Rangewide population genetic structure of the African malaria vector Anopheles funestus

Anopheles funestus is a primary vector of malaria in Africa south of the Sahara. We assessed its rangewide population genetic structure based on samples from 11 countries, using 10 physically mapped microsatellite loci, two per autosome arm and the X (N = 548), and 834 bp of the mitochondrial ND5 gene (N = 470). On the basis of microsatellite allele frequencies, we found three subdivisions: eastern (coastal Tanzania, Malawi, Mozambique and Madagascar), western (Burkina Faso, Mali, Nigeria and western Kenya), and central (Gabon, coastal Angola). A. funestus from the southwest of Uganda had affinities to all three subdivisions. Mitochondrial DNA (mtDNA) corroborated this structure, although mtDNA gene trees showed less resolution. The eastern subdivision had significantly lower diversity, similar to the pattern found in the codistributed malaria vector Anopheles gambiae. This suggests that both species have responded to common geographic and/or climatic constraints. The western division showed signatures of population expansion encompassing Kenya west of the Rift Valley through Burkina Faso and Mali. This pattern also bears similarity to A. gambiae, and may reflect a common response to expanding human populations following the development of agriculture. Due to the presumed recent population expansion, the correlation between genetic and geographic distance was weak. Mitochondrial DNA revealed further cryptic subdivision in A. funestus, not detected in the nuclear genome. Mozambique and Madagascar samples contained two mtDNA lineages, designated clade I and clade II, that were separated by two fixed differences and an average of 2% divergence, which implies that they have evolved independently for approximately 1 million years. Clade I was found in all 11 locations, whereas clade II was sampled only on Madagascar and Mozambique. We suggest that the latter clade may represent mtDNA capture by A. funestus, resulting from historical gene flow either among previously isolated and divergent populations or with a related species.     

A microsatellite map of the African human malaria vector Anopheles funestus

Microsatellite markers and chromosomal inversion polymorphisms are useful genetic markers for determining population structure in Anopheline mosquitoes. In Anopheles funestus (2N = 6), only chromosome arms 2R, 3R, and 3L are known to carry polymorphic inversions. The physical location of microsatellite markers with respect to polymorphic inversions is potentially important information for interpreting population genetic structure, yet none of the available marker sets have been physically mapped in this species. Accordingly, we mapped 32 polymorphic A. funestus microsatellite markers to the polytene chromosomes using fluorescent in situ hybridization (FISH) and identified 16 markers outside of known polymorphic inversions. Here we provide an integrated polytene chromosome map for A. funestus that includes the breakpoints of all known polymorphic inversions as well as the physical locations of microsatellite loci developed to date. Based on this map, we suggest a standard set of 16 polymorphic microsatellite markers that are distributed evenly across the chromosome complement, occur predominantly outside of inversions, and amplify reliably. Adoption of this set by researchers working in different regions of Africa will facilitate metapopulation analyses of this primary malaria vector.     

A quantitative model of population dynamics in malaria with drug treatment

In this paper we build a population dynamics of malaria including drug treatment. By taking into account both sensitive and resistant parasites, we want to see the effect of treatments on resistance phenomenon and prevent it from overspreading. Our main results include a new dynamics model, its mathematical properties which are found through analysis, the determination of unknown parameters with help of a data set for malaria from Burkina Faso and the numerical simulations of the fitted model. Based on these results, treatment strategies to reduce drug resistance can be elaborated.     

The transmission dynamics of a within-and between-hosts malaria model

In this paper, we developed a novel deterministic coupled model tying together the effects of within-host and population level dynamics on malaria transmission dynamics. We develop within-host and within-vector dynamic models, population level between-hosts models, and a nested coupled model combining these levels. The unique feature of this work is the way the coupling and feedback for the model use the various life stages of the malaria parasite both in the human host and the mosquito vector. Analysis of the coupled and the within-human host models indicate the existence of locally asymptotically stable infection- and parasite-free equilibria when the associated reproduction numbers are less than one. The population-level model, on the other hand, exhibits backward bifurcation, where the stable disease-free equilibrium co-exists with a stable endemic equilibrium. A global sensitivity analysis was carried out to measure the effects of the sensitivity and uncertainty in the various model parameters estimates. The results indicate that the most important parameters driving the pathogen level within an infected human are the production rate of the red blood cells from the bone marrow, the infection rate, the immunogenicity of the infected red blood cells, merozoites and gametocytes, and the immunosensitivity of the merozoites and gametocytes. The key parameters identified at the population level are the human recovery rate, the death rate of the mosquitoes, the recruitment rate of susceptible humans into the population, the mosquito biting rate, the transmission probabilities per contact in mosquitoes and in humans, and the parasite production and clearance rates in the mosquitoes. Defining the feedback functions as a linear function of the mosquito biting rate, numerical exploration of the coupled model reveals oscillations in the parasite populations within a human host in the presence of the host immune response. These oscillations dampen as the mosquito biting rate increases. We also observed that the oscillation and damping effect seen in the within-human host dynamics fed back into the population level dynamics; this in turn amplifies the oscillations in the parasite population within the mosquito-host.     

