Human Host Population Research Articles

Patterns of soil-transmitted helminth aggregation in the human host population after several years of intensive mass drug administration.

Community-wide mass drug administration (cMDA) is known as an effective, albeit costly, control strategy for soil-transmitted helminth (STH) parasites. A better understanding of STH aggregation after many rounds of cMDA could help shape more cost-effective policies. This analysis uses data from the Geshiyaro project, aiming to break STH transmission by cMDA and water, sanitation and hygiene interventions. Ascaris lumbricoides infection prevalence is derived from egg count data and parasite aggregation is obtained by fitting a negative binomial distribution to the frequency distribution of faecal egg counts. The relationship between parasite dispersion and infection prevalence is approximately linear. Parasite aggregation increases as infection prevalence decreases. A minority of individuals carry most parasites as prevalence decreases in the community. These individuals could be selectively targeted for repeated treatment.

Bacterial diversity dominates variable macrophage responses of tuberculosis patients in Tanzania

The Mycobacterium tuberculosis complex (MTBC) comprises nine human-adapted lineages that differ in their geographical distribution. Local adaptation of specific MTBC genotypes to the respective human host population has been invoked in this context. We aimed to assess if bacterial genetics governs MTBC pathogenesis or if local co-adaptation translates into differential susceptibility of human macrophages to infection by different MTBC genotypes. We generated macrophages from cryopreserved blood mononuclear cells of Tanzanian tuberculosis patients, from which the infecting MTBC strains had previously been phylogenetically characterized. We infected these macrophages ex vivo with a phylogenetically similar MTBC strain (“matched infection”) or with strains representative of other MTBC lineages (“mismatched infection”). We found that L1 infections resulted in a significantly lower bacterial burden and that the intra-cellular replication rate of L2 strains was significantly higher compared the other MTBC lineages, irrespective of the MTBC lineage originally infecting the patients. Moreover, L4-infected macrophages released significantly greater amounts of TNF-α, IL-6, IL-10, MIP-1β, and IL-1β compared to macrophages infected by all other strains. While our results revealed no measurable effect of local adaptation, they further highlight the strong impact of MTBC phylogenetic diversity on the variable outcome of the host–pathogen interaction in human tuberculosis.

Vector species richness predicts local mortality rates from Chagas disease

Vector species richness may drive the prevalence of vector-borne diseases by influencing pathogen transmission rates. The dilution effect hypothesis predicts that higher biodiversity reduces disease prevalence, but with inconclusive evidence. In contrast, the amplification effect hypothesis suggests that higher vector diversity may result in greater disease transmission by increasing and diversifying the transmission pathways. The relationship between vector diversity and pathogen transmission remains unclear and requires further study. Chagas disease is a vector-borne disease most prevalent in Brazil and transmitted by multiple species of insect vectors of the subfamily Triatominae, yet the drivers of spatial variation in its impact on human populations remain unresolved. We tested whether triatomine species richness, latitude, bioclimatic variables, human host population density, and socioeconomic variables predict Chagas disease mortality rates across over 5000 spatial grid cells covering all of Brazil. Results show that species richness of triatomine vectors is a good predictor of mortality rates caused by Chagas disease, which supports the amplification effect hypothesis. Vector richness and the impact of Chagas disease may also be driven by latitudinal components of climate and human socioeconomic factors. We provide evidence that vector diversity is a strong predictor of disease prevalence and give support to the amplification effect hypothesis.

On nonlinear dynamics of a fractional order monkeypox virus model

In this work, we examine a fractional-order model for simulating the spread of the monkeypox virus in the human host and rodent populations. The employment of the fractional form of the model gives a better insight into the dynamics and spread of the virus, which will help in providing some new control measures. The model is formulated into eight mutually exclusive compartments and the form of a nonlinear system of differential equations. The reproduction number for the present epidemic system is found. In addition, the equilibrium points of the model are investigated and the associated stability analysis is carried out. The influences of key parameters in the model and the ways to control the monkeypox epidemic have been thoroughly examined for the fractional model. To ensure that the model accurately simulates the nonlinear phenomenon, we adapt an efficient numerical technique to solve the presented model, and the acquired results reveal the dynamic behaviors of the model. It is observed that when memory influences are considered for the present model, through Caputo fractional-order derivatives, they affect the speed and time taken by solution trajectories towards steady-state equilibria.

Variant-Specific Analysis Reveals a Novel Long-Range RNA-RNA Interaction in SARS-CoV-2 Orf1a.

