Between-host Transmission Research Articles

Challenges and opportunities for plant viruses under a climate change scenario.

There is an increasing societal awareness on the enormous threat that climate change may pose for human, animal and plant welfare. Although direct effects due to exposure to heat, drought or elevated greenhouse gasses seem to be progressively more obvious, indirect effects remain debatable. A relevant aspect to be clarified relates to the relationship between altered environmental conditions and pathogen-induced diseases. In the particular case of plant viruses, it is still unclear whether climate change will primarily represent an opportunity for the emergence of new infections in previously uncolonized areas and hosts, or if it will mostly be a strong constrain reducing the impact of plant virus diseases and challenging the pathogen's adaptive capacity. This review focuses on current knowledge on the relationship between climate change and the outcome plant-virus interactions. We summarize work done on how this relationship modulates plant virus pathogenicity, between-host transmission (which include the triple interaction plant-virus-vector), ecology, evolution and management of the epidemics they cause. Considering these studies, we propose avenues for future research on this subject.

Daily rhythms in gene expression of the human parasite Schistosoma mansoni

BackgroundThe consequences of the earth’s daily rotation have led to 24-h biological rhythms in most organisms. Even some parasites are known to have daily rhythms, which, when in synchrony with host rhythms, can optimise their fitness. Understanding these rhythms may enable the development of control strategies that take advantage of rhythmic vulnerabilities. Recent work on protozoan parasites has revealed 24-h rhythms in gene expression, drug sensitivity and the presence of an intrinsic circadian clock; however, similar studies on metazoan parasites are lacking. To address this, we investigated if a metazoan parasite has daily molecular oscillations, whether they reveal how these longer-lived organisms can survive host daily cycles over a lifespan of many years and if animal circadian clock genes are present and rhythmic. We addressed these questions using the human blood fluke Schistosoma mansoni that lives in the vasculature for decades and causes the tropical disease schistosomiasis.ResultsUsing round-the-clock transcriptomics of male and female adult worms collected from experimentally infected mice, we discovered that ~ 2% of its genes followed a daily pattern of expression. Rhythmic processes included a stress response during the host’s active phase and a ‘peak in metabolic activity’ during the host’s resting phase. Transcriptional profiles in the female reproductive system were mirrored by daily patterns in egg laying (eggs are the main drivers of the host pathology). Genes cycling with the highest amplitudes include predicted drug targets and a vaccine candidate. These 24-h rhythms may be driven by host rhythms and/or generated by a circadian clock; however, orthologs of core clock genes are missing and secondary clock genes show no 24-h rhythmicity.ConclusionsThere are daily rhythms in the transcriptomes of adult S. mansoni, but they appear less pronounced than in other organisms. The rhythms reveal temporally compartmentalised internal processes and host interactions relevant to within-host survival and between-host transmission. Our findings suggest that if these daily rhythms are generated by an intrinsic circadian clock then the oscillatory mechanism must be distinct from that in other animals. We have shown which transcripts oscillate at this temporal scale and this will benefit the development and delivery of treatments against schistosomiasis.

Decomposing the sources of SARS-CoV-2 fitness variation in the United States.

The fitness of a pathogen is a composite phenotype determined by many different factors influencing growth rates both within and between hosts. Determining what factors shape fitness at the host population-level is especially challenging because both intrinsic factors like pathogen genetics and extrinsic factors such as host behavior influence between-host transmission potential. This challenge has been highlighted by controversy surrounding the population-level fitness effects of mutations in the SARS-CoV-2 genome and their relative importance when compared against non-genetic factors shaping transmission dynamics. Building upon phylodynamic birth–death models, we develop a new framework to learn how hundreds of genetic and non-genetic factors have shaped the fitness of SARS-CoV-2. We estimate the fitness effects of all amino acid variants and several structural variants that have circulated in the United States between February 2020 and March 2021 from viral phylogenies. We also estimate how much fitness variation among pathogen lineages is attributable to genetic versus non-genetic factors such as spatial heterogeneity in transmission rates. Before September 2020, most fitness variation between lineages can be explained by background spatial heterogeneity in transmission rates across geographic regions. Starting in late 2020, genetic variation in fitness increased dramatically with the emergence of several new lineages including B.1.1.7, B.1.427, B.1.429 and B.1.526. Our analysis also indicates that genetic variants in less well-explored genomic regions outside of Spike may be contributing significantly to overall fitness variation in the viral population.

