Partitioning regulatory mechanisms of within-host malaria dynamics using the effective propagation number

Proliferation in malaria parasites: How resource limitation can prevent evolution of greater virulence

For parasites, robust proliferation within hosts is crucial for establishing the infection and creating opportunities for onward transmission. While faster proliferation enhances transmission rates, it is often assumed to curtail transmission duration by killing the host (virulence), a trade-off constraining parasite evolution. Yet in many diseases, including malaria, the preponderance of infections with mild or absent symptoms suggests that host mortality is not a sufficient constraint, raising the question of what restrains evolution toward faster proliferation. In malaria infections, the maximum rate of proliferation is determined by the burst size, the number of daughter parasites produced per infected red blood cell. Larger burst sizes should expand the pool of infected red blood cells that can be used to produce the specialized transmission forms needed to infect mosquitoes. We use a within-host model parameterized for rodent malaria parasites (Plasmodium chabaudi) to project the transmission consequences of burst size, focusing on initial acute infection where resource limitation and risk of host mortality are greatest. We find that resource limitation restricts evolution toward higher burst sizes below the level predicted by host mortality alone. Our results suggest resource limitation could represent a more general constraint than virulence-transmission trade-offs, preventing evolution towards faster proliferation.

The impact of sterility-mortality tolerance and recovery-transmission trade-offs on host-parasite coevolution

Understanding the coevolutionary dynamics of hosts and their parasites remains a major focus of much theoretical literature. Despite empirical evidence supporting the presence of sterility-mortality tolerance trade-offs in hosts and recovery-transmission trade-offs in parasites, none of the current models have explored the potential outcomes when both trade-offs are considered within a coevolutionary framework. In this study, we consider a model where the host evolves sterility tolerance at the cost of increased mortality and the parasite evolves higher transmission rate at the cost of increased recovery rate (reduced infection duration), and use adaptive dynamics to predict the coevolutionary outcomes under such trade-off assumptions. We particularly aim to understand how our coevolutionary dynamics compare with single species evolutionary models. We find that evolutionary branching in the host can drive the parasite population to branch, but that cycles in the population dynamics can prevent the coexisting strains from reaching their extremes. We also find that varying crowding does not impact the recovery rate when only the parasite evolves, yet coevolution reduces recovery as crowding intensifies. We conclude by discussing how different host and parasite trade-offs shape coevolutionary outcomes, underscoring the pivotal role of trade-offs in coevolution.

P. falciparum Invasion and Erythrocyte Aging

Plasmodium parasites need to find red blood cells (RBCs) that, on the one hand, expose receptors for the pathogen ligands and, on the other hand, maintain the right geometry to facilitate merozoite attachment and entry into the red blood cell. Both characteristics change with the maturation of erythrocytes. Some Plasmodia prefer younger vs. older erythrocytes. How does the life evolution of the RBC affect the invasion of the parasite? What happens when the RBC ages? In this review, we present what is known up until now.

Red blood cell dynamics during malaria infection violate the assumptions of mathematical models of infection dynamics

For decades, mathematical models have been used to understand the course and outcome of malaria infections (i.e., infection dynamics) and the evolutionary dynamics of the parasites that cause them. A key conclusion of these models is that red blood cell (RBC) availability is a fundamental driver of infection dynamics and parasite trait evolution. The extent to which this conclusion holds will in part depend on model assumptions about the host-mediated processes that regulate RBC availability i.e., removal of uninfected RBCs and supply of RBCs. Diverse mathematical functions have been used to describe host-mediated RBC supply and clearance, but it remains unclear whether they adequately capture the dynamics of RBC supply and clearance during infection. Here, we use a unique dataset, comprising time-series measurements of erythrocyte (i.e., mature RBC) and reticulocyte (i.e., newly supplied RBC) densities during Plasmodium chabaudi malaria infection, and a quantitative data-transformation scheme to elucidate whether RBC dynamics conform to common model assumptions. We found that RBC clearance and supply are not well described by mathematical functions commonly used to model these processes. Furthermore, the temporal dynamics of both processes vary with parasite growth rate in a manner again not captured by existing models. Together, these finding suggest that new model formulations are required if we are to explain and ultimately predict the within-host population dynamics and evolution of malaria parasites.

The impact of innate immunity on malaria parasite infection dynamics in rodent models

Decades of research have probed the molecular and cellular mechanisms that control the immune response to malaria. Yet many studies offer conflicting results on the functional impact of innate immunity for controlling parasite replication early in infection. We conduct a meta-analysis to seek consensus on the effect of innate immunity on parasite replication, examining three different species of rodent malaria parasite. Screening published studies that span four decades of research we collate, curate, and statistically analyze infection dynamics in immune-deficient or -augmented mice to identify and quantify general trends and reveal sources of disagreement among studies. Additionally, we estimate whether host factors or experimental methodology shape the impact of immune perturbations on parasite burden. First, we detected meta-analytic mean effect sizes (absolute Cohen's h) for the difference in parasite burden between treatment and control groups ranging from 0.1475 to 0.2321 across parasite species. This range is considered a small effect size and translates to a modest change in parasitaemia of roughly 7-12% on average at the peak of infection. Second, we reveal that variation across studies using P. chabaudi or P. yoelii is best explained by stochasticity (due to small sample sizes) rather than by host factors or experimental design. Third, we find that for P. berghei the impact of immune perturbation is increased when young or female mice are used and is greatest when effector molecules (as opposed to upstream signalling molecules) are disrupted (up to an 18% difference in peak parasitaemia). Finally, we find little evidence of publication bias suggesting that our results are robust. The small effect sizes we observe, across three parasite species, following experimental perturbations of the innate immune system may be explained by redundancy in a complex biological system or by incomplete (or inappropriate) data reporting for meta-analysis. Alternatively, our findings might indicate a need to re-evaluate the efficiency with which innate immunity controls parasite replication early in infection. Testing these hypotheses is necessary to translate understanding from model systems to human malaria.

Extraordinary parasite multiplication rates in human malaria infections

For pathogenic organisms, faster rates of multiplication promote transmission success, the potential to harm hosts, and the evolution of drug resistance. Parasite multiplication rates (PMRs) are often quantified in malaria infections, given the relative ease of sampling. Using modern and historical human infection data, we show that established methods return extraordinarily - and implausibly - large PMRs. We illustrate how inflated PMRs arise from two facets of malaria biology that are far from unique: (i) some developmental ages are easier to sample than others; (ii) the distribution of developmental ages changes over the course of infection. The difficulty of accurately quantifying PMRs demonstrates a need for robust methods and a subsequent re-evaluation of what is known even in the well-studied system of malaria.

