For the people by the people: citizen science web interface for real-time monitoring of tick risk areas in Finland
Data files
Nov 07, 2023 version files 142.16 KB
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KL_grid_dryad.dbf
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KL_grid_dryad.prj
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KL_grid_dryad.shp
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KL_grid_dryad.shx
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OB_grid_dryad.dbf
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OB_grid_dryad.prj
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OB_grid_dryad.shp
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OB_grid_dryad.shx
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PM_grid_dryad.dbf
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PM_grid_dryad.prj
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PM_grid_dryad.shp
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PM_grid_dryad.shx
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README.md
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tick_data.csv
Abstract
Ticks and tick-borne diseases (TBDs) form a significant and growing threat to human health and well-being in Europe, with increasing numbers of tick-borne encephalitis (TBE) and Lyme borreliosis cases being reported during the past few decades. Increasing knowledge of tick risk areas and seasonal activity remains the primary method for preventing TBDs. Crowdsourcing provides the best alternative for rapidly obtaining data on tick occurrence on a national level.
In order to produce and share up-to-date data about tick risk areas in Finland, an online platform, Punkkilive (www.punkkilive.fi/en), was launched in April 2021. On the website, users can submit and browse tick observations, report tick numbers and hosts, and upload pictures of ticks.
Here, we looked at trends in the crowdsourced data from 2021, assessed the effect of local tick species on seasonality of observations, and examined sampling bias in the data.
The high number of tick observations (n=78 837) highlights that there was demand for such a service. Approximately 97% of 5573 uploaded pictures represented ticks. Seasonal patterns of tick observations varied across Finland, highlighting variability in the risk associated with the two human-biting tick species Ixodes ricinus and I. persulcatus, the latter having a shorter, unimodal activity peak in late spring–early summer. Tick numbers were low and the proportion of new sightings was high in northern Finland, as may be expected near the latitudinal distribution limits of both species. While the number of inhabitants generally explained the number of tick observations well, geographically weighted regression models also identified areas that deviated from this general pattern.
This study offers a prime example of how crowdsourcing can be applied to track vectors of zoonotic diseases, to the benefit of both researchers and the public. Areas with more or fewer observations than predicted based on number of inhabitants were revealed, wherein more specific analyses may reveal factors contributing to lower or higher risk levels that may be used in increasing awareness. We hope that the success of Punkkilive serves to highlight the usefulness of citizen science in the prevention of vector-borne diseases.
README: For the people by the people: citizen science web interface for real-time monitoring of tick risk areas in Finland
https://doi.org/10.5061/dryad.k6djh9wd9
The data set "tick_data.csv" contains crowdsourced tick observation numbers and associated data collected in Finland in 2021. The data was collected through an open website for reporting tick observations in Finland, Punkkilive (www.punkkilive.fi/en). The data is presented on the level of Finnish administrative regions, as it is presented also in the parent manuscript. Data is numbers of tick observations and answers in different categories of questions that are asked when reporting tick observations in Punkkilive.
The shapefile data (e.g., "PM_grid_dryad.sph") contain data that was generated and used in geographically weighted regression models to study observation bias in the parent manuscript. Data used in geographically weighted regression models is tick observations and population density on the grid level (10 x 10 km) in three chosen Finnish administrative regions. Files are named with the abbreviation of the administrative regions, which can be seen in "tick_data.csv".
Description of the data and file structure
"tick_data.cvs" is a simple data set with count data of tick observations and answers to questions asked when reporting tick observations. The columns are:
- region = administrative region of observation within Finland
- acronym = Acronym of the region as written in the manuscript where the data was orinigally used.
- n_jan, n_feb ... n_dec = number of observations recorded in January, February ... December, respectively
- n_tot = annual number of observations
- n_cat = number of observations from cats
- n_dog = number of observations from dogs
- n_oth = number of observations from animals other than cats and dogs
- n_hum = number of observations from humans
- n_pre = number of observations in which the observer had seen ticks in the region of observation before recording the observation in Punkkilive
- n_1 = number of observations reporting 1 tick observed
- n_2 = number of observations reporting 2-5 ticks observed
- n_6 = number of observations reporting >5 ticks observed
The shapefile dataset contains the material used to fit the geographically weighted regression analyses for Kymenlaakso (KL), Pirkanmaa (PM), and
Ostrobothnia (OB) administrative regions. The data are distributed as shapefiles which consist of grids with 10 km x 10 km cell size. The columns of the data are:
* id = running row id
* n_obs = annual number of tick observations within the cell
* pop_size = number of inhabitants in the cell at the year 2016
Sharing/Access information
Data is presented in the parent manuscript in Ecological Solution and Evidence and here.
Methods
The data was collected through an open website for reporting tick observations in Finland, Punkkilive (www.punkkilive.fi/en). Data is presented on the level of Finnish administrative regions, as it is presented also in the manuscript. Data is number of tick observations and answers to different categories of questions that are asked when reporting tick observations. Data used in geographically weighted regression models is tick observations and population density on the grid level (10 x 10 km) in three chosen administrative regions.