Options
Collins, Áine B.
Preferred name
Collins, Áine B.
Official Name
Collins, Áine B.
Research Output
Now showing 1 - 10 of 10
- PublicationCOVID-19 epidemiological parameters summary document(Department of Health, 2020-05-20)
; ; ; ; ; ; ; ; ; ; ; 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.127 - PublicationInferred duration of infectious period of SARS-CoV-2: rapid scoping review and analysis of available evidence for asymptomatic and symptomatic COVID-19 cases(BMJ Journals, 2020-08-01)
; ; ; ; ; ; ; ; ; ; ; 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.243Scopus© Citations 147 - PublicationIncubation period of COVID-19: a rapid systematic review and meta-analysis of observational research(BMJ, 2020-08-16)
; ; ; ; ; ; ; ; ; ; ; ; ; 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.266Scopus© Citations 246 - PublicationRapid review of available evidence on the serial interval and generation time of COVID-19(BMJ, 2020-11-23)
; ; ; ; ; ; ; ; ; 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-19.153Scopus© Citations 48 - PublicationRelative infectiousness of asymptomatic SARS-CoV-2 infected persons compared with symptomatic individuals: a rapid scoping review(BMJ, 2021-05)
; ; ; ; ; ; ; ; ; Objectives The 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. Design Rapid scoping review of peer-reviewed literature from 1 January to 5 December 2020 using the LitCovid database and the Cochrane library. Setting International studies on the infectiousness of individuals infected with SARS-CoV-2. Participants Studies 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 measures PCR 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. Results There 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. Conclusions There 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 1.175Scopus© Citations 19 - PublicationSpatial and network characteristics of Irish cattle movements(Elsevier, 2020-10)
; ; ; ; ; Our aim was to examine, for the first time, the spatial and network characteristics of cattle movements between herds in the Republic of Ireland (ROI), to inform policy and research of relevance to the surveillance and management of disease in Irish cattle. We analysed movements in 2016 as discrete herd to herd pairings (degree), herd to herd pairings by date of move (contacts) and herd to herd pairings by date and individual animal (transfers), and looked at each of these as movements out of a herd (out degree, out contacts, out transfers) and into a herd (in degree, in contacts, in transfers). We found that the frequency distributions, by herd, of these six move types were all heavily right skewed but in the case of the ‘out’ data types more closely followed a log-normal than the scale free distribution often reported for livestock movement data. For each distinct herd to herd contact in a given direction, over 90 % occurred only once, whereas the maximum number of occurrences was 62. Herd-level Spearman rank correlations between inward moves (represented as in degree, in contacts, in transfers) and outward moves (out degree, out contacts, out transfers) were weak or even negative whereas correlations between different measures of outward moves or inward moves (e.g. out degree vs. out contacts, in transfers vs. in degree) were stronger. Correlations between these variables and the network measure betweenness varied between r = 0.513 and r = 0.587. Some herds took part in a relatively large number of movements whilst also retaining their cattle for long periods (> 100 days) between moves. In and out degree, contacts and transfers were mapped across Ireland on a 5 km grid, and additionally normalized per 1000 animals and per herd. We found considerable variation in the number of movements by county. Approximately half of transfers were conducted within a single county, but the number and distance of between county movements varied considerably by county of origin and county of destination, with the proportion of moves completed within a single county correlated with its size. Herds exchanging cattle via a market were generally further apart than when moves were made directly herd to herd. For contacts, the distances moved away from the herd were on average greater for origin herds in the west of ROI whereas distances moved to a herd were generally greater for destination herds in the centre-east and the north-west.Our aim was to examine, for the first time, the spatial and network characteristics of cattle movements between herds in the Republic of Ireland (ROI), to inform policy and research of relevance to the surveillance and management of disease in Irish cattle. We analysed movements in 2016 as discrete herd to herd pairings (degree), herd to herd pairings by date of move (contacts) and herd to herd pairings by date and individual animal (transfers), and looked at each of these as movements out of a herd (out degree, out contacts, out transfers) and into a herd (in degree, in contacts, in transfers). We found that the frequency distributions, by herd, of these six move types were all heavily right skewed but in the case of the ‘out’ data types more closely followed a log-normal than the scale free distribution often reported for livestock movement data. For each distinct herd to herd contact in a given direction, over 90 % occurred only once, whereas the maximum number of occurrences was 62. Herd-level Spearman rank correlations between inward moves (represented as in degree, in contacts, in transfers) and outward moves (out degree, out contacts, out transfers) were weak or even negative whereas correlations between different measures of outward moves or inward moves (e.g. out degree vs. out contacts, in transfers vs. in degree) were stronger. Correlations between these variables and the network measure betweenness varied between r = 0.513 and r = 0.587. Some herds took part in a relatively large number of movements whilst also retaining their cattle for long periods (> 100 days) between moves. In and out degree, contacts and transfers were mapped across Ireland on a 5 km grid, and additionally normalized per 1000 animals and per herd. We found considerable variation in the number of movements by county. Approximately half of transfers were conducted within a single county, but the number and distance of between county movements varied considerably by county of origin and county of destination, with the proportion of moves completed within a single county correlated with its size. Herds exchanging cattle via a market were generally further apart than when moves were made directly herd to herd. For contacts, the distances moved away from the herd were on average greater for origin herds in the west of ROI whereas distances moved to a herd were generally greater for destination herds in the centre-east and the north-west.100Scopus© Citations 11 - PublicationPresymptomatic transmission of SARS-CoV-2 infection: a secondary analysis using published data(BMJ, 2021-06-28)
