Disease Transmission Rates Research Articles

Optimal control of susceptible mature pest concerning disease-induced pest-natural enemy system with cost-effectiveness

Abstract This article addresses the pressing issue of pest outbreaks in India, which poses significant challenges for farmers and ecologists. A novel system is proposed for effective control that leverages natural enemies. Here, the pests are classified into juveniles and mature individuals, further categorized as susceptible or infected. The study introduces harvesting, incorporating external efforts and natural phenomena, in a pest-epidemic prey–predator system featuring a prey-stage structure. The model reveals three equilibria: trivial, boundary (indicating the absence of natural enemies), and interior equilibria. Notably, the trivial equilibrium is consistently unstable. As demonstrated by stability analysis, the survival or extinction of natural enemies hinges on control variables, including the harvesting rate, disease transmission rate, and natural death rate. Local stability is assessed using the Routh–Hurwitz criterion, while global stability is explored through the Lyapunov method. Furthermore, optimal control theory and Pontryagin’s maximum principle are applied for model optimization, unveiling crucial optimality conditions and determining the optimal harvesting rate for susceptible mature prey. Numerical computations validate theoretical insights, offering valuable guidance for formulating policies that optimize the control of susceptible adult pests within a disease-induced pest-natural enemy system, ensuring sustained cost-effectiveness.

Dynamics of an EIS spatially heterogeneous rabies model

This paper is devoted to the study of population dynamics of an EIS epidemic reaction-diffusion model in spatially heterogeneous environments, where the rates of disease-induced mortality and disease transmission are space dependent. For such a class of systems, we provide clear pictures on the global dynamics in terms of the basic reproduction number R0, which improves the local dynamics proposed in Wang and Zhao (2012) [20]. When R0≤1, the disease-free steady state is globally asymptotically stable. Different from earlier works for many epidemic models, we obtain the positive steady states by using bifurcation theory for R0>1, which can be easily generalized to the case where the reaction-diffusion system involves partial diffusion coefficients of zero.

Functional data learning using convolutional neural networks

In this paper, we show how convolutional neural networks (CNNs) can be used in regression and classification learning problems for noisy and non-noisy functional data (FD). The main idea is to transform the FD into a 28 by 28 image. We use a specific but typical architecture of a CNN to perform all the regression exercises of parameter estimation and functional form classification. First, we use some functional case studies of FD with and without random noise to showcase the strength of the new method. In particular, we use it to estimate exponential growth and decay rates, the bandwidths of sine and cosine functions, and the magnitudes and widths of curve peaks. We also use it to classify the monotonicity and curvatures of FD, the algebraic versus exponential growth, and the number of peaks of FD. Second, we apply the same CNNs to Lyapunov exponent estimation in noisy and non-noisy chaotic data, in estimating rates of disease transmission from epidemic curves, and in detecting the similarity of drug dissolution profiles. Finally, we apply the method to real-life data to detect Parkinson’s disease patients in a classification problem. We performed ablation analysis and compared the new method with other commonly used neural networks for FD and showed that it outperforms them in all applications. Although simple, the method shows high accuracy and is promising for future use in engineering and medical applications.

Entomological Survey and Temephos Susceptibility of Aedes, Culex and Anopheles in Naena Muktipura Mimika Papua

Introduction: Arthropod-borne diseases are infectious diseases mediated by mosquitoes that have incurred a considerable health problem. The prevalence of this disease is notably high in some rural areas, such as Papua, due to some environmental conditions that support mosquitoes breeding sites and leads to high rate of disease transmission. Methods: This experimental research aims to determine the breeding site, mosquitos’ diversity, and susceptibility to temephos insecticide through an entomological survey to find out the breeding site of the larvae. The positive breeding sites of the larva were captured and identified in the laboratory. The temephos test were carried out for each species of larvae at dose 0,02 ppm for Aedes albopictus and Culex sp, and 0.25 ppm for Anopheles sp. Results and Discussion: Entomology survey showed that 5 of 27 stagnant water were positive breeding site of mosquito larvae. The following larvae were found: Aedes sp, Culex sp and Anopheles sp. Culex sp and Anopheles sp prefer dirty stagnant water covered with leaves, while Aedes albopictus likes puddles that are exposed to direct sunlight. The three species were known to be susceptible to temephos. Conclusion: There are three species of Diptera in Naena Muktipura village, with different characteristics of breeding site, but those mosquitoes are all susceptible to temephos.

