Semi-supervised water tank detection to support vector control of emerging infectious diseases transmitted by Aedes Aegpyti [Research Data] (doi:10.11588/data/7LLXFP)

View:

Part 1: Document Description
Part 2: Study Description
Part 5: Other Study-Related Materials
Entire Codebook

(external link)

Document Description

Citation

Title:

Semi-supervised water tank detection to support vector control of emerging infectious diseases transmitted by Aedes Aegpyti [Research Data]

Identification Number:

doi:10.11588/data/7LLXFP

Distributor:

heiDATA

Date of Distribution:

2023-04-17

Version:

1

Bibliographic Citation:

Knoblauch, Steffen; Li, Hao; Lautenbach, Sven; Elshiaty, Yara; Rocha, Antônio A. de A.; Resch, Bernd; Arifi, Dorian; Jänisch, Thomas; Ivonne Morales; Zipf, Alexander, 2023, "Semi-supervised water tank detection to support vector control of emerging infectious diseases transmitted by Aedes Aegpyti [Research Data]", https://doi.org/10.11588/data/7LLXFP, heiDATA, V1

Study Description

Citation

Title:

Semi-supervised water tank detection to support vector control of emerging infectious diseases transmitted by Aedes Aegpyti [Research Data]

Identification Number:

doi:10.11588/data/7LLXFP

Authoring Entity:

Knoblauch, Steffen (GIScience Chair, Institute of Geography, Heidelberg University, 69120 Heidelberg, Germany)

Li, Hao (Professorship of Big Geospatial Data Management, Technical University of Munich (TUM), Munich, Germany)

Lautenbach, Sven (GIScience Chair, Institute of Geography, Heidelberg University, 69120 Heidelberg, Germany)

Elshiaty, Yara (GIScience Chair, Institute of Geography, Heidelberg University, 69120 Heidelberg, Germany)

Rocha, Antônio A. de A. (Institute of Computing, Fluminense Federal University (UFF), Niterói, Brazil)

Resch, Bernd (Department of Geoinformatics, University of Salzburg,Salzburg, Austria)

Arifi, Dorian (Department of Geoinformatics, University of Salzburg,Salzburg, Austria)

Jänisch, Thomas (Colorado School of Public Health, Boulder, USA)

Ivonne Morales (Department of Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany)

Zipf, Alexander (GIScience Chair, Institute of Geography, Heidelberg University, 69120 Heidelberg, Germany)

Producer:

Knoblauch, Steffen

Date of Production:

2022

Grant Number:

451956976

Distributor:

heiDATA

Access Authority:

Knoblauch, Steffen

Holdings Information:

https://doi.org/10.11588/data/7LLXFP

Study Scope

Keywords:

Earth and Environmental Sciences, single shot detection network, urban epidemiology, water tank labels, aedes aegypti breeding site, Rio de Janeiro

Topic Classification:

Eco-epidemiology

Abstract:

WATER TANK DETECTION MODEL OF JOURNAL PAPER (Semi-supervised water tank detection to support vector control of emerging infectious diseases transmitted by Aedes Aegypti) The disease transmitting mosquito Aedes Aegypti is an increasing global threat. It breeds in small artificial containers such as rainwater tanks and can be characterized by a short flight range. The resulting high spatial variability of abundance is challenging to model. Therefore, we tested an approach to map water tank density as a spatial proxy for urban Aedes Aegypti habitat suitability. Water tank density mapping was performed by a semi-supervised self-training approach based on open accessible satellite imagery for the city of Rio de Janeiro. We ran a negative binomial generalized linear regression model to evaluate the statistical significance of water tank density for modeling inner-urban Aedes Aegypti distribution measured by an entomological surveillance system between January 2019 and December 2021. Our proposed semi-supervised model outperformed a supervised model for water tank detection with respect to the F1-score by 22%. Water tank density was a significant predictor for the mean eggs per trap rate of Aedes Aegypti. This shows the potential of the proposed indicator to enrich urban entomological surveillance systems to plan more targeted vector control interventions, presumably leading to less infectious rates of dengue, zika, and chikungunya in the future.

Country:

Brazil

Geographic Coverage:

Rio de Janeior, Rio de Janeiro

Geographic Unit(s):

200 meter

Geographic Bounding Box:

  • West Bounding Longitude: -43.7981573947594498
  • East Bounding Longitude: -43.0978356028405827
  • South Bounding Latitude: -23.0792075061769886
  • North Bounding Latitude: -22.7395994043423606

Methodology and Processing

Sources Statement

Data Access

Other Study Description Materials

Related Publications

Citation

Title:

Knoblauch, S., Li, H., Lautenbach, S., Elshiaty, Y., Rocha, A. A. D. A., Resch, B., Arifi, D., Jänisch, T., Morales, I., & Zipf, A. (2023). Semi-supervised water tank detection to support vector control of emerging infectious diseases transmitted by Aedes Aegypti. International Journal of Applied Earth Observation and Geoinformation, 119, 103304.

Identification Number:

https://doi.org/10.1016/j.jag.2023.103304

Bibliographic Citation:

Knoblauch, S., Li, H., Lautenbach, S., Elshiaty, Y., Rocha, A. A. D. A., Resch, B., Arifi, D., Jänisch, T., Morales, I., & Zipf, A. (2023). Semi-supervised water tank detection to support vector control of emerging infectious diseases transmitted by Aedes Aegypti. International Journal of Applied Earth Observation and Geoinformation, 119, 103304.

Other Study-Related Materials

Label:

water_tank_density.tif

Text:

200m water tank count above 90 percent confidence score in raster format with georeferenzed units

Notes:

image/tiff

Other Study-Related Materials

Label:

water_tank_detection_model.zip

Text:

water tank detection model SSST_50

Notes:

application/zip

Other Study-Related Materials

Label:

water_tank_labels.geojson

Text:

manually labelled water tank used for training and testing the water tank detection model for Rio de Janeiro

Notes:

application/geo+json