Forest disturbance and recovery in Peruvian Amazonia

Amazonian forests function as biomass and biodiversity reservoirs, contributing to climate change mitigation. While they continuously experience disturbance, the effect that disturbances have on biomass and biodiversity over time has not yet been assessed at a large scale. Here, we evaluate the degree of recent forest disturbance in Peruvian Amazonia and the effects that disturbance, environmental conditions and human use have on biomass and biodiversity in disturbed forests. We integrate tree-level data on aboveground biomass (AGB) and species richness from 1840 forest plots from Peru's National Forest Inventory with remotely sensed monitoring of forest change dynamics, based on disturbances detected from Landsat-derived Normalized Difference Moisture Index time series. Our results show a clear negative effect of disturbance intensity tree species richness. This effect was also observed on AGB and species richness recovery values towards undisturbed levels, as well as on the recovery of species composition towards undisturbed levels. Time since disturbance had a larger effect on AGB than on species richness. While time since disturbance has a positive effect on AGB, unexpectedly we found a small negative effect of time since disturbance on species richness. We estimate that roughly 15% of Peruvian Amazonian forests have experienced disturbance at least once since 1984, and that, following disturbance, have been increasing in AGB at a rate of 4.7 Mg ha-1  year-1 during the first 20 years. Furthermore, the positive effect of surrounding forest cover was evident for both AGB and its recovery towards undisturbed levels, as well as for species richness. There was a negative effect of forest accessibility on the recovery of species composition towards undisturbed levels. Moving forward, we recommend that forest-based climate change mitigation endeavours consider forest disturbance through the integration of forest inventory data with remote sensing methods.

Liver-stage fate determination in Plasmodium vivax parasites: Characterization of schizont growth and hypnozoite fating from patient isolates

Plasmodium vivax, one species of parasite causing human malaria, forms a dormant liver stage, termed the hypnozoite, which activate weeks, months or years after the primary infection, causing relapse episodes. Relapses significantly contribute to the vivax malaria burden and are only killed with drugs of the 8-aminoquinoline class, which are contraindicated in many vulnerable populations. Development of new therapies targeting hypnozoites is hindered, in part, by the lack of robust methods to continuously culture and characterize this parasite. As a result, the determinants of relapse periodicity and the molecular processes that drive hypnozoite formation, persistence, and activation are largely unknown. While previous reports have described vastly different liver-stage growth metrics attributable to which hepatocyte donor lot is used to initiate culture, a comprehensive assessment of how different P. vivax patient isolates behave in the same lots at the same time is logistically challenging. Using our primary human hepatocyte-based P. vivax liver-stage culture platform, we aimed to simultaneously test the effects of how hepatocyte donor lot and P. vivax patient isolate influence the fate of sporozoites and growth of liver schizonts. We found that, while environmental factors such as hepatocyte donor lot can modulate hypnozoite formation rate, the P. vivax case is also an important determinant of the proportion of hypnozoites observed in culture. In addition, we found schizont growth to be mostly influenced by hepatocyte donor lot. These results suggest that, while host hepatocytes harbor characteristics making them more- or less-supportive of a quiescent versus growing intracellular parasite, sporozoite fating toward hypnozoites is isolate-specific. Future studies involving these host–parasite interactions, including characterization of individual P. vivax strains, should consider the impact of culture conditions on hypnozoite formation, in order to better understand this important part of the parasite’s lifecycle.

Spatiotemporal Patterns and Drivers of the Carbon Budget in the Yangtze River Delta Region, China

Improving our understanding of the patterns and drivers of regional carbon budgets is critical to mitigating climate change regionally and globally. Different from previous research, our study attempts to reveal the comprehensive impact of climate change and human activities factors on the carbon budget. Based on the Carnegie–Ames–Stanford approach (CASA) model, the IPCC inventory method, the ordinary least squares (OLS) regression model, the Geodetector model, and the geographically weighted regression (GWR) method, we investigated the spatiotemporal patterns of the carbon budget in the Yangtze River Delta (YRD) region from 2000 to 2015 and analyzed the effects of climate change and human activities on the carbon budget. The results showed that the carbon budget in the YRD region changed from 271.33 million tons in 2000 to −1193.76 million tons in 2015. During this period, the changes in the carbon budget per unit area in the four provinces all showed a decreasing trend, among which Shanghai decreased the most, followed by Jiangsu, Zhejiang and Anhui. In terms of spatial pattern, the carbon budget of the YRD region has a “core-edge” structural feature. The closer it is to Shanghai, the core area, the more severe the carbon budget deficit; the farther from it, the greater the carbon budget surplus. Overall, we found that human activities have a greater impact on the carbon budget than climate change. The top three drivers were, in order, changes in population density, GDP per capita, and unused land, with q values of 0.3317, 0.1202, and 0.0998, respectively. Locally, the impact of the drivers on the carbon budget shows obvious spatial heterogeneity. In particular, the population density was negatively correlated with carbon budget changes in the entire study area, and the coefficients of GDP per capita and unused land were negative in most counties. Based on the results, we put forward suggestions for restricting population flow among the core area and the peripheral area, promoting industrial innovation in the core area and ecological protection in the peripheral area, as well as implementing three-dimensional space development in the core area and controlling the expansion of construction land in the peripheral area. Our study can provide a scientific basis for low-carbon development in the YRD region. The methodology and findings of this study can provide references for similar studies in other urbanized regions around the world.

Carbon Source Reduction Postpones Autumn Leaf Senescence in a Widespread Deciduous Tree

The growing-season length of temperate and boreal trees has a strong effect on the global carbon cycle. Yet, a poor understanding of the drivers of phenological processes, such as autumn leaf senescence in deciduous trees, limits our capacity to estimate growing-season lengths under climate change. While temperature has been shown to be an important driver of autumn leaf senescence, carbon source-sink dynamics have been proposed as a mechanism that could help explain variation of this important process. According to the carbon sink limitation hypothesis, senescence is regulated by the interplay between plant carbon source and sink dynamics, so that senescence occurs later upon low carbon inputs (source) and earlier upon low carbon demand (sink). Here, we manipulated carbon source-sink dynamics in birch saplings (Betula pendula) to test the relevance of carbon sink limitation for autumn leaf senescence and photosynthetic decline in a widespread deciduous tree. Specifically, we conducted a gradient of leaf and bud removal treatments and monitored the effects on autumnal declines in net photosynthesis and the timing of leaf senescence. In line with the carbon sink limitation hypothesis, we observed that leaf removal tended to increase total leaf-level autumn photosynthesis and delayed the timing of senescence. Conversely, we did not observe an effect of bud removal on either photosynthesis or senescence, which was likely caused by the fact that our bud removal treatment did not considerably affect the plant carbon sink. While we cannot fully rule out that the observed effect of leaf removal was influenced by possible treatment-level differences in leaf age or soil resource availability, our results provide support for the hypothesis of carbon sink limitation as a driver of growing-season length and move the scientific field closer to narrowing the uncertainty in climate change predictions.

