Postal survey of contacts between cattle farms on the Isle of Lewis

The British Cattle Movement Service (BCMS) database contains an unprecedented quantity of data on the movement of cattle within the UK. These data may be used to construct models of the contact structure of the UK cattle herd, for epidemiological purposes. There are two significant potential sources of inaccuracy within such models: movements that are not reported or are reported inaccurately to the BCMS, and contacts between farms that might transmit infection, but are not animal movements. This field study addressed these issues. Cattle farmers on the Isle of Lewis were recruited with the assistance of the local veterinary surgeon, and asked to record a range of potential risk behaviours for a one-month period. They were also asked questions about husbandry practices on their farm. Comparison of the BCMS contact data with that reported by Lewis' farmers highlighted use of common grazing land as a significant source of contact, and potential disease transmission, between cattle that currently goes unreported; around half of responding holdings on Lewis use common grazing land at some point during the year, and these movements are not reported to the BCMS

Construction of networks with intrinsic temporal structure from UK cattle movement data.

BACKGROUND: The implementation of national systems for recording the movements of cattle between agricultural holdings in the UK has enabled the development and parameterisation of network-based models for disease spread. These data can be used to form a network in which each cattle-holding location is represented by a single node and links between nodes are formed if there is a movement of cattle between them in the time period selected. However, this approach loses information on the time sequence of events thus reducing the accuracy of model predictions. In this paper, we propose an alternative way of structuring the data which retains information on the sequence of events but which still enables analysis of the structure of the network. The fundamental feature of this network is that nodes are not individual cattle-holding locations but are instead direct movements between pairs of locations. Links are made between nodes when the second node is a subsequent movement from the location that received the first movement. RESULTS: Two networks are constructed assuming (i) a 7-day and (ii) a 14-day infectious period using British Cattle Movement Service (BCMS) data from 2004 and 2005. During this time period there were 4,183,670 movements that could be derived from the database. In both networks over 98% of the connected nodes formed a single giant weak component. Degree distributions show scale-free behaviour over a limited range only, due to the heterogeneity of locations: farms, markets, shows, abattoirs. Simulation of the spread of disease across the networks demonstrates that this approach to restructuring the data enables efficient comparison of the impact of transmission rates on disease spread. CONCLUSION: The redefinition of what constitutes a node has provided a means to simulate disease spread using all the information available in the BCMS database whilst providing a network that can be described analytically. This will enable the construction of generic networks with similar properties with which to assess the impact of small changes in network structure on disease dynamics.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Predicting the potential for spread of emerald ash borer ( Agrilus planipennis ) in Great Britain: What can we learn from other affected areas?

Funder: United Kingdom Government Department for Environment, Food and Rural AffairsSocietal Impact Statement: Emerald ash borer (EAB) is thought to have arrived in North America and European Russia at least 10 years prior to detection. Despite heightened awareness that EAB could invade Great Britain (GB), detection in the early stages of establishment is difficult, and initial symptoms might be mistaken for Chalara ash dieback. Our results suggest that if partial resistance to EAB in Fraxinus excelsior does not significantly dampen EAB population dynamics, then EAB could establish and spread across large parts of southern England within a relatively short time period; however, further northern spread may be limited by the relatively cool climate. Summary: The accidental introduction of emerald ash borer (EAB) to North America and European Russia in the 1990s has resulted in an ongoing crisis with millions of ash trees damaged and killed at immense economic and social cost. Improving our understanding of how rapidly the pest might spread should it enter Great Britain (GB) plays an essential part in planning for a potential outbreak. Two metrics are used to investigate the potential dynamics of EAB in GB: the observed rate of spread in the North American and Russian regions; and the relationship between degree days and emergence that may determine environmental suitability and whether the life cycle is univoltine or semivoltine. The pest is still spreading in North America and European Russia with an overall average rate of spread between 2002 and 2018 of approximately 50 km a year. Early detection of the pest is difficult, but a similar delay in detection to that in North America would result in a costly and hard to control outbreak. Comparison of degree days between regions suggests that a semivoltine life cycle is most likely in most areas of GB but spread maybe limited by the relatively cool climate in parts of GB. There are several potentially important differences in the biophysical environment in GB compared with North America and European Russia. However, the speed with which it has invaded these areas highlights the need for early surveillance and mitigations to minimise human‐mediated spread of this highly destructive pest

Assessing the role of contact tracing in a suspected H7N2 influenza A outbreak in humans in Wales.

