This file was generated on 2026-03-06 by MAUREEN NABATANZI
A GENERAL INFORMATION
1. Title of the dataset: Data for modeling phylogeographic dynamics of Sindbis virus in Africa
2. Brief description of the research project and its aims: This dataset comprises Sindbis virus (SINV) genome sequences, their locations of sample collection, and the ecological variables used to conduct continuous phylogeographic and phylodynamic analysis of SINV dispersal in Africa. There are 23 complete and near-complete SINV genomes sampled across Africa between 1952 and 2022. We provide their alignment file and trait information comprising dates and locations of sampling. Ecological variables comprise 26 potential predictors with suspected associations with viral discovery and dispersal. Sequences and location data were used to generate time-calibrated phylogenies, their spatiotemporal dispersal history, and dispersal dynamics. We assessed the impact of the predictors on viral dispersal position, direction, and velocity. We also provide the results of the modeling as a video animation of the continuous phylogeographic spread of the virus across Africa.
3. Author Information
A. Investigator Contact Information
Name: Maureen Nabatanzi
Institution: Center for Development Research (ZEF), University of Bonn
Address: Genscherallee 3, 53113, Bonn
Email: maureen.nabatanzi@uni-bonn.de; mnabatanzi@musph.ac.ug; mrbnabatanzi@gmail.com
B. Project Supervisor (Principal Investigator) Contact Information
Name: Lisa Biber-Freudenberger
Institution: Center for Development Research (ZEF), University of Bonn
Address: Genscherallee 3, 53113, Bonn
Email: lfreuden@uni-bonn.de
C. In case of questions related to this dataset, please contact:
Name: Maureen Nabatanzi
Institution: Center for Development Research (ZEF), University of Bonn
Address: Genscherallee 3, 53113, Bonn
Email: maureen.nabatanzi@uni-bonn.de; mrbnabatanzi@gmail.com
4. Date of data collection: 2025-08-01 to 2025-12-01
5. Information about funding sources that supported the collection of the data: This study was funded by the German Research Foundation (DFG) under the grant titled “The Effects of Biodiversity loss and Land-Use Change on the Occurrence of Novel Infectious Diseases”, project number 458328858.
6. Language of the dataset: English
7. Geographic location of data collection: Germany
B DATA & FILE OVERVIEW
1. File List:
a) SINV_aligned.fasta
Complete and near-complete genome sequences of SINV sampled in Africa between 1952 and 2022 and downloaded from the National Center for Biotechnology Information (NCBI) on 9/08/2025. They were aligned in MAFFT (version 7), an online multiple sequence alignment program, and can be opened with a text editor and most sequence alignment software.
b) Traits.txt
Traits of the SINV genome sequences given by their NCBI accession number, country and year of sampling, and the coordinates of their sampling in latitude and longitude.
c) 26 Ecological variables:
i. Bio1.tif = Annual Mean Temperature (°C) for 2022
ii. Bio5.tif = Maximum Temperature (°C) of Warmest Month for 2022
iii. Bio12.tif = Annual Precipitation (mm), the sum of 12 months precipitation for 2022
iv. Built.tif = Built-Up areas given by the proportion of the building footprint area within the total size of the grid cell for 2014
v. Humanpop.tif = Human population distribution by number of people per grid cell for 2015
vi. Smod.tif = Human settlement model grid for 2015. Grid cells assigned with 2-digit codes in the following classes: 30 = "Urban Centre"; 23 = "Dense Urban Cluster"; 22 = "Semi-dense Urban Cluster"; 21 = "Suburban or peri-urban grid cells"; 13 = "Rural cluster"; 12 = "Low Density Rural grid cells"; 11 = "Very low density rural grid cells"; 10 = "Water grid cells"
vii. CulexP.tif = Culex pipiens presence for 2015. Values range from highest certainty (4) to least certainty (0) of presence.
viii. CulexU.tif = Culex univittatus presence for 2015. Values range from highest certainty (4) to least certainty (0) of presence.
ix. Mammals.tif = Grid cell values represent the number of mammalian species. Data from International Union for Conservation of Nature (IUCN) are dated April 2013.
x. Wetlands.tif = MCD12Q1_V61 Land Cover Type 1: Annual International Geosphere-Biosphere Programme (IGBP) dataset for 2020; class 11.