Fine-Scale Improved Carbon Bookkeeping Model Using Landsat Time Series for Subtropical Forest, Southern China

Subtropical forests easily suffer anthropogenic disturbance, including deforestation and reforestation management, which both highly affect the carbon pools. This study proposes spatial-temporal tracking of the carbon density dynamics to improve bookkeeping in the carbon model and applied to subtropical forest activities in Guangzhou, southern China, during the period of 1995 to 2014. Based on the overall accuracy of 87.5% ± 1.7% for forest change products using Landsat time series (LTS), we found that this is a typical period of deforestation conversion to reforestation activity accompanied with urbanization. Additionally, linear regression, random forest regression and allometric growth fitting were proposed by using forest field plots to obtain reliable per-pixel carbon density estimations. The cross-validation (CV) of random forest with LTS-derived parameters reached the highest accuracy of R2 and RMSE of 0.763 and 7.499 Mg ha−1. The RMES of the density estimation ranged between 78 and 84% of the mean observed biomass in the study area, which outperformed previous studies. Over the 20-year period, the study results showed that the explicit carbon emissions were (6.82 ± 0.26) × 104 Mg C yr−1 from deforestation; emissions increased to (1.02 ± 0.04) × 105 Mg C yr−1 given the implicit carbon not yet released to the atmosphere in the form of decomposing slash and wood products. In addition, a carbon uptake of about 1.91 ± 0.73 × 105 Mg C yr−1, presented as the net carbon pool. Based on the continuous detection capability, biennial reforestation activity has increased carbon density by a growth rate of 1.55 Mg ha−1, and the emission factors can be identified with LTS-derived parameters. In general, the study realizes the spatiotemporal improvement of carbon density and flux dynamics tracking, including the abrupt and graduate change based on fine-scale forest activity. It can provide more comprehensive and detailed feedback on the carbon source and sink change process of forest activities and disturbances.

The Potential of Fully Polarized ALOS-2 Data for Estimating Forest Above-Ground Biomass

SAR data have a longer wavelength and stronger penetrating power compared with traditional optical remote sensing. Therefore, SAR data are more suitable for the estimation of the above-ground biomass (AGB) of forests. This study was aimed at evaluating the sensitivity of L-band full polarization data to AGB. L-band data were improved to estimate the saturation point produced by AGB, and were found to be suitable for estimating a wide range of AGB. This study extracted backscattering coefficients, polarization decomposition variables, and terrain factors. New parameters were constructed from these variables, and their performance in predicting AGB was evaluated. Significant variables found with AGB were added to the multivariate linear model. A statistical analysis showed the presence of multicollinearity between the variables. Therefore, ridge regression, random forest method (RF), and principal component analysis (PCA) were introduced to solve the problem of collinearity. In all the three methods, the saturation of the ridge regression model was low, reaching it at 150 t/ha. Better accuracy was obtained with the RF model. No obvious saturation incident was detected in the model established using the principal component analysis. This could be attributed to the low biomass levels observed in our study area. This model provided accurate results (adjusted r2 = 0.90 rmse = 14.24 t/ha), indicating that L-band data have the potential to estimate AGB. Additionally, suitable variables and models were selected in this study, with the principal component analysis being more helpful in combining various SAR parameters. The achievement of these accurate results could be attributed to the synergy among variables.

Linking functional and molecular mechanisms of host resilience to malaria infection

It remains challenging to understand why some hosts suffer severe illnesses, while others are unscathed by the same infection. We fitted a mathematical model to longitudinal measurements of parasite and red blood cell density in murine hosts from diverse genetic backgrounds to identify aspects of within-host interactions that explain variation in host resilience and survival during acute malaria infection. Among eight mouse strains that collectively span 90% of the common genetic diversity of laboratory mice, we found that high host mortality was associated with either weak parasite clearance, or a strong, yet imprecise response that inadvertently removes uninfected cells in excess. Subsequent cross-sectional cytokine assays revealed that the two distinct functional mechanisms of poor survival were underpinned by low expression of either pro- or anti-inflammatory cytokines, respectively. By combining mathematical modelling and molecular immunology assays, our study uncovered proximate mechanisms of diverse infection outcomes across multiple host strains and biological scales.

Differential drivers of intraspecific and interspecific competition during malaria-helminth co-infection

Various host and parasite factors interact to determine the outcome of infection. We investigated the effects of two factors on the within-host dynamics of malaria in mice: initial infectious dose and co-infection with a helminth that limits the availability of red blood cells (RBCs). Using a statistical, time-series approach to model the within-host ‘epidemiology’ of malaria, we found that increasing initial dose reduced the time to peak cell-to-cell parasite propagation, but also reduced its magnitude, while helminth co-infection delayed peak cell-to-cell propagation, except at the highest malaria doses. Using a mechanistic model of within-host infection dynamics, we identified dose-dependence in parameters describing host responses to malaria infection and uncovered a plausible explanation of the observed differences in single vs co-infections. Specifically, in co-infections, our model predicted a higher background death rate of RBCs. However, at the highest dose, when intraspecific competition between malaria parasites would be highest, these effects of co-infection were not observed. Such interactions between initial dose and co-infection, although difficult to predict a priori, are key to understanding variation in the severity of disease experienced by hosts and could inform studies of malaria transmission dynamics in nature, where co-infection and low doses are the norm.

Immune selection suppresses the emergence of drug resistance in malaria parasites but facilitates its spread

Although drug resistance in Plasmodium falciparum typically evolves in regions of low transmission, resistance spreads readily following introduction to regions with a heavier disease burden. This suggests that the origin and the spread of resistance are governed by different processes, and that high transmission intensity specifically impedes the origin. Factors associated with high transmission, such as highly immune hosts and competition within genetically diverse infections, are associated with suppression of resistant lineages within hosts. However, interactions between these factors have rarely been investigated and the specific relationship between adaptive immunity and selection for resistance has not been explored. Here, we developed a multiscale, agent-based model of Plasmodium parasites, hosts, and vectors to examine how host and parasite dynamics shape the evolution of resistance in populations with different transmission intensities. We found that selection for antigenic novelty (“immune selection”) suppressed the evolution of resistance in high transmission settings. We show that high levels of population immunity increased the strength of immune selection relative to selection for resistance. As a result, immune selection delayed the evolution of resistance in high transmission populations by allowing novel, sensitive lineages to remain in circulation at the expense of the spread of a resistant lineage.

In contrast, in low transmission settings, we observed that resistant strains were able to sweep to high population prevalence without interference. Additionally, we found that the relationship between immune selection and resistance changed when resistance was widespread. Once resistance was common enough to be found on many antigenic backgrounds, immune selection stably maintained resistant parasites in the population by allowing them to proliferate, even in untreated hosts, when resistance was linked to a novel epitope. Our results suggest that immune selection plays a role in the global pattern of resistance evolution.