Periodic oscillations and backward bifurcation in a model for the dynamics of malaria transmission

A deterministic ordinary differential equation model for the dynamics of malaria transmission that explicitly integrates the demography and life style of the malaria vector and its interaction with the human population is developed and analyzed. The model is different from standard malaria transmission models in that the vectors involved in disease transmission are those that are questing for human blood. Model results indicate the existence of nontrivial disease free and endemic steady states, which can be driven to instability via a Hopf bifurcation as a parameter is varied in parameter space. Our model therefore captures oscillations that are known to exist in the dynamics of malaria transmission without recourse to external seasonal forcing. Additionally, our model exhibits the phenomenon of backward bifurcation. Two threshold parameters that can be used for purposes of control are identified and studied, and possible reasons why it has been difficult to eradicate malaria are advanced.     

A weather-driven model of malaria transmission

The classic formulae in malaria epidemiology are reviewed that relate entomological parameters to malaria transmission, including mosquito survivorship and age-at-infection, the stability index (S), the human blood index (HBI), proportion of infected mosquitoes, the sporozoite rate, the entomological inoculation rate (EIR), vectorial capacity (C) and the basic reproductive number (R ₀). The synthesis emphasizes the relationships among classic formulae and reformulates a simple dynamic model for the proportion of infected humans. The classic formulae are related to formulae from cyclical feeding models, and some inconsistencies are noted. The classic formulae are used to to illustrate how malaria control reduces malaria transmission and show that increased mosquito mortality has an effect even larger than was proposed by Macdonald in the 1950's.     

A mathematical model for the dynamics of malaria in mosquitoes feeding on a heterogeneous host population

We describe and develop a difference equation model for the dynamics of malaria in a mosquito population feeding on, infecting and getting infected from a heterogeneous population of hosts. Using the force of infection from different classes of humans to mosquitoes as parameters, we evaluate a number of entomological parameters, indicating malaria transmission levels, which can be compared to field data. By assigning different types of vector control interventions to different classes of humans and by evaluating the corresponding levels of malaria transmission, we can compare the effectiveness of these interventions. We show a numerical example of the effects of increasing coverage of insecticide-treated bed nets in a human population where the predominant malaria vector is Anopheles gambiae.     

A mathematical model for the dynamics of malaria in mosquitoes feeding on a heterogeneous host population

We describe and develop a difference equation model for the dynamics of malaria in a mosquito population feeding on, infecting and getting infected from a heterogeneous population of hosts. Using the force of infection from different classes of humans to mosquitoes as parameters, we evaluate a number of entomological parameters, indicating malaria transmission levels, which can be compared to field data. By assigning different types of vector control interventions to different classes of humans and by evaluating the corresponding levels of malaria transmission, we can compare the effectiveness of these interventions. We show a numerical example of the effects of increasing coverage of insecticide-treated bed nets in a human population where the predominant malaria vector is Anopheles gambiae.     

A mathematical model for the transmission of Plasmodium vivax malaria

We have proposed a mathematical model for the transmission of Plasmodium vivax malaria quantitatively, which is adjusted to the infected region, Guadalcanal, in the Solomon Islands. The simulation of a transmission model will be instrumental in planning the malaria control strategy. A characteristic of the life cycle of P. vivax is that a sporozoite injected into the blood stream by a mosquito bite may sometimes stay in a hepatocyte as a hypnozoite. Therefore, we have incorporated a phenomenon of renewed infections caused by a relapse into the transmission model. Also through the simulations we have attempted to evaluate the decline in prevalence caused by the programs of selective mass drug administration (MDA) and vector control such as the distribution of permethrin-treated bednets. The simulations have indicated that the concentrated repetition of MDA at 1-week intervals would reduce the prevalence of vivax malaria swiftly in the beginning and would keep the parasite rate below 1% for a few years but the prevalence would increase thereafter. In contrast, the parasite rate would remain below 1% for a long time if a trial of 1 or 2 times MDA is accompanied with some reduction of the vectorial capacity by the enforcement of vector control. In any case, it is important to beware of relapse cases because even after the execution of MDA it takes a long time to decrease the proportion of hypnozoite carriers.     