Modeling the response of an endangered rabbit population to RHDV2 and vaccination

AbstractRabbit hemorrhagic disease virus 2 (RHDV2), recently detected in the western United States, has the potential to cause mass mortality events in wild rabbit and hare populations. Currently, few management strategies exist other than vaccination. We developed a spatially explicit model of RHDV2 for a population of riparian brush rabbits (Sylvilagus bachmani riparius), a subspecies of brush rabbit classified as endangered in the United States, on a subsection of the San Joaquin River National Wildlife Refuge. The goal of our model was to provide guidance regarding vaccination strategies for an endangered rabbit species. Our model predicts that increased interactions between rabbits (a proxy for landscape connectivity) and disease transmission rates among susceptible hosts (individual brush rabbits and conspecifics) have the greatest influence on the outcome of a potential vaccination campaign. Our model projects that across a range of parameter estimates (given an RHDV2 incursion), the median estimated population size with a 0%–10% vaccination rate after 1 year is 538 rabbits (95% Confidence Interval [C.I.] 69–1235), approximately 36% of the expected size of the study population of 1470 rabbits without an RHDV2 introduction. With a 10%–20%, 20%–30%, or 30%–40% vaccination rate, the median estimated population size increased to 628 rabbits (95% C.I. 130–1298), 723 rabbits (95% C.I. 198–1317), and 774 rabbits (95% C.I. 228–1410), respectively. These estimates represent 43%, 49%, and 53% of the expected population size without an RHDV2 introduction. Overall, a 1% increase in vaccination rate was associated with a six rabbit (95% C.I. 5–7) increase in total remaining population size. This result is dependent on assumptions regarding environmental transmission, home range size (and contact rates of rabbits). Given the relatively short lifespan of rabbits and the potential need for boosters, vaccination programs are most likely to be successful for small target populations where relatively high vaccination rates can be maintained.

Detection of mycobacterium tuberculosis by microscopic examination and gene expert in a suspected patient with pulmonary tuberculosis disease, in Dili City, East Timor

Tuberculosis is one of the most dangerous and deadly diseases, so control is needed to reduce the transmission rate of TB disease and mortality among the community, so the gene method is very appropriate to be able to help in diagnosing TB. Acid-resistant bacilli are bacteria that have a very thick lipid content so that the staining cannot be affected by other dye reactions, except by using phenol and through the heating process. Mycobacterium tuberculosis has a cell wall consisting of a waxy coating and mycolic acid; therefore, these bacteria can only color with BTA. Mycbakterium Tuberculosis can maintain the first color, namely Carbun Fuchin, and fight decolorization with alcoholic acid, so this bacterium is called an acid-resistant bacillus. The right examination method to diagnose TB disease is necessary to be able to follow the appropriate treatment so as to reduce transmission and death rates due to TB disease. The aim of this research is to analyze the difference in examination results using microscopes and Gene Xpert machines in Dili district in suspected patients with pulmonary tuberculosis.

Global dynamics and optimal control of a nonlinear fractional-order cholera model

In this article, a fractional-order epidemic model for cholera is proposed and analyzed. Two transmission routes for cholera are considered to develop the compartmental epidemic model. The basic biological properties of the solutions of the fractional-order model are investigated. The global asymptotic stability of the equilibrium points have been established using appropriate Lyapunov functional. Moreover, a fractional-order control problem is presented, and its analytical solution is derived using Pontryagin’s maximum principle. Also, some graphical visualizations of the theoretical results are provided. It is found that the factional-order derivative only affect the time to reach the stationary states. Sensitivity analysis reveals that by reducing the rates of new recruitment and both the disease transmission rates, it may be possible to reduce the value of the basic reproduction number.

Global dynamics and optimal control of a nonlinear fractional-order cholera model

In this article, a fractional-order epidemic model for cholera is proposed and analyzed. Two transmission routes for cholera are considered to develop the compartmental epidemic model. The basic biological properties of the solutions of the fractional-order model are investigated. The global asymptotic stability of the equilibrium points have been established using appropriate Lyapunov functional. Moreover, a fractional-order control problem is presented, and its analytical solution is derived using Pontryagin’s maximum principle. Also, some graphical visualizations of the theoretical results are provided. It is found that the factional-order derivative only affect the time to reach the stationary states. Sensitivity analysis reveals that by reducing the rates of new recruitment and both the disease transmission rates, it may be possible to reduce the value of the basic reproduction number.

