements of susceptible individuals can eradicate the disease or not depends on not only the sign of the difference between the transmission rate and the recovery rate but also the total population size, which is different from that of the model with standard or bilinear incidence.

Dynamics and Control Strategies for SLBRS Model of Computer Viruses Based on Complex Networks

Dynamics and Control Strategies for SLBRS Model of Computer Viruses Based on Complex Networks

Dynamical behavior of a hepatitis B epidemic model and its NSFD scheme

AbstractHepatitis is inflammation of the liver, and one of its types, hepatitis B, is a contagious infection. Using mathematical models, the nature of the spread of the Hepatitis B virus can be predicted. In the present paper, a hepatitis B epidemic model with a Beddington–DeAngelis type incidence rate and a constant vaccination rate is considered. Some dynamical properties of this model, such as non-negativity, boundedness character, the basic reproduction number $$\mathcal {R}_0$$ R 0 , stability nature, and the bifurcation phenomenon, are investigated. By the Bendixson theorem, it is demonstrated that the disease-free equilibrium is globally asymptotically stable. It is shown that a transcritical bifurcation phenomenon occurs when $$\mathcal {R}_0=1$$ R 0 = 1 . It is concluded that the endemic equilibrium is globally asymptotically stable when $$\mathcal {R}_0&gt;1$$ R 0 &gt; 1 , by utilizing Dulac’s criteria. Also, a discrete system of difference equations is obtained by constructing a non-standard finite difference (NSFD) scheme for the continuous model. It is shown that the solutions of this discrete system are dynamically consistent for all finite step sizes. The theoretical results obtained are also supported and visualized by numerical simulations. These simulations also demonstrate that the NSFD scheme produces much more efficient results than the Euler or RK4 schemes, as shown in the theoretical results obtained.