Since the start of the COVID-19 pandemic, understanding the pathology of the SARS-CoV-2 RNA virus and its life cycle has been the priority of many researchers. Currently, new variants of the virus have emerged with various levels of pathogenicity and abundance within the human-host population. Although much of viral pathogenicity is attributed to the viral Spike protein’s binding affinity to human lung cells’ ACE2 receptor, comprehensive knowledge on the distinctive features of viral variants that might affect their life cycle and pathogenicity is yet to be attained. Recent in vivo studies into the RNA structure of the SARS-CoV-2 genome have revealed certain long-range RNA-RNA interactions. Using in silico predictions and a large population of SARS-CoV-2 sequences, we observed variant-specific evolutionary changes for certain long-range RRIs. We also found statistical evidence for the existence of one of the thermodynamic-based RRI predictions, namely Comp1, in the Beta variant sequences. A similar test that disregarded sequence variant information did not, however, lead to significant results. When performing population-based analyses, aggregate tests may fail to identify novel interactions due to variant-specific changes. Variant-specific analyses can result in de novo RRI identification.

The observed relationship between the degree of parasite aggregation and the prevalence of infection within human host populations for soil-transmitted helminth and schistosome infections.

Soil-transmitted helminths (STH) and schistosome parasites are highly aggregated within the human population. The probability distribution of worms per person is described well by the negative binomial probability distribution with aggregation parameter, k, which varies inversely with parasite clustering. The relationship between k and prevalence in defined populations subject to mass drug administration is not well understood. We use statistical methods to estimate k using two large independent datasets for STH and schistosome infections from India and Niger, respectively, both of which demonstrate increased aggregation of parasites in a few hosts, as the prevalence of infections declines across the dataset. A greater attention needs to be given in monitoring and evaluation programmes to find and treat the remaining aggregates of parasites.

HAMdetector: a Bayesian regression model that integrates information to detect HLA-associated mutations.

A key process in anti-viral adaptive immunity is that the human leukocyte antigen (HLA) system presents epitopes as major histocompatibility complex I (MHC I) protein-peptide complexes on cell surfaces and in this way alerts CD8+ cytotoxic T-lymphocytes (CTLs). This pathway exerts strong selection pressure on viruses, favoring viral mutants that escape recognition by the HLA/CTL system. Naturally, such immune escape mutations often emerge in highly variable viruses, e.g. HIV or HBV, as HLA-associated mutations (HAMs), specific to the hosts MHC I proteins. The reliable identification of HAMs is not only important for understanding viral genomes and their evolution, but it also impacts the development of broadly effective anti-viral treatments and vaccines against variable viruses. By their very nature, HAMs are amenable to detection by statistical methods in paired sequence/HLA data. However, HLA alleles are very polymorphic in the human host population which makes the available data relatively sparse and noisy. Under these circumstances, one way to optimize HAM detection is to integrate all relevant information in a coherent model. Bayesian inference offers a principled approach to achieve this. We present a new Bayesian regression model for the detection of HAMs that integrates a sparsity-inducing prior, epitope predictions and phylogenetic bias assessment, and that yields easily interpretable quantitative information on HAM candidates. The model predicts experimentally confirmed HAMs as having high posterior probabilities, and it performs well in comparison to state-of-the-art models for several datasets from individuals infected with HBV, HDV and HIV. The source code of this software is available at https://github.com/HAMdetector/Escape.jl under a permissive MIT license. The data underlying this article were provided by permission. Data will be shared on request to the corresponding author with permission of the respective co-authors. Supplementary data are available at Bioinformatics online.

Global diversity and balancing selection of 23 leading Plasmodium falciparum candidate vaccine antigens.

