Model Of Malaria Transmission Research Articles

Stability and bifurcation of a delayed Aron-May model for malaria transmission

Stability and bifurcation of a delayed Aron-May model for malaria transmission

Correction to: A mathematical model of malaria transmission with media-awareness and treatment interventions

Correction to: A mathematical model of malaria transmission with media-awareness and treatment interventions

Seasonal variability and stochastic branching process in malaria outbreak probability

Background: Malaria is the world’s most fatal and challenging parasitic disease, caused by the Plasmodium parasite, which is transmitted to humans by the bites of infected female mosquitoes. Bangladesh is the most vulnerable region to spread malaria because of its geographic position. In this paper, we have considered the dynamics of vector-host models and observed the stochastic behavior. This study elaborates on the seasonal variability and calculates the probability of disease outbreaks. Methods: We present a model for malaria disease transmission and develop its corresponding continuous-time Markov chain (CTMC) representation. The proposed vector-host models illustrate the malaria transmission model along with sensitivity analysis. The deterministic model with CTMC curves is depicted to show the randomness in real scenarios. Sequentially, we expand these studies to a time-varying stochastic vector-host model that incorporates seasonal variability. Phase plane analysis is conducted to explore the characteristics of the disease, examine interactions among various compartments, and evaluate the impact of key parameters. The branching process approximation is developed for the corresponding vector-host model to calculate the probability outbreak. Numerous numerical results are accomplished to observe the analytical investigation. Results: Seasonality and contact patterns affect the dynamics of disease outbreaks. The numerical illustration provides that the probability of a disease outbreak depends on the infected host or vector. Additionally, periodic transmission rates have a great influence on the probability outbreak. The basic reproduction number (R0) is derived, which is the main justification for studying the dynamical behavior of epidemic models. Conclusions: Seasonal variability significantly impacts malaria transmission, and the probability of disease outbreaks is influenced by time and the initial number of infected individuals. Moreover, the branching process approximation is applicable when the population size is large enough and the basic reproduction number is less than 1. In the future, such analysis can help decision-makers understand the impact of various parameters and their stochastic behavior in the vector-host model to prevent such types of disease outbreaks.

Seasonal malaria chemoprevention and the spread of Plasmodium falciparum quintuple-mutant parasites resistant to sulfadoxine–pyrimethamine: a modelling study

Seasonal malaria chemoprevention (SMC) with sulfadoxine-pyrimethamine plus amodiaquine prevents millions of clinical malaria cases in children younger than 5years in Africa's Sahel region. However, Plasmodium falciparum parasites partially resistant to sulfadoxine-pyrimethamine (with quintuple mutations) potentially threaten the protective effectiveness of SMC. We evaluated the spread of quintuple-mutant parasites and the clinical consequences. We used an individual-based malaria transmission model with explicit parasite dynamics and drug pharmacological models to identify and quantify the influence of factors driving quintuple-mutant spread and predict the time needed for the mutant to spread from 1% to 50% of inoculations for several SMC deployment strategies. We estimated the impact of this spread on SMC effectiveness against clinical malaria. Higher transmission intensity, SMC coverage, and expanded age range of chemoprevention promoted mutant spread. When SMC was implemented in a high-transmission setting (40% parasite prevalence in children aged 2-10years) with four monthly cycles to children aged 3months to 5years (with 95% initial coverage declining each cycle), the quintuple mutant required 53·1years (95% CI 50·5-56·0) to spread from 1% to 50% of inoculations. This time increased in lower-transmission settings and reduced by half when SMC was extended to children aged 3months to 10years, or reduced by 10-13years when an additional monthly cycle of SMC was deployed. For the same setting, the effective reduction in clinical cases in children receiving SMC was 79·0% (95%CI 77·8-80·8) and 60·4% (58·6-62·3) during the months of SMC implementation when the quintuple mutant was absent or fixed in the population, respectively. SMC with sulfadoxine-pyrimethamine plus amodiaquine leads to a relatively slow spread of sulfadoxine-pyrimethamine-resistant quintuple mutants and remains effective at preventing clinical malaria despite the mutant spread. SMC with sulfadoxine-pyrimethamine plus amodiaquine should be considered in seasonal settings where this mutant is already prevalent. Swiss National Science Foundation and Marie Curie Individual Fellowship.