xi. Livestock.tif = Livestock density in 2020. Animals or birds/pixel.
xii. Urban.tif = Urban land as unit fraction of grid cell in 2015.
xiii. Cropland.tif = Sum of annual crops, perennial crops, annual crops, perennial crops and nitrogen-fixing crops in 2015.
xiv. Pastureland.tif = Sum of managed pasture and rangeland in 2015
xv. Forest.tif = Sum of forested primary land and potentially forested secondary land in 2015.
xvi. NonForest.tif = Forested primary land and potentially non-forested secondary land in 2015.
xvii. Roads.tif = Total road density in meters per km² in 2018.
xviii. Mining.tif = Land used by mining industry between 2000 - 2017.
xix. GDP.tif = Gross Domestic Product per capita for 2020.
xx. IHR.tif = International Health Regulations (IHR) capacity score given by the electronic IHR States Parties Self-Assessment Annual Reporting Tool (eSPAR). An annual self-assessment of country capacity and compliance with the IHR. eSPAR total average capacity scores for 2020.
xxi. AccessCity.tif = Accessibility as travel time in minutes required to reach the nearest city if walking-only or using motorized transport in 2015.
xxii. AccessHealth.tif = Accessibility as time in walking minutes to nearest healthcare facility in 2015.
xxiii. BII.tif = Biodiversity Intactness Index (BII) are percentage values between 0 and 100, indicating the intactness of the ecosystem in 2020.
xxiv. IBA.tif = Important Bird and Biodiversity Areas (IBAs); boundaries of sites that are significant for the long-term viability of naturally occurring bird populations in 2025.
xxv. KBA.tif = Key Biodiversity Areas (KBA); boundaries of sites of significance for the global persistence of biodiversity in 2025.
xxvi. DistanceKBA.tif = Distance to nearest Key Biodiversity Area created from KBA dataset by computing Euclidean distances from each cell to the nearest KBA cell; 2025.
d) S1_Video.mp4
Video animation of the results of continuous phylogeographic spread of SINV in Africa.
2. Are there multiple versions of the dataset? No
3. Relationship between files:
4. Additional related data collected that was not included in the current data package:
C SHARING/ACCESS INFORMATION
1. Was data derived from another source?: yes
a) CRU-TS 4.09 (Harris et al., 2020) downscaled with WorldClim 2.1 (Fick and Hijmans, 2017). Fick, S.E. and R.J. Hijmans, 2017. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37 (12): 4302-4315.https://www.worldclim.org/data/monthlywth.html
b) Nabatanzi, Maureen, 2026, "Ecological niche and presence maps for Wesselsbron, Sindbis and Middelburg viruses and their vectors in Africa", https://doi.org/10.60507/FK2/FWVXDH, bonndata, v1
c) Center For International Earth Science Information Network-CIESIN-Columbia University. (2018). Gridded Population of the World, Version 4 (GPWv4): Population Count Adjusted to Match 2015 Revision of UN WPP Country Totals, Revision 11 (Version 4.11) [Data set]. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/H4PN93PB Date Accessed: 2025-11-10
d) World Health Organization. IHR eSPAR scores (2020). Available at https://extranet.who.int/e-spar/
e) https://www.nature.com/articles/nature25181
f) BirdLife International (2025) Digital boundaries of Important Bird and Biodiversity Areas (IBAs) and
Key Biodiversity Areas (KBAs) identified for birds. September 2025 version. BirdLife International,
Cambridge, UK. Available at: https://datazone.birdlife.org/contact-us/request-our-data
g) Adriana De Palma; Sara Contu; Gareth E Thomas; Connor Duffin; Sabine Nix; Andy Purvis (2024). The Biodiversity Intactness Index developed by The Natural History Museum, London, v2.1.1 (Open Access, Limited Release) (from The Biodiversity Intactness Index developed by The Natural History Museum, London, v2.1.1 (Open Access, Limited Release)) [Data set resource]. Natural History Museum. https://data.nhm.ac.uk/dataset/bii-developed-by-nhm-v2-1-1-limited-release/resource/c4c281c4-befa-4e1b-a162-ba2f25e5ae82
h) Friedl, M., Sulla-Menashe, D. (2022). MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500m SIN Grid V061. NASA EOSDIS Land Processes Distributed Active Archive Center. Accessed 2025-11-11 from https://doi.org/10.5067/MODIS/MCD12Q1.061. Accessed November 11, 2025.
