Now showing 1 - 10 of 12
  • Publication
    COVID-19 epidemiological parameters summary document
    In response to the coronavirus (COVID-19) outbreak, the Irish Epidemiological Modelling Advisory Group (IEMAG) for COVID-19 was established to assist the Irish National Public Health Emergency Team (NPHET) in their decision-making during the pandemic. A subcommittee from IEMAG (the epidemiological parameters team) was tasked with researching the various parameters, leading to the development of a series of synthesis documents relevant to the parameterisation of a COVID-19 transmission model for Ireland. These parameters include: • R0/R • Latent period & relative importance of pre-symptomatic period • Incubation period • Generation time & serial interval • Proportion of infected who are asymptomatic, by age • Length of infectious period in asymptomatic people and in symptomatic people who do not isolate • Time from onset of symptoms to diagnosis/test results and to hospitalisation • Length of hospital stay and admission to ICUs • Relative infectiousness of asymptomatic versus symptomatic infected people. The current document presents an up-to-date summary of these synthesis documents. A further synthesis document on age-related susceptibility and age-related infectiousness is in preparation.
  • Publication
    Ireland Red List No. 2 : Non-marine molluscs
    (National Parks and Wildlife Service, Department of the Environment, Heritage and Local Government, 2009) ; ; ; ;
    Based on almost 80,000 records for Ireland, 150 native species of non-marine mollusc are evaluated for their conservation status using International Union for the Conservation of Nature (IUCN) criteria (IUCN, 2001, 2003). Two are considered to be regionally extinct, five critically endangered, fourteen endangered, twenty-six vulnerable, six near threatened, and the rest of least concern, or data deficient. Ireland’s non-marine molluscan fauna is of international importance. Ten species have populations of significant international worth, having large proportions of their global population in Ireland. Ashfordia granulata and Leisotyla anglica are two examples of such species; both are near endemics to Britain and Ireland, with Ireland having at least a fifth of their global populations. Seven species have been listed on the global IUCN red list, for example Myxas glutinosa and Quickella arenaria, both of which are endangered species in Ireland. Six species are legally protected under European legislation. Of these legally protected species, only the Kerry slug, Geomalacus maculosus, is not considered threatened in Ireland. However, the Irish population of this species is of particular international importance as the species is restricted to south-west Ireland and northern Iberia, and the Iberian populations are severely threatened. Some species are rare in Ireland as they are at the edge of their range or climatic tolerances (e.g. Pomatias elegans). For species that are declining in Ireland there are multiple drivers of population loss. Species declines are primarily driven by habitat loss (e.g. loss of marginal agricultural wetlands through drainage impacting species such as Vertigo antivertigo), habitat change (e.g. reduced water quality impacting species such as Pisidium pseudosphaerium and Margaritifera margaritifera) and habitat management (e.g. woodland management practices impacting species such as Spermodea lamellata). To a lesser extent species may be declining due to climate change (e.g. Pisidium conventus, a cold, deep water, montane species) and the impact of invasive species (Anodonta cygnea and A. anatina, the swan and duck mussels, are being severely impacted by the invasive species Dreissena polymorpha, the zebra mussel). The importance of water quality and the reduction of habitat loss and change across a spectrum of habitats are identified as important components in conserving the non-marine molluscan fauna on the island of Ireland.
  • Publication
    Regional red list of Irish bees
    (National Parks and Wildlife Service (Ireland) and Environment and Heritage Service (N. Ireland), 2006) ; ; ; ;
    In 2003 the Higher Education Authority awarded funding for a three year project on the conservation of native Irish bees under their North-South programme for collaborative research. This work was undertaken by Dr. Úna Fitzpatrick and Dr. Mark Brown in the School of Natural Sciences, Trinity College Dublin and by Mr. Tomás Murray and Dr. Rob Paxton in the School of School of Biological Sciences, Queen’s University Belfast. One important element of this research has been the documentation of the conservation status of native bees in Ireland. A three-step sequential process has been used to document the status of each of the native species, indicate the conservation action required, and highlight those species of most importance from a conservation perspective: (1) Identification of the threatened species using internationally recognized methodology - production of an IUCN regional red list for the island of Ireland. (2) Documentation of the total conservation actions required for the assessed group - completed IUCN conservation action authority files for threatened, near threatened and data deficient species. (3) Conversion from the regional red list to a national list of conservation priority species This summary report contains the Regional Red List of Irish bees, IUCN conservation actions authority files for all threatened, near threatened and data deficient species in the red list, and a list of national conservation priority species.
  • Publication
    Large-scale movements in European badgers: has the tail of the movement kernel been underestimated?