Drug resistance in the malaria parasite, Plasmodium falciparum, presents an ongoing public health challenge, but aspects of its evolution are poorly understood. Although antimalarial resistance is common worldwide, it can typically be traced to just a handful of evolutionary origins. Counterintuitively, although Sub Saharan Africa bears 90% of the global malaria burden, resistance typically originates in regions where transmission intensity is low. In high transmission regions, infections are genetically diverse, and hosts have significant standing adaptive immunity, both of which are known to suppress the frequency of resistance within infections. However, interactions between immune-driven selection, transmission intensity, and resistance have not been investigated. Using a multiscale, agent-based model, we found that high transmission intensity slowed the evolution of resistance via its effect on host population immunity. High host immunity strengthened selection for antigenic novelty, interfering with selection for resistance and allowing sensitive lineages to suppress resistant lineages in untreated hosts. However, once resistance was common in the circulating parasite population, immune selection maintained it in the population at a high prevalence. Our findings provide a novel explanation for observations about the origin of resistance and suggest that adaptive immunity is a critical component of selection.

Deconstructing the parasite multiplication rate of Plasmodium falciparum

Epidemiological indicators describing population-level malaria transmission dynamics are widely used to guide policy recommendations. However, the determinants of malaria outcomes within individuals are still poorly understood. This conceptual gap partly reflects the fact that there are few indicators that robustly predict the trajectory of individual infections or clinical outcomes. The parasite multiplication rate (PMR) is a widely used indicator for the Plasmodium intraerythrocytic development cycle (IDC), for example, but its relationship to clinical outcomes is complex. Here, we review its calculation and use in P. falciparum malaria research, as well as the parasite and host factors that impact it. We also provide examples of metrics that can help to link within-host dynamics to malaria clinical outcomes when used alongside the PMR.

Disentangling the dynamical underpinnings of differences in SARS-CoV-2 pathology using within-host ecological models

Health outcomes following infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) are remarkably variable. The way the virus spreads inside hosts, and how this spread interacts with host immunity and physiology, is likely to determine variation in health outcomes. Decades of data and dynamical analyses of how other viruses spread and interact with host cells could shed light on SARS-CoV-2 within-host trajectories. We review how common axes of variation in within-host dynamics and emergent pathology (such as age and sex) might be combined with ecological principles to understand the case of SARS-CoV-2. We highlight pitfalls in application of existing theoretical frameworks relevant to the complexity of the within-host context and frame the discussion in terms of growing knowledge of the biology of SARS-CoV-2. Viewing health outcomes for SARS-CoV-2 through the lens of ecological models underscores the value of repeated measures on individuals, especially since many lines of evidence suggest important contingence on trajectory.

Uncovering drivers of dose-dependence and individual variation in malaria infection outcomes

To understand why some hosts get sicker than others from the same type of infection, it is essential to explain how key processes, such as host responses to infection and parasite growth, are influenced by various biotic and abiotic factors. In many disease systems, the initial infection dose impacts host morbidity and mortality. To explore drivers of dose-dependence and individual variation in infection outcomes, we devised a mathematical model of malaria infection that allowed host and parasite traits to be linear functions (reaction norms) of the initial dose. We fitted the model, using a hierarchical Bayesian approach, to experimental time-series data of acute Plasmodium chabaudi infection across doses spanning seven orders of magnitude. We found evidence for both dose-dependent facilitation and debilitation of host responses. Most importantly, increasing dose reduced the strength of activation of indiscriminate host clearance of red blood cells while increasing the half-life of that response, leading to the maximal response at an intermediate dose. We also explored the causes of diverse infection outcomes across replicate mice receiving the same dose. Besides random noise in the injected dose, we found variation in peak parasite load was due to unobserved individual variation in host responses to clear infected cells. Individual variation in anaemia was likely driven by random variation in parasite burst size, which is linked to the rate of host cells lost to malaria infection. General host vigour in the absence of infection was also correlated with host health during malaria infection. Our work demonstrates that the reaction norm approach provides a useful quantitative framework for examining the impact of a continuous external factor on within-host infection processes.

Effect of drug dose and timing of treatment on the emergence of drug resistance in vivo in a malaria model

BACKGROUND AND OBJECTIVES

There is a significant interest in identifying clinically effective drug treatment regimens that minimize the de novo evolution of antimicrobial resistance in pathogen populations. However, in vivo studies that vary treatment regimens and directly measure drug resistance evolution are rare. Here, we experimentally investigate the role of drug dose and treatment timing on resistance evolution in an animal model.

METHODOLOGY

In a series of experiments, we measured the emergence of atovaquone-resistant mutants of Plasmodium chabaudi in laboratory mice, as a function of dose or timing of treatment (day post-infection) with the antimalarial drug atovaquone.

RESULTS

The likelihood of high-level resistance emergence increased with atovaquone dose. When varying the timing of treatment, treating either very early or late in infection reduced the risk of resistance. When we varied starting inoculum, resistance was more likely at intermediate inoculum sizes, which correlated with the largest population sizes at time of treatment.

CONCLUSIONS AND IMPLICATIONS

(i) Higher doses do not always minimize resistance emergence and can promote the emergence of high-level resistance. (ii) Altering treatment timing affects the risk of resistance emergence, likely due to the size of the population at the time of treatment, although we did not test the effect of immunity whose influence may have been important in the case of late treatment. (iii) Finding the 'right' dose and 'right' time to maximize clinical gains and limit resistance emergence can vary depending on biological context and was non-trivial even in our simplified experiments.

LAY SUMMARY

In a mouse model of malaria, higher drug doses led to increases in drug resistance. The timing of drug treatment also impacted resistance emergence, likely due to the size of the population at the time of treatment.

Simulation modelling for immunologists

The immune system is inordinately complex with many interacting components determining overall outcomes. Mathematical and computational modelling provides a useful way in which the various contributions of different immunological components can be probed in an integrated manner. Here, we provide an introductory overview and review of mechanistic simulation models. We start out by briefly defining these types of models and contrasting them to other model types that are relevant to the field of immunology. We follow with a few specific examples and then review the different ways one can use such models to answer immunological questions. While our examples focus on immune responses to infection, the overall ideas and descriptions of model uses can be applied to any area of immunology.

