Analyzing the Potential Risk of Climate Change on Lyme Disease in Eastern Ontario, Canada Using Time Series Remotely Sensed Temperature Data and Tick Population Modelling
The number of Lyme disease cases (Lyme borreliosis) in Ontario, Canada has increased over the last decade, and that figure is projected to continue to increase. The northern limit of Lyme disease cases has also been progressing northward from the northeastern United States into southeastern Ontario....
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2017-06-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2072-4292/9/6/609 |
| _version_ | 1818083915020107776 |
|---|---|
| author | Angela Cheng Dongmei Chen Katherine Woodstock Nicholas H. Ogden Xiaotian Wu Jianhong Wu |
| author_facet | Angela Cheng Dongmei Chen Katherine Woodstock Nicholas H. Ogden Xiaotian Wu Jianhong Wu |
| author_sort | Angela Cheng |
| collection | DOAJ |
| description | The number of Lyme disease cases (Lyme borreliosis) in Ontario, Canada has increased over the last decade, and that figure is projected to continue to increase. The northern limit of Lyme disease cases has also been progressing northward from the northeastern United States into southeastern Ontario. Several factors such as climate change, changes in host abundance, host and vector migration, or possibly a combination of these factors likely contribute to the emergence of Lyme disease cases in eastern Ontario. This study first determined areas of warming using time series remotely sensed temperature data within Ontario, then analyzed possible spatial-temporal changes in Lyme disease risk in eastern Ontario from 2000 to 2013 due to climate change using tick population modeling. The outputs of the model were validated by using tick surveillance data from 2002 to 2012. Our results indicated areas in Ontario where Lyme disease risk changed from unsustainable to sustainable for sustaining Ixodes scapularis (black-legged tick) populations. This study provides evidence that climate change has facilitated the northward expansion of black-legged tick populations’ geographic range over the past decade. The results demonstrate that remote sensing data can be used to increase the spatial detail for Lyme disease risk mapping and provide risk maps for better awareness of possible Lyme disease cases. Further studies are required to determine the contribution of host migration and abundance on changes in eastern Ontario’s Lyme disease risk. |
| first_indexed | 2024-12-10T19:45:34Z |
| format | Article |
| id | doaj.art-45b7bcf1493d4275b24098aae3a176c5 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-10T19:45:34Z |
| publishDate | 2017-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-45b7bcf1493d4275b24098aae3a176c52022-12-22T01:35:53ZengMDPI AGRemote Sensing2072-42922017-06-019660910.3390/rs9060609rs9060609Analyzing the Potential Risk of Climate Change on Lyme Disease in Eastern Ontario, Canada Using Time Series Remotely Sensed Temperature Data and Tick Population ModellingAngela Cheng0Dongmei Chen1Katherine Woodstock2Nicholas H. Ogden3Xiaotian Wu4Jianhong Wu5Department of Geography and Planning, Queen’s University, Kingston, ON K7L 3N6, CanadaDepartment of Geography and Planning, Queen’s University, Kingston, ON K7L 3N6, CanadaDepartment of Geography and Planning, Queen’s University, Kingston, ON K7L 3N6, CanadaPublic Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, 3200 rue Sicotte, CP 5000, Saint-Hyacinthe, QC J2S 7C6, CanadaDepartment of Mathematics, Shanghai Maritime University, Shanghai 201306, ChinaLaboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, CanadaThe number of Lyme disease cases (Lyme borreliosis) in Ontario, Canada has increased over the last decade, and that figure is projected to continue to increase. The northern limit of Lyme disease cases has also been progressing northward from the northeastern United States into southeastern Ontario. Several factors such as climate change, changes in host abundance, host and vector migration, or possibly a combination of these factors likely contribute to the emergence of Lyme disease cases in eastern Ontario. This study first determined areas of warming using time series remotely sensed temperature data within Ontario, then analyzed possible spatial-temporal changes in Lyme disease risk in eastern Ontario from 2000 to 2013 due to climate change using tick population modeling. The outputs of the model were validated by using tick surveillance data from 2002 to 2012. Our results indicated areas in Ontario where Lyme disease risk changed from unsustainable to sustainable for sustaining Ixodes scapularis (black-legged tick) populations. This study provides evidence that climate change has facilitated the northward expansion of black-legged tick populations’ geographic range over the past decade. The results demonstrate that remote sensing data can be used to increase the spatial detail for Lyme disease risk mapping and provide risk maps for better awareness of possible Lyme disease cases. Further studies are required to determine the contribution of host migration and abundance on changes in eastern Ontario’s Lyme disease risk.http://www.mdpi.com/2072-4292/9/6/609Lyme diseaseclimate changeIxodes scapularisMODIS temperature productremote sensingmathematic population modeling |
| spellingShingle | Angela Cheng Dongmei Chen Katherine Woodstock Nicholas H. Ogden Xiaotian Wu Jianhong Wu Analyzing the Potential Risk of Climate Change on Lyme Disease in Eastern Ontario, Canada Using Time Series Remotely Sensed Temperature Data and Tick Population Modelling Remote Sensing Lyme disease climate change Ixodes scapularis MODIS temperature product remote sensing mathematic population modeling |
| title | Analyzing the Potential Risk of Climate Change on Lyme Disease in Eastern Ontario, Canada Using Time Series Remotely Sensed Temperature Data and Tick Population Modelling |
| title_full | Analyzing the Potential Risk of Climate Change on Lyme Disease in Eastern Ontario, Canada Using Time Series Remotely Sensed Temperature Data and Tick Population Modelling |
| title_fullStr | Analyzing the Potential Risk of Climate Change on Lyme Disease in Eastern Ontario, Canada Using Time Series Remotely Sensed Temperature Data and Tick Population Modelling |
| title_full_unstemmed | Analyzing the Potential Risk of Climate Change on Lyme Disease in Eastern Ontario, Canada Using Time Series Remotely Sensed Temperature Data and Tick Population Modelling |
| title_short | Analyzing the Potential Risk of Climate Change on Lyme Disease in Eastern Ontario, Canada Using Time Series Remotely Sensed Temperature Data and Tick Population Modelling |
| title_sort | analyzing the potential risk of climate change on lyme disease in eastern ontario canada using time series remotely sensed temperature data and tick population modelling |
| topic | Lyme disease climate change Ixodes scapularis MODIS temperature product remote sensing mathematic population modeling |
| url | http://www.mdpi.com/2072-4292/9/6/609 |
| work_keys_str_mv | AT angelacheng analyzingthepotentialriskofclimatechangeonlymediseaseineasternontariocanadausingtimeseriesremotelysensedtemperaturedataandtickpopulationmodelling AT dongmeichen analyzingthepotentialriskofclimatechangeonlymediseaseineasternontariocanadausingtimeseriesremotelysensedtemperaturedataandtickpopulationmodelling AT katherinewoodstock analyzingthepotentialriskofclimatechangeonlymediseaseineasternontariocanadausingtimeseriesremotelysensedtemperaturedataandtickpopulationmodelling AT nicholashogden analyzingthepotentialriskofclimatechangeonlymediseaseineasternontariocanadausingtimeseriesremotelysensedtemperaturedataandtickpopulationmodelling AT xiaotianwu analyzingthepotentialriskofclimatechangeonlymediseaseineasternontariocanadausingtimeseriesremotelysensedtemperaturedataandtickpopulationmodelling AT jianhongwu analyzingthepotentialriskofclimatechangeonlymediseaseineasternontariocanadausingtimeseriesremotelysensedtemperaturedataandtickpopulationmodelling |