Skip to main content
×
Home
    • Aa
    • Aa

Integrating serological and genetic data to quantify cross-species transmission: brucellosis as a case study

  • MAFALDA VIANA (a1), GABRIEL M. SHIRIMA (a2), KUNDA S. JOHN (a3), JULIE FITZPATRICK (a4), RUDOVICK R. KAZWALA (a5), JORAM J. BUZA (a2), SARAH CLEAVELAND (a1), DANIEL T. HAYDON (a1) and JO E. B. HALLIDAY (a1)...
Abstract
SUMMARY

Epidemiological data are often fragmented, partial, and/or ambiguous and unable to yield the desired level of understanding of infectious disease dynamics to adequately inform control measures. Here, we show how the information contained in widely available serology data can be enhanced by integration with less common type-specific data, to improve the understanding of the transmission dynamics of complex multi-species pathogens and host communities. Using brucellosis in northern Tanzania as a case study, we developed a latent process model based on serology data obtained from the field, to reconstruct Brucella transmission dynamics. We were able to identify sheep and goats as a more likely source of human and animal infection than cattle; however, the highly cross-reactive nature of Brucella spp. meant that it was not possible to determine which Brucella species (B. abortus or B. melitensis) is responsible for human infection. We extended our model to integrate simulated serology and typing data, and show that although serology alone can identify the host source of human infection under certain restrictive conditions, the integration of even small amounts (5%) of typing data can improve understanding of complex epidemiological dynamics. We show that data integration will often be essential when more than one pathogen is present and when the distinction between exposed and infectious individuals is not clear from serology data. With increasing epidemiological complexity, serology data become less informative. However, we show how this weakness can be mitigated by integrating such data with typing data, thereby enhancing the inference from these data and improving understanding of the underlying dynamics.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle.

      Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Integrating serological and genetic data to quantify cross-species transmission: brucellosis as a case study
      Available formats
      ×
      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about sending content to Dropbox.

      Integrating serological and genetic data to quantify cross-species transmission: brucellosis as a case study
      Available formats
      ×
      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about sending content to Google Drive.

      Integrating serological and genetic data to quantify cross-species transmission: brucellosis as a case study
      Available formats
      ×
Copyright
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Corresponding author
*Corresponding author: Daniel T. Haydon, Boyd Orr Centre for Population and Ecosystem Health, Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK. E-mail: Daniel.Haydon@glasgow.ac.uk
Linked references
Hide All

This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

A. J. Bouley , H. M. Biggs , R. A. Stoddard , A. B. Morrissey , J. A. Bartlett , I. A. Afwamba , V. P. Maro , G. D. Kinabo , W. Saganda , S. Cleaveland and J. A. Crump (2012). Brucellosis among hospitalized febrile patients in Northern Tanzania. American Journal of Tropical Medicine and Hygiene 87, 11051111.

A. T. Gilbert , A. R. Fooks , D. T. Hayman , D. L. Horton , T. Muller , R. Plowright , A. J. Peel , R. Bowen , J. L. Wood , J. Mills , A. A. Cunningham and C. E. Rupprecht (2013). Deciphering serology to understand the ecology of infectious diseases in wildlife. EcoHealth 10, 298313.

J. Godfroid , H. C. Scholz , T. Barbier , C. Nicolas , P. Wattiau , D. Fretin , A. M. Whatmore , A. Cloeckaert , J. M. Blasco , I. Moriyon , C. Saegerman , J. B. Muma , S. Al Dahouk , H. Neubauer and J. J. Letesson (2011). Brucellosis at the animal/ecosystem/human interface at the beginning of the 21st century. Preventive Veterinary Medicine 102, 118131.

G. Jones , W. O. Johnson and W. D. Vink (2009). Evaluating a continuous biomarker for infection by using observed disease status with covariate effects on disease. Journal of the Royal Statistical Society Series C – Applied Statistics 58, 705717.

L. L. Perrett , J. A. McGiven , S. D. Brew and J. A. Stack (2010). Evaluation of competitive ELISA for detection of antibodies to Brucella infection in domestic animals. Croatian Medical Journal 51, 314319.

Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Parasitology
  • ISSN: 0031-1820
  • EISSN: 1469-8161
  • URL: /core/journals/parasitology
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Keywords:

Type Description Title
PDF
Supplementary Materials

Viana supplementary material
Viana supplementary material 1

 PDF (203 KB)
203 KB

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 9
Total number of PDF views: 103 *
Loading metrics...

Abstract views

Total abstract views: 256 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 27th June 2017. This data will be updated every 24 hours.