51³Ô¹ÏÍø

Department: Pathobiology & Population Sciences

Campus: Hawkshead

Research Groups: Pathogen Flow in Ecosystems, Sustainable Food Systems, Food Safety, Antimicrobial Resistance, Host-Pathogen Interactions and Vaccinology, IRLFS (Research Programme)

Research Centres: Veterinary Epidemiology, Economics and Public Health

Julian is Professor of Veterinary Epidemiological Surveillance within the VEEPH group at the RVC (see our current projects and ). He studies patterns of animal and human diseases; this helps us identify the drivers of disease spread and to improve methods to control diseases. Julian is particularly interested in disease surveillance systems (asking such questions as: which diseases are out there, where are they, and where is the next outbreak of new disease likely to pop up?). He studies uncertainty (how confident are we about what we think we might know) and understanding the effects of biases in decision-making processes for disease management. Julian is an  in Veterinary Epidemiology, and a in Wildlife Population Health. He is the RVC lead for Epidemiological and Statistical Modelling in the WOAH (formerly OIE) Collaborating Centre for Risk Analysis & Modelling, a joint venture with the Animal and Plant Health Agency. From 2018 to 2024 Julian was a scientific expert on the  of the European Food Safety Authority. Find out more about Julian's research in the TB@RVC hub check it out here

Career
2024-date   Professor of Veterinary Epidemiological Suvreillance, RVC
2018-2024  Associate Professor of Veterinary Epidemiology, RVC
2015-2018  Senior Lecturer in Veterinary Epidemiology, RVC
2012-2015  Lecturer in Veterinary Epidemiology, RVC
2010-2012  Postdoctoral research: development of the , RVC/AHVLA
2009-2010  Research Fellow in Veterinary Epidemiology, 51³Ô¹ÏÍø (RVC), London
2005-2008  PhD, University of Cambridge (fieldwork conducted at the in South Africa)
2001-2005  Veterinary surgeon in general practice and a zoo, UK and South Africa

Qualifications and recognitions
2018-2024 Member of the Animal Health and Welfare Panel, European Food Safety Authority
2016 Specialist in Veterinary Epidemiology, Royal College of Veterinary Surgeons 
2014 Postgraduate Certificate in Veterinary Education and Fellow of the Higher Education Academy
2010 Diplomate of the European College of Zoological Medicine in the specialty of Wildlife Population Health
2009 PhD in Veterinary Epidemiology, University of Cambridge
2004 Master of Science in Wild Animal Health, Institute of Zoology and 51³Ô¹ÏÍø
2004 Certificate in Zoological Medicine, Royal College of Veterinary Surgeons
2001 Bachelor of Veterinary Medicine, 51³Ô¹ÏÍø London

I study diseases that spread between humans, domestic animals and wildlife. In our group, we conduct interdisciplinary research which brings together people with different areas of expertise. For example: by combining epidemiology, mathematics and social sciences we can identify risk factors for disease occurence, model the likely impact of inteventions such as vaccination, and understand the impact of human behaviour on disease control.  Find out more about my research in the TB@RVC hub check it out here

My main research Interests are:

  • Surveillance: Designing, evaluating and improving animal and public health surveillance systems
  • Risk analysis: Estimating the likelihood and potential impact of major disease incursions
  • Diagnosis: Developing ways to improve the value of information gained from using diagnostic tests in animal populations

In addition to working with colleagues at the RVC, I am/have been involved in collaborative research projects with scientists at the , UK (TB in meerkats), Animal Health and Veterinary Laboratories Agency, UK (disease surveillance evaluation), , UK (tuberculosis in badgers: important because the same form of TB is found in cattle - read  and ) and the , South Africa (diseases in wild baboons).

PhD supervision
• Current PhD students: (2022-date); Mary Tivey (2019-date); 
• Previous PhD students: Sonny Bacigalupo (2017-2022);  (2017-2022); Stuart Patterson (2013-2017);  (2012-2016).

For an up-to-date list and links, please look at my  and our group's .