Mathematical Modelling and Analysis of Dengue Transmission Dynamics

Understanding and resolving the complexity of diseases such as dengue need the use of mathematical modelling, which enables us to forecast outbreaks, create practical solutions, and allocate resources effectively to lessen the disease's effects. This research proposes a mathematical model that examines the dynamics of dengue illness transmission. Te model accounts for a number of important factors that affect the disease's spread, including the increase of the mosquito population, how long it takes an illness to develop and the extent to which infected humans also infect mosquitoes. Further, basic reproduction number has been calculated using the next generation matrix method for the single strain dengue model and SEIR-SEI model has been analyzed via mathematical theorems showing the positivity of the solutions and boundedness of the equations governing the proposed model. Sensitivity analysis has been done for basic reproduction number R0. Te findings indicate that the basic reproduction number primarily depends on factors such as the transmission rate of disease and the rate at which mosquitoes become infected by infectious human beings and depends inversely on factors such as the recovery rate of humans and the rate at which mosquitoes transmit the virus to humans. Numerical simulations have been done on a small population to show the number of people and number of mosquitoes in different compartments at any given time t and it shows the progress of disease transmission in a population.

Mathematical modeling of infectious diseases and the impact of vaccination strategies.

Mathematical modeling plays a crucial role in understanding and combating infectious diseases, offering predictive insights into disease spread and the impact of vaccination strategies. This paper explored the significance of mathematical modeling in epidemic control efforts, focusing on the interplay between vaccination strategies, disease transmission rates, and population immunity. To facilitate meaningful comparisons of vaccination strategies, we maintained a consistent framework by fixing the vaccination capacity to vary from 10 to 100% of the total population. As an example, at a 50% vaccination capacity, the pulse strategy averted approximately 45.61% of deaths, while continuous and hybrid strategies averted around 45.18 and 45.69%, respectively. Sensitivity analysis further indicated that continuous vaccination has a more direct impact on reducing the basic reproduction number $ R_0 $ compared to pulse vaccination. By analyzing key parameters such as $ R_0 $, pulse vaccination coefficients, and continuous vaccination parameters, the study underscores the value of mathematical modeling in shaping public health policies and guiding decision-making during disease outbreaks.

Modeling and optimal control of COVID-19 and malaria co-infection based on vaccination

<p>Malaria is a serious health problem in Africa, and the ongoing COVID-19 pandemic has affected the implementation of key malaria control interventions. This jeopardizes the gains made in malaria. As a result, a new co-infection model of COVID-19 and malaria is constructed, and the role of vaccination in COVID-19-malaria co-infection is analyzed. The existence and stability of the equilibria of each single infection are first studied by their respective basic reproduction numbers. When the basic reproduction numbers $ R_{C0} $ and $ R_{M0} $ are both below unity, the COVID-19-malaria-free equilibrium is locally asymptotically stable. Sensitivity analysis reveals that the main parameters affecting the spread of diseases are their respective disease transmission rate and vaccine efficacy. Further, we introduce the effect of vaccination rate and efficacy on controlling the co-infected population. It also shows that under the condition of a low recovery rate caused by the shortage of medical resources, improving the vaccination rate and effectiveness of vaccines has a positive impact on suppressing diseases. The model is then extended into an optimal control system by introducing prevention and treatment measures for COVID-19 and malaria. The results suggest that applying each strategy alone can reduce the scale of co-infection, but strategy A increases the number of malaria cases and strategy B prolongs the period of COVID-19 infection. Measures to control COVID-19 must be combined with efforts to ensure malaria control is maintained.</p>

Situational Analysis of Malaria Incidence Under Integrated Malaria Service in Hotspot Township - Minbya Township, Rakhine State, Myanmar, 2017-2020.