The Analysis of a Co-Dynamic Ebola and Malaria Transmission Model Using the Laplace Adomian Decomposition Method with Caputo Fractional-Order

The Analysis of a Co-Dynamic Ebola and Malaria Transmission Model Using the Laplace Adomian Decomposition Method with Caputo Fractional-Order

Mathematical Assessment of the Role of Intervention Programs for Malaria Control

Malaria remains a global health problem despite the many attempts to control and eradicate it. There is an urgent need to understand the current transmission dynamics of malaria and to determine the interventions necessary to control malaria. In this paper, we seek to develop a fit-for-purpose mathematical model to assess the interventions needed to control malaria in an endemic setting. To achieve this, we formulate a malaria transmission model to analyse the spread of malaria in the presence of interventions. A sensitivity analysis of the model is performed to determine the relative impact of the model parameters on disease transmission. We explore how existing variations in the recruitment and management of intervention strategies affect malaria transmission. Results obtained from the study imply that the discontinuation of existing interventions has a significant effect on malaria prevalence. Thus, the maintenance of interventions is imperative for malaria elimination and eradication. In a scenario study aimed at assessing the impact of long-lasting insecticidal nets (LLINs), indoor residual spraying (IRS), and localized individual measures, our findings indicate that increased LLINs utilization and extended IRS coverage (with longer-lasting insecticides) cause a more pronounced reduction in symptomatic malaria prevalence compared to a reduced LLINs utilization and shorter IRS coverage. Additionally, our study demonstrates the impact of localized preventive measures in mitigating the spread of malaria when compared to the absence of interventions.

A mathematical model of malaria transmission with media-awareness and treatment interventions

A mathematical model of malaria transmission with media-awareness and treatment interventions

MGDrivE 3: A decoupled vector-human framework for epidemiological simulation of mosquito genetic control tools and their surveillance.

Novel mosquito genetic control tools, such as CRISPR-based gene drives, hold great promise in reducing the global burden of vector-borne diseases. As these technologies advance through the research and development pipeline, there is a growing need for modeling frameworks incorporating increasing levels of entomological and epidemiological detail in order to address questions regarding logistics and biosafety. Epidemiological predictions are becoming increasingly relevant to the development of target product profiles and the design of field trials and interventions, while entomological surveillance is becoming increasingly important to regulation and biosafety. We present MGDrivE 3 (Mosquito Gene Drive Explorer 3), a new version of a previously-developed framework, MGDrivE 2, that investigates the spatial population dynamics of mosquito genetic control systems and their epidemiological implications. The new framework incorporates three major developments: i) a decoupled sampling algorithm allowing the vector portion of the MGDrivE framework to be paired with a more detailed epidemiological framework, ii) a version of the Imperial College London malaria transmission model, which incorporates age structure, various forms of immunity, and human and vector interventions, and iii) a surveillance module that tracks mosquitoes captured by traps throughout the simulation. Example MGDrivE 3 simulations are presented demonstrating the application of the framework to a CRISPR-based homing gene drive linked to dual disease-refractory genes and their potential to interrupt local malaria transmission. Simulations are also presented demonstrating surveillance of such a system by a network of mosquito traps. MGDrivE 3 is freely available as an open-source R package on CRAN (https://cran.r-project.org/package=MGDrivE2) (version 2.1.0), and extensive examples and vignettes are provided. We intend the software to aid in understanding of human health impacts and biosafety of mosquito genetic control tools, and continue to iterate per feedback from the genetic control community.

Analysis of a delayed malaria transmission model including vaccination with waning immunity and reinfection

Analysis of a delayed malaria transmission model including vaccination with waning immunity and reinfection

Design and selection of drug properties to increase the public health impact of next-generation seasonal malaria chemoprevention: a modelling study.

Seasonal malaria chemoprevention (SMC) is recommended for disease control in settings with moderate to high Plasmodium falciparum transmission and currently depends on the administration of sulfadoxine-pyrimethamine plus amodiaquine. However, poor regimen adherence and the increased frequency of parasite mutations conferring sulfadoxine-pyrimethamine resistance might threaten the effectiveness of SMC. Guidance is needed to de-risk the development of drug compounds for malaria prevention. We aimed to provide guidance for the early prioritisation of new and alternative SMC drugs and their target product profiles. In this modelling study, we combined an individual-based malaria transmission model that has explicit parasite growth with drug pharmacokinetic and pharmacodynamic models. We modelled SMC drug attributes for several possible modes of action, linked to their potential public health impact. Global sensitivity analyses identified trade-offs between drug elimination half-life, maximum parasite killing effect, and SMC coverage, and optimisation identified minimum requirements to maximise malaria burden reductions. Model predictions show that preventing infection for the entire period between SMC cycles is more important than drug curative efficacy for clinical disease effectiveness outcomes, but similarly important for impact on prevalence. When children younger than 5 years receive four SMC cycles with high levels of coverage (ie, 69% of children receiving all cycles), drug candidates require a duration of protection half-life higher than 23 days (elimination half-life >10 days) to achieve reductions higher than 75% in clinical incidence and severe disease (measured over the intervention period in the target population, compared with no intervention across a range of modelled scenarios). High coverage is crucial to achieve these targets, requiring more than 60% of children to receive all SMC cycles and more than 90% of children to receive at least one cycle regardless of the protection duration of the drug. Although efficacy is crucial for malaria prevalence reductions, chemoprevention development should select drug candidates for their duration of protection to maximise burden reductions, with the duration half-life determining cycle timing. Explicitly designing or selecting drug properties to increase community uptake is paramount. Bill & Melinda Gates Foundation and the Swiss National Science Foundation.