Examples of some previous publications:

44. Bacigalupo, S.A., Dixon, L.K., Gubbins, S., Kucharski, A.J. and Drewe, J.A. (2020) PeerJ 8: e10221. doi:
Highlights: Many infectious diseases of people and livestock originate in wild animals. We systematically reviewed the literature to find out which livestock-wildlife contacts have been studied and why, as well as the methods used to observe each species. We found a wide variation and lack of consensus in the definitions of direct and indirect contacts, so we developed a unified framework to define livestock-wildlife contacts that is sufficiently flexible to be applied to most wildlife and livestock species. This framework will help standardise the collection and reporting of contact data; a valuable step towards being able to compare the efficacy of wildlife-livestock observation methods. In doing so, it may aid the development of better disease transmission models and improve the design and effectiveness of interventions to reduce or prevent disease transmission.

43. Chinchio, E., Crotta, M., Romeo, C., Drewe J.A., Guitian, J. and Ferrari, N. (2020) . PLoS Pathogens 16: e1008922. doi:
Highlights: Pandemics such as the coronavirus usually arise from viruses in animals, particuarly wildlife. The world is now so interconnected that diseases can spread and take hold rapidly. People move huge numbers of animals around the world and these animals may themselves become inavsive and host diseases. In order to tackle this problem, a stronger connection between ecologists, biologists, and other people working in the fields of animal and public health and beyond is needed. Only through wider collaboration and dialogue will the potential health impacts of biological invasions be fully appreciated and, perhaps, ameliorated.?

42. Ballesteros, C., Foddai, A., Smith, R.P., Stevens, K. and Drewe, J.A. (2020) . Preventive Veterinary Medicine 182: 105099. doi:
Highlights: Data from diagnostic laboratories are an important source of information for animal health surveillance. But not all samples generate a definite diagnosis. We analysed these “diagnosis not reached” (DNR) data to provide a better understanding about the reasons of this occurrence and to inform improvements of the coverage and reporting of this kind of surveillance data. This is important because it is an early warning system: unexpectedly high occurence of DNR data could indicate the presence of a new or emerging disease in British livestock populations. 

41. Nielsen S, Alvarez J, Bicout D, Calistri P, Depner K, Drewe, J.A., Garin-Bastuji B, Gonzales Rojas JL, Gortazar Schmidt C., Michel V, Miranda MA, Roberts H, Sihvonen L, Stahl K, Calvo AV, Viltrop A, Winckler C, Bett B, Cetre-Sossah. C, Chevalier V, Devos C, Gubbins S, Monaco F, Sotiria-Eleni A, Broglia A, Cortinas Abrahantes J, Dhollander S, Van Der Stede Y and Zancanaro G (2020) EFSA Journal 18:e06041. doi: 
Highlights: Rift Valley Fever (RVF) is caused by a virus that mainly affects animals but can also infect humans if they come into contact with the blood of infected animals, or through bites from infected mosquitoes. RVF is endemic in sub-Saharan Africa and the Arabian Peninsula but currently absent in Europe. Recent outbreaks in a French overseas department and cases in countries close to Europe have raised the possibility of incursion of this disease into EU territory. Improved surveillance and response preparedness is recommended.

40.  Romero, M.P., Chang, Y.-M., Brunton, L.A., Parry, J., Prosser, A., Upton, P., Rees, E., Tearne, O., Arnold, M., Stevens, K. and Drewe, J.A. (2020) . Preventive Veterinary Medicine 175:104860. doi:
Highlights: We apply machine-learning approaches to the national disease dataset to identify risk factors for bovine tuberculosis from webs of causation involving thousands of cattle farms. This information will be useful to help control this hugely problematic disease.

39.  Nielsen S, Alvarez J, Bicout D, Calistri P, Depner K, Drewe, J.A., Garin-Bastuji B, Gonzales Rojas JL, Michel V, Miranda MA, Roberts H, Sihvonen L, Spoolder H, Stahl K, Viltrop A, Winckler C, Boklund A, Bøtner A, Gonzales Rojas J, More S, Thulke H-H, Antoniou S-E, Cortinas Abrahantes J, Dhollander S, Gogin A, Papanikolaou A, Gonzalez Villeta L and Gortazar Schmidt C. (2019) . EFSA Journal 17:e5861. doi:
Highlights: The current African swine fever pandemic poses a huge threat to Europe. This assessment scientifically estimates the potential for the disease to spread across south-eastern Europe. It was requested by the European Commission to support efforts to control and prevent the spread of the disease. Improved surveillance, communication and collaboration will be key to limiting the spread of this disease. More details in 