Investigation of the diversity of malaria parasite antigens can help prioritize and validate them as vaccine candidates and identify the most common variants for inclusion in vaccine formulations. Studies of vaccine candidates of the most virulent human malaria parasite, Plasmodium falciparum, have focused on a handful of well-known antigens, while several others have never been studied. Here we examine the global diversity and population structure of leading vaccine candidate antigens of P. falciparum using the MalariaGEN Pf3K (version 5.1) resource, comprising more than 2600 genomes from 15 malaria endemic countries. A stringent variant calling pipeline was used to extract high quality antigen gene ‘haplotypes’ from the global dataset and a new R-package named VaxPack was used to streamline population genetic analyses. In addition, a newly developed algorithm that enables spatial averaging of selection pressure on 3D protein structures was applied to the dataset. We analysed the genes encoding 23 leading and novel candidate malaria vaccine antigens including csp, trap, eba175, ama1, rh5, and CelTOS. Our analysis shows that current malaria vaccine formulations are based on rare haplotypes and thus may have limited efficacy against natural parasite populations. High levels of diversity with evidence of balancing selection was detected for most of the erythrocytic and pre-erythrocytic antigens. Measures of natural selection were then mapped to 3D protein structures to predict targets of functional antibodies. For some antigens, geographical variation in the intensity and distribution of these signals on the 3D structure suggests adaptation to different human host or mosquito vector populations. This study provides an essential framework for the diversity of P. falciparum antigens to be considered in the design of the next generation of malaria vaccines.

On the approximate solutions and asymptotic stability of an onchocerciasis transmission model

This article describes the mathematical model derivation describing river blindness disease transmission in human and vector (blackflies) host population. The effect of incomplete resistance to re-infection in human individuals who recovered from the disease after treatment but are still subjected to repeated exposures to infected blackflies bite is investigated. Also, the basic reproduction number [Formula: see text] is obtained and it is shown that if [Formula: see text], the onchocerciasis-free equilibrium is locally and globally asymptotically stable. Also, if [Formula: see text], the onchocerciasis-endemic equilibrium is globally asymptotically stable. Moreover, the Differential Transform Method (DTM) and Runge–Kutta fourth-order method is employed via the computational software Maple 18 to solve and obtain the approximate solutions of the model system equations, which showed that the numerical results favorably compare with each other. Simulations reveal that increase in biting and transmission rates leads to an increase of [Formula: see text] and incomplete resistance to re-infection due to consistent exposure to blackflies bites. Also, simulations of the approximate solutions of the model state equations are provided.

Probability distributions of helminth parasite burdens within the human host population following repeated rounds of mass drug administration and their impact on the transmission breakpoint.

The existence of multiple stable equilibria in models of parasitic helminth transmission was a ground-breaking discovery over 30 years ago. An implication of this discovery, that there is a level of infection below which transmission cannot self-sustain called the transmission breakpoint, has in part motivated the push towards the elimination of many human diseases caused by the multiple species of helminth worldwide. In the absence of vaccines, the predominant method in this push towards elimination is to repeatedly administer endemic populations with anthelmintic drugs, over several treatment rounds, in what has become to be known as mass drug administration (MDA). MDA will inevitably alter the distribution of parasite burdens among hosts from the baseline distribution, and significantly, the location of the transmission breakpoint is known to be dependent on the level of aggregation of this distribution—for a given mean worm burden, more highly aggregated distributions where fewer individuals harbour most of the burden, will have a lower transmission breakpoint. In this paper, we employ a probabilistic analysis of the changes to the distribution of burdens in a population undergoing MDA, and simple approximations, to determine how key aspects of the programmes (including compliance, drug efficacy and treatment coverage) affect the location of the transmission breakpoint. We find that individual compliance to treatment, which determines the number of times an individual participates in mass drug administration programmes, is key to the location of the breakpoint, indicating the vital importance to ensure that people are not routinely missed in these programmes.

An Evolutionary Arms Race Between Burkholderia pseudomallei and Host Immune System: What Do We Know?

A better understanding of co-evolution between pathogens and hosts holds promise for better prevention and control strategies. This review will explore the interactions between Burkholderia pseudomallei, an environmental and opportunistic pathogen, and the human host immune system. B. pseudomallei causes “Melioidosis,” a rapidly fatal tropical infectious disease predicted to affect 165,000 cases annually worldwide, of which 89,000 are fatal. Genetic heterogeneities were reported in both B. pseudomallei and human host population, some of which may, at least in part, contribute to inter-individual differences in disease susceptibility. Here, we review (i) a multi-host—pathogen characteristic of the interaction; (ii) selection pressures acting on B. pseudomallei and human genomes with the former being driven by bacterial adaptation across ranges of ecological niches while the latter are driven by human encounter of broad ranges of pathogens; (iii) the mechanisms that generate genetic diversity in bacterial and host population particularly in sequences encoding proteins functioning in host—pathogen interaction; (iv) reported genetic and structural variations of proteins or molecules observed in B. pseudomallei—human host interactions and their implications in infection outcomes. Together, these predict bacterial and host evolutionary trajectory which continues to generate genetic diversity in bacterium and operates host immune selection at the molecular level.

