Biology subjects

Conlan, A. J.

Publications and source records attributed to Conlan, A. J..

4 recordsLinked to original sources

bioRxiv2021

Inferring Mycobacterium bovis transmission between cattle and badgers using isolates from the Randomised Badger Culling Trial

Mycobacterium bovis (M. bovis) is a causative agent of bovine tuberculosis, a significant source of morbidity and mortality in the global cattle industry. The Randomised Badger Culling Trial was a field experiment carried out between 1998 and 2005 in the South West of England. As part of this trial, M. bovis isolates were collected from contemporaneous and overlapping populations of badgers and cattle within ten defined trial areas. We combined whole genome sequences from 1,442 isolates with location and cattle movement data, identifying transmission clusters and inferred rates and routes of transmission of M. bovis. Most trial areas contained a single transmission cluster that had been established shortly before sampling, often contemporaneous with the expansion of bovine tuberculosis in the 1980s. The estimated rate of transmission from badger to cattle was approximately two times higher than from cattle to badger, and the rate of within-species transmission considerably exceeded these for both species. We identified long distance transmission events linked to cattle movement, recurrence of herd breakdown by infection within the same transmission clusters and superspreader events driven by cattle but not badgers. Overall, our data suggests that the transmission clusters in different parts of South West England that are still evident today were established by long-distance seeding events involving cattle movement, not by recrudescence from a long-established wildlife reservoir. Clusters are maintained primarily by within-species transmission, with less frequent spill-over both from badger to cattle and cattle to badger.

genomics↗

bioRxiv2020

Population structure and transmission of Mycobacterium bovis in Ethiopia

Bovine tuberculosis (bTB) is endemic in cattle in Ethiopia, a country that hosts the largest national cattle herd in Africa. The intensive dairy sector, most of which is peri-urban, has the highest prevalence of disease. Previous studies in Ethiopia have demonstrated that the main cause is Mycobacterium bovis (M. bovis), which has been investigated using conventional molecular tools including deletion typing, spoligotyping and Mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR). Here we use whole genome sequencing (WGS) to examine the population structure of M. bovis in Ethiopia. A total of 134 M. bovis isolates were sequenced including 128 genomes from 85 mainly dairy cattle and six genomes isolated from humans, originating from 12 study sites across Ethiopia. These genomes provided a good representation of the previously described population structure of M. bovis, based on spoligotyping and demonstrated that the population is dominated by the clonal complexes African 2 (Af2) and European 3 (Eu3). A range of within-host diversity was observed amongst the isolates and evidence was found for both short- and long-distance transmission. Detailed analysis of available genomes from the Eu3 clonal complex combined with previously published genomes revealed two distinct introductions of this clonal complex into Ethiopia between 1950 and 1987, likely from Europe. This work is important to help better understand bTB transmission in cattle in Ethiopia and can potentially inform national strategies for bTB control in Ethiopia and beyond.

genomics↗

bioRxiv2018

Sparking \"The BBC Four Pandemic\": Leveraging citizen science and mobile phones to model the spread of disease

The nexus of mobile technology, mass media, and public engagement is opening new opportunities for research into the human behaviours relevant to the spread of disease. On 22 March 2018, the British Broadcasting Corporation (BBC) released the documentary "Contagion! The BBC Four Pandemic" to describe the science behind pandemic preparedness in the UK. The authors of this article were responsible for producing a mathematical simulation for that documentary of how a highly contagious respiratory pathogen might spread across the UK. According to the documentary narrative, the outbreak begins in the town of Haslemere, England. To ground the simulation in true human interaction patterns, a three-day citizen science experiment was conducted during which the pairwise distances between 469 volunteers in Haslemere were tracked continuously using a mobile phone app. Here, we offer a scientific companion to the documentary in which we describe the methods behind our simulation and release the pairwise interpersonal distance dataset. We discuss salient features of the dataset, including daily patterns in the clustering and volatility of interpersonal interactions. Our epidemiological analysis of the simulated Haslemere outbreak serves as a springboard to discuss scientific opportunities opened by the Haslemere dataset and others like it. We believe that the Haslemere dataset will productively challenge current strategies for incorporating population structure into disease transmission models, and hope that it will inspire the collection and analysis of other similar datasets in the future.

epidemiology↗

bioRxiv2018

Structure and consistency of self-reported social contact networks in British secondary schools

Self-reported social mixing patterns are commonly used in mathematical models of infectious diseases. It is particularly important to quantify patterns for school-age children given their disproportionate role in transmission, but it remains unclear how the structure of such social interactions changes over time. By integrating data collection into a public engagement programme, we examined self-reported contact networks in year 7 groups in four UK secondary schools. We collected data from 460 unique participants across four rounds of data collection conducted between January and June 2015, with 7,315 identifiable contacts reported in total. Although individual-level contacts varied over the study period, we were able to obtain out-of-sample accuracies of more than 90% and F-scores of 0.49-0.84 when predicting the presence or absence of social contacts between specific individuals across rounds of data collection. Network properties such as clustering and number of communities were broadly consistent within schools between survey rounds, but varied significantly between schools. Networks were assortative according to gender, and to a lesser extent school class, with the estimated clustering coefficient larger among males in all surveyed co-educational schools. Our results demonstrate that it is feasible to collect longitudinal self-reported social contact data from school children and that key properties of these data are consistent between rounds of data collection.

epidemiology↗