38.  Comin, A., Grewar, J., van Schaik, G., Schwermer, H., Paré, J., El Allaki, F., Drewe, J.A., Lopez Antunes, A.C., Estberg, L., Horan, H., Calvo-Artavia, F.F., Jibril, A.H., Aviles, M.M., Van der Stede, Y., Antoniou, S. and Lindberg, A. (2019) Frontiers in Veterinary Science 6:426. doi:
Highlights: The objective of this project is to produce a set of reporting guidelines to facilitate consistent and credible reporting of animal health surveillance activities and their outcomes. The rationale behind it is that by moving towards more output−based standards for surveillance, and allowing greater flexibility in surveillance design, there will be an increased need for transparency about design features as well as how the activities are actually implemented. More information in  

37. Peyre, M., Hoinville, L., Njoroge, J., Cameron, A., Traon, D., Goutard, F., Calba, C., Grosbois, V., Delabouglise, A., Varan, V., Drewe, J.A., Pfeiffer, D. and Haesler, B. (2019) Preventive Veterinary Medicine 173:104777. doi:
Highlights: This is the latest version of a framework that we developed to guide the evaluation of animal health surveillance systems.

36. Vergne, T. and Drewe, J.A. (2019) Frontiers in Veterinary Science 6: 310. doi:
Highlights: This is an introduction to a collection of eight papers which explore sources of bias in science and ways of dealing with it.

35. Silk, M.J., Drewe, J.A., Delahay, R.J., Weber, N., Steward, L.C., Wilson-Aggarwal, J., Boots, M., Hodgson, D.J., Croft, D.P. and McDonald, R.A. (2018) . Behaviour 155: 731-757.
Highlights: Identifying when and how diseases pass between species is difficult because you can't see it happening. Here, we present a multilayer network framework to quantify disease transmission between species, by modelling real data on direct and indirect contacts between European badgers and domestic cattle. We include environmental transmission too. This novel network approach can provide general insights into disease transmission in other multi-host disease systems.

34. Nichols, C.P., Gregory, N.G., Goode, N., Gill, R.M.A. and Drewe, J.A. (2018) Journal of Animal Physiology and Animal Nutrition 102: 330-336.
Highlights: Grey squirrels damage trees when they peel the bark off, but we don't know why they do this. It could be becasue they are searching for sugary sap or a source of calcium, or perhaps they just enjoy doing it. As part of his PhD, Chris Nichols investigated whether squirrels can use the calcium found under bark to add to their bone stores of calcium: the answer from this study was no.

33. Buzdugan, S.N., Chambers, M.A., Delahay, R.J. and Drewe, J.A. (2017) . Epidemiology and Infection 145: 3204-3213.
Highlights: Many wild badgers are infected with cattle tuberculosis in the UK. Diagnosing whether a badger is infected is difficult because it is practically difficult to catch and test badgers, and also the diagnostic tests available are not very accurate. Here, we analyse data from a range of badger TB test results. We show that some test results can be used to predict which badgers are most likely to go on to develop advanced disease and become infectious. These findings contribute to a better understanding of disease progression and potentially improved control.

32.   Buzdugan, S.N., Vergne, T., Grosbois, V., Delahay, R.J. and Drewe, J.A. (2017) Scientific Reports 7: 1111. 
Highlights: This is a complicated-sounding paper but its message is quite straightforward. Confidently ascertaining whether an individual is infected can be challenging when diagnostic tests are imperfect and when some individuals go for long periods of time without being observed or sampled (this is what the cryptic bit in the title refers to: for example, nocturnal animals or 'hard-to-reach' people). Here, we present a new approach to diagnosis in which we move from the traditional way (an individual is either infected or uninfected) to a new way in which each individual is given a probability (likelihood) of infection that is constantly updated.This novel approach to combining ecological and epidemiological data is relevant to the diagnosis of diseases in animals and in humans.  

31.   Patterson, S.J., Drewe, J.A., Pfeiffer, D.U. and Clutton-Brock, T.H. (2017) Journal of Animal Ecology 86: 442-450. 
Highlights: Our findings identify characteristics on which to base targeted control measures such as vaccination. Keep your eyes here for updates in the near future as we are currently testing this very approach.