Inference and dynamic simulation of malaria using a simple climate-driven entomological model of malaria transmission

Given the crucial role of climate in malaria transmission, many mechanistic models of malaria represent vector biology and the parasite lifecycle as functions of climate variables in order to accurately capture malaria transmission dynamics. Lower dimension mechanistic models that utilize implicit vector dynamics have relied on indirect climate modulation of transmission processes, which compromises investigation of the ecological role played by climate in malaria transmission. In this study, we develop an implicit process-based malaria model with direct climate-mediated modulation of transmission pressure borne through the Entomological Inoculation Rate (EIR). The EIR, a measure of the number of infectious bites per person per unit time, includes the effects of vector dynamics, resulting from mosquito development, survivorship, feeding activity and parasite development, all of which are moderated by climate. We combine this EIR-model framework, which is driven by rainfall and temperature, with Bayesian inference methods, and evaluate the model’s ability to simulate local transmission across 42 regions in Rwanda over four years. Our findings indicate that the biologically-motivated, EIR-model framework is capable of accurately simulating seasonal malaria dynamics and capturing of some of the inter-annual variation in malaria incidence. However, the model unsurprisingly failed to reproduce large declines in malaria transmission during 2018 and 2019 due to elevated anti-malaria measures, which were not accounted for in the model structure. The climate-driven transmission model also captured regional variation in malaria incidence across Rwanda’s diverse climate, while identifying key entomological and epidemiological parameters important to seasonal malaria dynamics. In general, this new model construct advances the capabilities of implicitly-forced lower dimension dynamical malaria models by leveraging climate drivers of malaria ecology and transmission.     

Molecular identification of the Anopheles nili group of African malaria vectors

Distinction between members of the Anopheles nili group of mosquitoes (Diptera: Culicidae), including major malaria vectors in riverside villages of tropical Africa, has been based mainly on doubtful morphological characters. Sequence variations of the ribosomal DNA second internal transcribed spacer (ITS2) and D3 28S region between morphological forms revealed four genetic patterns corresponding to typical An. nili (Theobald), An. carnevalei Brunhes et al., An. somalicus Rivola & Holstein and the newly identified variant provisionally named Oveng form. Primers were designed based on ITS2 fixed nucleotide differences between haplotypes to develop a multiplex PCR for rapid and specific identification of each species or molecular form. Specimens of the An. nili group from Cameroon, Burkina Faso, Ivory Coast and Senegal were successfully identified to species, demonstrating the general applicability of this technique based on criteria described in this paper.     

A population balance model for fish population dynamics

A population balance model of fish population dynamics for batch systems was developed. A growth rate expression was introduced and coupled with the population balance. Solutions of the model provide predictions of such fish size distribution characteristics as average size, standard deviation and coefficient of variation. A growth diffusivity mechanism was found to be inapplicable to systems where a terminal size is reached. A study of the two parameter growth rate expression was conducted, illustrating that conditions conducive to high growth rates also resulted in broadening of size distributions. The model was compared to data found in the literature to demonstrate its predictive capabilities.     

Distribution of African malaria mosquitoes belonging to the Anopheles gambiae complex

The distribution of malaria vector mosquitoes, especially those belonging to species complexes that contain non-vector species, is important for strategic planning of malaria control programmes. Geographical information systems have allowed researchers to visualize distribution data on maps together with environmental parameters, such as rainfall and temperature. Here, Maureen Coetzee, Marlies Craig and David le Sueur review our current knowledge on the distribution of the members of the Anopheles gambiae complex.     

Modeling the role of environmental variables on the population dynamics of the malaria vector Anopheles gambiae sensu stricto

ABSTRACT: BACKGROUND: The impact of weather and climate on malaria transmission has attracted considerable attention in recent years, yet uncertainties around future disease trends under climate change remain. Mathematical models provide powerful tools for addressing such questions and understanding the implications for interventions and eradication strategies, but these require realistic modeling of the vector population dynamics and its response to environmental variables. METHODS: Published and unpublished field and experimental data are used to develop new formulations for modeling the relationships between key aspects of vector ecology and environmental variables. These relationships are integrated within a validated deterministic model of Anopheles gambiae s.s. population dynamics to provide a valuable tool for understanding vector response to biotic and abiotic variables. RESULTS: A novel, parsimonious framework for assessing the effects of rainfall, cloudiness, wind speed, desiccation, temperature, relative humidity and density-dependence on vector abundance is developed, allowing ease of construction, analysis, and integration into malaria transmission models. Model validation shows good agreement with longitudinal vector abundance data from Tanzania, suggesting that recent malaria reductions in certain areas of Africa could be due to changing environmental conditions affecting vector populations. CONCLUSIONS: Mathematical models provide a powerful, explanatory means of understanding the role of environmental variables on mosquito populations and hence for predicting future malaria transmission under global change. The framework developed provides a valuable advance in this respect, but also highlights key research gaps that need to be resolved if we are to better understand future malaria risk in vulnerable communities.     