The contribution of host cell-directed vs. parasite-directed immunity to the disease and dynamics of malaria infections

Hosts defend themselves against pathogens by mounting an immune response. Fully understanding the immune response as a driver of host disease and pathogen evolution requires a quantitative account of its impact on parasite population dynamics. Here, we use a data-driven modeling approach to quantify the birth and death processes underlying the dynamics of infections of the rodent malaria parasite, Plasmodium chabaudi, and the red blood cells (RBCs) it targets. We decompose the immune response into 3 components, each with a distinct effect on parasite and RBC vital rates, and quantify the relative contribution of each component to host disease and parasite density. Our analysis suggests that these components are deployed in a coordinated fashion to realize distinct resource-directed defense strategies that complement the killing of parasitized cells. Early in the infection, the host deploys a strategy reminiscent of siege and scorched-earth tactics, in which it both destroys RBCs and restricts their supply. Late in the infection, a "juvenilization" strategy, in which turnover of RBCs is accelerated, allows the host to recover from anemia while holding parasite proliferation at bay. By quantifying the impact of immunity on both parasite fitness and host disease, we reveal that phenomena often interpreted as immunopathology may in fact be beneficial to the host. Finally, we show that, across mice, the components of the host response are consistently related to each other, even when infections take qualitatively different trajectories. This suggests the existence of simple rules that govern the immune system's deployment.

Partitioning the influence of ecology across scales on parasite evolution

Vector-borne parasites must succeed at three scales to persist: they must proliferate within a host, establish in vectors, and transmit back to hosts. Ecology outside the host undergoes dramatic seasonal and human-induced changes, but predicting parasite evolutionary responses requires integrating their success across scales. We develop a novel, data-driven model to titrate the evolutionary impact of ecology at multiple scales on human malaria parasites. We investigate how parasites invest in transmission versus proliferation, a life-history trait that influences disease severity and spread. We find that transmission investment controls the pattern of host infectiousness over the course of infection: a trade-off emerges between early and late infectiousness, and the optimal resolution of that trade-off depends on ecology outside the host. An expanding epidemic favors rapid proliferation, and can overwhelm the evolutionary influence of host recovery rates and mosquito population dynamics. If transmission investment and recovery rate are positively correlated, then ecology outside the host imposes potent selection for aggressive parasite proliferation at the expense of transmission. Any association between transmission investment and recovery represents a key unknown, one that is likely to influence whether the evolutionary consequences of interventions are beneficial or costly for human health.

Within-host modeling of blood-stage malaria

Malaria infection continues to be a major health problem worldwide and drug resistance in the major human parasite species, Plasmodium falciparum, is increasing in South East Asia. Control measures including novel drugs and vaccines are in development, and contributions to the rational design and optimal usage of these interventions are urgently needed. Infection involves the complex interaction of parasite dynamics, host immunity, and drug effects. The long life cycle (48 hours in the common human species) and synchronized replication cycle of the parasite population present significant challenges to modeling the dynamics of Plasmodium infection. Coupled with these, variation in immune recognition and drug action at different life cycle stages leads to further complexity. We review the development and progress of "within-host" models of Plasmodium infection, and how these have been applied to understanding and interpreting human infection and animal models of infection.

The Challenge of Quantifying Synchrony in Malaria Parasites

Malaria infection is often accompanied by periodic fevers, triggered by synchronous cycles of parasite replication within the host. The degree of synchrony in parasite development influences the efficacy of drugs and immune defenses and is therefore relevant to host health and infectiousness. Synchrony is thought to vary over the course of infection and across different host-parasite genotype or species combinations, but the evolutionary significance - if any - of this diversity remains elusive. Standardized methods are lacking, but the most common metric for quantifying synchrony is the percentage of parasites in a particular developmental stage. We use a heuristic model to show that this metric is often unacceptably biased. Methodological challenges must be addressed to characterize diverse patterns of synchrony and their consequences for disease severity and spread.

Structured mathematical models to investigate the interactions between Plasmodium falciparum malaria parasites and host immune response

Malaria infection has posed a major health threat for hundreds of years in human history. Yet, due to the complex interactions between a host immune response and the parasite, no sophisticated mathematical models exist to study its dynamics. In this work, we propose a new system of structured partial differential equations that account for the dependence of red blood cell infectivity on maturation level. These equations are coupled with another set of differential equations for investigating the population dynamics of Plasmodium falciparum and its interaction with red blood cells and cells of the immune system. A finite difference scheme is developed to solve the system. Numerical simulations are applied to investigate the interplay between the host immune response and the parasite dynamics, the disease dynamics in acute infection, and treatment effectiveness with different drugs.

Immune system handling time may alter the outcome of competition between pathogens and the immune system

Predators may be limited in their ability to kill prey (i.e., have type II or III functional responses), an insight that has had far-reaching consequences in the ecological literature. With few exceptions, however, this possibility has not been extended to the behaviour of immune cells, which kill pathogens much as predators kill their prey. Rather, models of the within-host environment have tended to tacitly assume that immune cells have an unlimited ability to target and kill pathogens (i.e., a type I functional response). Here we explore the effects of changing this assumption on infection outcomes (i.e., pathogen loads). We incorporate immune cell handling time into an ecological model of the within-host environment that considers both the predatory nature of the pathogen-immune cell interaction as well as competition between immune cells and pathogens for host resources. Unless pathogens can preempt immune cells for host resources, adding an immune cell handling time increases equilibrium pathogen load. We find that the shape of the relationship between energy intake and pathogen load can change: with a type I functional response, pathogen load is maximised at intermediate inputs, while for a type II or III functional response, pathogen load is solely increasing. With a type II functional response, pathogen load can fluctuate rather than settling to an equilibrium, a phenomenon unobserved with type I or III functional responses. Our work adds to a growing literature highlighting the role of resource availability in host-parasite interactions. Implications of our results for adaptive anorexia are discussed.

A nutrient mediates intraspecific competition between rodent malaria parasites in vivo

Hosts are often infected with multiple strains of a single parasite species. Within-host competition between parasite strains can be intense and has implications for the evolution of traits that impact patient health, such as drug resistance and virulence. Yet the mechanistic basis of within-host competition is poorly understood. Here, we demonstrate that a parasite nutrient, para-aminobenzoic acid (pABA), mediates competition between a drug resistant and drug susceptible strain of the malaria parasite, Plasmodium chabaudi. We further show that increasing pABA supply to hosts infected with the resistant strain worsens disease and changes the relationship between parasite burden and pathology. Our experiments demonstrate that, even when there is profound top-down regulation (immunity), bottom-up regulation of pathogen populations can occur and that its importance may vary during an infection. The identification of resources that can be experimentally controlled opens up the opportunity to manipulate competitive interactions between parasites and hence their evolution.

