European projections of West Nile virus transmission under climate change scenarios
(2023) In One Health 16.- Abstract
West Nile virus (WNV), a mosquito-borne zoonosis, has emerged as a disease of public health concern in Europe. Recent outbreaks have been attributed to suitable climatic conditions for its vectors favoring transmission. However, to date, projections of the risk for WNV expansion under climate change scenarios is lacking. Here, we estimate the WNV-outbreaks risk for a set of climate change and socioeconomic scenarios. We delineate the potential risk-areas and estimate the growth in the population at risk (PAR). We used supervised machine learning classifier, XGBoost, to estimate the WNV-outbreak risk using an ensemble climate model and multi-scenario approach. The model was trained by collating climatic, socioeconomic, and reported... (More)
West Nile virus (WNV), a mosquito-borne zoonosis, has emerged as a disease of public health concern in Europe. Recent outbreaks have been attributed to suitable climatic conditions for its vectors favoring transmission. However, to date, projections of the risk for WNV expansion under climate change scenarios is lacking. Here, we estimate the WNV-outbreaks risk for a set of climate change and socioeconomic scenarios. We delineate the potential risk-areas and estimate the growth in the population at risk (PAR). We used supervised machine learning classifier, XGBoost, to estimate the WNV-outbreak risk using an ensemble climate model and multi-scenario approach. The model was trained by collating climatic, socioeconomic, and reported WNV-infections data (2010−22) and the out-of-sample results (1950–2009, 2023–99) were validated using a novel Confidence-Based Performance Estimation (CBPE) method. Projections of area specific outbreak risk trends, and corresponding population at risk were estimated and compared across scenarios. Our results show up to 5-fold increase in West Nile virus (WNV) risk for 2040-60 in Europe, depending on geographical region and climate scenario, compared to 2000-20. The proportion of disease-reported European land areas could increase from 15% to 23-30%, putting 161 to 244 million people at risk. Across scenarios, Western Europe appears to be facing the largest increase in the outbreak risk of WNV. The increase in the risk is not linear but undergoes periods of sharp changes governed by climatic thresholds associated with ideal conditions for WNV vectors. The increased risk will require a targeted public health response to manage the expansion of WNV with climate change in Europe.
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- author
- Farooq, Zia ; Sjödin, Henrik LU ; Semenza, Jan C. ; Tozan, Yesim ; Sewe, Maquines Odhiambo ; Wallin, Jonas LU and Rocklöv, Joacim
- organization
- publishing date
- 2023-06
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Artificial intelligence, Climate change, Climate impacts, Confidence-based performance estimation (CBPE) method, Europe, West Nile virus, WNV risk projections, XGBoost, Zoonoses
- in
- One Health
- volume
- 16
- article number
- 100509
- publisher
- Elsevier
- external identifiers
-
- scopus:85148667157
- pmid:37363233
- ISSN
- 2352-7714
- DOI
- 10.1016/j.onehlt.2023.100509
- language
- English
- LU publication?
- yes
- id
- b615b399-6b67-473d-8875-55aae184bddf
- date added to LUP
- 2023-03-20 08:28:06
- date last changed
- 2024-06-15 03:18:41
@article{b615b399-6b67-473d-8875-55aae184bddf,
abstract = {{<p>West Nile virus (WNV), a mosquito-borne zoonosis, has emerged as a disease of public health concern in Europe. Recent outbreaks have been attributed to suitable climatic conditions for its vectors favoring transmission. However, to date, projections of the risk for WNV expansion under climate change scenarios is lacking. Here, we estimate the WNV-outbreaks risk for a set of climate change and socioeconomic scenarios. We delineate the potential risk-areas and estimate the growth in the population at risk (PAR). We used supervised machine learning classifier, XGBoost, to estimate the WNV-outbreak risk using an ensemble climate model and multi-scenario approach. The model was trained by collating climatic, socioeconomic, and reported WNV-infections data (2010−22) and the out-of-sample results (1950–2009, 2023–99) were validated using a novel Confidence-Based Performance Estimation (CBPE) method. Projections of area specific outbreak risk trends, and corresponding population at risk were estimated and compared across scenarios. Our results show up to 5-fold increase in West Nile virus (WNV) risk for 2040-60 in Europe, depending on geographical region and climate scenario, compared to 2000-20. The proportion of disease-reported European land areas could increase from 15% to 23-30%, putting 161 to 244 million people at risk. Across scenarios, Western Europe appears to be facing the largest increase in the outbreak risk of WNV. The increase in the risk is not linear but undergoes periods of sharp changes governed by climatic thresholds associated with ideal conditions for WNV vectors. The increased risk will require a targeted public health response to manage the expansion of WNV with climate change in Europe.</p>}},
author = {{Farooq, Zia and Sjödin, Henrik and Semenza, Jan C. and Tozan, Yesim and Sewe, Maquines Odhiambo and Wallin, Jonas and Rocklöv, Joacim}},
issn = {{2352-7714}},
keywords = {{Artificial intelligence; Climate change; Climate impacts; Confidence-based performance estimation (CBPE) method; Europe; West Nile virus; WNV risk projections; XGBoost; Zoonoses}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{One Health}},
title = {{European projections of West Nile virus transmission under climate change scenarios}},
url = {{http://dx.doi.org/10.1016/j.onehlt.2023.100509}},
doi = {{10.1016/j.onehlt.2023.100509}},
volume = {{16}},
year = {{2023}},
}