2,070 research outputs found

    The influence of biological rhythms on host–parasite interactions

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    Biological rhythms, from circadian control of cellular processes to annual cycles in life history, are a main structural element of biology. Biological rhythms are considered adaptive because they enable organisms to partition activities to cope with, and take advantage of, predictable fluctuations in environmental conditions. A flourishing area of immunology is uncovering rhythms in the immune system of animals, including humans. Given the temporal structure of immunity, and rhythms in parasite activity and disease incidence, we propose that the intersection of chronobiology, disease ecology, and evolutionary biology holds the key to understanding host–parasite interactions. Here, we review host–parasite interactions while explicitly considering biological rhythms, and propose that rhythms: influence within-host infection dynamics and transmission between hosts, might account for diel and annual periodicity in host–parasite systems, and can lead to a host–parasite arms race in the temporal domain

    Application of Species Distribution Modeling for Avian Influenza surveillance in the United States considering the North America Migratory Flyways.

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    Highly Pathogenic Avian Influenza (HPAI) has recently (2014-2015) re-emerged in the United States (US) causing the largest outbreak in US history with 232 outbreaks and an estimated economic impact of $950 million. This study proposes to use suitability maps for Low Pathogenic Avian Influenza (LPAI) to identify areas at high risk for HPAI outbreaks. LPAI suitability maps were based on wild bird demographics, LPAI surveillance, and poultry density in combination with environmental, climatic, and socio-economic risk factors. Species distribution modeling was used to produce high-resolution (cell size: 500m x 500m) maps for Avian Influenza (AI) suitability in each of the four North American migratory flyways (NAMF). Results reveal that AI suitability is heterogeneously distributed throughout the US with higher suitability in specific zones of the Midwest and coastal areas. The resultant suitability maps adequately predicted most of the HPAI outbreak areas during the 2014-2015 epidemic in the US (i.e. 89% of HPAI outbreaks were located in areas identified as highly suitable for LPAI). Results are potentially useful for poultry producers and stakeholders in designing risk-based surveillance, outreach and intervention strategies to better prevent and control future HPAI outbreaks in the US

    A Simple Stochastic Model with Environmental Transmission Explains Multi-Year Periodicity in Outbreaks of Avian Flu

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    Avian influenza virus reveals persistent and recurrent outbreaks in North American wild waterfowl, and exhibits major outbreaks at 2–8 years intervals in duck populations. The standard susceptible-infected- recovered (SIR) framework, which includes seasonal migration and reproduction, but lacks environmental transmission, is unable to reproduce the multi-periodic patterns of avian influenza epidemics. In this paper, we argue that a fully stochastic theory based on environmental transmission provides a simple, plausible explanation for the phenomenon of multi-year periodic outbreaks of avian flu. Our theory predicts complex fluctuations with a dominant period of 2 to 8 years which essentially depends on the intensity of environmental transmission. A wavelet analysis of the observed data supports this prediction. Furthermore, using master equations and van Kampen system-size expansion techniques, we provide an analytical expression for the spectrum of stochastic fluctuations, revealing how the outbreak period varies with the environmental transmission

    The Role of Environmental Transmission in Recurrent Avian Influenza Epidemics

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    Avian influenza virus (AIV) persists in North American wild waterfowl, exhibiting major outbreaks every 2–4 years. Attempts to explain the patterns of periodicity and persistence using simple direct transmission models are unsuccessful. Motivated by empirical evidence, we examine the contribution of an overlooked AIV transmission mode: environmental transmission. It is known that infectious birds shed large concentrations of virions in the environment, where virions may persist for a long time. We thus propose that, in addition to direct fecal/oral transmission, birds may become infected by ingesting virions that have long persisted in the environment. We design a new host–pathogen model that combines within-season transmission dynamics, between-season migration and reproduction, and environmental variation. Analysis of the model yields three major results. First, environmental transmission provides a persistence mechanism within small communities where epidemics cannot be sustained by direct transmission only (i.e., communities smaller than the critical community size). Second, environmental transmission offers a parsimonious explanation of the 2–4 year periodicity of avian influenza epidemics. Third, very low levels of environmental transmission (i.e., few cases per year) are sufficient for avian influenza to persist in populations where it would otherwise vanish

    From regional pulse vaccination to global disease eradication: insights from a mathematical model of Poliomyelitis

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    Mass-vaccination campaigns are an important strategy in the global fight against poliomyelitis and measles. The large-scale logistics required for these mass immunisation campaigns magnifies the need for research into the effectiveness and optimal deployment of pulse vaccination. In order to better understand this control strategy, we propose a mathematical model accounting for the disease dynamics in connected regions, incorporating seasonality, environmental reservoirs and independent periodic pulse vaccination schedules in each region. The effective reproduction number, ReR_e, is defined and proved to be a global threshold for persistence of the disease. Analytical and numerical calculations show the importance of synchronising the pulse vaccinations in connected regions and the timing of the pulses with respect to the pathogen circulation seasonality. Our results indicate that it may be crucial for mass-vaccination programs, such as national immunisation days, to be synchronised across different regions. In addition, simulations show that a migration imbalance can increase ReR_e and alter how pulse vaccination should be optimally distributed among the patches, similar to results found with constant-rate vaccination. Furthermore, contrary to the case of constant-rate vaccination, the fraction of environmental transmission affects the value of ReR_e when pulse vaccination is present.Comment: Added section 6.1, made other revisions, changed titl

    Presence of Avian Influenza Viruses in Waterfowl and Wetlands during Summer 2010 in California: Are Resident Birds a Potential Reservoir?

