Subthreshold and superthreshold coexistence of pathogen variants: the impact of host age-structure

Infections and Influencing Factors of Pathogens in Rattus norvegicus along the Zengjiang River in Guangzhou, China

Background: Rattus norvegicus can carry and transmit various zoonotic pathogens. Some studies were conducted to investigate a few zoonotic pathogens in Guangzhou, China, but no coinfections were investigated or specifically mentioned. Studies on the infections and the influencing factors of various zoonotic pathogens in R. norvegicus along the Zengjiang River in Guangzhou have not been carried out. Materials and Methods: In this study, R. norvegicus was captured in November 2020 and September 2021 along the Zengjiang River, and was tested for Bartonella spp., Leptospira spp., Orientia tsutsugamushi, Borrelia burgdorferi, Hantavirus (HV), Ehrlichia spp., and severe fever with thrombocytopenia syndrome virus (SFTSV) by the RT-PCR. Logistic regression analysis was used to determine the impact of habitat and demographic factors on the infections and coinfections of the surveyed pathogens. Results: In 119 R. norvegicus, the detection rates of Bartonella spp., Leptospira spp., O. tsutsugamushi, B. burgdorferi, and HV were 46.2%, 31.9%, 5%, 0.8%, and 18.5%, respectively. Ehrlichia spp. and SFTSV were negative. The triple coinfection rate of Bartonella spp., Leptospira spp., and HV was 11.8%. In addition, the coinfection of Bartonella spp., Leptospira spp., and B. burgdorferi was 0.8%. Dual coinfection of Bartonella spp. and Leptospira spp., Leptospira spp. and HV, Bartonella spp. and O. tsutsugamushi, Leptospira spp. and O. tsutsugamushi, and HV and O. tsutsugamushi was 9.2%, 3.4%, 1.7%, 1.7%, and 0.8%, respectively. Infections of these pathogens in R. norvegicus were found in habitats of banana plantation, grassland, and bush. Weight affected the infection of Bartonella spp., Leptospira spp., or HV in R. norvegicus. Conclusions: R. norvegicus along the Zengjiang River not only carried various potentially zoonotic pathogens but also had a variety of coinfections. Surveillance of the density and pathogens in R. norvegicus should be strengthened to reduce the incidence of relevant zoonotic diseases.

Dynamics of co-infection in fish: A review of pathogen-host interaction and clinical outcome

Co-infections can affect the transmission of a pathogen within a population and the pathogen's virulence, ultimately affecting the disease's dynamics. In addition, co-infections can potentially affect the host's immunological responses, clinical outcomes, survival, and disease control efficacy. Co-infections significantly impact fish production and can change several fish diseases' progression and severity. However, the effect of co-infection has only recently garnered limited attention in aquatic animals such as fish, and there is currently a dearth of studies on this topic. This study, therefore, presents an in-depth summary of the dynamics of co-infection in fish. This study reviewed the co-infection of fish pathogens, the interaction of pathogens and fish, clinical outcomes and impacts on fish immune responses, and fish survival. Most studies described the prevalence of co-infections in fish, with various parameters influencing their outcomes. Bacterial co-infection increased fish mortality, ulcerative dermatitis, and intestinal haemorrhage. Viral co-infection resulted in osmoregulatory effects, increased mortality and cytopathic effect (CPE). More severe histological alterations and clinical symptoms were related to the co-infection of fish than in single-infected fish. In parasitic co-infection, there was increased mortality, high kidney swelling index, and severe necrotic alterations in the kidney, liver, and spleen. In other cases, there were more severe kidney lesions, cartilage destruction and displacement. There was a dearth of information on mitigating co-infections in fish. Therefore, further studies on the mitigation strategies of co-infections in fish will provide valuable insights into this research area. Also, more research on the immunology of co-infection specific to each fish pathogen class (bacteria, viruses, fungi, and parasites) is imperative. The findings from such studies would provide valuable information on the relationship between fish immune systems and targeted responses.

Leptospirosis and Coinfection: Should We Be Concerned?