; ; ; ; ; ; ; ; ; ; ; ; ; ; Objective To estimate the proportion of presymptomatic transmission of SARS-CoV-2 infection that can occur, and the timing of transmission relative to symptom onset.Setting/design Secondary analysis of international published data.Data sources Meta-analysis of COVID-19 incubation period and a rapid review of serial interval and generation time, which are published separately.Participants Data from China, the Islamic Republic of Iran, Italy, Republic of Korea, Singapore and Vietnam from December 2019 to May 2020.Methods Simulations 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 measures Transmission time of SARS-CoV-2 relative to symptom onset and proportion of presymptomatic transmission.Results Based 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%).Conclusions There 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.188Scopus© Citations 20 - PublicationPrevalence of Mycobacterium bovis in milk on dairy cattle farms: An international systematic literature review and meta-analysisBovine tuberculosis, caused by Mycobacterium bovis (M. bovis), is a globally distributed chronic disease of animals. The bacteria can be transmitted to humans via the consumption of unpasteurised (raw) milk, thus representing an important public health risk. To investigate the risk of zoonotic transmission of M. bovis via raw milk, this study systematically reviewed published studies to estimate the prevalence of M. bovis in on-farm bulk-tank milk (BTM) and individual cow's milk (IM) by meta-analysis. In total, 1,339 articles were identified through seven electronic databases and initially screened using titles and abstracts. The quality of 108 potentially relevant articles was assessed using full texts, and 67 articles comprising 83 studies (76 IM and 7 BTM), were included in the meta-analysis. The prevalence of M. bovis in IM and BTM was summarised according to the diagnostic test used, and the tuberculin skin test (TST) infection status of the individual cows (for IM) or herds (for BTM). Heterogeneity was quantified using the I-squared statistic. Prediction intervals (95% PIs) were also estimated. For IM, the overall prevalence was summarised at 5% (95%CI: 3%–7%). In TST positive cows, prevalence was summarised at 8% (95%CI: 4%–13%). For BTM, the overall prevalence independent of individual herd TST infection status was summarised at 5% (95%CI: 0%–21%). There was considerable heterogeneity evident among the included studies, while PIs were also wide. Inconsistency in the quality of reporting was also observed resulting in missing information, such as the TST infection status of the individual animal/herd. No study reported the number of M. bovis bacteria in test-positive milk samples. Several studies reported the detection of M. tuberculosis and M. africanum in milk. Despite international efforts to control tuberculosis, this study highlights the risk of zoonotic transmission of M. bovis via unpasteurised milk and dairy products made using raw milk.
22Scopus© Citations 4 - PublicationCurrent antimicrobial use in farm animals in the Republic of Ireland(Springer Nature, 2020-06-26)
; ; ; ; ; ; ; 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.72Scopus© Citations 5 - PublicationParameter estimates to support future risk assessment of Mycobacterium bovis in raw milk cheeseZoonotic tuberculosis, caused by Mycobacterium bovis, is mainly linked to the consumption of raw milk from infected cows. In many countries, cases are rare, due to pasteurisation of milk and national programmes to control M. bovis infection in cattle. Speciality cheeses, which are often produced using raw milk, present challenges to risk managers in countries where M. bovis is endemic or (re-) emerging. A key concern is the potential risk of zoonotic transmission of M. bovis via the consumption of dairy products produced using raw milk originating from herds infected with M. bovis (bovine tuberculosis, bTB). The aim of this study was to determine parameter estimates to support the future risk assessment of M. bovis in raw milk cheese. In this study, the hazard was identified as viable M. bovis organisms in raw milk cheese. Parameters of interest in this study related to exposure assessment (the estimated extent of human exposure to viable M. bovis organisms) and hazard characterisation (the risk posed to human health following exposure to viable M. bovis organisms). The pathway for exposure assessment was visualised using a conceptual framework, which describes the steps through which M. bovis may be transferred from an infected animal(s) through manufacturing to the final cheese product. Estimation of most parameters for exposure assessment and hazard characterisation was undertaken using systematic literature reviews. Estimates could be derived for many parameters, but not all. In particular, the number of M. bovis organisms excreted in the milk and present in the faeces of infected cattle are unknown. There is zero-tolerance for M. bovis in foods of animal origin destined for human consumption in European legislation. This work has highlighted important gaps in knowledge, and areas for further research. For each of the parameters for which estimates are available, we outline the types/sources of uncertainty as reflected in relevant published papers. In any future application of these parameter estimates, care will be needed to reflect the uncertainties associated with these elements of exposure assessment.
23