Optimal control of educational campaign applied to the transmission of trachoma disease: a mathematical model

This paper presents a mathematical model describing the transmission of trachoma disease in human host population. The model is analyzed in a feasible region and the basic reproduction number $$(R_{tr})$$ of trachoma epidemic is obtained to show that if $$R_{tr}<1$$ , the model system at the fixed trachoma-free equilibrium is locally and globally asymptotically stable. An optimal control of educational campaign strategy is imposed on the model system to investigate the impact of education campaign control on the sub-population of the total human host population towards minimizing trachoma infection by initiating compliance to healthy behavior in the human host community. The existence and uniqueness and the characterization of the optimal control model analysis is carried out, while the optimality system is derived and solved using the finite difference scheme in the absence and presence of control. The results reveal that varying the control parameter at $$u = 0.5$$ and $$u = 0.9$$ shows that the maximum coverage is attained within few days before declining to the lower bound in one month. This further shows that the initiation of positive behavior and strict compliance to educational instructions through campaign is effective in minimizing trachoma in human host community.

Genetic variation in the MacAB-TolC efflux pump influences pathogenesis of invasive Salmonella isolates from Africa.

The various sub-species of Salmonella enterica cause a range of disease in human hosts. The human-adapted Salmonella enterica serovar Typhi enters the gastrointestinal tract and invades systemic sites to cause enteric (typhoid) fever. In contrast, most non-typhoidal serovars of Salmonella are primarily restricted to gut tissues. Across Africa, invasive non-typhoidal Salmonella (iNTS) have emerged with an ability to spread beyond the gastrointestinal tract and cause systemic bloodstream infections with increased morbidity and mortality. To investigate this evolution in pathogenesis, we compared the genomes of African iNTS isolates with other Salmonella enterica serovar Typhimurium and identified several macA and macB gene variants unique to African iNTS. MacAB forms a tripartite efflux pump with TolC and is implicated in Salmonella pathogenesis. We show that macAB transcription is upregulated during macrophage infection and after antimicrobial peptide exposure, with macAB transcription being supported by the PhoP/Q two-component system. Constitutive expression of macAB improves survival of Salmonella in the presence of the antimicrobial peptide C18G. Furthermore, these macAB variants affect replication in macrophages and influence fitness during colonization of the murine gastrointestinal tract. Importantly, the infection outcome resulting from these macAB variants depends upon both the Salmonella Typhimurium genetic background and the host gene Nramp1, an important determinant of innate resistance to intracellular bacterial infection. The variations we have identified in the MacAB-TolC efflux pump in African iNTS may reflect evolution within human host populations that are compromised in their ability to clear intracellular Salmonella infections.

Stability analysis and optimal control strategies of direct and indirect transmission dynamics of conjunctivitis

This article concerns the S–E–I–R (Susceptible–Exposed–Infected–Recovered) mathematical model formulation describing the dynamics of the spread of conjunctivitis predominant in human host population. The model considered possesses two equilibrium points, namely, the conjunctivitis‐free and conjunctivitis‐present equilibrium, which are dependent on the basic reproduction number (Rco). The local and global stabilities of derived model system were investigated at the equilibrium solutions, and it was found that if Rco &lt; 1, the conjunctivitis‐free equilibrium is both locally and globally asymptotically stable. Also, if Rco &gt; 1, the conjunctivitis‐present equilibrium is globally asymptotically stable. The sensitivity analysis of Rco is performed, and the corresponding graphical results are presented to examine the relative importance of conjunctivitis model parameters as to conjunctivitis prevalence. The model is reformulated by applying control measures of isolation and hygiene compliance to minimize conjunctivitis infection and irritants concentration as well as the cost associated with it. An optimality system is derived and numerically solved with and without controls using the forward–backward Runge–Kutta scheme via computational software MATLAB. The graphical results obtained showed that each of the control strategies has its own importance for conjunctivitis elimination. Further graphical descriptions reveal that the combination of isolation and hygiene compliance strategies are more effective in curtailing conjunctivitis prevalence in human and environmental host community.