Quantifying rapid bacterial evolution and transmission within the mouse intestine

Due to limitations on high-resolution strain tracking, selection dynamics during gut microbiota colonization and transmission between hosts remain mostly mysterious. Here, we introduced hundreds of barcoded Escherichiacoli strains into germ-free mice and quantified strain-level dynamics and metagenomic changes. Mutations in genes involved in motility and metabolite utilization are reproducibly selected within days. Even with rapid selection, coprophagy enforced similar barcode distributions across co-housed mice. Whole-genome sequencing of hundreds of isolates revealed linked alleles that demonstrate between-host transmission. A population-genetics model predicts substantial fitness advantages for certain mutants and that migration accounted for ∼10% of the resident microbiota each day. Treatment with ciprofloxacin suggests interplay between selection and transmission. While initial colonization was mostly uniform, in two mice a bottleneck reduced diversity and selected for ciprofloxacin resistance in the absence of drug. These findings highlight the interplay between environmental transmission and rapid, deterministic selection during evolution of the intestinal microbiota.

Plasmodium vivax From Duffy-Negative and Duffy-Positive Individuals Share Similar Gene Pools in East Africa.

Plasmodium vivax malaria was thought to be rare in Africa, but an increasing number of P. vivax cases reported across Africa and in Duffy-negative individuals challenges this dogma. The genetic characteristics of P. vivax in Duffy-negative infections, the transmission of P. vivax in East Africa, and the impact of environments on transmission remain largely unknown. This study examined genetic and transmission features of P. vivax from 107 Duffy-negative and 305 Duffy-positive individuals in Ethiopia and Sudan. No clear genetic differentiation was found in P. vivax between the 2 Duffy groups, indicating between-host transmission. P. vivax from Ethiopia and Sudan showed similar genetic clusters, except samples from Khartoum, possibly due to distance and road density that inhibited parasite gene flow. This study is the first to show that P. vivax can transmit to and from Duffy-negative individuals and provides critical insights into the spread of P. vivax in sub-Saharan Africa.

Antibiotic Treatment, Duration of Infectiousness, and Disease Transmission

By curing infectious individuals, antibiotic therapy must sometimes limit the spread of contagious disease among hosts. But suppose that a diseased host stops transmitting infection due either to antibiotic cure or to non-therapeutic removal (e.g., isolation or mortality). An antibiotic`s suppression of within-host pathogen growth increases the likelihood of curing a single infection and may also reduce the probability of non-therapeutic removal. If antibiotic treatment relaxes the total rate of infection removal sufficiently to extend the average duration of infectiousness, between-host transmission can increase. That is, under some conditions, curing individuals with antibiotics can impact public health negatively (more new infections). To explore this counter-intuitive, but plausible effect, this paper assumes that a deterministic within-host dynamics drives the infectious host's time-dependent probability of pathogen transmission, as well as the probabilistic duration of the infectious period. At the within-host scale, the model varies (1) inoculum size, (2) bacterial self-regulation, (3) the time between infection and initiation of therapy, and (4) antibiotic efficacy. At the between-host scale the model varies (5) the size of groups randomly encountered in the infectious host’s environment. Results identify conditions where an antibiotic can increase duration of a host`s infectiousness, and consequently increase the expected number of new infections. At lower antibiotic efficacy, therapy might convert a rare, serious bacterial disease into a common, but treatable infection.