Dynamics of gene introgression in the African malaria vector Anopheles gambiae

Anopheles gambiae is a major malaria vector in Africa and a popular model species for a variety of ecological, evolutionary, and genetic studies on vector control. Genetic manipulation of mosquito vectorial capacity is a promising new weapon for the control of malaria. However, the release of exotic transgenic mosquitoes will bring in novel alleles in addition to the parasite-inhibiting genes, which may have unknown effects on the local population. Therefore, it is necessary to develop methodologies that can be used to evaluate the spread rate of introduced genes in A. gambiae. In this study, the effects and dynamics of genetic introgression between two geographically distinct A. gambiae populations from western Kenya (Mbita) and eastern Tanzania (Ifakara) were investigated with amplified fragment length polymorphisms (AFLPs) and microsatellite markers. Microsatellites and polymorphic cDNA markers revealed a large genetic differentiation between the two populations (average F(ST) = 0.093, P < 0.001). When the two strains were crossed in random mating between the two populations, significant differences in the rate of genetic introgression were found in the mixed populations. Allele frequencies of 18 AFLP markers (64.3%) for Mbita and of 26 markers (92.9%) for Ifakara varied significantly from F5 to F20. This study provides basic information on how a mosquito release program would alter the genetic makeup of natural populations, which is critical for pilot field testing and ecological risk evaluation of transgenic mosquitoes.     

Evidence for recent population expansion in the evolutionary history of the malaria vectors Anopheles arabiensis and Anopheles gambiae.

Gene flow in malaria vectors is usually estimated based on differentiation indices (e.g., F(ST)) in order to predict the contemporary spread of genes such as those conferring resistance to insecticides. This approach is reliant on a number of assumptions, the most crucial, and the one most likely to be violated in these species, being mutation-migration-drift equilibrium. Tests of this assumption for the African malaria vectors Anopheles gambiae and Anopheles arabiensis are the focus of this study. We analyzed variation at 18 microsatellite loci and the ND5 region of the mitochondrial genome in two populations of each species. Equilibrium was rejected by six of eight tests for the A. gambiae population from western Kenya and by three tests in eastern Kenya. In western Kenya, all departures from equilibrium were consistent with a recent population expansion, but in eastern Kenya, there were traces of a recent expansion and a bottleneck. Equilibrium was also rejected by two of the eight tests for both A. arabiensis populations; the departure from equilibrium was consistent with an expansion. These multiple-locus tests detected a genomewide effect and therefore a demographic event rather than a locus-specific effect, as would be caused by selection. Disequilibrium due to a recent expansion in these species implies that rates of gene flow, as inferred from differentiation indices, are overestimates as they include a historical component. We argue that the same effect applies to the majority of pest species due to the correlation of their demography with that of humans.     

Spatial simulation of malaria transmission and its control by malaria transmission blocking vaccination

A simple, visual representation of spatial aspects of malaria transmission in successive snap-shots in time, is presented. The spatial components of the simulation involve (i) the identification of mosquito vector breeding sites of defined shape and area, (ii) the identification of a zone of malaria transmission determined by the shapes and areas of the vector breeding sites and the distance from these sites that the mosquitoes disperse, (iii) a human population dispersed in relation to the malaria transmission zone, (iv) perimeters around each individual human within which his or her infection can be transmitted by the local vector mosquitoes. The intensity of transmission within a malaria transmission zone is given by a number which is the number of new cases of malaria that each existing case will distribute through the human population within the duration of an infection. The simulation has been used here to examine the effects of vaccination against malaria transmission. Different levels of vaccine coverage are represented under endemic and epidemic malaria. The consequences of full or partial coverage of a zone of malaria transmission are also examined. The results are numerically compatible with the predictions of previous simple mathematical simulations of malaria transmission and interventions. The present simulation allows the nature of malaria transmission and the effects of interventions to be communicated easily and directly to an audience. It could have practical value in discussions of malaria control strategies with health planners.     

按蚊肠道微生物及其在阻断疟疾传播上的应用

按蚊体内,尤其是中肠内定殖着大量的微生物群落。肠道菌群通过与按蚊的长期协同进化形成了相互依存的共生关系。肠道共生菌参与调节按蚊的多种生命活动,对于维持按蚊的健康发挥着重要作用,已经成为一个与宿主按蚊密不可分的重要"器官"。研究表明,肠道共生菌在按蚊物质代谢、营养、发育、生殖、免疫调控和免疫防御等生理过程中发挥着重要的调节作用。蚊虫是疟疾、登革、寨卡等多种疾病的传播媒介,而肠道共生菌对寄生虫和病毒在蚊虫肠道内的发育和感染具有重要影响,因此研究蚊虫与共生菌的相互作用有着重要的理论和实践意义。本文将对按蚊肠道共生菌的多样性、生物学功能、与宿主相互作用的机制及其在防治疟疾上的应用进展进行综述,并对未来的研究提出展望。