Geographic variation in seasonality and its influence on the dynamics of an infectious disease

Seasonal changes in environmental drivers – such as temperature, rainfall, and resource availability – have the potential to shape infection dynamics through their reverberating effects on biological processes including host abundance and susceptibility to infection. However, seasonality varies geographically. We therefore expect marked differences in infection dynamics between regions with different seasonal patterns. By pairing extensive Avian Influenza Virus (AIV) surveillance data – 65 358 individual bird samples from 12 species of dabbling ducks sampled at 174 locations across North America – with quantification of seasonality using remote sensed data indicative for primary productivity (normalised differenced vegetation index, NDVI), we provide evidence that seasonal dynamics influence infection dynamics across a continent. More pronounced epidemics were seen to occur in regions experiencing a higher degree of seasonality, and epidemics of lower amplitude and longer duration occurred in regions with a more protracted and lower seasonal amplitude. These results demonstrate the potential importance of geographic variation in seasonality for explaining geographic variation in the dynamics of infectious diseases in wildlife.     

Capturing escape in infectious disease dynamics

Identifying the causes of interannual variability in disease dynamics is important for understanding and managing epidemics. Traditionally, these causes have been classified as intrinsic (e.g. immunity fluctuations) or extrinsic (e.g. climate forcing); ecologists determine the relative contributions of these factors by applying statistical models to time series of cases. Here we address the problem of isolating the drivers of pathogen dynamics that are influenced by antigenic evolution. Recent findings indicate that many pathogens escape immunity in a punctuated manner; for them, we argue that time series of cases alone will be insufficient to isolate causal drivers. We detail observations that can reveal the presence of punctuated immune escape, and which can be used in new statistical approaches to identify extrinsic and intrinsic regulators of disease.     

Types of immune response in acute infectious diseases

The author's concept on the system of self regulation of immune response is described. Four types of this response are proposed, which differ by total intensity of cytokine reaction, the development time as well as manifestation degree of non specific immunosuppression, and, most importantly, the profile of specific immune response to the antigens of the infective agent. These four types of immune response are closely linked with increased severity of clinical manifestations.     

Transient dynamics and early diagnostics in infectious disease

To date, mathematical models of the dynamics of infectious disease have consistently focused on understanding the long-term behavior of the interacting components, where the steady state solutions are paramount. However for most acute infections, the long-term behavior of the pathogen population is of little importance to the host and population health. We introduce the notion of transient pathology, where the short-term dynamics of interaction between the immune system and pathogens is the principal focus. We identify the amplifying effect of the absence of a fully operative immune system on the pathogenesis of the initial inoculum, and its implication for the acute severity of the infection. We then formalize the underlying dynamics, and derive two measures of transient pathogenicity: the peak of infection (maximum pathogenic load) and the time to peak of infection, both crucial to understanding the early dynamics of infection and its consequences for early intervention. Received: 25 January 2000 / Revised version: 30 November 2000 / Published online: 12 October 2001     

Effects of heterogeneous and clustered contact patterns on infectious disease dynamics

The spread of infectious diseases fundamentally depends on the pattern of contacts between individuals. Although studies of contact networks have shown that heterogeneity in the number of contacts and the duration of contacts can have far-reaching epidemiological consequences, models often assume that contacts are chosen at random and thereby ignore the sociological, temporal and/or spatial clustering of contacts. Here we investigate the simultaneous effects of heterogeneous and clustered contact patterns on epidemic dynamics. To model population structure, we generalize the configuration model which has a tunable degree distribution (number of contacts per node) and level of clustering (number of three cliques). To model epidemic dynamics for this class of random graph, we derive a tractable, low-dimensional system of ordinary differential equations that accounts for the effects of network structure on the course of the epidemic. We find that the interaction between clustering and the degree distribution is complex. Clustering always slows an epidemic, but simultaneously increasing clustering and the variance of the degree distribution can increase final epidemic size. We also show that bond percolation-based approximations can be highly biased if one incorrectly assumes that infectious periods are homogeneous, and the magnitude of this bias increases with the amount of clustering in the network. We apply this approach to model the high clustering of contacts within households, using contact parameters estimated from survey data of social interactions, and we identify conditions under which network models that do not account for household structure will be biased.     

Use of the internet to enhance infectious disease surveillance and outbreak investigation

Modernization of electronic communication systems to facilitate infectious disease surveillance and outbreak investigation became a priority after the 2001 anthrax attacks. However, the extent to which communicable disease investigators are using web-based information resources, e-mail notifications, or secure information exchange systems to facilitate surveillance is unknown. To address this question, we conducted a survey in 2004 of state and local communicable disease investigators responsible for infectious disease surveillance and outbreak investigation in three states. The majority (70.7%) of the 297 respondents accessed the Internet for information regarding infectious disease surveillance and outbreaks at least weekly. Most (74%) respondents who searched for information from the Centers for Disease Control and Prevention (CDC) website reported that they found what they were looking for 75-100% of the time, compared with 54% who found the information from their state health department websites 75-100% of the time. One-third of respondents read e-mail notifications regarding outbreaks under investigation in their state less frequently than monthly; 34% of those enrolled in CDC's Epidemic Information Exchange (Epi-X) read e-mail notifications of new reports less frequently than monthly. Forty-seven (18%) respondents read ProMED-mail at least monthly, while 46% indicated they had never consulted MEDLINE/PubMed. Some progress has been made in use of the Internet to facilitate communication in infectious disease surveillance and outbreak investigation. Addressing barriers to access and usability of new information systems in conjunction with training and technical support could enhance infectious disease surveillance and timely investigation of outbreaks and bioterrorism events.     

