Epidemiological and ecological consequences of virus manipulation of host and vector in plant virus transmission.

Many plant viruses are transmitted by insect vectors. Transmission can be described as persistent or non-persistent depending on rates of acquisition, retention, and inoculation of virus. Much experimental evidence has accumulated indicating vectors can prefer to settle and/or feed on infected versus noninfected host plants. For persistent transmission, vector preference can also be conditional, depending on the vector's own infection status. Since viruses can alter host plant quality as a resource for feeding, infection potentially also affects vector population dynamics. Here we use mathematical modelling to develop a theoretical framework addressing the effects of vector preferences for landing, settling and feeding-as well as potential effects of infection on vector population density-on plant virus epidemics. We explore the consequences of preferences that depend on the host (infected or healthy) and vector (viruliferous or nonviruliferous) phenotypes, and how this is affected by the form of transmission, persistent or non-persistent. We show how different components of vector preference have characteristic effects on both the basic reproduction number and the final incidence of disease. We also show how vector preference can induce bistability, in which the virus is able to persist even when it cannot invade from very low densities. Feedbacks between plant infection status, vector population dynamics and virus transmission potentially lead to very complex dynamics, including sustained oscillations. Our work is supported by an interactive interface https://plantdiseasevectorpreference.herokuapp.com/. Our model reiterates the importance of coupling virus infection to vector behaviour, life history and population dynamics to fully understand plant virus epidemics

Modelling Vector Transmission and Epidemiology of Co-Infecting Plant Viruses.

Co-infection of plant hosts by two or more viruses is common in agricultural crops and natural plant communities. A variety of models have been used to investigate the dynamics of co-infection which track only the disease status of infected and co-infected plants, and which do not explicitly track the density of inoculative vectors. Much less attention has been paid to the role of vector transmission in co-infection, that is, acquisition and inoculation and their synergistic and antagonistic interactions. In this investigation, a general epidemiological model is formulated for one vector species and one plant species with potential co-infection in the host plant by two viruses. The basic reproduction number provides conditions for successful invasion of a single virus. We derive a new invasion threshold which provides conditions for successful invasion of a second virus. These two thresholds highlight some key epidemiological parameters important in vector transmission. To illustrate the flexibility of our model, we examine numerically two special cases of viral invasion. In the first case, one virus species depends on an autonomous virus for its successful transmission and in the second case, both viruses are unable to invade alone but can co-infect the host plant when prevalence is high

Effects of plant pathogens on population dynamics and community composition in grassland ecosystems: two case studies

Grassland ecosystems comprise a major portion of the earth’s terrestrial surface, ranging from high-input cultivated monocultures or simple species mixtures to relatively unmanaged but dynamic systems. Plant pathogens are a component of these systems with their impact dependent on many interacting factors, including grassland species population dynamics and community composition, the topics covered in this paper. Plant pathogens are affected by these interactions and also act reciprocally by modifying their nature. We review these features of disease in grasslands and then introduce the 150-year long-term Park Grass Experiment (PGE) at Rothamsted Research in the UK. We then consider in detail two plant-pathogen systems present in the PGE, Tragopogon pratensis-Puccinia hysterium and Holcus lanata-Puccinia coronata. These two systems have very different life history characteristics: the first, a biennial member of the Asteraceae infected by its host-specific, systemic rust; the second, a perennial grass infected by a host-non-specific rust. We illustrate how observational, experimental and modelling studies can contribute to a better understanding of population dynamics, competitive interactions and evolutionary outcomes. With Tragopogon pratensis-Puccinia hysterium, characterised as an “outbreak” species in the PGE, we show that pathogen-induced mortality is unlikely to be involved in host population regulation; and that the presence of even a short-lived seed-bank can affect the qualitative outcomes of the host-pathogen dynamics. With Holcus lanata-Puccinia coronata, we show how nutrient conditions can affect adaptation in terms of host defence mechanisms, and that co-existence of competing species affected by a common generalist pathogen is unlikely

Coinfections by noninteracting pathogens are not independent and require new tests of interaction.