Pathogenic Leptospira is the causative agent of leptospirosis, an emerging zoonotic disease affecting animals and humans worldwide. The risk of host infection following interaction with environmental sources depends on the ability of Leptospira to persist, survive, and infect the new host to continue the transmission chain. Leptospira may coexist with other pathogens, thus providing a suitable condition for the development of other pathogens, resulting in multi-pathogen infection in humans. Therefore, it is important to better understand the dynamics of transmission by these pathogens. We conducted Boolean searches of several databases, including Google Scholar, PubMed, SciELO, and ScienceDirect, to identify relevant published data on Leptospira and coinfection with other pathogenic bacteria. We review the role of the host-microbiota in determining the synanthropic interaction of Leptospira sp. with other bacteria, thus creating a suitable condition for the leptospira to survive and persist successfully. We also discuss the biotic and abiotic factors that amplify the viability of Leptospira in the environment. The coinfection of leptospira with pathogenic bacteria has rarely been reported, potentially contributing to a lack of awareness. Therefore, the occurrence of leptospirosis coinfection may complicate diagnosis, long-lasting examination, and mistreatment that could lead to mortality. Identifying the presence of leptospirosis with other bacteria through metagenomic analysis could reveal possible coinfection. In conclusion, the occurrence of leptospirosis with other diseases should be of concern and may depend on the success of the transmission and severity of individual infections. Medical practitioners may misdiagnose the presence of multiple infections and should be made aware of and receive adequate training on appropriate treatment for leptospirosis patients. Physicians could undertake a more targeted approach for leptospirosis diagnosis by considering other symptoms caused by the coinfected bacteria; thus, more specific treatment could be given.

Coinfection dynamics of heroin transmission and HIV infection in a single population

We propose a model of a joint spread of heroin use and HIV infection. The unique disease-free equilibrium always exists and it is stable if the basic reproduction numbers of heroin use and HIV infection are both less than 1. The semi-trivial equilibrium of HIV infection (heroin use) exists if the basic reproduction number of HIV infection (heroin use) is larger than 1 and it is locally stable if and only if the invasion number of heroin use (HIV infection) is less than 1. When both semi-trivial equilibria lose their stability, a coexistence equilibrium occurs, which may not be unique. We compare the model to US data on heroin use and HIV transmission. We conclude that the two diseases in the US are in a coexistence regime. Elasticities of the invasion numbers suggest two foci for control measures: targeting the drug abuse epidemic and reducing HIV risk in drug-users.

Interplay between competitive and cooperative interactions in a three-player pathogen system

In ecological systems, heterogeneous interactions between pathogens take place simultaneously. This occurs, for instance, when two pathogens cooperate, while at the same time, multiple strains of these pathogens co-circulate and compete. Notable examples include the cooperation of human immunodeficiency virus with antibiotic-resistant and susceptible strains of tuberculosis or some respiratory infections with Streptococcus pneumoniae strains. Models focusing on competition or cooperation separately fail to describe how these concurrent interactions shape the epidemiology of such diseases. We studied this problem considering two cooperating pathogens, where one pathogen is further structured in two strains. The spreading follows a susceptible-infected-susceptible process and the strains differ in transmissibility and extent of cooperation with the other pathogen. We combined a mean-field stability analysis with stochastic simulations on networks considering both well-mixed and structured populations. We observed the emergence of a complex phase diagram, where the conditions for the less transmissible, but more cooperative strain to dominate are non-trivial, e.g. non-monotonic boundaries and bistability. Coupled with community structure, the presence of the cooperative pathogen enables the coexistence between strains by breaking the spatial symmetry and dynamically creating different ecological niches. These results shed light on ecological mechanisms that may impact the epidemiology of diseases of public health concern.

Modeling Antibiotic Use Strategies in Intensive Care Units: Comparing De-escalation and Continuation

Antimicrobial de-escalation refers to the treatment mechanism of switching from empiric antibiotics with good coverage to alternatives based on laboratory susceptibility test results, with the aim of avoiding unnecessary use of broad-spectrum antibiotics. In a previous study, we have developed multi-strain and multi-drug models in an intensive care unit setting, to evaluate the benefits and trade-offs of de-escalation in comparison with the conventional strategy called antimicrobial continuation. Our simulation results indicated that for a large portion of credible parameter combinations, de-escalation reduces the use of the empiric antibiotic but increases the probabilities of colonization and infections. In this paper, we first simplify the previous models to compare the long-term dynamical behaviors between de-escalation and continuation systems under a two-strain scenario. The analytical results coincide with our previous findings in the complex models, indicating the benefits and unintended consequences of de-escalation strategy result from the nature of this treatment mechanism, not from the complexity of the high-dimensional systems. By extending the models to three-strain scenarios, we find that de-escalation is superior than continuation in preventing outbreaks of invading strains that are resistant to empiric antibiotics. Thus decisions on antibiotic use strategies should be made specifically according to ICU conditions and intervention objectives.

Methods for deriving necessary and sufficient conditions for backward bifurcation

Backward bifurcation has significant implications for disease control. Deriving necessary and sufficient conditions for backward bifurcation is of paramount importance to understand the reasons for its occurrence and devise effective control strategies. In this paper, we review the methods that lead to necessary and sufficient conditions for backward bifurcation in infectious disease models. We review separately the methods that apply to ODEs and methods that apply to PDEs. We further propose a new method, applicable to both ODEs and PDEs. We illustrate the methods on three examples: a novel ODE model of cholera with vaccination, a PDE version of the cholera model with vaccination, and on an eight equation model of dengue, taken from the literature.

