Epidemiological impacts of age structures on human malaria transmission

Malaria is one of the most common mosquito-borne diseases widespread in tropical and subtropical regions, causing thousands of deaths every year in the world. In a previous paper, we formulated an age-structured model containing three structural variables: (i) the chronological age of human and mosquito populations, (ii) the time since they are infected, and (iii) humans waning immunity (i.e. the progressive loss of protective antibodies after recovery). In the present paper, we expand the analysis of this age-structured model and focus on the derivation of entomological and epidemiological results commonly used in the literature, following the works of Smith and McKenzie. We generalize their results to the age-structured case. In order to quantify the impact of neglecting structuring variables such as chronological age, we assigned values from the literature to our model parameters. While some parameters values are readily accessible from the literature, at least those about the human population, the parameters concerning mosquitoes are less commonly documented and the values of a number of them (e.g. mosquito survival in the presence or in absence of infection) can be discussed extensively

Optimal intervention strategies of staged progression HIV infections through an age-structured model with probabilities of ART drop out

In this paper, we construct a model to describe the transmission of HIV in a homogeneous host population. By considering the specific mechanism of HIV, we derive a model structured in three successive stages: (i) primary infection, (ii) long phase of latency without symptoms and (iii) AIDS. Each HIV stage is stratified by the duration for which individuals have been in the stage, leading to a continuous age-structure model. In the first part of the paper, we provide a global analysis of the model depending upon the basic reproduction number R 0. When R 0 ≤ 1, then the disease-free equilibrium is globally asymptotically stable and the infection is cleared in the host population. On the contrary, if R 0 > 1, we prove the epidemic's persistence with the asymptotic stability of the endemic equilibrium. By performing the sensitivity analysis, we then determine the impact 1 of control-related parameters of the outbreak severity. For the second part, the initial model is extended with intervention methods. By taking into account ART interventions and the probability of treatment drop out, we discuss optimal interventions methods which minimize the number of AIDS cases

Predator-Prey Model with Prey Harvesting, Holling Response Function of Type III and SIS Disease

The populations of prey and predator interact with prey harvesting. When there is no predator, the logistic equation models the behavior of the preys. For interactions between preys and predators, we use the generalized Holling response function of type III. This function which models the consumption of preys by predators is such that the predation rate of predators increases when the preys are few and decreases when they reach their satiety. Our main goal is to analyze the influence of a SIS infectious disease in the community. The epidemiological SIS model with simple mass incidence is chosen, where only susceptibles and infectious are counted. We assume firstly that the disease spreads only among the prey population and secondly that it spreads only among the predator population. There are many bifurcations as: Hopf bifurcation, transcritical bifurcation and saddle-node bifurcation. The results indicate that either the disease dies out or persists and then, at least one population can disappear because of infection. For some particular choices of the parameters however, there exists endemic equilibria in which both populations survive. Numerical simulations on MATLAB and SCILAB are used to illustrate our results

Optimizing MDA and antimalarial treatment in the presence of drug resistance for effective malaria control

Antimalarial drugs are critical for controlling malaria, but the emergence of drug resistance poses a significant challenge to global eradication efforts. This study explores strategies to minimize resistance prevalence and improve malaria control, particularly through the use of mass drug administration (MDA) in combination with antimalarial drugs. We develop a compartmental mathematical model that incorporates asymptomatic, paucisymptomatic, and clinical states of infection and evaluates the impact of resistance mutations on transmission dynamics. The model includes both treated and untreated states among infected and recovered individuals, with a focus on optimizing control strategies through MDA and antimalarial treatment. A global sensitivity analysis identifies the critical factors that influence malaria dynamics, including MDA coverage, treatment access for different infection states, the probability of mutation from treated sensitive human infections, to treated resistant human infections and the initial prevalence of resistance. The model is extended to include optimal control strategies that provide time-dependent control interventions for treatment and MDA. Intuitively, when the mutation rate is relatively low, the optimal strategy combines the use of antimalarial drugs and MDA, with a gradual decrease in antimalarial drug use over time, ensuring sustainable malaria control. In contrast, at higher mutation rates, the strategy prioritizes broader deployment of MDA while significantly reducing reliance on antimalarial to minimize the risk of resistance developing. Numerical simulations of the optimal control problem reinforce the importance of strategic intervention in mitigating drug resistance. This study contributes to understanding the role of MDA and treatment strategies in the control of malaria, with implications for optimizing malaria control programs in endemic regions.</p

Mosquito ageing modulates the development, virulence and transmission potential of pathogens

Host age variation is a striking source of heterogeneity that can shape the evolution and transmission dynamic of pathogens. Compared with vertebrate systems, our understanding of the impact of host age on invertebrate–pathogen interactions remains limited. We examined the influence of mosquito age on key life-history traits driving human malaria transmission. Females of Anopheles coluzzii, a major malaria vector, belonging to three age classes (4-, 8- and 12-day-old), were experimentally infected with Plasmodium falciparum field isolates. Our findings revealed reduced competence in 12-day-old mosquitoes, characterized by lower oocyst/sporozoite rates and intensities compared with younger mosquitoes. Despite shorter median longevities in older age classes, infected 12-day-old mosquitoes exhibited improved survival, suggesting that the infection might act as a fountain of youth for older mosquitoes specifically. The timing of sporozoite appearance in the salivary glands remained consistent across mosquito age classes, with an extrinsic incubation period of approximately 13 days. Integrating these results into an epidemiological model revealed a lower vectorial capacity for older mosquitoes compared with younger ones, albeit still substantial owing to extended longevity in the presence of infection. Considering age heterogeneity provides valuable insights for ecological and epidemiological studies, informing targeted control strategies to mitigate pathogen transmission