Global Stability Analysis of the Mathematical Model for Malaria Transmission between Vector and Host Population

Global Stability Analysis of the Mathematical Model for Malaria Transmission between Vector and Host Population

Mathematical analysis and numerical simulations of the piecewise dynamics model of Malaria transmission: A case study in Yemen

<abstract><p>This study presents a mathematical model capturing Malaria transmission dynamics in Yemen, incorporating a social hierarchy structure. Piecewise Caputo-Fabrizio derivatives are utilized to effectively capture intricate dynamics, discontinuities, and different behaviors. Statistical data from 2000 to 2021 is collected and analyzed, providing predictions for Malaria cases in Yemen from 2022 to 2024 using Eviews and Autoregressive Integrated Moving Average models. The model investigates the crossover effect by dividing the study interval into two subintervals, establishing existence, uniqueness, positivity, and boundedness of solutions through fixed-point techniques and fractional-order properties of the Laplace transformation. The basic reproduction number is computed using a next-generation technique, and numerical solutions are obtained using the Adams-Bashforth method. The results are comprehensively discussed through graphs. The obtained results can help us to better control and predict the spread of the disease.</p></abstract>

Optimal Control of a Malaria Transmission Model with Saturated Incidence

Optimal Control of a Malaria Transmission Model with Saturated Incidence

Relative importance of VECTRI model parameters in the malaria disease transmission and prevalence.

In this study, a sensitivity analysis on a VECTRI dynamical model of malaria transmission is investigated to determine the relative importance of model parameters to disease transmission and prevalence. Apart from being most climatic prone, Odisha is a highly endemic state for malaria in India. The lack in sufficient modeling studies severely impacts the malarial process studies which further hinder the possibility of malaria early warning systems and preventive measures to be undertaken beforehand. Therefore, modeling studies and investigating the relationship between malaria transmission process studies and associated climatic factors are the need of the hour. Environmental conditions have pronounced effects on the malaria transmission dynamics and abundance of the poikilothermic vectors, but the exact relationship of sensitivity for these parameters is not well established. Sensitivity analysis is a useful tool for ascertaining model responses to different input variables. Therefore, in order to perform the requisite study, a dynamical model, VECTRI, is utilized. The study period ranges from 2000 to 2013, where several sensitivity tests are performed using different model parameters such as infiltration and evaporation rate loss of ponds, degree-days for parasite development, threshold temperature for parasite development, threshold temperature for egg development in the vector, and maximum and minimum temperature for larvae survival. The experiments suggest that the lower value of minimum temperature for larvae survival (rlarv_tmin), i.e., 16°C, provides higher vector density and entomological inoculation rate (EIR) values. EIR reaches its maximum, when the threshold temperature for parasite development (rtsporo) is 22°C and degree-days for parasite development (dsporo) is 8 degree-days. No change is observed in the vector density; even when rtsporo is 30°C, values of EIR are close to 0. A successive increment of infiltration and evaporation rate loss of ponds (rwaterfrac evap126) values from 130 to 200 mm/day result in approximately 5% consistent decline in vector density and EIR. The study concludes that the most sensitive parameters are dsporo, rlarv_tmin, and rwaterfrac evap126. The VECTRI model is rather insensitive to maximum temperature for larvae survival (rlarv_tmin) for vector density and EIR variables. Further certain modifications and improvements are required in VECTRI to predict out variables like vector density and EIR more accurately in highly endemic region.