The impact of community-wide, mass drug administration on aggregation of soil-transmitted helminth infection in human host populations

BackgroundSoil-transmitted helminths (STH) are intestinal parasites estimated to infect over 1.5 billion people. Current treatment programmes are aimed at morbidity control through school-based deworming programmes (targeting school-aged children, SAC) and treating women of reproductive age (WRA), as these two groups are believed to record the highest morbidity. More recently, however, the potential for interrupting transmission by treating entire communities has been receiving greater emphasis and the feasibility of such programmes are now under investigation in randomised clinical trials through the Bill & Melinda Gates Foundation funded DeWorm3 studies. Helminth parasites are known to be highly aggregated within human populations, with a small minority of individuals harbouring most worms. Empirical evidence from the TUMIKIA project in Kenya suggests that aggregation may increase significantly after anthelminthic treatment.MethodsA stochastic, age-structured, individual-based simulation model of parasite transmission is employed to better understand the factors that might induce this pattern. A simple probabilistic model based on compounded negative binomial distributions caused by age-dependencies in both treatment coverage and exposure to infection is also employed to further this understanding.ResultsBoth approaches confirm helminth aggregation is likely to increase post-mass drug administration as measured by a decrease in the value of the negative binomial aggregation parameter, k. Simple analytical models of distribution compounding describe the observed patterns well.ConclusionsThe helminth aggregation that was observed in the field was replicated with our stochastic individual-based model. Further work is required to generalise the probabilistic model to take account of the respective sensitivities of different diagnostics on the presence or absence of infection.

Dynamics of Influenza A (H5N1) virus protein sequence diversity.

BackgroundInfluenza A (H5N1) virus is a global concern with potential as a pandemic threat. High sequence variability of influenza A viruses is a major challenge for effective vaccine design. A continuing goal towards this is a greater understanding of influenza A (H5N1) proteome sequence diversity in the context of the immune system (antigenic diversity), the dynamics of mutation, and effective strategies to overcome the diversity for vaccine design.MethodsHerein, we report a comprehensive study of the dynamics of H5N1 mutations by analysis of the aligned overlapping nonamer positions (1–9, 2–10, etc.) of more than 13,000 protein sequences of avian and human influenza A (H5N1) viruses, reported over at least 50 years. Entropy calculations were performed on 9,408 overlapping nonamer position of the proteome to study the diversity in the context of immune system. The nonamers represent the predominant length of the binding cores for peptides recognized by the cellular immune system. To further dissect the sequence diversity, each overlapping nonamer position was quantitatively analyzed for four patterns of sequence diversity motifs: index, major, minor and unique.ResultsAlmost all of the aligned overlapping nonamer positions of each viral proteome exhibited variants (major, minor, and unique) to the predominant index sequence. Each variant motif displayed a characteristic pattern of incidence change in relation to increased total variants. The major variant exhibited a restrictive pyramidal incidence pattern, with peak incidence at 50% total variants. Post this peak incidence, the minor variants became the predominant motif for majority of the positions. Unique variants, each sequence observed only once, were present at nearly all of the nonamer positions. The diversity motifs (index and variants) demonstrated complex inter-relationships, with motif switching being a common phenomenon. Additionally, 25 highly conserved sequences were identified to be shared across viruses of both hosts, with half conserved to several other influenza A subtypes.DiscussionThe presence of distinct sequences (nonatypes) at nearly all nonamer positions represents a large repertoire of reported viral variants in the proteome, which influence the variability dynamics of the viral population. This work elucidated and provided important insights on the components that make up the viral diversity, delineating inherent patterns in the organization of sequence changes that function in the viral fitness-selection. Additionally, it provides a catalogue of all the mutational changes involved in the dynamics of H5N1 viral diversity for both avian and human host populations. This work provides data relevant for the design of prophylactics and therapeutics that overcome the diversity of the virus, and can aid in the surveillance of existing and future strains of influenza viruses.

The paleopathological evidence on the origins of human tuberculosis: a review

SummaryTuberculosis (TB) has been one of the most important infectious diseases affecting mankind and still represents a plague on a global scale. In this narrative review the origins of tuberculosis are outlined, according to the evidence of paleopathology. In particular the first cases of human TB in ancient skeletal remains are presented, together with the most recent discoveries resulting from the paleomicrobiology of the tubercle bacillus, which provide innovative information on the history of TB. The paleopathological evidence of TB attests the presence of the disease starting from Neolithic times. Traditionally, it was thought that TB has a zoonotic origin, being acquired by humans from cattle during the Neolithic revolution. However, the biomolecular studies proposed a new evolutionary scenario demonstrating that human TB has a human origin. The researches show that the disease was present in the early human populations of Africa at least 70000 years ago and that it expanded following the migrations of Homo sapiens out of Africa, adapting to the different human groups. The demographic success of TB during the Neolithic period was due to the growth of density and size of the human host population, and not the zoonotic transfer from cattle, as previously hypothesized. These data demonstrate a long coevolution of the disease and its human host. Understanding the changes of TB through time thanks to the advances in the field of paleopathology can help to solve the present problems and understand the future evolution of TB.