A REACTION-DIFFUSION MODEL FOR NESTED WITHIN-HOST AND BETWEEN-HOST DYNAMICS IN AN ENVIRONMENTALLY-DRIVEN INFECTIOUS DISEASE

<abstract> A reaction-diffusion model for nested within-host and between-host dynamics in an environmentally-driven infectious disease is proposed. The model is composed of the within-host virus infectious fast time model of ordinary differential equations and the between-host disease transmission slow time model of reaction-diffusion equations. The isolated fast model has been investigated in previous literature, and the main results are summarized. For the isolated slow model, the well-posedness of solutions, and the basic reproduction number $ R_{b} $ are obtained. When $ R_{b}\leq1 $, the model only has the disease-free equilibrium which is globally asymptotically stable, and when $ R_{b}&gt;1 $ the model has a unique endemic equilibrium which is globally asymptotically stable. For the nested slow model, the positivity and boundedness of solutions, the basic reproduction number $ R_{c} $ and the existence of equilibrium are firstly obtained. Particularly, the nested slow model can exist two positive equilibrium when $ R_{c}&lt;1 $ and a unique endemic equilibrium when $ R_{c}&gt;1 $. When $ R_{c}&lt;1 $ the disease-free equilibrium is locally asymptotically stable, and when $ R_{c}&gt;1 $ and an additional condition is satisfied the unique endemic equilibrium is locally asymptotically stable. When there are two positive equilibria, then a positive equilibria is locally asymptotically stable under an additional condition and the other one is unstable, which implies that the nested slow model occurs the backward bifurcation at $ R_c = 1 $. Lastly, numerical examples are given to verify the main conclusions. The research shows that the nested slow model has more complex dynamical behavior than the corresponding isolated slow model. </abstract>

Identifying likely transmissions in Mycobacterium bovis infected populations of cattle and badgers using the Kolmogorov Forward Equations

Established methods for whole-genome-sequencing (WGS) technology allow for the detection of single-nucleotide polymorphisms (SNPs) in the pathogen genomes sourced from host samples. The information obtained can be used to track the pathogen’s evolution in time and potentially identify ‘who-infected-whom’ with unprecedented accuracy. Successful methods include ‘phylodynamic approaches’ that integrate evolutionary and epidemiological data. However, they are typically computationally intensive, require extensive data, and are best applied when there is a strong molecular clock signal and substantial pathogen diversity. To determine how much transmission information can be inferred when pathogen genetic diversity is low and metadata limited, we propose an analytical approach that combines pathogen WGS data and sampling times from infected hosts. It accounts for ‘between-scale’ processes, in particular within-host pathogen evolution and between-host transmission. We applied this to a well-characterised population with an endemic Mycobacterium bovis (the causative agent of bovine/zoonotic tuberculosis, bTB) infection. Our results show that, even with such limited data and low diversity, the computation of the transmission probability between host pairs can help discriminate between likely and unlikely infection pathways and therefore help to identify potential transmission networks. However, the method can be sensitive to assumptions about within-host evolution.

Patch dynamics modeling framework from pathogens' perspective: Unified and standardized approach for complicated epidemic systems.

Mathematical models are powerful tools to investigate, simulate, and evaluate potential interventions for infectious diseases dynamics. Much effort has focused on the Susceptible-Infected-Recovered (SIR)-type compartment models. These models consider host populations and measure change of each compartment. In this study, we propose an alternative patch dynamic modeling framework from pathogens’ perspective. Each patch, the basic module of this modeling framework, has four standard mechanisms of pathogen population size change: birth (replication), death, inflow, and outflow. This framework naturally distinguishes between-host transmission process (inflow and outflow) and within-host infection process (replication) during the entire transmission-infection cycle. We demonstrate that the SIR-type model is actually a special cross-sectional and discretized case of our patch dynamics model in pathogens’ viewpoint. In addition, this patch dynamics modeling framework is also an agent-based model from hosts’ perspective by incorporating individual host’s specific traits. We provide an operational standard to formulate this modular-designed patch dynamics model. Model parameterization is feasible with a wide range of sources, including genomics data, surveillance data, electronic health record, and from other emerging technologies such as multiomics. We then provide two proof-of-concept case studies to tackle some of the existing challenges of SIR-type models: sexually transmitted disease and healthcare acquired infections. This patch dynamics modeling framework not only provides theoretical explanations to known phenomena, but also generates novel insights of disease dynamics from a more holistic viewpoint. It is also able to simulate and handle more complicated scenarios across biological scales such as the current COVID-19 pandemic.