Phenotypic plasticity in reproductive effort: malaria parasites respond to resource availability

The trade-off between survival and reproduction is fundamental in the life history of all sexually reproducing organisms. This includes malaria parasites, which rely on asexually replicating stages for within-host survival and on sexually reproducing stages (gametocytes) for between-host transmission. The proportion of asexual stages that form gametocytes (reproductive effort) varies during infections-i.e. is phenotypically plastic-in response to changes in a number of within-host factors, including anaemia. However, how the density and age structure of red blood cell (RBC) resources shape plasticity in reproductive effort and impacts upon parasite fitness is controversial. Here, we examine how and why the rodent malaria parasite Plasmodium chabaudi alters its reproductive effort in response to experimental perturbations of the density and age structure of RBCs. We show that all four of the genotypes studied increase reproductive effort when the proportion of RBCs that are immature is elevated during host anaemia, and that the responses of the genotypes differ. We propose that anaemia (counterintuitively) generates a resource-rich environment in which parasites can afford to allocate more energy to reproduction (i.e. transmission) and that anaemia also exposes genetic variation to selection. From an applied perspective, adaptive plasticity in parasite reproductive effort could explain the maintenance of genetic variation for virulence and why anaemia is often observed as a risk factor for transmission in human infections.

Host-mediated impairment of parasite maturation during blood-stage Plasmodium infection

Severe malaria and associated high parasite burdens occur more frequently in humans lacking robust adaptive immunity to Plasmodium falciparum Nevertheless, the host may partly control blood-stage parasite numbers while adaptive immunity is gradually established. Parasite control has typically been attributed to enhanced removal of parasites by the host, although in vivo quantification of this phenomenon remains challenging. We used a unique in vivo approach to determine the fate of a single cohort of semisynchronous, Plasmodium berghei ANKA- or Plasmodium yoelii 17XNL-parasitized red blood cells (pRBCs) after transfusion into naive or acutely infected mice. As previously shown, acutely infected mice, with ongoing splenic and systemic inflammatory responses, controlled parasite population growth more effectively than naive controls. Surprisingly, however, this was not associated with accelerated removal of pRBCs from circulation. Instead, transfused pRBCs remained in circulation longer in acutely infected mice. Flow cytometric assessment and mathematical modeling of intraerythrocytic parasite development revealed an unexpected and substantial slowing of parasite maturation in acutely infected mice, extending the life cycle from 24 h to 40 h. Importantly, impaired parasite maturation was the major contributor to control of parasite growth in acutely infected mice. Moreover, by performing the same experiments in rag1^-/- mice, which lack T and B cells and mount weak inflammatory responses, we revealed that impaired parasite maturation is largely dependent upon the host response to infection. Thus, impairment of parasite maturation represents a host-mediated, immune system-dependent mechanism for limiting parasite population growth during the early stages of an acute blood-stage Plasmodium infection.

South-East Asian strains of Plasmodium falciparum display higher ratio of non-synonymous to synonymous polymorphisms compared to African strains

Resistance to frontline anti-malarial drugs, including artemisinin, has repeatedly arisen in South-East Asia, but the reasons for this are not understood. Here we test whether evolutionary constraints on Plasmodium falciparum strains from South-East Asia differ from African strains. We find a significantly higher ratio of non-synonymous to synonymous polymorphisms in P. falciparum from South-East Asia compared to Africa, suggesting differences in the selective constraints on P. falciparum genome in these geographical regions. Furthermore, South-East Asian strains showed a higher proportion of non-synonymous polymorphism at conserved positions, suggesting reduced negative selection. There was a lower rate of mixed infection by multiple genotypes in samples from South-East Asia compared to Africa. We propose that a lower mixed infection rate in South-East Asia reduces intra-host competition between the parasite clones, reducing the efficiency of natural selection. This might increase the probability of fixation of fitness-reducing mutations including drug resistant ones.

Facilitation through altered resource availability in a mixed-species rodent malaria infection

A major challenge in disease ecology is to understand how co-infecting parasite species interact. We manipulate in vivo resources and immunity to explain interactions between two rodent malaria parasites, Plasmodium chabaudi and P. yoelii. These species have analogous resource-use strategies to the human parasites Plasmodium falciparum and P. vivax: P. chabaudi and P. falciparum infect red blood cells (RBC) of all ages (RBC generalist); P. yoelii and P. vivax preferentially infect young RBCs (RBC specialist). We find that: (1) recent infection with the RBC generalist facilitates the RBC specialist (P. yoelii density is enhanced ~10 fold). This occurs because the RBC generalist increases availability of the RBC specialist's preferred resource; (2) co-infections with the RBC generalist and RBC specialist are highly virulent; (3) and the presence of an RBC generalist in a host population can increase the prevalence of an RBC specialist. Thus, we show that resources shape how parasite species interact and have epidemiological consequences.

Within-host competition and drug resistance in the human malaria parasite Plasmodium falciparum

Infections with the malaria parasite Plasmodium falciparum typically comprise multiple strains, especially in high-transmission areas where infectious mosquito bites occur frequently. However, little is known about the dynamics of mixed-strain infections, particularly whether strains sharing a host compete or grow independently. Competition between drug-sensitive and drug-resistant strains, if it occurs, could be a crucial determinant of the spread of resistance. We analysed 1341 P. falciparum infections in children from Angola, Ghana and Tanzania and found compelling evidence for competition in mixed-strain infections: overall parasite density did not increase with additional strains, and densities of individual chloroquine-sensitive (CQS) and chloroquine-resistant (CQR) strains were reduced in the presence of competitors. We also found that CQR strains exhibited low densities compared with CQS strains (in the absence of chloroquine), which may underlie observed declines of chloroquine resistance in many countries following retirement of chloroquine as a first-line therapy. Our observations support a key role for within-host competition in the evolution of drug-resistant malaria. Malaria control and resistance-management efforts in high-transmission regions may be significantly aided or hindered by the effects of competition in mixed-strain infections. Consideration of within-host dynamics may spur development of novel strategies to minimize resistance while maximizing the benefits of control measures.

Quantifying Transmission Investment in Malaria Parasites

Many microparasites infect new hosts with specialized life stages, requiring a subset of the parasite population to forgo proliferation and develop into transmission forms. Transmission stage production influences infectivity, host exploitation, and the impact of medical interventions like drug treatment. Predicting how parasites will respond to public health efforts on both epidemiological and evolutionary timescales requires understanding transmission strategies. These strategies can rarely be observed directly and must typically be inferred from infection dynamics. Using malaria as a case study, we test previously described methods for inferring transmission stage investment against simulated data generated with a model of within-host infection dynamics, where the true transmission investment is known. We show that existing methods are inadequate and potentially very misleading. The key difficulty lies in separating transmission stages produced by different generations of parasites. We develop a new approach that performs much better on simulated data. Applying this approach to real data from mice infected with a single Plasmodium chabaudi strain, we estimate that transmission investment varies from zero to 20%, with evidence for variable investment over time in some hosts, but not others. These patterns suggest that, even in experimental infections where host genetics and other environmental factors are controlled, parasites may exhibit remarkably different patterns of transmission investment.