30.   Clarke, C., Patterson, S.J., Drewe, J.A., Van Helden, P.D., Miller, M.A. and Parsons, S.D.C. (2017) BMC Veterinary Research 13: 2.
Highlights: Tests for tuberculosis in most species (inlcuding humans) are imperfect. Here, we develop a new test for detecting TB in meerkats.

29.   Bisdorff, B., Schauer, B., Taylor, N., Rodríguez-Prieto, V., Comin, A., Brouwer, A., Dórea, F., Drewe, J.A., Hoinville, L., Lindberg, A., Martinez Avilés, M., Martínez-López, B., Peyre, M., Pinto-Ferreira, J., Rushton, J. Van Schaik, G., Stärk, K.D.C., Staubach, C., Vicente-Rubiano, M., Witteveen, G., Pfeiffer, D.U., Häsler, B. (2017) Epidemiology and Infection 145: 802-817. 
Highlights: A review of the results of a survey of how surveillance for animal diseases in currently conducted across the EU; identifies opportunities for improvements.

28. Nichols, C.P., Drewe, J.A., Gill, R., Goode, N., Gregory, N. (2016) Forest Ecology and Management. 367: 12-20.
Highlights: Grey squirrels damage trees in the UK by stripping bark and eating the underlying phloem. Squirrel motivation for damage is, however, unknown. Damage can result in deterioration of timber quality and a significant economic toll on the forestry industry. A better understanding of what motivates grey squirrels to strip bark may enable a preventive approach to be developed. This paper reviews the evidence that squirrels damage trees to ameliorate a calcium deficiency.

27. Buzdugan, S.N., Chambers, M.A., Delahay, R.J. and Drewe, J.A. (2016) . Epidemiology and Infection 144: 1717-1727.
Highlights: Current methods for diagnosing tuberculosis (TB) in live badgers are not very accurate. One way to improve this might be to diagnose infection at the group (rather than the individual) level. In this research paper, we model field data spanning 7 years containing over 2000 sampling events from a population of wild badgers in southwest England to quantify the ability to correctly identify the infection status of badgers at the group level. We explore the effects of variations in: (1) trapping efficiency; (2) prevalence of infection; (3) using three diagnostic tests singly and in combination with one another; and (4) the number of badgers required to test positive in order to classify groups as infected. We use our findings to make practical recommendations which may help improve TB diagnosis (and therefore control) in badgers.

26. DelBarco-Trillo, J., Greene, L.K., Goncalves, I.B., Fenkes, M., Wisseb, J.H., Drewe, J.A., Manser, M.A., Clutton-Brock, T.H. and Drea, C.M. (2016) . Hormones & Behavior 78: 95-106. 
Highlights: In male mammals, the hormone testosterone affects reproduction, social dominance, and aggressive behaviour. We examined the effect of temporarily blocking the effect of testosterone in  male meerkats. We found that testosterone plays an important role in mediating social interactions, which in turn has the potential to affect the chances of diseases being transmitted between individuals.

25. Drewe, J.A. (2015) Editorial: Bovine tuberculosis: how likely is a skin test reactor to be uninfected? Veterinary Record 177: 256-257. doi: 10.1136/vr.h4760.

24. Dippenaar, A., Parsons, S.D.C., Sampson, S.L., van der Merwe, R.G., Drewe, J.A., Abdallah, A.M., Siame, K.K., van Pittius, N.C.G., van Helden, P.D., Pain, A. and Warren, R.M. (2015) . Tuberculosis 95: 682-688.
Highlights: We present the entire genetic sequence (the DNA code) from the bacterium which causes tuberculosis (TB) in meerkats in southern Africa, and show how it is related to the bacteria which cause TB in other species.This is a new breakthrough in our understanding of the evolution of this ancient disease.

23. Velasova, M., Drewe, J.A., Gibbons, J., Green, M and Guitian, F.J. (2015) . Veterinary Record doi: 10.1136/vr.103034. 
Highlights: We looked at the ability of 59 existing recording systems to generate accurate and reliable estimates of the frequency of important health conditions in the dairy herd of Great Britain. Johne’s disease, bovine viral diarrhoea, mastitis and lameness were the most commonly recorded conditions, but there were considerable differences in the coverage, implementation and objectives of the systems evaluated. We found that even though the individual systems could provide reliable estimates of dairy health for individual farmers, none of the systems alone could provide accurate and reliable estimates for any of the conditions of interest at national level.