    1. Characterising patterns of animal movement is a major aim in population ecology, and yet doing so at an appropriate spatial-scale remains a majorchallenge. Estimating the frequency and distances of movements are of particularimportance when species are implicated in the transmission of zoonotic diseases. 2. European badgers (Meles meles) are classically viewed as exhibiting limited dispersal, and yet their movements bring them into conflict with farmers due to their potential to spread bovine tuberculosis in parts of their range. Considerable uncertainty surrounds the movement potential of badgers, and this may be related to the spatial-scale of previous empirical studies. We conducted a large-scale mark-recapture study (755km231 ; 2008-2012; 1,935 capture-events; 963 badgers) to investigate movement patterns in badgers, and undertook a comparative meta analysis using published data from 15 European populations. 3. The dispersal movement (>1km) kernel followed an inverse power-law function, with a substantial 'tail' indicating the occurrence of rare long-distance dispersal attempts during the study period. The mean recorded distance from this distribution was 2.6km., the upper 95%ile was 7.3km and the longest recorded was 22.1km. Dispersal frequency distributions were significantly different between genders; males dispersed more frequently than females but females made proportionally more long-distance dispersal attempts than males. 4. We used a subsampling approach to demonstrate that the appropriate minimum spatial-scale to characterise badger movements in our study population was 80km243 , substantially larger than many previous badger studies. Furthermore, the meta-analysis indicated a significant association between maximum movement distance and study area size, while controlling for population density. Maximum long-distance movements were often only recorded by chance beyond the boundaries of study areas. 5. These findings suggest that the tail of the badger movement distribution is currently underestimated. The implications of this for understanding the spatial ecology of badger populations and for the design of disease intervention strategies are potentially significant.
      387Scopus© Citations 32
  • Publication
    Rapid review of available evidence on the serial interval and generation time of COVID-19
    The serial interval is the time between symptom onsets in an infector–infectee pair. The generation time, also known as the generation interval, is the time between infection events in an infector–infectee pair. The serial interval and the generation time are key parameters for assessing the dynamics of a disease. A number of scientific papers reported information pertaining to the serial interval and/or generation time for COVID-19.
      120Scopus© Citations 44
  • Publication
    Incubation period of COVID-19: a rapid systematic review and meta-analysis of observational research
    Objectives: The aim of this study was to conduct a rapid systematic review and meta-analysis of estimates of the incubation period of COVID-19. Design: Rapid systematic review and meta-analysis of observational research. Setting: International studies on incubation period of COVID-19. Participants: Searches were carried out in PubMed, Google Scholar, Embase, Cochrane Library as well as the preprint servers MedRxiv and BioRxiv. Studies were selected for meta-analysis if they reported either the parameters and CIs of the distributions fit to the data, or sufficient information to facilitate calculation of those values. After initial eligibility screening, 24 studies were selected for initial review, nine of these were shortlisted for meta-analysis. Final estimates are from meta-analysis of eight studies. Primary outcome measures: Parameters of a lognormal distribution of incubation periods. Results: The incubation period distribution may be modelled with a lognormal distribution with pooled mu and sigma parameters (95% CIs) of 1.63 (95% CI 1.51 to 1.75) and 0.50 (95% CI 0.46 to 0.55), respectively. The corresponding mean (95% CIs) was 5.8 (95% CI 5.0 to 6.7) days. It should be noted that uncertainty increases towards the tail of the distribution: the pooled parameter estimates (95% CIs) resulted in a median incubation period of 5.1 (95% CI 4.5 to 5.8) days, whereas the 95th percentile was 11.7 (95% CI 9.7 to 14.2) days. Conclusions: The choice of which parameter values are adopted will depend on how the information is used, the associated risks and the perceived consequences of decisions to be taken. These recommendations will need to be revisited once further relevant information becomes available. Accordingly, we present an R Shiny app that facilitates updating these estimates as new data become available.
      243Scopus© Citations 235
  • Publication
    Population estimation and trappability of the European badger (Meles meles): implications for tuberculosis management
    Estimates of population size and trappability inform vaccine efficacy modelling and are required for adaptive management during prolonged wildlife vaccination campaigns. We present an analysis of mark-recapture data from a badger vaccine (Bacille Calmette-Guérin) study in Ireland. This study is the largest scale (755 km²) mark-recapture study ever undertaken with this species. The study area was divided into three approximately equal-sized zones, each with similar survey and capture effort. A mean badger population size of 671 (SD: 76) was estimated using a closed-subpopulation model (CSpM) based on data from capturing sessions of the entire area and was consistent with a separate multiplicative model. Minimum number alive estimates calculated from the same data were on average 49-51% smaller than the CSpM estimates, but these are considered severely negatively biased when trappability is low. Population densities derived from the CSpM estimates were 0.82-1.06 badgers kmˉ², and broadly consistent with previous reports for an adjacent area. Mean trappability was estimated to be 34-35% per session across the population. By the fifth capture session, 79% of the adult badgers caught had been marked previously. Multivariable modelling suggested significant differences in badger trappability depending on zone, season and age-class. There were more putatively trap-wary badgers identified in the population than trap-happy badgers, but wariness was not related to individual's sex, zone or season of capture. Live-trapping efficacy can vary significantly amongst sites, seasons, age, or personality, hence monitoring of trappability is recommended as part of an adaptive management regime during large-scale wildlife vaccination programs to counter biases and to improve efficiencies.
