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In Autumn 2011, nonspecific clinical signs of pyrexia, diarrhoea, and drop in milk yield were observed in dairy cattle near the German town of Schmallenberg at the Dutch/German border. Targeted veterinary diagnostic investigations for classical endemic and emerging viruses could not identify a causal agent. Blood samples were collected from animals with clinical signs and subjected to metagenomic analysis; a novel orthobunyavirus was identified and named Schmallenberg virus (SBV). In late 2011/early 2012, an epidemic of abortions and congenital malformations in calves, lambs and goat kids, characterised by arthrogryposis and hydranencephaly were reported in continental Europe. Subsequently, SBV RNA was confirmed in both aborted and congenitally malformed foetuses and also in Culicoides species biting midges. It soon became evident that SBV was an arthropod-borne teratogenic virus affecting domestic ruminants. SBV rapidly achieved a pan-European distribution with most countries confirming SBV infection within a year or two of the initial emergence. The first Irish case of SBV was confirmed in the south of the country in late 2012 in a bovine foetus. Since SBV was first identified in 2011, a considerable body of scientific research has been conducted internationally describing this novel emerging virus. The aim of this systematic review is to provide a comprehensive synopsis of the most up-to-date scientific literature regarding the origin of SBV and the spread of the Schmallenberg epidemic, in addition to describing the species affected, clinical signs, pathogenesis, transmission, risk factors, impact, diagnostics, surveillance methods and control measures. This review also highlights current knowledge gaps in the scientific literature regarding SBV, most notably the requirement for further research to determine if, and to what extent, SBV circulation occurred in Europe and internationally during 2017 and 2018. Moreover, recommendations are also made regarding future arbovirus surveillance in Europe, specifically the establishment of a European-wide sentinel herd surveillance program, which incorporates bovine serology and Culicoides entomology and virology studies, at national and international level to monitor for the emergence and re-emergence of arboviruses such as SBV, bluetongue virus and other novel Culicoides -borne arboviruses.

Antimicrobial resistance has been recognised as one of the most difficult challenges facing human and animal health in recent decades. The surveillance of antimicrobial use in animal health plays a major role in dealing with the growing issue of resistance. This paper reviews current data available on antimicrobial use in farmed animals in the Republic of Ireland, including each of the major livestock production sectors; pigs, poultry, dairy, beef and sheep. A systematic literature search was conducted to identify relevant published literature, and ongoing research was identified through the network of authors and searches of each of the research databases of the main agriculture funding bodies in Ireland. The varying quantities and quality of data available across each livestock sector underlines the need for harmonisation of data collection methods. This review highlights the progress that has been made regarding data collection in the intensive production sectors such as pigs and poultry, however, it is clear there are significant knowledge gaps in less intensive industries such as dairy, beef and sheep. To comply with European regulations an antimicrobial data collection system is due to be developed for all food-producing animals in the future, however in the short-term surveillance studies have allowed us to build a picture of current use within the Republic of Ireland. Further studies will allow us to fill current knowledge gaps and build a more comprehensive overview of antimicrobial use in farm animals in Ireland.

Background Following the emergence of Schmallenberg virus (SBV) in Ireland in 2012, a sentinel herd surveillance program was established in the south of Ireland with the primary aim of investigating the species composition and abundance of Culicoides on livestock farms in the region. Methods Ultraviolet-light trapping for Culicoides was carried out on 10 sentinel farms. Each site was sampled fortnightly over 16 weeks (21st July to 5th November 2014). One Onderstepoort Veterinary Institute UV light trap was run overnight at each site and catches were transferred immediately into 70% ethanol. Culicoides were morphologically identified to species level. Collection site habitats were characterised using the Phase 1 habitat survey technique (Joint Nature Conservation Committee). Results A total of 23,929 individual Culicoides from 20 species was identified, including one species identified in Ireland for the first time, Culicoides cameroni. The most abundant species identified were Culicoides obsoletus/Culicoides scoticus (38%), Culicoides dewulfi (36%), Culicoides pulicaris (9%), Culicoides chiopterus (5%) and Culicoides punctatus (5%), comprising 93% of all Culicoides specimens identified. Collection site habitats were dominated by improved grassland and a combination of broadleaf woodland and native woodland species. Conclusions The most abundant species of Culicoides identified were the putative vectors of bluetongue virus (BTV) and SBV in northern Europe. Their presence and abundance demonstrates the potential for future transmission of arboviruses among livestock in this region.

Pooled samples of female and male Culicoides midges (5146 and 332 pools, respectively) that corresponded to a total number of 124,957 specimens were collected between 2013–2017 in the vicinity of cattle barns that were distributed throughout Poland were analyzed for the presence of Schmallenberg virus (SBV) RNA. Sixty-six pools tested positive (1.2%) with mean Ct value of 34.95. The maximum likelihood estimated infection rate (MLE) was calculated at 0.53 per 1000 individuals; however, it peaked in 2016 with MLE of 3.7. Viral RNA was detected in C. obsoletus/scoticus complex, C. punctatus, and C. pulicaris pools. Moreover, viral material was present in nulliparous (virgin) Culicoides females (MLE 0.27) and for the first time reported in males (MLE 0.34), which suggests the possibility of transovarial route of SBV or virus RNA transmission, as both do not fed on host blood. The accuracy of targeted versus random SBV surveillance in Culicoides vectors was compared. The relationship between infection rate (expressed as minimum infection rate; MIR), in addition to MLE, was compared with the density of virus infected midges (DIM). In conclusion, the SBV infection rate in the vector was significantly higher in 2016 as compared to other surveillance years; this is consistent with the simultaneous increase in SBV seroprevalence (seroconversion) in ruminants during the same year.