22. O’Hagan, M.J.H., Courcier, E.A., Drewe, J.A., Gordon, A.W, McNair, J. and Abernethy, D.A. (2015) . Preventive Veterinary Medicine 120: 283–290. 
Highlights: This study discovered factors which increase the chance that a cow will test positive for TB. Risk factors apepar to be related to the time since infection, the strength of the challenge of infection and the susceptibility of the animal. These findings are important because the detection of lesions and the confirmation of TB are an integral part of the overall bTB control programme in Northern Ireland. The apparent TB status of an animal can affect the way in which TB breakdowns are managed, since failure to detect visible lesions or the causal bacteria can lead to a less stringent follow-up which may mean the disease is not controlled optimally.

21. Wang, J., Wang, M., Wang, S., Liu, Z., Shen, N., Si, W., Sun, G., Drewe, J.A., Cai, X. (2015) . Emerging Infectious Diseases 21: 677-680. doi: 10.3201/eid2104.141627.
Highlights: We investigated 11 outbreaks of a virus affecting small ruminants in Heilongjiang Province, China in early 2014. We found that the most likely source of the virus that caused these outbreaks was animals introduced from livestock markets. This research is a result of collaborations formed between RVC staff and Chinese researchers during the ongoing , for which RVC is the lead training institution.

20. Drewe, J.A., Haesler, B., Rushton, J. and Staerk, K.D.C. (2014) . Veterinary Record 174: 16. doi: 10.1136/vr.101846. 
Highlights: We developed an inventory of livestock health surveillance programmes in GB in 2011. We found livestock health surveillance funding to be unevenly distributed between species: the vast majority (approximately 94 per cent) was spent on cattle diseases (tuberculosis surveillance accounted for most of this expenditure). Consequently, surveillance an effort in GB appears heavily skewed towards regions with high cattle densities, particularly high-prevalence tuberculosis areas such as the southwest. Also see in the same edition of Vet Record which discusses the importance of this paper's findings.

19. Parsons, S.D.C., Drewe, J.A., Gey van Pittius, N.C., Warren, R.M. and van Helden, P.D. (2013) . Emerging Infectious Diseases 19: 2004-2007.
Highlights: The organism that causes tuberculosis in meerkats (Suricata suricatta) has been poorly characterised. Our genetic analysis showed it to be a new species of bacteria which is epidemiologically and genetically unique. We name this new species as Mycobacterium suricattae.

18. Kukielka, E., Barasona, J.A., Cowie, C.E., Drewe, J.A., Gortazar, C., Cotarelo, I. and Vicente, J. (2013) . Preventive Veterinary Medicine 112: 213–221. 
Highlights: Camera traps were used to record interactions between livestock (cattle and domestic pigs) and wildlife (red deer and wild boar) over 12 months in south-central Spain. Direct contacts between wildlife and livestock were rare but indirect interactions were far more common, which reflects what has been found in other countries (e.g. badgers and cattle in UK: see reference 16 below). Areas near water were a hotspot for interactions between species which suggests that preventing animals from aggregating at such areas might reduce transmission risks of diseases such as bovine tuberculosis.

17. Hoinville, L.J., Alban, L., Drewe, J.A., Gibbens, J., Gustafson, L., Häsler, B., Saegerman, C., Salman, M. and Stärk, K.D.C. (2013) . Preventive Veterinary Medicine 112: 1-12.
Highlights: Widespread movement of animals and their products around the world increases the risk of international disease spread. There is, therefore, a need for exchange between countries of comparable information about disease incidence; the exchange must be based on a common understanding of surveillance approaches and how surveillance systems are designed and implemented. This paper establishes agreed-upon definitions of surveillance terms as a first step in achieving this standardisation, to enhance transparency and confidence in international animal health surveillance.

16. Drewe, J.A., O’Connor, H., Weber, N., McDonald, R.A. and Delahay, R.J. (2013) . Epidemiology and Infection 141: 1467–1475.
Highlights: We investigated interactions between badgers and cattle using automated proximity loggers. Direct contacts between badgers and cattle at pasture were very rare despite ample opportunity for interactions to occur. Indirect interactions (visits to badger latrines by badgers and cattle) were much more frequent than direct contacts. Our findings suggest that indirect contacts might be more important than direct contacts in terms of transmission of diseases such as TB. See also in The Ecologist magazine.

