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Project properties |
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| Title | Early warning signals of disease using google search behaviour or social media data |
| Group | Aquatic Ecology and Water Quality Management Group |
| Project type | thesis |
| Credits | 24-39 |
| Supervisor(s) | Clara Delecroix (clara.delecroix@wur.nl)
Ingrid Van de Leemput (ingrid.vandeleemput@wur.nl) |
| Examiner(s) | Ingrid van de Leemput |
| Contact info | Clara Delecroix (clara.delecroix@wur.nl)
Ingrid Van de Leemput (ingrid.vandeleemput@wur.nl) Edwin Peeters (edwin.peeters@wur.nl) for general issues on thesis/internship |
| Begin date | 2021/02/22 |
| End date | 2023/12/29 |
| Description | We want to study whether it is possible to detect early-warning signals of upcoming diseases, or disease eradication, in google search behavior and/or social media data. Early warnings signals are indicators of an upcoming sharp change. When a system approaches a critical threshold, we may see minor local outbreaks that take longer to recover. By measuring these rates, and potentially statistical indicators about the correlation structure in timeseries, we might be able to point to the likelihood of un upcoming shift. The student will collect the data, create the datasets, calculate early warning indicators in the dataset and estimate their reliability. |
| Used skills | Literature review, data analysis, modelling |
| Requirements | The student is expected to have experience with Python or another coding language, or be willing to learn |