Malaria is a significant public health concern and tropical disease, particularly affecting Myanmar within the Greater Mekong Subregion. The annual parasite index (API) exceeds 1 per 10,000 population in the northern seven townships of Rakhine State, with Minbya Township designated as a high-burden area for malaria by the World Health Organization (WHO) Myanmar and the National Malaria Control Programme (NMCP). Since 2017, the Malaria reduction intensification plan has been in place in this township to combat the high disease transmission rates. This study aims to assess the malaria epidemiology in Minbya Township from 2017 to 2020 under the intensification plan for elimination, as well as to evaluate the effectiveness of the integrated strategy in reducing cases in hotspot areas. The study utilized a surveillance study design to collect secondary data from the Malaria surveillance system (MSS) and the epidemiologic monitoring dashboard of Minbya Township, Maruk-U District, located in Rakhine State. Since 2017, the Malaria prevention and control (P&C) Program in Minbya Township has successfully decreased malaria morbidity, eliminated malaria-related deaths, and bolstered malaria testing capabilities through the participation of village health volunteers (VHVs). Approximately 87% of malaria prevention and control services are executed by the township's malaria elimination and disease control programs, with additional support from stakeholders. The API dropped from 13 in 2017 to 2.5 in 2020, with Plasmodium vivax being the most prevalent malaria species, accounting for 55% of cases. The study suggests that early diagnosis and promotion of artemisinin-based combination treatment (ACT), along with strategic planning including expanding active case detection in rural health centers and implementing a community-based integrated healthcare approach, are effective and efficient strategies for malaria elimination.

Mathematical analysis and simulation of COVID-19 model with booster dose vaccination strategy in Bangladesh

The control of COVID-19 transmission remains a crucial issue despite the administration of multiple doses of vaccines, given the ongoing emergence of new variants. This study proposes a mathematical model of COVID-19 with multiple doses of vaccinations. We find disease-free equilibrium (DFE) and disease-endemic equilibrium (DEE) and perform their stability analysis to explore in which parameters space the disease will be fade-out or persists in the population. This study derives mathematical expressions for the basic reproductive numbers (R0) using the Next-Generation Matrix method. Using surface and contour plots, we brought to light the exciting consequences of disease transmission rate and other parameter values on the basic reproduction number (R0). It demonstrates that the disease-free equilibrium point is locally stable when R0 < 1, whereas the disease-endemic equilibrium point is locally stable for R0 > 1. We also perform bifurcation analysis to demonstrate in which conditions the disease will be stable or unstable when R0 = 1. Numerical simulations show that increasing first dose vaccination rate is more effective than second and booster doses vaccination rate for reducing the number of asymptomatic and symptomatic cases in Bangladesh. We use COVID-19 incidence data from WHO between January and December 2022 and estimate parameters using the least-squares technique. We perform the sensitivity index of symptomatic and asymptomatic cases to identify the most significant parameter for disease outbreaks and found that transmission rate had the highest impact on disease prevalence. This research provides insight to prevent and control of COVID-19 transmission with booster-dose vaccination in Bangladesh.

A mathematical model for predicting and controlling COVID-19 transmission with impulsive vaccination

&lt;abstract&gt;&lt;p&gt;This study examines an epidemiological model known as the susceptible-exposed-infected-hospitalized-recovered (SEIHR) model, with and without impulsive vaccination strategies. First, the model was analyzed without impulsive vaccination in the presence of a reinfection effect. Subsequently, it was studied as part of a periodic impulsive vaccination strategy targeting the susceptible population. These vaccination impulses were administered in very brief intervals at specific time instants, with a fixed time gap between each impulse. The two approaches can be modified to respond to different amounts of susceptibility, with control efforts intensifying as susceptibility levels rise. The model's analysis includes crucial aspects such as the non-negativity of solutions, the existence of steady states, and the stability corresponding to the basic reproduction number. We demonstrate that when vaccination measures are taken into account, the basic reproduction number remains as less than one. Therefore, the disease-free equilibrium in the case of vaccination could still be asymptotically stable at the higher disease transmission rate, as compared to the case of no vaccination in which the disease-free equilibrium may no longer be asymptotically stable. Furthermore, we show that when the disease-free equilibrium is stable, the endemic equilibrium cannot be attained, and that when the reproduction number rises above unity, the disease-free equilibrium becomes unstable while the endemic equilibrium becomes stable. We have also derived conditions for the global stability of both equilibriums. To support our theoretical results, we have constructed a time series of numerical simulations and compared them with real-world data from the ongoing SARS-CoV-2 (COVID-19) pandemic.&lt;/p&gt;&lt;/abstract&gt;

