Conor McAloon

Dr. Conor McAloon

orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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16 August 2020 in BMJ Open
Verified
Journal Article
Open access
PDF file
CMConor McAloon
Conor McAloon
ÁCÁine Collins
Áine Collins
KHKevin Hunt
Kevin Hunt
ABAnn Barber
Ann Barber
Andrew ByrneAndrew Byrne
Andrew Byrne
SMSimon More
Simon More
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.

5 August 2020 in BMJ Open
Verified
Journal Article
Open access
PDF file
Andrew ByrneAndrew Byrne
Andrew Byrne
DMDavid McEvoy
David McEvoy
ACAine B Collins
Aine B Collins
KHKevin Hunt
Kevin Hunt
MCMiriam Casey
Miriam Casey
SMSimon More
Simon More
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.

23 November 2020 in BMJ Open
Verified
Journal Article
Open access
PDF file
JGJohn Griffin
John Griffin
MCMiriam Casey
Miriam Casey
ÁCÁine Collins
Áine Collins
KHKevin Hunt
Kevin Hunt
DMDavid McEvoy
David McEvoy
SMSimon More
Simon More
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. Objective Conduct 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. Methods We 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. Results The 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. Discussion Estimates 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.

1 February 2016 in Journal of Dairy Science
Verified
Journal Article
Open access
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CMConor McAloon
Conor McAloon
PWPaul Whyte
Paul Whyte
SMSimon More
Simon More
MGMartin Green
Martin Green
LOLuke O’gRady
Luke O’gRady
MDMichael L. Doherty
Michael L. Doherty
Bovine paratuberculosis is a disease characterized by chronic granulomatous enteritis causing protein-losing enteropathy. Adverse effects on animal productivity are key drivers in the attempt to control paratuberculosis at the farm level. Economic models require an accurate estimation of the production effects associated with paratuberculosis. The aim of this study was to conduct a systematic review and meta-analysis to investigate the effect of paratuberculosis on milk production. A total of 20 effect estimates from 15 studies were included in the final meta-analysis. Substantial between-study heterogeneity was observed. Subgroup analysis by case definition and study design was carried out to investigate heterogeneity. The majority of between-study variation was attributed to studies that defined cases on serology. Calculation of a pooled effect estimate was only appropriate for studies that defined cases by organism detection. A reduction in milk yield, corrected for lactation number and herd of origin of 1.87 kg/d, equivalent to 5.9% of yield, was associated with fecal culture or PCR positivity in individual cows.

4 May 2021 in BMJ Open
Verified
Journal Article
Open access
PDF file
DMDavid McEvoy
David McEvoy
CMConor McAloon
Conor McAloon
ACAine Collins
Aine Collins
KHKevin Hunt
Kevin Hunt
FBFrancis Butler
Francis Butler
SMSimon More
Simon More
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.

1 February 2020 in Journal of Dairy Science
Verified
Journal Article
Closed access
KMK.M. McCarthy
K.M. McCarthy
CMConor McAloon
Conor McAloon
MLM.B. Lynch
M.B. Lynch
KPK.M. Pierce
K.M. Pierce
FMFinbar Mulligan
Finbar Mulligan
A systematic review and meta-analysis were conducted to estimate the effect of herb species on milk production and urinary nitrogen (UN) excretion from grazing dairy cows. Grazing swards consisting of herb species grown with either a grass species or a grass and legume (multispecies swards) were compared with non-herb-containing swards consisting of a grass species grown as a monoculture or grass-legume swards (simple swards). A literature search was completed using the online databases CAB Direct, Web of Science, and Google Scholar, using the search strategy "dairy cow", "herb OR forb OR phorb", and "grazing". Milk production data, variance, and sample size were required for eligibility. In all, 116 studies were identified. Following eligibility screening, 11 papers from 6 journals, published between 2006 and 2018, were available for analysis. Studies were from New Zealand (N = 7), Australia (N = 3), and the United States (N = 1). The population was either Holstein Friesian or Holstein Friesian × Jersey dairy cows, with a range in mean daily milk yield (MY) from 12.1 kg to 34.7 kg (mean = 18.6 kg). A total of 25 comparisons were used for milk production analysis, with 324 and 284 cows included in multispecies and simple sward groups respectively. Data analysis was conducted in R using a random effects, robust variance estimation model (R Foundation for Statistical Computing, Vienna, Austria). Heterogeneity was reported using the I2 statistic. Milk production was significantly increased. Analysis of MY resulted in a weighted mean difference (WMD) of +1.20 kg/d (95% CI = 0.90, 1.49; I2 = 4%). Fat and protein kg were also significantly increased (WMD +0.06 kg/d; CI = 0.01, 0.11). Urinary nitrogen excretion was estimated from milk urea nitrogen when reported (n = 6). A WMD of -28.1 g of N/d (95% CI = -81.1, 24.9) was generated, with heterogeneity high among studies (I2 = 75%). This meta-analysis shows the potential benefits of multispecies swards. Although we saw no significant difference in UN excretion, an increase in milk production was found.