If pathogen species, strains, or clones do not interact, intuition suggests the proportion of coinfected hosts should be the product of the individual prevalences. Independence consequently underpins the wide range of methods for detecting pathogen interactions from cross-sectional survey data. However, the very simplest of epidemiological models challenge the underlying assumption of statistical independence. Even if pathogens do not interact, death of coinfected hosts causes net prevalences of individual pathogens to decrease simultaneously. The induced positive correlation between prevalences means the proportion of coinfected hosts is expected to be higher than multiplication would suggest. By modelling the dynamics of multiple noninteracting pathogens causing chronic infections, we develop a pair of novel tests of interaction that properly account for nonindependence between pathogens causing lifelong infection. Our tests allow us to reinterpret data from previous studies including pathogens of humans, plants, and animals. Our work demonstrates how methods to identify interactions between pathogens can be updated using simple epidemic models

Effect of COVID-19 on acute treatment of ST-segment elevation and Non-ST-segment elevation acute coronary syndrome in northwestern Switzerland

To investigate the effect of the corona virus disease 2019 (COVID-19) pandemic on the acute treatment of patients with ST-segment elevation (STEMI) and Non-ST-segment elevation acute coronary syndrome (NSTE-ACS).; We retrospectively identified patients presenting to the emergency department (ED) with suspected ACS. We evaluated the number of percutaneous coronary interventions (PCIs) for STEMI, NSTE-ACS, and elective PCI cases. In STEMI patients, we assessed the time from chest pain onset (cpo) to ED presentation, post-infarction left ventricular ejection fraction (LVEF), and time from ED presentation to PCI. We directly compared cases from two time intervals: January/February 2020 versus March/April 2020 (defined as 2 months before and after the COVID-19 outbreak). In a secondary analysis, we directly compared cases from March/April 2020 with patients from the same time interval in 2019.; From January to April 2020, 765 patients presented with acute chest pain to the ED. A dramatic reduction of ED presentations after compared to before the COVID-19 outbreak (31% relative reduction) was observed. Overall, 398 PCIs were performed, 220/398 PCIs (55.3%) before versus 178/398 PCIs (44.7%) after the outbreak. While numbers for NSTE-ACS and elective interventions declined by 21% and 31%, respectively, the number of STEMI cases remained stable. Time from cpo to ED presentation, post-infarction LVEF, and median door-to-balloon time remained unchanged.; In contrast to previous reports, our findings do not confirm the dramatic drop in STEMI cases and interventions in northwestern Switzerland as observed in other regions and hospitals around the world

Outbreak of H3N2 influenza at a US military base in Djibouti during the H1N1 pandemic of 2009.

PMC3855413BACKGROUND: Influenza pandemics have significant operational impact on deployed military personnel working in areas throughout the world. The US Department of Defense global influenza-like illness (ILI) surveillance network serves an important role in establishing baseline trends and can be leveraged to respond to outbreaks of respiratory illness. OBJECTIVE: We identified and characterized an operationally unique outbreak of H3N2 influenza at Camp Lemonnier, Djibouti occurring simultaneously with the H1N1 pandemic of 2009 [A(H1N1)pdm09]. METHODS: Enhanced surveillance for ILI was conducted at Camp Lemonnier in response to local reports of a possible outbreak during the A(H1N1)pdm09 pandemic. Samples were collected from consenting patients presenting with ILI (utilizing a modified case definition) and who completed a case report form. Samples were cultured and analyzed using standard real-time reverse transcriptase PCR (rt-RT-PCR) methodology and sequenced genetic material was phylogenetically compared to other published strains. RESULTS: rt-RT-PCR and DNA sequencing revealed that 25 (78%) of the 32 clinical samples collected were seasonal H3N2 and only 2 (6%) were A(H1N1)pdm09 influenza. The highest incidence of H3N2 occurred during the month of May and 80% of these were active duty military personnel. Phylogenetic analysis revealed that sequenced H3N2 strains were genetically similar to 2009 strains from the United States of America, Australia, and South east Asia. CONCLUSIONS: This outbreak highlights challenges in the investigation of influenza among deployed military populations and corroborates the public health importance of maintaining surveillance systems for ILI that can be enhanced locally when needed.JH Libraries Open Access Fun