Molecular causes of an evolutionary shift along the parasitism–mutualism continuum in a bacterial symbiont

Symbiosis with microbes is a ubiquitous phenomenon with a massive impact on all living organisms, shaping the world around us today. Theoretical and experimental studies show that vertical transmission of symbionts leads to the evolution of mutualistic traits, whereas horizontal transmission facilitates the emergence of parasitic features. However, these studies focused on phenotypic data, and we know little about underlying molecular changes at the genomic level. Here, we combined an experimental evolution approach with infection assays, genome resequencing, and global gene expression analysis to study the effect of transmission mode on an obligate intracellular bacterial symbiont. We show that a dramatic shift in the frequency of genetic variants, coupled with major changes in gene expression, allow the symbiont to alter its position in the parasitism-mutualism continuum depending on the mode of between-host transmission. We found that increased parasitism in horizontally transmitted chlamydiae residing in amoebae was a result of processes occurring at the infectious stage of the symbiont's developmental cycle. Specifically, genes involved in energy production required for extracellular survival and the type III secretion system-the symbiont's primary virulence mechanism-were significantly up-regulated. Our results identify the genomic and transcriptional dynamics sufficient to favor parasitic or mutualistic strategies.

Host age alters disease life history. A case study in zooplankton and a castrating pathogen

Host age alters disease life history. A case study in zooplankton and a castrating pathogen

An age-structured model for coupling within-host and between-host dynamics in environmentally-driven infectious diseases.

In this paper, an age-structured epidemic model for coupling within-host and between-host dynamics in environmentally-driven infectious diseases is investigated. The model is described by a mixed system of ordinary and partial differential equations which is constituted by the within-host virus infectious fast time ordinary system and the between-host disease transmission slow time age-structured system. The isolated fast system has been investigated in previous literatures, and the main results are introduced. For the isolated slow system, the basic reproduction number Rb0, the positivity and ultimate boundedness of solutions are obtained, the existence of equilibria, the local stability of equilibria, and the global stability of disease-free equilibrium are established. We see that when Rb0 ≤ 1 the system only has the disease-free equilibrium which is globally asymptotically stable, and when Rb0 > 1 the system has a unique endemic equilibrium which is local asymptotically stable. With regard to the coupled slow system, the basic reproduction number Rb, the positivity and boundedness of solutions and the existence of equilibria are firstly obtained. Particularly, the coupled slow system can exist two positive equilibria when Rb < 1 and a unique endemic equilibrium when Rb > 1. When Rb < 1 the disease-free equilibrium is local asymptotically stable, and when Rb > 1 and an additional condition is satisfied the unique endemic equilibrium is local asymptotically stable. When there exist two positive equilibria, under an additional condition the local asymptotic stability of a positive equilibrium and the instability of other positive equilibrium also are established. The numerical examples show that the additional condition may be removed. The research shows that the coupled slow age-structured system has more complex dynamical behavior than the corresponding isolated slow system.

Declining trend in HIV new infections in Guangxi, China: insights from linking reported HIV/AIDS cases with CD4-at-diagnosis data

BackgroundThe Guangxi Zhuang Autonomous Region bears a relatively high burden of HIV/AIDS infection. The number of accumulatively reported HIV/AIDS cases in Guangxi is the third highest among 31 provinces or Autonomous Region from 2004 to 2007, changed to the second highest between 2011 and 2013, then returned to the third highest again after 2014. We aim to estimate the new infections and evaluate the real-time HIV epidemic in Guangxi, China, in order to reveal the rule of HIV transmission.MethodsFirstly, the number of annually reported HIV and AIDS cases, as well as the number of cases linked with CD4 data are extracted from the HIV/AIDS information system in China. Secondly, two CD4-staged models are formulated by linking the with-host information on CD4 level to between-host transmission and surveillance data. Thirdly, new HIV infections, diagnosis rates and undiagnosed infections over time are estimated by using Bayesian method and Maximum Likelihood Estimation method.ResultsThe data reveal that the newly reported cases have been decreasing since 2011, while lots of cases are identified at late CD4 stage. The data fitted results indicate that both models can describe the trend of the epidemic well. The estimation results show that the new and undiagnosed infections began to decrease from the period2006 - 2008. However, the diagnosis probabilities/rates keep at a very low level, and there are still a large number of infections undiagnosed, most of which have a large probability to be identified at late CD4 stage.ConclusionsOur findings suggest that HIV/AIDS epidemic in Guangxi has been controlled to a certain extent, while the diagnosis rate still needs to be improved. More attentions should be paid to identify infections at their early CD4 stages. Meanwhile, comprehensive intervention measures should be continually strengthened in avoid of the rebound of new infections.