BACKGROUND: The detailed analysis of an outbreak database has been undertaken to examine the role of contact tracing in controlling an outbreak of possible avian influenza in humans. The outbreak, initiating from the purchase of infected domestic poultry, occurred in North Wales during May and June 2007. During this outbreak, extensive contact tracing was carried out. Following contact tracing, cases and contacts believed to be at risk of infection were given treatment/prophylaxis. METHODS: We analyse the database of cases and their contacts identified for the purposes of contact tracing in relation to both the contact tracing burden and effectiveness. We investigate the distribution of numbers of contacts identified, and use network structure to explore the speed with which treatment/prophylaxis was made available and to estimate the risk of transmission in different settings. RESULTS: Fourteen cases of suspected H7N2 influenza A in humans were associated with a confirmed outbreak among poultry in May-June 2007. The contact tracing dataset consisted of 254 individuals (cases and contacts, of both poultry and humans) who were linked through a network of social contacts. Of these, 102 individuals were given treatment or prophylaxis. Considerable differences between individuals' contact patterns were observed. Home and workplace encounters were more likely to result in transmission than encounters in other settings. After an initial delay, while the outbreak proceeded undetected, contact tracing rapidly caught up with the cases and was effective in reducing the time between onset of symptoms and treatment/prophylaxis. CONCLUSIONS: Contact tracing was used to link together the individuals involved in this outbreak in a social network, allowing the identification of the most likely paths of transmission and the risks of different types of interactions to be assessed. The outbreak highlights the substantial time and cost involved in contact tracing, even for an outbreak affecting few individuals. However, when sufficient resources are available, contact tracing enables cases to be identified before they result in further transmission and thus possibly assists in preventing an outbreak of a novel virus.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Challenges on the interaction of models and policy for pandemic control.

The COVID-19 pandemic has seen infectious disease modelling at the forefront of government decision-making. Models have been widely used throughout the pandemic to estimate pathogen spread and explore the potential impact of different intervention strategies. Infectious disease modellers and policymakers have worked effectively together, but there are many avenues for progress on this interface. In this paper, we identify and discuss seven broad challenges on the interaction of models and policy for pandemic control. We then conclude with suggestions and recommendations for the future

Estimating expansion of the range of oak processionary moth ( Thaumetopoea processionea ) in the UK from 2006 to 2019

Funder: Department for Environment, Food and Rural Affairs, UK GovernmentAbstract: The expansion of oak processionary moth (OPM) in South‐East England continues despite ongoing efforts to control the pest since its introduction in 2006. Using locations of OPM larval nests, supplied by the Forestry Commission and recorded as part of ongoing surveillance and control measures from 2006 onwards, we show that the expansion of the range of OPM in South‐East England up to 2019 was biphasic with a higher rate of expansion from 2015 onwards. The maximum rate of OPM range expansion in the United Kingdom from 2006 to 2014 was estimated as 1.66 km/year (95% CI = [1.22, 2.09]), whereas the 2015–2019 expansion rate was estimated as 6.17 km/year (95% CI = [5.49, 6.84]). This corresponds to an estimated species range distribution area of 7077 km2 in 2019. To explain the faster expansion of OPM range from 2015 onwards, we discuss potential reasons that include: natural capability of species of both short‐ and long‐distance dispersal; external factors such as environmental heterogeneity; a reduction of active control