Zebrafish as a model for infectious disease and immune function

The zebrafish, Danio rerio, has come to the forefront of biomedical research as a powerful model for the study of development, neurobiology, and genetics of humans. In recent years, use of the zebrafish system has extended into studies in behaviour, immunology and toxicology, retaining the concept that it will serve as a model for human disease. As one of the most thoroughly studied teleosts, with a wealth of genetic and genomic information available, the zebrafish is now being considered as a model for pathogen studies in finfishes. Its genome is currently being sequenced and annotated, and gene microarrays and insertional mutants are commercially available. The use of gene-specific knockdown of translation through morpholino oligonucleotides is widespread. As a result, several laboratories have developed bacterial and viral disease models with the zebrafish to study immune responses to infection. Although many of the zebrafish pathogen models were developed to address human infectious disease, the results of these studies should provide important clues for the development of effective vaccines and prophylactic measures against bacterial and viral pathogens in economically important fishes. In this review, the capabilities and potential of the zebrafish model system will be discussed and an overview of information on zebrafish infectious disease models will be presented.     

Non-linear transmission rates and the dynamics of infectious disease.

This study considers how non-linearities in the transmission of microparasitic infections affect the population dynamics of host-parasite systems in which the disease is potentially lethal to the host. Non-linearities can either lead to a locally stable or unstable host-parasite equilibrium point, depending on the respective contributions of healthy and infected hosts to the functional form of the transmission rate. Analysis of the non-linear transmission model results in a revealing pair of local stability criteria. Specifically, stability requires sufficient total levels of intrinsic growth of the host population and total levels of density-dependent transmission. The most stable systems occur when increases in the density of healthy hosts result in increases in transmission efficiency, and increases in the number of infected hosts result in small decreases in transmission efficiency. These appear to be very reasonable relationships for directly transmitted microparasites.     

Modeling the adaptive immune response in HBV infection

The aim of this work is to investigate a new mathematical model that describes the interactions between Hepatitis B virus (HBV), liver cells (hepatocytes), and the adaptive immune response. The qualitative analysis of this as cytotoxic T lymphocytes (CTL) cells and the antibodies. These outcomes are (1) a disease free steady state, which its local stability is characterized as usual by R ₀ < 1, (2) and the existence of four endemic steady states when R ₀ > 1. The local stability of these steady states depends on functions of R ₀. Our study shows that although we give conditions of stability of these steady states, not all conditions are feasible. This rules out the local stability of two steady states. The conditions of stability of the two other steady states (which represent the complete failure of the adaptive immunity and the persistence of the disease) are formulated based on the domination of CTL cells response or the antibody response.     

Effects of chorionic gonadotropin on dynamics of primary immune response]

The effect of chorionic gonadotropin (CG) on primary immune response was estimated according to the level of direct and indirect plaque-forming cells (PFC) on day 5, 8 and 12 after immunization of non-castrated and ovariectomized female mice of CBA strain. It was established, that on the 5th day CG (40-200 IU) did not influence the direct PFC level in ovariectomized animals, but stimulated them in non-ovariectomized mice (40 IU). In ovariectomized animals the selective immunodepressive effect of hormone on the IgG-PFC formation processes has been revealed. The CG effect depended on the time of PFC number examination as well as on the hormone dose. In non-castrated animals, where immunomodulating CG effects are partially mediated by ovarian hormones, the injection of hormone only in the dose of 200 IU significantly lowered the number of IgM and IgG-PFC. It is suggested, that sex steroids on the late stages of PFC formation, when the processes of isotype antibody synthesis switch take place, appear to be synergists of CG immunodepressive effect.     

Modeling within-host dynamics of influenza virus infection including immune responses

Influenza virus infection remains a public health problem worldwide. The mechanisms underlying viral control during an uncomplicated influenza virus infection are not fully understood. Here, we developed a mathematical model including both innate and adaptive immune responses to study the within-host dynamics of equine influenza virus infection in horses. By comparing modeling predictions with both interferon and viral kinetic data, we examined the relative roles of target cell availability, and innate and adaptive immune responses in controlling the virus. Our results show that the rapid and substantial viral decline (about 2 to 4 logs within 1 day) after the peak can be explained by the killing of infected cells mediated by interferon activated cells, such as natural killer cells, during the innate immune response. After the viral load declines to a lower level, the loss of interferon-induced antiviral effect and an increased availability of target cells due to loss of the antiviral state can explain the observed short phase of viral plateau in which the viral level remains unchanged or even experiences a minor second peak in some animals. An adaptive immune response is needed in our model to explain the eventual viral clearance. This study provides a quantitative understanding of the biological factors that can explain the viral and interferon kinetics during a typical influenza virus infection.     

