Forecasting risk of tick-borne encephalitis (TBE): Using data from wildlife and climate to predict next year's number of human victims
(2011) In Scandinavian Journal of Infectious Diseases 43(5). p.366-372- Abstract
- Background: Over the past quarter century, the incidence of tick-borne encephalitis (TBE) has increased in most European nations. However, the number of humans stricken by the disease varies from year to year. A method for predicting major increases and decreases is needed. Methods: We assembled a 25-y database (1984-2008) of the number of human TBE victims and wildlife and climate data for the Stockholm region of Sweden, and used it to create easy-to-use mathematical models that predict increases and decreases in the number of humans stricken by TBE. Results: Our best model, which uses December precipitation and mink (Neovison vison, formerly Mustela vison) bagging figures, successfully predicted every major increase or decrease in TBE... (More)
- Background: Over the past quarter century, the incidence of tick-borne encephalitis (TBE) has increased in most European nations. However, the number of humans stricken by the disease varies from year to year. A method for predicting major increases and decreases is needed. Methods: We assembled a 25-y database (1984-2008) of the number of human TBE victims and wildlife and climate data for the Stockholm region of Sweden, and used it to create easy-to-use mathematical models that predict increases and decreases in the number of humans stricken by TBE. Results: Our best model, which uses December precipitation and mink (Neovison vison, formerly Mustela vison) bagging figures, successfully predicted every major increase or decrease in TBE during the past quarter century, with a minimum of false alarms. However, this model was not efficient in predicting small increases and decreases. Conclusions: Predictions from our models can be used to determine when preventive and adaptive programmes should be implemented. For example, in years when the frequency of TBE in humans is predicted to be high, vector control could be intensified where infested ticks have a higher probability of encountering humans, such as at playgrounds, bathing lakes, barbecue areas and camping facilities. Because our models use only wildlife and climate data, they can be used even when the human population is vaccinated. Another advantage is that because our models employ data from previously-established databases, no additional funding for surveillance is required. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1965176
- author
- Haemig, Paul D. ; de Luna, S. Sjostedt ; Grafstrom, A. ; Lithner, Stefan ; Lundkvist, Ake ; Waldenström, Jonas LU ; Kindberg, Jonas ; Stedt, Johan and Olsen, Bjorn
- organization
- publishing date
- 2011
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- TBE, tick-borne encephalitis, tick-borne diseases, prediction, forecasting, early warning
- in
- Scandinavian Journal of Infectious Diseases
- volume
- 43
- issue
- 5
- pages
- 366 - 372
- publisher
- Informa Healthcare
- external identifiers
-
- wos:000289560500009
- scopus:79954506817
- ISSN
- 1651-1980
- DOI
- 10.3109/00365548.2011.552072
- language
- English
- LU publication?
- yes
- additional info
- The information about affiliations in this record was updated in December 2015. The record was previously connected to the following departments: Animal Ecology (Closed 2011) (011012001)
- id
- 06640a14-4164-4f01-8f10-47b900dd09f7 (old id 1965176)
- date added to LUP
- 2016-04-01 13:45:15
- date last changed
- 2022-01-27 20:53:55
@article{06640a14-4164-4f01-8f10-47b900dd09f7,
abstract = {{Background: Over the past quarter century, the incidence of tick-borne encephalitis (TBE) has increased in most European nations. However, the number of humans stricken by the disease varies from year to year. A method for predicting major increases and decreases is needed. Methods: We assembled a 25-y database (1984-2008) of the number of human TBE victims and wildlife and climate data for the Stockholm region of Sweden, and used it to create easy-to-use mathematical models that predict increases and decreases in the number of humans stricken by TBE. Results: Our best model, which uses December precipitation and mink (Neovison vison, formerly Mustela vison) bagging figures, successfully predicted every major increase or decrease in TBE during the past quarter century, with a minimum of false alarms. However, this model was not efficient in predicting small increases and decreases. Conclusions: Predictions from our models can be used to determine when preventive and adaptive programmes should be implemented. For example, in years when the frequency of TBE in humans is predicted to be high, vector control could be intensified where infested ticks have a higher probability of encountering humans, such as at playgrounds, bathing lakes, barbecue areas and camping facilities. Because our models use only wildlife and climate data, they can be used even when the human population is vaccinated. Another advantage is that because our models employ data from previously-established databases, no additional funding for surveillance is required.}},
author = {{Haemig, Paul D. and de Luna, S. Sjostedt and Grafstrom, A. and Lithner, Stefan and Lundkvist, Ake and Waldenström, Jonas and Kindberg, Jonas and Stedt, Johan and Olsen, Bjorn}},
issn = {{1651-1980}},
keywords = {{TBE; tick-borne encephalitis; tick-borne diseases; prediction; forecasting; early warning}},
language = {{eng}},
number = {{5}},
pages = {{366--372}},
publisher = {{Informa Healthcare}},
series = {{Scandinavian Journal of Infectious Diseases}},
title = {{Forecasting risk of tick-borne encephalitis (TBE): Using data from wildlife and climate to predict next year's number of human victims}},
url = {{http://dx.doi.org/10.3109/00365548.2011.552072}},
doi = {{10.3109/00365548.2011.552072}},
volume = {{43}},
year = {{2011}},
}