Exploring the population-level impact of MenB vaccination via modeling: Potential for serogroup replacement

Various meningococcal conjugate vaccines exist against serogroups A, C, W and Y. A new protein-based vaccine targeting serogroup B (MenB) is also now available. The potential of such vaccines to drive serogroup replacement is considered a possible public health concern when implementing nationwide routine immunization programmes. The aim of this work was to investigate if and how serogroup replacement may occur following widespread vaccination with a MenB vaccine that may protect against carriage. To that end, we built a dynamic transmission model with age and serogroup stratification, focusing on European settings where most invasive meningococcal disease (IMD) cases are caused by serogroups B and C. For illustration purposes, the model was employed in 2 such settings: UK (England and Wales) and Czech Republic. Preliminary model-based projections suggest that, under strong serogroup competition for colonization, vaccine-induced serogroup replacement may occur even with a relatively low vaccine efficacy against serogroup B carriage (e.g., 20%), with potential subsequent increase in serogroup C IMD. The magnitude and speed of the model-projected serogroup C IMD increase depend on the MenB vaccination strategy, vaccine efficacy against carriage and the extent of any potential cross-protection against other serogroups. These analyses are neither exhaustive nor definitive, and focused on simulating potential population-level trends in IMD post-vaccination, under certain assumptions. Due to present inherent limitations and uncertainties, this study has limited quantitative value and is best regarded as an explorative qualitative modeling approach, to complement and challenge the current status quo, and suggest areas where collecting additional data may be essential.

Implication of vaccination against dengue for Zika outbreak

Zika virus co-circulates with dengue in tropical and sub-tropical regions. Cases of co-infection by dengue and Zika have been reported, the implication of this co-infection for an integrated intervention program for controlling both dengue and Zika must be addressed urgently. Here, we formulate a mathematical model to describe the transmission dynamics of co-infection of dengue and Zika with particular focus on the effects of Zika outbreak by vaccination against dengue among human hosts. Our analysis determines specific conditions under which vaccination against dengue can significantly increase the Zika outbreak peak, and speed up the Zika outbreak peak timing. Our results call for further study about the co-infection to direct an integrated control to balance the benefits for dengue control and the damages of Zika outbreak.

Host age modulates within-host parasite competition

In many host populations, one of the most striking differences among hosts is their age. While parasite prevalence differences in relation to host age are well known, little is known on how host age impacts ecological and evolutionary dynamics of diseases. Using two clones of the water flea Daphnia magna and two clones of its bacterial parasite Pasteuria ramosa, we examined how host age at exposure influences within-host parasite competition and virulence. We found that multiply-exposed hosts were more susceptible to infection and suffered higher mortality than singly-exposed hosts. Hosts oldest at exposure were least often infected and vice versa. Furthermore, we found that in young multiply-exposed hosts competition was weak, allowing coexistence and transmission of both parasite clones, whereas in older multiply-exposed hosts competitive exclusion was observed. Thus, age-dependent parasite exposure and host demography (age structure) could together play an important role in mediating parasite evolution. At the individual level, our results demonstrate a previously unnoticed interaction of the host's immune system with host age, suggesting that the specificity of immune function changes as hosts mature. Therefore, evolutionary models of parasite virulence might benefit from incorporating age-dependent epidemiological parameters.

The importance of multiparasitism: examining the consequences of co-infections for human and animal health

Most parasites co-occur with other parasites, although the importance of such multiparasitism has only recently been recognised. Co-infections may result when hosts are independently infected by different parasites at the same time or when interactions among parasite species facilitate co-occurrence. Such interactions can have important repercussions on human or animal health because they can alter host susceptibility, infection duration, transmission risks, and clinical symptoms. These interactions may be synergistic or antagonistic and thus produce diverse effects in infected humans and animals. Interactions among parasites strongly influence parasite dynamics and therefore play a major role in structuring parasite populations (both within and among hosts) as well as host populations. However, several methodological challenges remain when it comes to detecting parasite interactions. The goal of this review is to summarise current knowledge on the causes and consequences of multiparasitism and to discuss the different methods and tools that researchers have developed to study the factors that lead to multiparasitism. It also identifies new research directions to pursue.

A TWO-STRAIN EPIDEMIC MODEL WITH DIFFERENTIAL SUSCEPTIBILITY AND MUTATION

A two-strain epidemic model with differential susceptibility and mutation is formulated and analyzed in this paper. The susceptible population is divided into two subgroups according to the vaccine that provides complete protection against one of the strains (strain two) but only partial against the other (strain one). The explicit formulae for the basic reproduction number and invasion reproduction number corresponding to each strain with and without mutation are derived, respectively. It is shown that there exist exclusive equilibria and coexistence equilibria, even if the reproduction number is below one. The stability of the disease-free equilibrium, strain dominance with or without mutation are investigated. The persistence of the disease is also briefly discussed. Numerical simulations are presented to illustrate the results.