The Application of SLAM in Life and Scientific Research

This article mainly focuses on the application of SLAM in technology and provides a literature review on the following aspects: 1) The application of SLAM in automatic parking of automobiles. This includes using AVP-SLAM for high-precision automatic parking in outdoor parking lots using convolutional neural networks, and using MOFISLM for high-precision automatic parking when indoor GPS signals are poor. 2) The application of SLAM in robotics. It includes three aspects. The first is using the GMapping algorithm to construct and locate maps with high accuracy, low computational complexity, and high robustness, enabling robots to plan the shortest path in unknown environments. The second is to use ORB-SLAM2, which can handle more complex situations, to navigate medical institution robots to improve hospital efficiency and reduce disease transmission rates. The third is for robots that perform tasks in complex and unknown terrains. The improved version of LAMP1.0, LAMP2.0, which is suitable for complex underground environments, can achieve multi robot collaborative cooperation with high accuracy and robustness. 3) Application of SLAM in the field of unmanned aerial vehicles. This article mainly elaborates on four aspects. The first is to use visual SLAM to achieve collaborative work between ground robots and drones, and to utilize the high camera advantage of drones to quickly build maps for ground robots, improve accuracy, and save time. The second is to utilize the application of VSLAM on unmanned aerial vehicles to contribute to agriculture. The third is ORB-SLAM3 to provide rapid and high-precision landing on deck for unmanned aerial vehicles in maritime missions. The fourth is using SLAM to assist unmanned aerial vehicles in landing in emergency or position situations (such, when GPS signals are lost).

High-Density Communities and Infectious Disease Vulnerability: A Built Environment Perspective for Sustainable Health Development

High-density communities have proliferated globally during rapid urbanization. They are characterized by a high population density and limited per capita public spaces, making them susceptible to infectious disease risks. The impact of infectious diseases in these communities, as evident during the COVID-19 pandemic, underscores their vulnerabilities. Yet, research on disease prevention in high-density areas remains limited. This study aims to investigate the relationship between the built environment and the transmission of infectious diseases in high-density urban communities, with a particular focus on the lessons learned during the COVID-19 pandemic. Utilizing Shenzhen city as a case study, this study collected data on the built environment and epidemic trends and involved a generalized linear regression analysis, aiming to understand the key built environment factors that affect epidemic spread in high-density areas. The results from the study revealed that high-density communities experience higher rates of infectious disease transmission compared to their medium- to low-density counterparts. The significant factors identified include land use mixture and walkability, with land use mixture showing the most substantial impact on infection rates. Through a combination of qualitative analysis and empirical research, we constructed a conceptual framework linking containment measures, non-pharmaceutical interventions, and the built environment. The findings emphasize the significance to focus on the health development of high-density communities and offer valuable insights for tailored urban planning and built environment design. These insights are crucial for promoting the healthy and sustainable transformation of existing high-density communities.

Impacts of non-locality and memory kernel of fractional derivative, awareness and treatment strategies on HIV/AIDS prevalence

We propose a Liouville–Caputo non-linear fractional order α(0<α≤1) epidemic model to understand the transmission dynamics of infectious diseases, like HIV/AIDS, and explore the presence of memory kernel of fractional derivative for the precautionary measure against the transmission of disease to control HIV/AIDS prevalence. A proper sex education, which depends on number of HIV and AIDS, to unaware susceptible as well as fear of infection among these aware susceptible are employed here. Treatment compartment is incorporated to treat the symptomatic HIV and AIDS infected individuals.Using the Banach fixed point theorem, we first ensure the positivity, existence and uniqueness of solution, and biologically feasible region. Next after defining the basic reproduction number (R0), its uses on stability (local and global) and direction of bifurcation are manifested here. A quantitative assessment is conducted onR0and then we explore the sensitive parameter/s, which control the HIV/AIDS prevalence.Numerical experiment is conducted based on the Adams–Bashforth–Moulton predictor corrector method to obtain the approximate solution of the proposed model. Impacts of disease transmission rate, awareness, psychological fear of infection and treatment strategies on the HIV/AIDS prevalence are analysed based on non-linear dynamical tools, like, time series, phase diagram and spectra analysis. An effort is made to see how the order and kernel of the fractional derivative play a crucial role on the dynamics of the system and in the precautionary measure against the transmission of disease during transition as well as post-transition phases. We employ intervention strategies for controlling the spread as well as possibility of eradicating the HIV/AIDS prevalence. It is seen that the reduction ofαis comparable to awareness, psychological fear of infection and treatment strategies to control disease. Finally, it is shown that the use of fractional derivative in disease transmission dynamics is one of the most efficient applied mathematics content compatible with the natural characteristics of human memory.