Modeling mitigation of influenza epidemics by baloxavir

Influenza viruses annually kill 290,000–650,000 people worldwide. Antivirals can reduce death tolls. Baloxavir, the recently approved influenza antiviral, inhibits initiation of viral mRNA synthesis, whereas oseltamivir, an older drug, inhibits release of virus progeny. Baloxavir blocks virus replication more rapidly and completely than oseltamivir, reducing the duration of infectiousness. Hence, early baloxavir treatment may indirectly prevent transmission. Here, we estimate impacts of ramping up and accelerating baloxavir treatment on population-level incidence using a new model that links viral load dynamics from clinical trial data to between-host transmission. We estimate that ~22 million infections and >6,000 deaths would have been averted in the 2017–2018 epidemic season by administering baloxavir to 30% of infected cases within 48 h after symptom onset. Treatment within 24 h would almost double the impact. Consequently, scaling up early baloxavir treatment would substantially reduce influenza morbidity and mortality every year. The development of antivirals against the SARS-CoV2 virus that function like baloxavir might similarly curtail transmission and save lives.

Global analysis of an environmental disease transmission model linking within-host and between-host dynamics

In this paper, a multi-scale mathematical model for environmentally transmitted diseases is proposed which couples the pathogen-immune interaction inside the human body with the disease transmission at the population level. The model is based on the nested approach that incorporates the infection-age-structured immunological dynamics into an epidemiological system structured by the chronological time, the infection age and the vaccination age. We conduct detailed analysis for both the within-host and between-host disease dynamics. Particularly, we derive the basic reproduction number R0 for the between-host model and prove the uniform persistence of the system. Furthermore, using carefully constructed Lyapunov functions, we establish threshold-type results regarding the global dynamics of the between-host system: the disease-free equilibrium is globally asymptotically stable when R0 < 1, and the endemic equilibrium is globally asymptotically stable when R0 > 1. We explore the connection between the within-host and between-host dynamics through both mathematical analysis and numerical simulation. We show that the pathogen load and immune strength at the individual level contribute to the disease transmission and spread at the population level. We also find that, although the between-host transmission risk correlates positively with the within-host pathogen load, there is no simple monotonic relationship between the disease prevalence and the individual pathogen load.

AN IMMUNO-EPIDEMIOLOGICAL VECTOR–HOST MODEL WITH WITHIN-VECTOR VIRAL KINETICS

A current challenge for disease modeling and public health is understanding pathogen dynamics across scales since their ecology and evolution ultimately operate on several coupled scales. This is particularly true for vector-borne diseases, where within-vector, within-host, and between vector–host populations all play crucial roles in diversity and distribution of the pathogen. Despite recent modeling efforts to determine the effect of within-host virus-immune response dynamics on between-host transmission, the role of within-vector viral dynamics on disease spread is overlooked. Here, we formulate an age-since-infection-structured epidemic model coupled to nonlinear ordinary differential equations describing within-host immune-virus dynamics and within-vector viral kinetics, with feedbacks across these scales. We first define the within-host viral-immune response and within-vector viral kinetics-dependent basic reproduction number [Formula: see text] Then we prove that whenever [Formula: see text] the disease-free equilibrium is locally asymptotically stable, and under certain biologically interpretable conditions, globally asymptotically stable. Otherwise, if [Formula: see text] it is unstable and the system has a unique positive endemic equilibrium. In the special case of constant vector to host inoculum size, we show the positive equilibrium is locally asymptotically stable and the disease is weakly uniformly persistent. Furthermore, numerical results suggest that within-vector-viral kinetics and dynamic inoculum size may play a substantial role in epidemics. Finally, we address how the model can be utilized to better predict the success of control strategies such as vaccination and drug treatment.

Analysis of a multiscale HIV-1 model coupling within-host viral dynamics and between-host transmission dynamics.