Malaria parasites are carried from host to host by blood-feeding insects, a process that requires some portion of the parasite population to develop into transmission forms that cannot replicate within the current host. The fraction of parasites specialized for transmission instead of replication (transmission investment) could change with each cycle of replication in response to changing conditions within the host. Measuring how transmission investment changes through time could help us understand how malaria spreads so efficiently through populations of human and other animals. However, transmission investment is usually impossible to measure directly and instead has to be estimated by comparing the number of transmission forms with total parasite numbers in blood samples. Here we use a model to simulate data from an infection—so that the true level of transmission investment is known—and test published methods for estimation. We find that existing methods do not accurately estimate transmission investment from simulated data, and we propose a new statistical method that works substantially better. When applied to rodent malaria data, our method suggests that transmission investment can vary substantially over the course of infection, with notably different patterns of allocation across hosts.

Opportunities and challenges of Integral Projection Models for modelling host-parasite dynamics

Epidemiological dynamics are shaped by and may in turn shape host demography. These feedbacks can result in hard to predict patterns of disease incidence. Mathematical models that integrate infection and demography are consequently a key tool for informing expectations for disease burden and identifying effective measures for control.

A major challenge is capturing the details of infection within individuals and quantifying their downstream impacts to understand population‐scale outcomes. For example, parasite loads and antibody titres may vary over the course of an infection and contribute to differences in transmission at the scale of the population. To date, to capture these subtleties, models have mostly relied on complex mechanistic frameworks, discrete categorization and/or agent‐based approaches.

Integral Projection Models (IPMs) allow variance in individual trajectories of quantitative traits and their population‐level outcomes to be captured in ways that directly reflect statistical models of trait–fate relationships. Given increasing data availability, and advances in modelling, there is considerable potential for extending this framework to traits of relevance for infectious disease dynamics.

Here, we provide an overview of host and parasite natural history contexts where IPMs could strengthen inference of population dynamics, with examples of host species ranging from mice to sheep to humans, and parasites ranging from viruses to worms. We discuss models of both parasite and host traits, provide two case studies and conclude by reviewing potential for both ecological and evolutionary research.

Mathematical model of susceptibility, resistance, and resilience in the within-host dynamics between a Plasmodium parasite and the immune system

We developed a coupled age-structured partial differential equation model to capture the disease dynamics during blood-stage malaria. The addition of age structure for the parasite population, with respect to previous models, allows us to better characterize the interaction between the malaria parasite and red blood cells during infection. Here we prove that the system we propose is well-posed and there exist at least two global states. We further demonstrate that the numerical simulation of the system coincides with clinically observed outcomes of primary and secondary malaria infection. The well-posedness of this system guarantees that the behavior of the model remains smooth, bounded, and continuously dependent on initial conditions; calibration with clinical data will constrain domains of parameters and variables to physiological ranges.

Bottom-up regulation of malaria population dynamics in mice co-infected with lung-migratory nematodes

When and how populations are regulated by bottom up vs. top down processes, and how those processes are affected by co-occurring species, are poorly characterised across much of ecology. We are especially interested in the community ecology of parasites that must share a host. Here, we quantify how resources and immunity affect parasite propagation in experiments in near-replicate 'mesocosms'' - i.e. mice infected with malaria (Plasmodium chabaudi) and nematodes (Nippostrongylus brasiliensis). Nematodes suppressed immune responses against malaria, and yet malaria populations were smaller in co-infected hosts. Further analyses of within-host epidemiology revealed that nematode co-infection altered malaria propagation by suppressing target cell availability. This is the first demonstration that bottom-up resource regulation may have earlier and stronger effects than top-down immune mechanisms on within-host community dynamics. Our findings demonstrate the potential power of experimental ecology to disentangle mechanisms of population regulation in complex communities.

The role of models in translating within-host dynamics to parasite evolution

Mathematical modelling provides an effective way to challenge conventional wisdom about parasite evolution and investigate why parasites ‘do what they do’ within the host. Models can reveal when intuition cannot explain observed patterns, when more complicated biology must be considered, and when experimental and statistical methods are likely to mislead. We describe how models of within-host infection dynamics can refine experimental design, and focus on the case study of malaria to highlight how integration between models and data can guide understanding of parasite fitness in three areas: (1) the adaptive significance of chronic infections; (2) the potential for tradeoffs between virulence and transmission; and (3) the implications of within-vector dynamics. We emphasize that models are often useful when they highlight unexpected patterns in parasite evolution, revealing instead why intuition yields the wrong answer and what combination of theory and data are needed to advance understanding.

Do mixed infections matter? Assessing virulence of mixed-clone infections in experimental human and murine malaria

BACKGROUND

Malaria parasites within an individual infection often consist of multiple strains (clonal populations) of a single species, which have the potential to interact both with one another, and with the host immune system. Several effects of these interactions have been measured in different parasite systems including competition and mutualism; however, direct observation of these effects in human malaria has been limited by sampling complexities and inherent ethical limitations.

METHODS

Using multiple complementary epidemiological models, we propose a suite of analyses to more fully utilize data from challenge experiments, and re-examine historical human challenge studies with mixed-strain Plasmodium vivax inocula. We then compare these results with murine model systems using mixed-strain Plasmodium yoelii or Plasmodium chabaudi, to explore the utility of these methods in fully utilizing these data, including the first quantitative estimates of effect sizes for mixed-strain parasitemia. These models also provide a method to assess consistency within these animal model systems.

RESULTS

We find that amongst a limited set of P. vivax (incubation time) and P. yoelii infections (time-to-mortality), survival times at a study population-level are intermediate between each single-clone infection, and are not dominated by the more virulent clone; in P. vivax relapses, mixed clone infections also show intermediate survival curves. In these infections, the results strongly suggest that highly virulent clones have their virulence attenuated by the presence of less-virulent clones. The analysis of multiple experiments with P. chabaudi suggests greater nuances in the interactions between strains, and that mortality and time-to-event in mixed-strain infections are both indistinguishable from single infections with the more virulent strain.

CONCLUSIONS

These divergent dynamics support earlier work that suggested drivers of virulence may differ in fundamental ways between malaria species that are reticulocyte-specific and those that readily infect all red blood cell stages which should be studied in greater detail. The effect sizes (magnitude of biological effects) from these analyses are significant, and suggest the potential for important gains in malaria control by greater incorporation of evolutionary epidemiology theory. Moreover, we suggest that using these epidemiological models may generally allow fuller use of data from experimentally challenging animal model experiments.