15. Drewe, J.A., Hoinville, L.J., Cook, A.J.C., Floyd, T., Gunn, G. and Stärk, K.D.C. (2013) . Transboundary and Emerging Diseases (62: 33-45, doi: 10.1111/tbed.12063). 
Highlights: Animal health surveillance protects animal and human health. Surveillance systems should be regularly evaluated to determine if they are providing useful information and to identify needed improvements. This paper introduces SERVAL, a SuRveillance EVALuation framework developed at RVC and AHVLA. SERVAL is novel and generic which makes it suitable for the evaluation of any animal health surveillance system. For more information and to download the SERVAL framework free of charge, visit the .

14. Abeyesinghe, S.M., Drewe, J.A., Asher, L., Wathes, C.M. and Collins, L.M. (2013)  Applied Animal Behaviour Science 143: 61-66. 
Highlights: We investigated the possibility that domesticated egg-laying hens form distinct 'friendships' by examining whether or not individual chickens were particular about who they spent most time with. This is not so odd a question as might be thought: in humans and other species, friendships have been shown to enrich life positively, buffer against stressful experiences and even improve reproductive success. However, we found no evidence to suggest that modern hens reared in commercial conditions form such friendships, even when they are housed in small groups where it is possible to know every other bird. So the answer to the question "do hens have best friends?" is: "it seems not"!

13. Drewe, J.A., Weber, N., Carter, S.P., Bearhop, S., Harrison, X.A., Dall, S.R.X., McDonald, R. A. and Delahay, R.J. (2012) . PLoS One 7: e39068. 
Highlights: Automated proximity loggers are increasingly being used to record interactions between animals but their accuracy and reliability remained largely un-assessed until now. We assessed the performance of these devices in the lab and in the field by fitting them to cattle and badgers and using static base stations. We demonstrate how data can be manipulated to ensure it accurately reflects real life. We make five recommendations for the effective use of proximity loggers in future studies.

12. Drewe, J.A., O’Riain, J., Beamish, E., Currie, H. and Parsons, S. (2012) . Emerging Infectious Diseases 18: 298-301. 
Highlights: Baboons on South Africa’s Cape Peninsula come in frequent contact with humans. To determine potential health risks for both species, we screened 27 baboons from 5 troops for 10 infections of public health importance. Most (56%) baboons had antibodies reactive or cross-reactive to human viruses. We conclude that spatial overlap between these species poses low but potential health risks. Read more about this study .

11. Drewe, J.A., Hoinville, L.J., Cook, A.J.C., Floyd, T. and Stärk,

I teach and examine on a range of courses at RVC and beyond:

Undergraduate level
• BSc in Bioveterinary Sciences and BSc in Biological Sciences 
• BVetMed3 (Outbreak investigation)
• BVetMed4 (Disease emergence from wildlife)
• BVetMed5 (Population Medicine and Veterinary Public Health)

Postgraduate level
Julian created and runs the MSc module Principles of Epidemiology and Surveillance which is taken by students from five Masters courses.
•  (MSc course director from 2016 to 2018)
•  by distance learning (also module leader for Surveillance and Investigation of Animal Health)
• MSc in One Health 
• MSc in Wild Animal Biology
• MSc in Wild Animal Health

Residents
I supervise jointly with at the Zoological Society of London. These residencies are 3-year training programmes in the applicatino of epidemiology to free-living wildlife populations.
• (2021-2024)
•  (2018-2022)
•  (2015-2019)

From 2012 to 2020 I taught on the . I also deliver workshops internationally for MSc students.

I collaborate with colleagues working in allied disciplines, for example the Animal and Plant Health Agency, European Food Saftey Authority, Food and Agricultural Organisation of the United Nations, and the World Organisation for Animal Health.

Overview

I run science seminars in local schools to encourage pupils to be interested in careers in science, as part of the RVC outreach programme. School classes curious about science can attend interactive masterclasses that I hold periodically at RVC. A typical topic is 'Deadly contacts: how your social network could trigger the next pandemic'. Contact the if you would like more information.

From 2012 to 2020 I was an international trainer on the . This included field studies and  to explore the interface between animal and public health in China and ways to improve collaboration across disciplines.