THE COMPUTATION OF REPRODUCTION NUMBERS FOR THE ENVIRONMENT-HOST-ENVIRONMENT CHOLERA TRANSMISSION DYNAMICS

This study presents a new model for the environment-host-environment transmission dynamics of V. cholerae in a community with an interconnected aquatic pond–river water network. For the case when the human host is the sole target of anti-cholera control and the volume of water in the pond is maximum, the disease-free equilibrium of the model is shown to be globally asymptotically stable whenever a certain epidemiological threshold, known as the basic reproduction number [Formula: see text], is less than unity. The epidemiological implication of this result is that cholera can be eliminated from the community if the control strategies implemented can bring (and maintain) [Formula: see text] to a value less than unity. Four scenarios, that represent different interpretations of the role of the V. cholerea pathogen within the environment, were studied. The corresponding basic reproduction numbers were shown to exhibit the same threshold property with respect to the value unity (i.e., if one is less (equal, greater) than unity, then the three others are also less (equal, greater) than unity. Further, it was shown that for the case where anti-cholera control is focused on the human host population, the associated type reproduction number of the model (corresponding to each of the four transmission scenarios considered) is unique. The implication of this result is that the estimate of the effort needed for disease elimination (i.e., the required herd immunity threshold) is unique, regardless of which of the four transmission scenarios is considered. However, when any of the other two bacterial population types in the aquatic environment (i.e., bacterial in the pond or river) is the focus of the control efforts, this study shows that the associated type reproduction number is not unique. Extensive numerical simulations of the model, using a realistic set of parameters from the published literature, show that the community-wide implementation of a strategy that focus on improved water quality, sanitation, and hygiene (known as WASH-only strategy), using the current estimated coverage of 50% and efficacy of 60%, is unable to lead to the elimination of the disease. Such elimination is attainable if the coverage and efficacy are increased (e.g., to 80% and 90%, respectively). Further, elimination can be achieved using a strategy that focuses on oral rehydration therapy and the use of antibiotics to treat the infected humans (i.e., treatment-only strategy) for moderate effectiveness and coverage levels. The combined hybrid WASH-treatment strategy provides far better population-level impact vis a vis disease elimination. This study ranks the three interventions in the following order of population-level effectiveness: combined WASH-treatment, followed by treatment-only and then WASH-only strategy.

Mathematical Modeling and Stability Analysis of a SIRV Epidemic Model with Non-linear Force of Infection and Treatment

This paper considers the Susceptible-Infected-Vaccinated-Recovered ( SIRV ) deterministic model with a non linear force of infection and treatment, where individual humans that are vaccinated losses their vaccination after some time and become vulnerable to infections. The basic reproduction number \(R_0\) obtained from the model system is an epidemic threshold that determines if a disease will continue to ravage the human population or not. The model state equations considered in this paper possess two steady-state solutions such that if \(R_0 1\), a unique infection-persistent steady-state solutions are established, which is also locally and globally asymptotically stable. Thus, it leads to the persistence of infections in the human host population. Finally, numerical simulations were carried out to validate our theoretical results.

Mathematical Modeling of the Coinfection Dynamics of Malaria-Toxoplasmosis in the Tropics

Summary Coinfection by Plasmodium species and Toxoplasma gondii in humans is widespread, with its endemic impact mostly felt in the tropics. A mathematical model is formulated as a first-order nonlinear system of ordinary differential equations to describe the coinfection dynamics of malaria-toxoplasmosis in the mainly human and feline susceptible host population in tropical regions. Comprehensive mathematical techniques are applied to show that the model system is bounded, positive and realistic in an epidemiological sense. Also, the basic reproduction number (Romt ) of the coinfection model is obtained. It is shown that if Romt &lt; 1, the model system at its malaria-toxoplasmosis absent equilibrium is both locally and globally asymptotically stable. The impact of toxoplasmosis and its treatment on malaria, and vice versa, is studied and analyzed. Sensitivity analysis was performed to investigate the impact of the model system parameters on the reproduction number of the transmission of malaria-toxoplasmosis coinfection. Simulations and graphical illustrations were made to validate the results obtained from the theoretical model.