Host resource supplies influence the dynamics and outcome of infectious disease

Pathogens and their host organisms share a wide range of resourceneeds that are required to support normal metabolism and growth.Because the development of infectious disease on or within thehost involves the processes of invasion and resource consumption,competition for growth-limiting resources potentially may occurbetween pathogens and cellular or sub-cellular components ofthe host ecosystem. Examples from the plant, animal, and microbiologicalliterature provide unambiguous evidence that external resourcesupplies to the host organism can have profound effects on theoutcome of infection by a broad diversity of bacterial, fungal,metazoan, protozoan, and viral pathogens.     

A landscape for the dynamics of an immune response

Dynamic shaping of the antibody repertoire is essential for effective immunity. We describe here a novel approach for clarifying how the antibody repertoire is shaped over time for development of a specific immune response. We obtained over 500 immunoglobulin G1 clones harboring VH186.2 from the spleen, bone marrow, and microdissected individual germinal centers of (4-hydroxy-3-nitrophenyl) acetyl-immunized C57BL/6 mice at various time points postimmunization. Statistical analyses provided an index for defining clonal diversity and cluster analyses gave us a three-dimensional landscape with which clone distance was visualized with the expression level of antibodies. This landscape approach facilitated our understanding of the dynamics shaping the actual antibody repertoire, in which pre-existing naturally occurring population persisted and provided a significant impact upon the repertoire. To the established model for describing production of the antibody-forming cells, we were able to append an indispensable issue in considering the maturation of humoral immune response.     

Modeling coronavirus spike protein dynamics: implications for immunogenicity and immune escape

The ongoing COVID-19 pandemic is a global public health emergency requiring urgent development of efficacious vaccines. While concentrated research efforts have focused primarily on antibody-based vaccines that neutralize SARS-CoV-2, and several first-generation vaccines have either been approved or received emergency use authorization, it is forecasted that COVID-19 will become an endemic disease requiring updated second-generation vaccines. The SARS-CoV-2 surface spike (S) glycoprotein represents a prime target for vaccine development because antibodies that block viral attachment and entry, i.e., neutralizing antibodies, bind almost exclusively to the receptor-binding domain. Here, we develop computational models for a large subset of S proteins associated with SARS-CoV-2, implemented through coarse-grained elastic network models and normal mode analysis. We then analyze local protein domain dynamics of the S protein systems and their thermal stability to characterize structural and dynamical variability among them. These results are compared against existing experimental data and used to elucidate the impact and mechanisms of SARS-CoV-2 S protein mutations and their associated antibody binding behavior. We construct a SARS-CoV-2 antigenic map and offer predictions about the neutralization capabilities of antibody and S mutant combinations based on protein dynamic signatures. We then compare SARS-CoV-2 S protein dynamics to SARS-CoV and MERS-CoV S proteins to investigate differing antibody binding and cellular fusion mechanisms that may explain the high transmissibility of SARS-CoV-2. The outbreaks associated with SARS-CoV, MERS-CoV, and SARS-CoV-2 over the last two decades suggest that the threat presented by coronaviruses is ever-changing and long term. Our results provide insights into the dynamics-driven mechanisms of immunogenicity associated with coronavirus S proteins and present a new, to our knowledge, approach to characterize and screen potential mutant candidates for immunogen design, as well as to characterize emerging natural variants that may escape vaccine-induced antibody responses.     

Tumour-induced suppression of immune response and its correction

Immunosuppressive features of tumour cells are a major obstacle for immunotherapy of cancer. We recently noted that RENCA cells effectively interfere with the in vivo activation of RENCA-specific T cells. To unravel the underlying mechanism, we evaluated the influence of RENCA cells on a mixed-lymphocyte/ tumour reaction as well as an allogeneic mixed-lymphocyte reaction. We observed that RENCA cells were not directly immunosuppressive. Instead, they initiated deviation of an immune response in at least two independent directions: (i) expansion of a population of NK1.1+/CD3+ cells, which was accompanied by elimination of mainly CD4+ lymphocytes, and (ii) production of a leukocyte-derived inhibitory factor. Expression of the costimulatory molecule B7.1 by RENCA cells prevented induction of anergy, while expression of MHC class II molecules prevented expansion of NK1.1+ cells, which was accompanied by a significant decrease in cell death. Hence, an unimpaired response was observed only when RENCA cells expressed B7.1 plus MHC class II molecules. Thus, even if a tumour itself is not immunosuppressive, it can induce a strong deviation of the immune response. It is concluded that the first contact between elements of the immune system and the tumour cell can confer a severe bias on immunoregulatory circuits.     

Innate immune response triggers lupus-like autoimmune disease

Autoimmune disease is typically defined as an aberrant response of lymphocytes to self antigens that ultimately leads to tissue damage. Reporting in Immunity, Green et al. (2007) now show that mice lacking alpha-mannosidase II develop an autoimmune disease similar to lupus. Remarkably, this illness is precipitated by an innate immune response to altered self glycans that mimic molecular patterns found on pathogens.