There are many challenges to constitute the linkage from the macroscale to the microscale and analyze the multiscale model. We proposed a bidirectional coupling model with standard incidence which includes the interaction of between-host transmission dynamics and within-host viral dynamics, and investigated the dynamic behaviors of the multiscale system on two time-scales. We found that the multiscale system exhibits more complex dynamics including backward bifurcation, which means that the usual thresholds for infection control or virus elimination obtained from the epidemiological model or virus dynamic model may not act as threshold parameter under a certain condition. There may be multiple epidemic equilibriums, one of which is stable, although the basic reproduction number is less than 1. We numerically examine the synergistic impact between the macro and micro dynamics. In particular, increasing the drug efficacy can decrease the prevalence of disease. The contact rate may affect the number and size of equilibria of viral dynamics model by inducing the occurrence of backward bifurcation. The finding suggests that the effective control measures may include both the reduction in contact rate or transmission rate at the population level and the increase in drug efficacy at the individual level, and using these control measures together can effectively control the diseases.

Quantifying between-Host Transmission in Influenza Virus Infections

The error-prone replication and life cycle of influenza virus generate a diverse set of genetic variants. Transmission between hosts strictly limits both the number of virus particles and the genetic diversity of virus variants that reach a new host and establish an infection. This sharp reduction in the virus population at transmission--the transmission bottleneck--is significant to the evolution of influenza virus and to its epidemic and pandemic potential. This review describes transmission bottlenecks and their effect on the diversity and evolution of influenza virus. It also reviews the methods for calculating and predicting bottleneck sizes and highlights the host and viral determinants of influenza transmissibility.

Multi-scale modeling of cholera dynamics in a spatially heterogeneous environment.

We propose a multi-group, multi-scale mathematical model to investigate the betweenhost and within-host dynamics of cholera. At the between-host level, we divide the total population into a number of host groups with different characteristics representing spatial heterogeneity. Our model incorporates the dual transmission pathways that include both the environment-to-human and human-to-human transmission routes. At the within-host level, our model describes the interaction among the pathogenic bacteria, viruses, and host immune response. For each host group, we couple the between-host disease transmission and within-host pathogen dynamics at different time scales. Our study thus integrates multi-scale modeling and multi-group modeling into one single framework. We describe the general modeling framework and demonstrate it through two specific and biologically important cases. We conduct detailed analysis for each case and obtain threshold results regarding the multi-scale dynamics of cholera in a spatially heterogeneous environment. In particular, we find that the between-host reproduction number is shaped by the collection of the disease risk factors from all the individual host groups. Our findings highlight the importance of a whole-population approach for cholera prevention and intervention.

Endemicity and prevalence of multipartite viruses under heterogeneous between-host transmission.

Multipartite viruses replicate through a puzzling evolutionary strategy. Their genome is segmented into two or more parts, and encapsidated in separate particles that appear to propagate independently. Completing the replication cycle, however, requires the full genome, so that a systemic infection of a host requires the concurrent presence of several particles. This represents an apparent evolutionary drawback of multipartitism, while its advantages remain unclear. A transition from monopartite to multipartite viral forms has been described in vitro under conditions of high multiplicity of infection, suggesting that cooperation between defective mutants is a plausible evolutionary pathway towards multipartitism. However, it is unknown how the putative advantages that multipartitism might enjoy at the microscopic level affect its epidemiology, or if an explicit advantange is needed to explain its ecological persistence. In order to disentangle which mechanisms might contribute to the rise and fixation of multipartitism, we here investigate the interaction between viral spreading dynamics and host population structure. We set up a compartmental model of the spread of a virus in its different forms and explore its epidemiology using both analytical and numerical techniques. We uncover that the impact of host contact structure on spreading dynamics entails a rich phenomenology of ecological relationships that includes cooperation, competition, and commensality. Furthermore, we find out that multipartitism might rise to fixation even in the absence of explicit microscopic advantages. Multipartitism allows the virus to colonize environments that could not be invaded by the monopartite form, while homogeneous contacts between hosts facilitate its spread. We conjecture that these features might have led to an increase in the diversity and prevalence of multipartite viral forms concomitantly with the expansion of agricultural practices.