Evolutionary modelling indicates that mosquito metabolism shapes the life-history strategies of Plasmodium parasites

Within-host survival and between-host transmission are key life-history traits of single-celled malaria parasites. Understanding the evolutionary forces that shape these traits is crucial to predict malaria epidemiology, drug resistance, and virulence. However, very little is known about how Plasmodium parasites adapt to their mosquito vectors. Here, we examine the evolution of the time Plasmodium parasites require to develop within the vector (extrinsic incubation period) with an individual-based model of malaria transmission that includes mosquito metabolism. Specifically, we model the metabolic cascade of resource allocation induced by blood-feeding, as well as the influence of multiple blood meals on parasite development. Our model predicts that successful vector-to-human transmission events are rare, and are caused by long-lived mosquitoes. Importantly, our results show that the life-history strategies of malaria parasites depend on the mosquito’s metabolic status. In our model, additional resources provided by multiple blood meals lead to selection for parasites with slow or intermediate developmental time. These results challenge the current assumption that evolution favors fast developing parasites to maximize their chances to complete their within-mosquito life cycle. We propose that the long sporogonic cycle observed for Plasmodium is not a constraint but rather an adaptation to increase transmission potential.

Propagation dynamics of cooperative reaction-diffusion systems in a periodic shifting environment

This paper is devoted to the study of propagation dynamics for a large class of nonautonomous cooperative reaction-diffusion systems in a time-periodic shifting environment. We first establish the spreading properties of solutions and the existence of forced time-periodic waves for such a system by appealing to the abstract theory developed for monotone semiflows with asymptotic translation invariance. Then we prove the uniqueness of the forced wave and its attractivity under appropriate conditions. Finally, we apply our analytical results to a reaction-diffusion-advection model of malaria transmission.

Role of Differential Susceptibility and Infectiousness on the Dynamics of an SIRS Model for Malaria Transmission

A deterministic model for the transmission dynamics of SIRS-type malaria in hosts and SI in mosquito populations is proposed. The host population is differentiated between naive, primary, and secondary susceptible individuals. Primary and secondary infected individuals (and also recovered) are differentiated from each other according to their degree of infectiousness. The impact of changing the relative susceptibilities of primary and secondary (with respect to naive) susceptible individuals on the dynamics is investigated. Also, the impact of changing the relative infectiousness of secondary infected, primary, and secondary recovered individuals (with respect to primary infected) on the transmission dynamics of malaria is studied.

Threshold dynamics of an almost periodic vector-borne disease model.

Many infectious diseases cannot be transmitted from human to human directly, and the transmission needs to be done via a vector. It is well known that vectors' life cycles are highly dependent on their living environment. In order to investigate dynamics of vector-borne diseases under environment influence, we propose a vector-borne disease model with almost periodic coefficients. We derive the basic reproductive number [Formula: see text] for this model and establish a threshold type result on its global dynamics in terms of [Formula: see text]. As an illustrative example, we consider an almost periodic model of malaria transmission. Our numerical simulation results show that the basic reproductive number may be underestimated if almost periodic coefficients are replaced by their average values . Finally, we use our model to study the dengue fever transmission in Guangdong, China. The parameters are chosen to fit the reported data available for Guangdong. Numerical simulations indicate that the annual dengue fever case in Guangdong will increase steadily in the near future unless more effective control measures are implemented. Sensitivity analysis implies that the parameters with strong impact on the outcome are recovery rate, mosquito recruitment rate, mosquito mortality rate, baseline transmission rates between mosquito and human. This suggests that the effective control strategies may include intensive treatment, mosquito control, decreasing human contact number with mosquitoes (e.g., using bed nets and preventing mosquito bites), and environmental modification.

A two-strain malaria transmission model with seasonality and incubation period

A two-strain malaria transmission model with seasonality and incubation period

Threshold dynamics and regional optimal control of a malaria model with spatial heterogeneity and ivermectin therapy

The recent experimental results illustrate that adding ivermectin to artemisinin-based combination therapy can target malaria parasite and its vector, which may be a new treatment option. In this paper, we present a new malaria transmission model, which incorporates spatial heterogeneity, general incidence rate and treatment plan with ivermectin. The basic reproduction number R0 is introduced as a threshold parameter to determine whether malaria will eventually die out or not. Further, we propose and analyze the regional optimal control problem to minimize mosquito population, exposed and infectious humans as well as cost. Numerically, we investigate the transmission and control of malaria in The Gambia. Results show that the treatment plans with ivermectin and without ivermectin have the same contribution to R0, but have different effects on the epidemic level of malaria. This conclusion also holds for different incidence rates with some assumptions. Moreover, by comparing the cost and benefit of different strategies, the most cost-effective strategy is found.