Key questions for modelling COVID-19 exit strategies

Combinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement lockdown exit strategies that allow restrictions to be relaxed while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, will allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. The roadmap requires a global collaborative effort from the scientific community and policy-makers, and is made up of three parts: i) improve estimation of key epidemiological parameters; ii) understand sources of heterogeneity in populations; iii) focus on requirements for data collection, particularly in Low-to-Middle-Income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health

Meticillin-resistant Staphylococcus aureus with a novel mecA homologue in human and bovine populations in the UK and Denmark: a descriptive study

SummaryBackgroundAnimals can act as a reservoir and source for the emergence of novel meticillin-resistant Staphylococcus aureus (MRSA) clones in human beings. Here, we report the discovery of a strain of S aureus (LGA251) isolated from bulk milk that was phenotypically resistant to meticillin but tested negative for the mecA gene and a preliminary investigation of the extent to which such strains are present in bovine and human populations.MethodsIsolates of bovine MRSA were obtained from the Veterinary Laboratories Agency in the UK, and isolates of human MRSA were obtained from diagnostic or reference laboratories (two in the UK and one in Denmark). From these collections, we searched for mecA PCR-negative bovine and human S aureus isolates showing phenotypic meticillin resistance. We used whole-genome sequencing to establish the genetic basis for the observed antibiotic resistance.FindingsA divergent mecA homologue (mecALGA251) was discovered in the LGA251 genome located in a novel staphylococcal cassette chromosome mec element, designated type-XI SCCmec. The mecALGA251 was 70% identical to S aureus mecA homologues and was initially detected in 15 S aureus isolates from dairy cattle in England. These isolates were from three different multilocus sequence type lineages (CC130, CC705, and ST425); spa type t843 (associated with CC130) was identified in 60% of bovine isolates. When human mecA-negative MRSA isolates were tested, the mecALGA251 homologue was identified in 12 of 16 isolates from Scotland, 15 of 26 from England, and 24 of 32 from Denmark. As in cows, t843 was the most common spa type detected in human beings.InterpretationAlthough routine culture and antimicrobial susceptibility testing will identify S aureus isolates with this novel mecA homologue as meticillin resistant, present confirmatory methods will not identify them as MRSA. New diagnostic guidelines for the detection of MRSA should consider the inclusion of tests for mecALGA251.FundingDepartment for Environment, Food and Rural Affairs, Higher Education Funding Council for England, Isaac Newton Trust (University of Cambridge), and the Wellcome Trust

Construction of networks with intrinsic temporal structure from UK cattle movement data.

BACKGROUND: The implementation of national systems for recording the movements of cattle between agricultural holdings in the UK has enabled the development and parameterisation of network-based models for disease spread. These data can be used to form a network in which each cattle-holding location is represented by a single node and links between nodes are formed if there is a movement of cattle between them in the time period selected. However, this approach loses information on the time sequence of events thus reducing the accuracy of model predictions. In this paper, we propose an alternative way of structuring the data which retains information on the sequence of events but which still enables analysis of the structure of the network. The fundamental feature of this network is that nodes are not individual cattle-holding locations but are instead direct movements between pairs of locations. Links are made between nodes when the second node is a subsequent movement from the location that received the first movement. RESULTS: Two networks are constructed assuming (i) a 7-day and (ii) a 14-day infectious period using British Cattle Movement Service (BCMS) data from 2004 and 2005. During this time period there were 4,183,670 movements that could be derived from the database. In both networks over 98% of the connected nodes formed a single giant weak component. Degree distributions show scale-free behaviour over a limited range only, due to the heterogeneity of locations: farms, markets, shows, abattoirs. Simulation of the spread of disease across the networks demonstrates that this approach to restructuring the data enables efficient comparison of the impact of transmission rates on disease spread. CONCLUSION: The redefinition of what constitutes a node has provided a means to simulate disease spread using all the information available in the BCMS database whilst providing a network that can be described analytically. This will enable the construction of generic networks with similar properties with which to assess the impact of small changes in network structure on disease dynamics.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are