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    Although wild waterfowl are the main reservoir for low pathogenic avian influenza viruses (LPAIv), the environment plays a critical role for the circulation and persistence of AIv. LPAIv may persist for extended periods in cold environments, suggesting that waterfowl breeding areas in the northern hemisphere may be an important reservoir for AIv in contrast to the warmer southern wintering areas. We evaluated whether southern wetlands, with relatively small populations (thousands) of resident waterfowl, maintain AIv in the summer, prior to the arrival of millions of migratory birds. We collected water and fecal samples at ten wetlands in two regions (Yolo Bypass and Sacramento Valley) of the California Central Valley during three bi-weekly intervals beginning in late July, 2010. We detected AIv in 29/367 fecal samples (7.9%) and 12/597 water samples (2.0%) by matrix real time Reverse Transcription Polymerase Chain Reaction (rRT-PCR). We isolated two H3N8, two H2N3, and one H4N8 among rRT-PCR positive fecal samples but no live virus from water samples. Detection of AIv RNA in fecal samples was higher from wetlands in the Sacramento Valley (11.9%) than in the Yolo Bypass (0.0%), but no difference was found for water samples (2.7 vs. 1.7%, respectively). Our study showed that low densities of hosts and unfavorable environmental conditions did not prevent LPAIv circulation during summer in California wetlands. Our findings justify further investigations to understand AIv dynamics in resident waterfowl populations, compare AIv subtypes between migratory and resident waterfowl, and assess the importance of local AIv as a source of infection for migratory birds

    Avian influenza infection dynamics under variable climatic conditions, viral prevalence is rainfall driven in waterfowl from temperate, south-east Australia

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    Understanding Avian Influenza Virus (AIV) infection dynamics in wildlife is crucial because of possible virus spill over to livestock and humans. Studies from the northern hemisphere have suggested several ecological and environmental drivers of AIV prevalence in wild birds. To determine if the same drivers apply in the southern hemisphere, where more irregular environmental conditions prevail, we investigated AIV prevalence in ducks in relation to biotic and abiotic factors in south-eastern Australia. We sampled duck faeces for AIV and tested for an effect of bird numbers, rainfall anomaly, temperature anomaly and long-term ENSO (El-Niño Southern Oscillation) patterns on AIV prevalence. We demonstrate a positive long term effect of ENSO-related rainfall on AIV prevalence. We also found a more immediate response to rainfall where AIV prevalence was positively related to rainfall in the preceding 3-7 months. Additionally, for one duck species we found a positive relationship between their numbers and AIV prevalence, while prevalence was negatively or not affected by duck numbers in the remaining four species studied. In Australia largely non-seasonal rainfall patterns determine breeding opportunities and thereby influence bird numbers. Based on our findings we suggest that rainfall influences age structures within populations, producing an influx of immunologically naïve juveniles within the population, which may subsequently affect AIV infection dynamics. Our study suggests that drivers of AIV dynamics in the northern hemisphere do not have the same influence at our south-east Australian field site in the southern hemisphere due to more erratic climatological conditions

    Effects of infection-induced migration delays on the epidemiology of avian influenza in wild mallard populations

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    Wild waterfowl populations form a natural reservoir of Avian Influenza (AI) virus, and fears exist that these birds may contribute to an AI pandemic by spreading the virus along their migratory flyways. Observational studies suggest that individuals infected with AI virus may delay departure from migratory staging sites. Here, we explore the epidemiological dynamics of avian influenza virus in a migrating mallard (Anas platyrhynchos) population with a specific view to understanding the role of infection-induced migration delays on the spread of virus strains of differing transmissibility. We develop a host-pathogen model that combines the transmission dynamics of influenza with the migration, reproduction and mortality of the host bird species. Our modeling predicts that delayed migration of individuals influences both the timing and size of outbreaks of AI virus. We find that (1) delayed migration leads to a lower total number of cases of infection each year than in the absence of migration delay, (2) when the transmission rate of a strain is high, the outbreak starts at the staging sites at which birds arrive in the early part of the fall migration, (3) when the transmission rate is low, infection predominantly occurs later in the season, which is further delayed when there is a migration delay. As such, the rise of more virulent AI strains in waterfowl could lead to a higher prevalence of infection later in the year, which could change the exposure risk for farmed poultry. A sensitivity analysis shows the importance of generation time and loss of immunity for the effect of migration delays. Thus, we demonstrate, in contrast to many current transmission risk models solely using empirical information on bird movements to assess the potential for transmission, that a consideration of infection-induced delays is critical to understanding the dynamics of AI infection along the entire flyway.<br /
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