The potential impact of coinfection on antimicrobial chemotherapy and drug resistance

Across a range of pathogens, resistance to chemotherapy is a growing problem in both public health and animal health. Despite the ubiquity of coinfection, and its potential effects on within-host biology, the role played by coinfecting pathogens on the evolution of resistance and efficacy of antimicrobial chemotherapy is rarely considered. In this review, we provide an overview of the mechanisms of interaction of coinfecting pathogens, ranging from immune modulation and resource modulation, to drug interactions. We discuss their potential implications for the evolution of resistance, providing evidence in the rare cases where it is available. Overall, our review indicates that the impact of coinfection has the potential to be considerable, suggesting that this should be taken into account when designing antimicrobial drug treatments.

Reduced erythrocyte susceptibility and increased host clearance of young parasites slows Plasmodium growth in a murine model of severe malaria

The best correlate of malaria severity in human Plasmodium falciparum (Pf) infection is the total parasite load. Pf-infected humans could control parasite loads by two mechanisms, either decreasing parasite multiplication, or increasing parasite clearance. However, few studies have directly measured these two mechanisms in vivo. Here, we have directly quantified host clearance of parasites during Plasmodium infection in mice. We transferred labelled red blood cells (RBCs) from Plasmodium infected donors into uninfected and infected recipients, and tracked the fate of donor parasites by frequent blood sampling. We then applied age-based mathematical models to characterise parasite clearance in the recipient mice. Our analyses revealed an increased clearance of parasites in infected animals, particularly parasites of a younger developmental stage. However, the major decrease in parasite multiplication in infected mice was not mediated by increased clearance alone, but was accompanied by a significant reduction in the susceptibility of RBCs to parasitisation.

Seven challenges in modeling pathogen dynamics within-host and across scales

The population dynamics of infectious disease is a mature field in terms of theory and to some extent, application. However for microparasites, the theory and application of models of the dynamics within a single infected host is still an open field. Further, connecting across the scales--from cellular to host level, to population level--has potential to vastly improve our understanding of pathogen dynamics and evolution. Here, we highlight seven challenges in the following areas: transmission bottlenecks, heterogeneity within host, dynamic fitness landscapes within hosts, making use of next-generation sequencing data, capturing superinfection and when and how to model more than two scales.

Within-host spatiotemporal dynamics of plant virus infection at the cellular level

A multicellular organism is not a monolayer of cells in a flask; it is a complex, spatially structured environment, offering both challenges and opportunities for viruses to thrive. Whereas virus infection dynamics at the host and within-cell levels have been documented, the intermediate between-cell level remains poorly understood. Here, we used flow cytometry to measure the infection status of thousands of individual cells in virus-infected plants. This approach allowed us to determine accurately the number of cells infected by two virus variants in the same host, over space and time as the virus colonizes the host. We found a low overall frequency of cellular infection (<0.3), and few cells were coinfected by both virus variants (<0.1). We then estimated the cellular contagion rate (R), the number of secondary infections per infected cell per day. R ranged from 2.43 to values not significantly different from zero, and generally decreased over time. Estimates of the cellular multiplicity of infection (MOI), the number of virions infecting a cell, were low (<1.5). Variance of virus-genotype frequencies increased strongly from leaf to cell levels, in agreement with a low MOI. Finally, there were leaf-dependent differences in the ease with which a leaf could be colonized, and the number of virions effectively colonizing a leaf. The modeling of infection patterns suggests that the aggregation of virus-infected cells plays a key role in limiting spread; matching the observation that cell-to-cell movement of plant viruses can result in patches of infection. Our results show that virus expansion at the between-cell level is restricted, probably due to the host environment and virus infection itself.

Immune-mediated competition in rodent malaria is most likely caused by induced changes in innate immune clearance of merozoites

Malarial infections are often genetically diverse, leading to competitive interactions between parasites. A quantitative understanding of the competition between strains is essential to understand a wide range of issues, including the evolution of virulence and drug resistance. In this study, we use dynamical-model based Bayesian inference to investigate the cause of competitive suppression of an avirulent clone of Plasmodium chabaudi (AS) by a virulent clone (AJ) in immuno-deficient and competent mice. We test whether competitive suppression is caused by clone-specific differences in one or more of the following processes: adaptive immune clearance of merozoites and parasitised red blood cells (RBCs), background loss of merozoites and parasitised RBCs, RBC age preference, RBC infection rate, burst size, and within-RBC interference. These processes were parameterised in dynamical mathematical models and fitted to experimental data. We found that just one parameter , the ratio of background loss rate of merozoites to invasion rate of mature RBCs, needed to be clone-specific to predict the data. Interestingly, was found to be the same for both clones in single-clone infections, but different between the clones in mixed infections. The size of this difference was largest in immuno-competent mice and smallest in immuno-deficient mice. This explains why competitive suppression was alleviated in immuno-deficient mice. We found that competitive suppression acts early in infection, even before the day of peak parasitaemia. These results lead us to argue that the innate immune response clearing merozoites is the most likely, but not necessarily the only, mediator of competitive interactions between virulent and avirulent clones. Moreover, in mixed infections we predict there to be an interaction between the clones and the innate immune response which induces changes in the strength of its clearance of merozoites. What this interaction is unknown, but future refinement of the model, challenged with other datasets, may lead to its discovery.

Malaria infections often consist of more than one strain of the same parasitic species. Understanding the within-host competition between these various strains is essential to understanding the evolution and epidemiology of drug resistance in malarial infections. The infection process and the competition between strains involve complicated biological processes that are explained by various hypotheses. Mathematical models tested against experimental data provide quantitative measures to compare these hypotheses and enable us to discern the actual biological processes that contribute to the observed dynamics. We use a group of models against experimental data on rodent malaria to test various hypotheses. Such quantitative measures, in understanding rodent malaria, can be considered as a step towards understanding within-host parasite dynamics. Our work presented here demonstrates how confronting mathematical models with data allows the discovery of subtle and novel interactions between hosts and parasites that would be impractical to do in an experiment and allows the rejection of hypotheses that are incorrect. It is our contention that understanding the forces controlling within-host parasite dynamics in well-defined experimental model is a necessary step towards understanding these features in natural infections.

Synchrony in malaria infections: how intensifying within-host competition can be adaptive

Malaria parasites exhibit great diversity in the coordination of their asexual life cycle within the host, ranging from asynchronous growth to tightly synchronized cycles of invasion and emergence from red blood cells. Synchronized reproduction should come at a high cost--intensifying competition among offspring--so why would some Plasmodium species engage in such behavior and others not? We use a delayed differential equation model to show that synchronized infections can be favored when (1) there is limited interference among parasites competing for red blood cells, (2) transmission success is an accelerating function of sexual parasite abundance, (3) the target of saturating immunity is short-lived, and (4) coinfections with asynchronous parasites are rare. As a consequence, synchrony may be beneficial or costly, in line with the diverse patterns of synchronization observed in natural and lab infections. By allowing us to characterize diverse temporal dynamics, the model framework provides a basis for making predictions about disease severity and for projecting evolutionary responses to interventions.