Chemostats and epidemics: competition for nutrients/hosts

In a chemostat, several species compete for the same nutrient, while in an epidemic, several strains of the same pathogen may compete for the same susceptible hosts. As winner, chemostat models predict the species with the lowest break-even concentration, while epidemic models predict the strain with the largest basic reproduction number. We show that these predictions amount to the same if the per capita functional responses of consumer species to the nutrient concentration or of infective individuals to the density of susceptibles are proportional to each other but that they are different if the functional responses are nonproportional. In the second case, the correct prediction is given by the break-even concentrations. In the case of nonproportional functional responses, we add a class for which the prediction does not only rely on local stability and instability of one-species (strain) equilibria but on the global outcome of the competition. We also review some results for nonautonomous models.

COEXISTENCE OF THE STRAINS INDUCED BY MUTATION

In this paper, we propose a two strain epidemic model with single host population. It is assumed that strain one can mutate into strain two. Also latent-stage progression age and mutation are incorporated into the model. Stability of equilibria (including the disease free equilibrium, dominant equilibria and the coexistence equilibrium) is investigated and it is found that they are locally stable under suitable and biological feasible constraints. Results indicate that the competition exclusion and coexistence of the two strains are possible depending on the mutation. Numerical simulations are also performed to illustrate these results.

How hepatitis D virus can hinder the control of hepatitis B virus

Background

Hepatitis D (or hepatitis delta) virus is a defective virus that relies on hepatitis B virus (HBV) for transmission; infection with hepatitis D can occur only as coinfection with HBV or superinfection of an existing HBV infection. Because of the bond between the two viruses, control measures for HBV may have also affected the spread of hepatitis D, as evidenced by the decline of hepatitis D in recent years. Since the presence of hepatitis D is associated with suppressed HBV replication and possibly infectivity, it is reasonable to speculate that hepatitis D may facilitate the control of HBV.

Methodology and Principal Findings

We introduced a mathematical model for the transmission of HBV and hepatitis D, where individuals with dual HBV and hepatitis D infection transmit both viruses. We calculated the reproduction numbers of single HBV infections and dual HBV and hepatitis D infections and examined the endemic prevalences of the two viruses. The results show that hepatitis D virus modulates not only the severity of the HBV epidemic, but also the impact of interventions for HBV. Surprisingly we find that the presence of hepatitis D virus may hamper the eradication of HBV. Interventions that aim to reduce the basic reproduction number of HBV below one may not be sufficient to eradicate the virus, as control of HBV depends also on the reproduction numbers of dual infections.

Conclusions and Significance

For populations where hepatitis D is endemic, plans for control programs ignoring the presence of hepatitis D may underestimate the HBV epidemic and produce overoptimistic results. The current HBV surveillance should be augmented with monitoring of hepatitis D, in order to improve accuracy of the monitoring and the efficacy of control measures.

A non-autonomous multi-strain SIS epidemic model

In this paper we consider a non-autonomous multi-strain SIS epidemic model with periodic coefficients. Reproduction numbers and invasion reproduction numbers are derived which agree well with their counterparts usually derived from autonomous epidemic models. With conditions on these reproduction numbers typical results are obtained, such as the local and global stability of the disease-free equilibrium. Existence and uniqueness of a single-strain periodic solution is established. Based on conditions on the invasion reproduction numbers, local stability of the single-strain periodic solution is shown. In a two-strain version of the model, conditions for uniform strong persistence are derived, and coexistence of the two strains is established. Coexistence, however, does not occur if the transmission rates of the different strains are linearly dependent.

Latent coinfection and the maintenance of strain diversity

Technologies for strain differentiation and typing have made it possible to detect genetic diversity of pathogens, both within individual hosts and within communities. Coinfection of a host by more than one pathogen strain may affect the relative frequency of these strains at the population level through complex within- and between-host interactions; in infectious diseases that have a long latent period, interstrain competition during latency is likely to play an important role in disease dynamics. We show that SEIR models that include a class of latently coinfected individuals can have markedly different long-term dynamics than models without coinfection, and that coinfection can greatly facilitate the stable coexistence of strains. We demonstrate these dynamics using a model relevant to tuberculosis in which people may experience latent coinfection with both drug sensitive and drug resistant strains. Using this model, we show that the existence of a latent coinfected state allows the possibility that disease control interventions that target latency may facilitate the emergence of drug resistance.