Managing Addiction and Overdose Deaths: The Debate Over America's Safe Injection Spaces.

In the decade between 2010 and 2020, the number of people killed by opioid overdoses more than tripled, reaching 68,630. Among drug users in their second and third decades of life, hepatitis B and C are also on the rise. New York City's two new supervised drug injection sites (SDISs) reversed 114 overdoses within two months, and 585 people injecting drugs visited the facility 4,974 times. By providing medical professionals and a sterile and safe environment, supervised injection sites reduce overdose risk and save lives. This suggests that SDISs could be an important adjunct to currently failing strategies to combat the nation's raging opioid crisis, particularly in the aftermath of the COVID-19 pandemic. Here, we examine the perception and impact of SDISs as well as efforts by the United States Congress (H.R. 7029 and H.R. 6159) toward their prevention. We look into the perspectives of major stakeholders, such as residents, business owners, drug users, legislators, taxpayers, and the general public, and investigate the short- and long-term consequences of SDISs based on crime statistics and published data on opioid use, overdose deaths, and blood-borne disease transmission rates.

ANALISIS KESTABILAN MODEL SI UNTUK PENYAKIT MENULAR DENGAN ADANYA TRANSMISI VERTIKAL DAN TINGKAT KEJADIAN JENUH

The transmission of infectious diseases can occur through two pathways: horizontal and vertical. Horizontal transmission occurs through direct or indirect physical contact with the infectious agent, while vertical transmission takes place when an infected mother transmits the disease to a fetus or a newborn. Within the context of disease transmission models, a critical feature is the saturation incidence rate, which refers to the impact of interventions that can reduce the rate of disease transmission among susceptible and infected individuals. This research aims to elucidate the formation of a model, determine equilibrium points, and calculate the basic reproduction number using the Next Generation Matrix method. The analysis involves assessing local stability through linearization methods and global stability using Lyapunov functions. Sensitivity analysis is conducted on the basic reproduction number, and numerical simulations are performed using the fourth-order Runge-Kutta method. The research findings indicate the establishment of an SIS (Susceptible-Infected) model for infectious diseases with vertical transmission and saturation incidence. This model depicts the spread of the disease in a population, where individuals can exist in susceptible or infected conditions. Equilibrium points include a disease-free equilibrium that is locally and globally stable when the basic reproduction number is less than one, and an endemic equilibrium that is locally and globally stable when the basic reproduction number exceeds one. Sensitivity analysis reveals that each parameter has varying influences on the basic reproduction number. An increase in the saturation incidence rate leads to a decrease in the number of infected subpopulations, while an increase in the vertical transmission rate results in a similar decline. Numerical simulations support stability analyses at equilibrium points. These findings provide a deeper understanding of the factors influencing the spread of diseases within a population.

The analysis of deterministic and stochastic SIM model with general information intervention

In this paper, we propose an epidemic model with the impact of information intervention and general incidence rate in deterministic and stochastic environment, respectively. The information intervention prompts susceptible individuals to change their behavior to protect themselves from infection. First, the asymptotic dynamics of the disease-free equilibrium and the unique endemic equilibrium are analyzed and the results indicate that the basic reproduction number is a pointy disease threshold about the stability under some conditions. Then, we formulate the corresponding stochastic model by perturbing the disease transmission rate and information response rate parameters by white noise terms and provide verifiable sufficient conditions for extinction and persistence in mean. Two sufficient conditions for extinction show that if the noise intensity of the disease transmission rate is large enough or small enough, the infected population of the stochastic system will tend to go extinct. For the persistence, we get the sufficient conditions which guarantee the infected population to be persistent in the mean. Finally, we perform some numerical simulations to compare the dynamic behaviors of the deterministic and the stochastic system.