ObjectivesThe aim of this study was to conduct a rapid systematic review and meta-analysis of estimates of the incubation period of COVID-19.DesignRapid systematic review and meta-analysis of observational research.SettingInternational studies on incubation period of COVID-19.ParticipantsSearches 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 measuresParameters of a lognormal distribution of incubation periods.ResultsThe 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.ConclusionsThe 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.

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.ObjectiveConduct a review of available evidence to advise on appropriate parameter values for serial interval and generation time in national COVID-19 transmission models for Ireland and on methodological issues relating to those parameters.MethodsWe conducted a rapid review of the literature covering the period 1 January 2020 and 21 August 2020, following predefined eligibility criteria. Forty scientific papers met our inclusion criteria and were included in the review.ResultsThe mean of the serial interval ranged from 3.03 to 7.6 days, based on 38 estimates, and the median from 1.0 to 6.0 days (based on 15 estimates). Only three estimates were provided for the mean of the generation time. These ranged from 3.95 to 5.20 days. One estimate of 5.0 days was provided for the median of the generation time.DiscussionEstimates of the serial interval and the generation time are very dependent on the specific factors that apply at the time that the data are collected, including the level of social contact. Consequently, the estimates may not be entirely relevant to other environments. Therefore, local estimates should be obtained as soon as possible. Careful consideration should be given to the methodology that is used. Real-time estimations of the serial interval/generation time, allowing for variations over time, may provide more accurate estimates of reproduction numbers than using conventionally fixed serial interval/generation time distributions.

ObjectivesOur 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.DesignRapid 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 sourcesSearch 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.ResultsThere 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.ConclusionsThere 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.

ObjectiveTo estimate the proportion of presymptomatic transmission of SARS-CoV-2 infection that can occur, and the timing of transmission relative to symptom onset.Setting/designSecondary analysis of international published data.Data sourcesMeta-analysis of COVID-19 incubation period and a rapid review of serial interval and generation time, which are published separately.ParticipantsData from China, the Islamic Republic of Iran, Italy, Republic of Korea, Singapore and Vietnam from December 2019 to May 2020.MethodsSimulations were generated of incubation period and of serial interval or generation time. From these, transmission times relative to symptom onset, and the proportion of presymptomatic transmission, were estimated.Outcome measuresTransmission time of SARS-CoV-2 relative to symptom onset and proportion of presymptomatic transmission.ResultsBased on 18 serial interval/generation time estimates from 15 papers, mean transmission time relative to symptom onset ranged from −2.6 (95% CI −3.0 to –2.1) days before infector symptom onset to 1.4 (95% CI 1.0 to 1.8) days after symptom onset. The proportion of presymptomatic transmission ranged from 45.9% (95% CI 42.9% to 49.0%) to 69.1% (95% CI 66.2% to 71.9%).ConclusionsThere is substantial potential for presymptomatic transmission of SARS-CoV-2 across a range of different contexts. This highlights the need for rapid case detection, contact tracing and quarantine. The transmission patterns that we report reflect the combination of biological infectiousness and transmission opportunities which vary according to context.

ObjectivesThe aim of this study was to determine the relative infectiousness of asymptomatic SARS-CoV-2 infected persons compared with symptomatic individuals based on a scoping review of available literature.DesignRapid scoping review of peer-reviewed literature from 1 January to 5 December 2020 using the LitCovid database and the Cochrane library.SettingInternational studies on the infectiousness of individuals infected with SARS-CoV-2.ParticipantsStudies were selected for inclusion if they defined asymptomatics as a separate cohort distinct from presymptomatics and if they provided a quantitative measure of the infectiousness of asymptomatics relative to symptomatics.Primary outcome measuresPCR result (PCR studies), the rate of infection (mathematical modelling studies) and secondary attack rate (contact tracing studies) - in each case from asymptomatic in comparison with symptomatic individuals.ResultsThere are only a limited number of published studies that report estimates of relative infectiousness of asymptomatic compared with symptomatic individuals. 12 studies were included after the screening process. Significant differences exist in the definition of infectiousness. PCR studies in general show no difference in shedding levels between symptomatic and asymptomatic individuals; however, the number of study subjects is generally limited. Two modelling studies estimate relative infectiousness to be 0.43 and 0.57, but both of these were more reflective of the infectiousness of undocumented rather than asymptomatic cases. The results from contact tracing studies include estimates of relative infectiousness of 0, but with insufficient evidence to conclude that it is significantly different from 1.ConclusionsThere is considerable heterogeneity in estimates of relative infectiousness highlighting the need for further investigation of this important parameter. It is not possible to provide any conclusive estimate of relative infectiousness, as the estimates from the reviewed studies varied between 0 and 1.

[...]analyses to determine the host-feeding preferences of Culicoides arbovirus vector species (blood meal analyses) are also ongoing; the results of these studies will help to elucidate the epidemiology and transmission dynamics of arboviruses in these herds.