i) Hurtt, G. C., L. Chini, R. Sahajpal, S. Frolking, B. L. Bodirsky, K. Calvin, J. C. Doelman, J. Fisk, S. Fujimori, K. Klein Goldewijk, T. Hasegawa, P. Havlik, A. Heinimann, F. Humpenöder, J. Jungclaus, J. O. Kaplan, J. Kennedy, T. Krisztin, D. Lawrence, P. Lawrence, L. Ma, O. Mertz, J. Pongratz, A. Popp, B. Poulter, K. Riahi, E. Shevliakova, E. Stehfest, P. Thornton, F. N. Tubiello, D. P. van Vuuren and X. Zhang (2020). "Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6." Geosci. Model Dev. 13(11): 5425-5464.
j) Maus, Victor; da Silva, Dieison M; Gutschlhofer, Jakob; da Rosa, Robson; Giljum, Stefan; Gass, Sidnei L B; Luckeneder, Sebastian; Lieber, Mirko; McCallum, Ian (2022): Global-scale mining polygons (Version 2) [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.942325
k) Kummu, M., Kosonen, M. & Masoumzadeh Sayyar, S. 2025. Downscaled gridded global dataset for gross domestic product (GDP) per capita PPP over 1990–2022. Scientific Data 12: 178. https://doi.org/10.1038/s41597-025-04487-x
l) Joint Research Centre - JRC - European Commission, & Center for International Earth Science Information Network - CIESIN - Columbia University. (2021). Global Human Settlement Layer: Population and Built-Up Estimates, and Degree of Urbanization Settlement Model Grid. Retrieved from: https://doi.org/10.7927/h4154f0w
m) NSAL, F. a. A. O.-. (2024). GLW 4: Gridded Livestock Density (Global - 2020 - 10 km) [mapDigital]. Retrieved from: https://data.apps.fao.org/catalog/iso/9d1e149b-d63f-4213-978b-317a8eb42d02
n) National Center for Biotechnology Information, NCBI Virus [Internet]. National Library of Medicine. 2024. Available from: https://www.ncbi.nlm.nih.gov/labs/virus/vssi/#/virus?SeqType_s=Nucleotide.
2. Licenses/restrictions placed on the data: CC-BY 4.0
3. Links to publications that cite or use the data:
4. Links to other publicly accessible locations of the data:
5. Links/relationships to ancillary datasets:
D METHODOLOGICAL INFORMATION
1. Description of methods used for collection/generation of data:
a) SINV sequences and traits data:
During September 2025, we searched the National Center for Biotechnology Information (NCBI) Virus database to extract SINV sequences and the corresponding coordinates of sampling sites from which the species were identified.
b) Ecological data:
Data were extracted as raster files from various databases listed in the sources.
2. Methods for processing the data:
i. Genome sequences were aligned using MAFFT (version 7), an online multiple sequence alignment program.
ii. All raster files were processed to cover a uniform spatial extent (Africa), with the same projection (EPSG: 4326-WGS 84), resolution (0.00833 × 0.00833 grid cell size where 1-degree latitude ~111.32 km2 per grid), alignment, and GeoTiff format.
3. Instrument- and/or software-specific information needed to interpret the data:
i. R and the packages “sf” and “terra” to process raster data
ii. Phylogenetic analyses require the Bayesian Evolutionary Analysis Sampling Trees (BEAST X version 10.5.0) program and supporting software
iii. R package "seraphim" is needed for phylogeographic analyses
4. People involved in sample collection, processing, analysis and/or submission:
Maureen Nabatanzi was involved in data extraction, analysis, and submission.
5. Describe any quality-assurance procedures performed on the data:
6. Standards and calibration information :
7. Environmental/experimental conditions :
E DATA-SPECIFIC INFORMATION FOR:
1. Variable list including full names and definitions (please spell out abbreviated words) of column headings for tabular data:
The variables are listed as files in section "B DATA & FILE OVERVIEW"
2. Units of measurement used:
3. Missing data codes/symbols:
4. Specialized formats or other abbreviations used: