Assessing the public health impact of tolerance-based therapies with mathematical models

Dissecting transmission to understand parasite evolution

Parasite transmission is a complex, multi-stage process that significantly impacts host-parasite dynamics. Transmission plays a key role in epidemiology and virulence evolution, where it is expected to trade off with virulence. However, the extent to which classical models on virulence-transmission relationships apply in the real world is unclear. This insight piece proposes a novel framework that breaks transmission into three distinct stages: within-host infectiousness, an intermediate between-host stage (biotic or abiotic), and new host infection. Each stage is influenced by intrinsic and extrinsic factors to the parasite, which together will determine its transmission success. Analyzing the transmission stages separately and how they affect each other might enhance our understanding of which host-, parasite- or environmental-driven factors might shape parasite evolution and inform us about new effectors to act on when designing disease control strategies.

Intraspecific genetic variation in host vigour, viral load and disease tolerance during Drosophila C virus infection

Genetic variation for resistance and disease tolerance has been described in a range of species. In Drosophila melanogaster, genetic variation in mortality following systemic Drosophila C virus (DCV) infection is driven by large-effect polymorphisms in the restriction factor pastrel (pst). However, it is unclear if pst contributes to disease tolerance. We investigated systemic DCV challenges spanning nine orders of magnitude, in males and females of 10 Drosophila Genetic Reference Panel lines carrying either a susceptible (S) or resistant (R) pst allele. We find among-line variation in fly survival, viral load and disease tolerance measured both as the ability to maintain survival (mortality tolerance) and reproduction (fecundity tolerance). We further uncover novel effects of pst on host vigour, as flies carrying the R allele exhibited higher survival and fecundity even in the absence of infection. Finally, we found significant genetic variation in the expression of the JAK-STAT ligand upd3 and the epigenetic regulator of JAK-STAT G9a. However, while G9a has been previously shown to mediate tolerance of DCV infection, we found no correlation between the expression of either upd3 or G9a on fly tolerance or resistance. Our work highlights the importance of both resistance and tolerance in viral defence.

Can Infectious Disease Control Be Achieved without Antibiotics by Exploiting Mechanisms of Disease Tolerance?

Antimicrobial use in animal agriculture may be contributing to the emerging public health crisis of antimicrobial resistance. The sustained prevalence of infectious diseases driving antimicrobial use industry-wide suggests that traditional methods of bolstering disease resistance are, for some diseases, ineffective. A paradigm shift in our approach to infectious disease control is needed to reduce antimicrobial use and sustain animal and human health and the global economy. Targeting the defensive mechanisms that promote the health of an infected host without impacting pathogen fitness, termed “disease tolerance,” is a novel disease control approach ripe for discovery. This article presents examples of disease tolerance dictating clinical outcomes for several infectious diseases in humans, reveals evidence suggesting a similarly critical role of disease tolerance in the progression of infectious diseases plaguing animal agriculture, and thus substantiates the assertion that exploiting disease tolerance mechanisms can positively impact animal and human health.

How the epidemiology of disease-resistant and disease-tolerant varieties affects grower behaviour

Population-scale effects of resistant or tolerant crop varieties have received little consideration from epidemiologists. When growers deploy tolerant crop, population-scale disease pressures are often unaffected. This only benefits growers using tolerant varieties, selfishly decreasing yields for others. However, resistant crop can reduce disease pressure for all. We coupled an epidemiological model with game theory to understand how this affects uptake of control. Each time a grower plants a new crop, they must decide whether to use an improved (i.e. tolerant/resistant) or unimproved variety. This decision is based on strategic-adaptive expectations in our model, with growers comparing last season's profit with an estimate of what is expected from the alternative crop. Despite the positive feedback loop promoting use of a tolerant variety whenever it is available, a mixed unimproved- and tolerant-crop equilibrium can persist. Tolerant crop can also induce bistability between a scenario in which all growers use tolerant crop and the disease-free equilibrium, where no growers do. However, due to 'free-riding' by growers of unimproved crop, resistant crop nearly always exists in a mixed equilibrium. This work highlights how growers respond to contrasting incentives caused by tolerant and resistant varieties, and the distinct effects on yields and population-scale deployment.

Treatment timing shifts the benefits of short and long antibiotic treatment over infection

Antibiotics are the major tool for treating bacterial infections. Rising antibiotic resistance, however, calls for a better use of antibiotics. While classical recommendations favor long and aggressive treatments, more recent clinical trials advocate for moderate regimens. In this debate, two axes of 'aggression' have typically been conflated: treatment intensity (dose) and treatment duration. The third dimension of treatment timing along each individual's infection course has rarely been addressed. By using a generic mathematical model of bacterial infection controlled by immune response, we examine how the relative effectiveness of antibiotic treatment varies with its timing, duration and antibiotic kill rate. We show that short or long treatments may both be beneficial depending on treatment onset, the target criterion for success and on antibiotic efficacy. This results from the dynamic trade-off between immune response build-up and resistance risk in acute, self-limiting infections, and uncertainty relating symptoms to infection variables. We show that in our model early optimal treatments tend to be 'short and strong', while late optimal treatments tend to be 'mild and long'. This suggests a shift in the aggression axis depending on the timing of treatment. We find that any specific optimal treatment schedule may perform more poorly if evaluated by other criteria, or under different host-specific conditions. Our results suggest that major advances in antibiotic stewardship must come from a deeper empirical understanding of bacterial infection processes in individual hosts. To guide rational therapy, mathematical models need to be constrained by data, including a better quantification of personal disease trajectory in humans. Lay summary: Bacterial infections are becoming more difficult to treat worldwide because bacteria are becoming resistant to the antibiotics used. Addressing this problem requires a better understanding of how treatment along with other host factors impact antibiotic resistance. Until recently, most theoretical research has focused on the importance of antibiotic dosing on antibiotic resistance, however, duration and timing of treatment remain less explored. Here, we use a mathematical model of a generic bacterial infection to study three aspects of treatment: treatment dose/efficacy (defined by the antibiotic kill rate), duration, and timing, and their impact on several infection endpoints. We show that short and long treatment success strongly depends on when treatment begins (defined by the symptom threshold), the target criterion to optimize, and on antibiotic efficacy. We find that if administered early in an infection, "strong and short" therapy performs better, while if treatment begins at higher bacterial densities, a "mild and long" course of antibiotics is favored. In the model host immune defenses are key in preventing relapses, controlling antibiotic resistant bacteria and increasing the effectiveness of moderate intervention. In order to improve rational treatments of human infections, we call for a better quantification of individual disease trajectories in bacteria-immunity space.

Virulence-mediated infectiousness and activity trade-offs and their impact on transmission potential of influenza patients

Communicable diseases are often virulent, i.e. they cause morbidity symptoms in those infected. While some symptoms may be transmission-enhancing, other symptoms are likely to reduce transmission potential. For human diseases, the reduction in transmission opportunities is commonly caused by reduced activity. There is limited data regarding the potential impact of virulence on transmission potential. We performed an exploratory data analysis of 324 influenza patients at a university health centre during the 2016/2017 influenza season. We classified symptoms as infectiousness-related or morbidity-related and calculated two scores. The scores were used to explore the relationship between infectiousness, morbidity (virulence), and activity level. We found a decrease in the activity level with increasing morbidity scores. There was no consistent pattern between an activity level and an infectiousness score. We also found a positive correlation between morbidity and infectiousness scores. Overall, we find that increasing virulence leads to increased infectiousness and reduced activity, suggesting a trade-off that can impact overall transmission potential. Our findings indicate that a reduction of systemic symptoms may increase host activity without reducing infectiousness. Therefore, interventions should target both systemic- and infectiousness-related symptoms to reduce overall transmission potential. Our findings can also inform simulation models that investigate the impact of different interventions on transmission.

How are arbovirus vectors able to tolerate infection?

One of the defining features of mosquito vectors of arboviruses such as Dengue and Zika is their ability to tolerate high levels of virus proliferation without suffering significant pathology. This adaptation is central to vector competence and disease spread. The molecular mechanisms, pathways, cellular and metabolic adaptations responsible for mosquito disease tolerance are still largely unknown and may represent effective ways to control mosquito populations and prevent arboviral diseases. In this review article, we describe the key link between disease tolerance and pathogen transmission, and how vector control methods may benefit by focusing efforts on dissecting the mechanisms underlying mosquito tolerance of arboviral infections. We briefly review recent work investigating tolerance mechanisms in other insects, describe the state of the art regarding the mechanisms of disease tolerance in mosquitos, and highlight the emerging role of gut microbiota in mosquito immunity and disease tolerance.

How Individual Variation in Host Tolerance Affects Competence to Transmit Parasites

Tolerance, or the maintenance of host health or fitness at a given parasite burden, has often been studied in evolutionary and medical contexts, particularly with respect to effects on the evolution of parasite virulence and individual patient outcomes. These bodies of work have provided insight about tolerance for evolutionary phenomena (e.g., virulence) and individual health (e.g., recovering from an infection). However, due to the specific motivations of that work, few studies have considered the ecological ramifications of variation in tolerance, namely, how variation in forms of tolerance could mediate parasite movement through populations and even community-level disease dynamics. Tolerance is most commonly regarded as the relationship between host fitness and parasite burden. However, few if any studies have actually quantified host fitness, instead utilizing proxies of fitness as the response variables to be regressed against parasite burden. Here, we address how attention to the effects of parasite burden on traits that are relevant to host competence (i.e., the ability to amplify parasites to levels transmissible to other hosts/vectors) will enhance our understanding of disease dynamics in nature. We also provide several forms of guidance for how to overcome the challenges of quantifying tolerance in wild organisms.