      269Scopus© Citations 36
  • Publication
    Reflecting on One Health in Action During the COVID-19 Response
    The COVID-19 pandemic, a singular disruptive event in recent human history, has required rapid, innovative, coordinated and collaborative approaches to manage and ameliorate its worst impacts. However, the threat remains, and learning from initial efforts may benefit the response management in the future. One Health approaches to managing health challenges through multi-stakeholder engagement are underscored by an enabling environment. Here we describe three case studies from state (New South Wales, Australia), national (Ireland), and international (sub-Saharan Africa) scales which illustrate different aspects of One Health in action in response to the COVID-19 pandemic. In Ireland, a One Health team was assembled to help parameterise complex mathematical and resource models. In New South Wales, state authorities engaged collaboratively with animal health veterinarians and epidemiologists to leverage disease outbreak knowledge, expertise and technical and support structures for application to the COVID-19 emergency. The African One Health University Network linked members from health institutions and universities from eight countries to provide a virtual platform knowledge exchange on COVID-19 to support the response. Themes common to successful experiences included a shared resource base, interdisciplinary engagement, communication network strategies, and looking global to address local need. The One Health approaches used, particularly shared responsibility and knowledge integration, are benefiting the management of this pandemic and future One Health global challenges.
      118Scopus© Citations 9
  • Publication
    The ecology of the European badger (Meles meles) in Ireland - a review
    The badger is an ecologically and economically important species. Detailed knowledge of aspects of the ecology of this animal in Ireland has only emerged through research over recent decades. Here, we review what is known about the species’ Irish populations and compare these findings with populations in Britain and Europe. Like populations elsewhere, setts are preferentially constructed on south or southeast facing sloping ground in well-drained soil types. Unlike in Britain, Irish badger main setts are less complex and most commonly found in hedgerows. Badgers utilise many habitat types, but greater badger densities have been associated with landscapes with high proportions of pasture and broadleaf woodlands. Badgers in Ireland tend to have seasonally varied diets, with less dependence on earthworms than some other populations in northwest Europe. Recent research suggests that females exhibit later onset and timing of reproductive events, smaller litter sizes and lower loss of blastocysts than populations studied in Britain. Adult social groups in Ireland tend to be smaller than in Britain, though significantly larger than social groups from continental Europe. Although progress has been made in estimating the distribution and density of badger populations, national population estimates have varied widely in the Republic of Ireland. Future research should concentrate on filling gaps in our knowledge, including population models and predictive spatial modelling that will contribute to vaccine delivery, management and conservation strategies.
      1002Scopus© Citations 44
  • Publication
    Inferred duration of infectious period of SARS-CoV-2: rapid scoping review and analysis of available evidence for asymptomatic and symptomatic COVID-19 cases
    Objectives. Our objective was to review the literature on the inferred duration of the infectious period of COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, and provide an overview of the variation depending on the methodological approach. Design. Rapid scoping review. Literature review with fixed search terms, up to 1 April 2020. Central tendency and variation of the parameter estimates for infectious period in (A) asymptomatic and (B) symptomatic cases from (1) virological studies (repeated testing), (2) tracing studies and (3) modelling studies were gathered. Narrative review of viral dynamics. Information sources. Search strategies developed and the following searched: PubMed, Google Scholar, MedRxiv and BioRxiv. Additionally, the Health Information Quality Authority (Ireland) viral load synthesis was used, which screened literature from PubMed, Embase, ScienceDirect, NHS evidence, Cochrane, medRxiv and bioRxiv, and HRB open databases. Results. There was substantial variation in the estimates, and how infectious period was inferred. One study provided approximate median infectious period for asymptomatic cases of 6.5–9.5 days. Median presymptomatic infectious period across studies varied over <1–4 days. Estimated mean time from symptom onset to two negative RT-PCR tests was 13.4 days (95% CI 10.9 to 15.8) but was shorter when studies included children or less severe cases. Estimated mean duration from symptom onset to hospital discharge or death (potential maximal infectious period) was 18.1 days (95% CI 15.1 to 21.0); time to discharge was on average 4 days shorter than time to death. Viral dynamic data and model infectious parameters were often shorter than repeated diagnostic data. Conclusions. There are limitations of inferring infectiousness from repeated diagnosis, viral loads and viral replication data alone and also potential patient recall bias relevant to estimating exposure and symptom onset times. Despite this, available data provide a preliminary evidence base to inform models of central tendency for key parameters and variation for exploring parameter space and sensitivity analysis.
      219Scopus© Citations 141