Previously I have delivered workshops on epidemiology (including topics such as surveillance, risk analysis and outbreak investigation) at the at the University of Peradeniya in Sri Lanka, and at the Southern African Centre for Infectious Disease Surveillance () summer school in Morogoro, Tanzania. It was great to meet students who attended from across eastern and southern Africa, including: Tanzania, Malawi, Zimbabwe, Mozambique, Zambia, Botswana and Democratic Republic of the Congo.

These workshops link to the RVC's distance learning MSc course in .


Podcasts

  • (April 2014). Highlights: A short interview in which we discuss research we are conducting in Malaysia looking at how land use changes influence the behaviour of wild monkeys and their interactions with humans, with implications for the transmission of infectious diseases such as malaria. This research is funded by a fellowship grant from the London International Development Centre and is being conudcted researchers from the RVC (Julian Drewe and Martha Betson) and the London School of Hygiene and Tropical Medicine (Kimberly Fornace). You can .
  • (January 2010, 6.1MB, MPEG-4, also available via  or the : RVC podcast no. 42). Highlights: Badgers are often blamed for the persistence of tuberculosis in cattle herds in parts of the UK. Here Dr Julian Drewe describes his research on the dynamics of UK badger populations and meerkat communities in Africa and the potential importance of this for the spread of TB within and between species.


Popular articles

How do we solve a problem like tuberculosis in badgers?  I wrote for the American magazine The Wildlife Professional which outlines some ideas.

What do epidemiology conferences have in common with wooden elephants and Marmite? Read  to find out.

  • Epidemiology of Tuberculosis in Cattle

    We study the epidemiology of tuberculosis in cattle using a combination of fieldwork and the analysis of big data. Bovine tuberculosis (bTB) is caused by infection with Mycobacterium bovis. It is the most pressing animal health problem in Great Britain. Around 40,000 cattle test bTB-positive each year and are slaughtered in an effort to control this disease. This comes at a cost to the taxpayer of around £100 million per year in surveillance testing and compensation.


  • Epidemiology of Tuberculosis in Meerkats of the Kalahari

    Research project by the 51³Ô¹ÏÍø investigating the epidemiology of Tuberculosis in meerkats in the Kalahari Desert in southern Africa.

    Meerkats (Suricata suricatta) are social mammals that live in groups. A potential disadvantage of being social is that infectious diseases are more likely to spread. Tuberculosis (TB: a bacterial infection) was first detected in wild meerkats in southern Africa in the late 1990s.


  • Field approaches to identifying tuberculosis in badger populations

    We study the epidemiology of tuberculosis in wild badgers using a combination of fieldwork, laboratory investigations and long-term data analysis.

    Tuberculosis (TB) occurs worldwide and affects many animals (farmed and wild) as well as humans. In cattle, TB is caused by infection with the bacterium Mycobacterium bovis and is sometimes referred to as bovine TB.


  • Improving animal health surveillance through better engagement between farmers, vets and government

    The current research into animal health surveillance has been predominantly focused on improving the technical aspects and there is little work looking at the engagement of stakeholders with the surveillance system. UK scanning surveillance relies on the submission of samples or reports from private veterinary surgeons, which in turn rely on the propensity of farmers to seek veterinary advice. Farmers and veterinary practitioners are therefore at the forefront of disease surveillance and the data being received is shaped by what they perceive to be a threat.


  • Interactions between species: Implications for disease transmission

    A study of the contact patterns between a wide range of species to better understand the risks of disease transmission between livestock, wildlife and people. Many diseases spread between species. Humans are no exception: we share most of our infectious diseases with other hosts. This means we may become infected from other species (for example, catching rabies through being bitten by an infected dog) or we may be the source of infection to other species (for example, spreading antibiotic-resistant bacteria to livestock or pets).


  • SERVAL (SuRveillance EVALuation framework)

    A generic framework for the evaluation of animal health surveillance. SERVAL is based on a conceptual model that can be applied to any surveillance system. A set of 22 system attributes are defined and guidelines to their qualitative and/or quantitative assessment are provided.

    Animal health surveillance programmes are necessary to obtain quality evidence to inform the management of threats to animal and public health. This investment yields benefits for animal owners and for industries including food and leisure that depend upon a healthy animal population.


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