Use Case Overview (Demo Template)

NOTE: This Use Case Summary serves as a template for documenting research workflows. As an example - dengue outbreak risk assessment in Ghana - this Markdown-based approach enables teams to collaboratively define data requirements, harmonization strategies, and analysis plans. This example is illustrative and not validated. Looking ahead, we aim to integrate automated documentation tools that generate summaries directly from curated metadata, reducing manual effort and ensuring consistency across use cases.

1. Use Case Specification


Disease under study	Arboviral diseases
Spatial coverage	Ghana (GHA)
Highest-level shape	Country (admin0)
Lowest-level	District (admin2)
Resolution applicable to use case	Region (admin1)
Temporal coverage	2020-01-01 - 2025-12-31
Highest-level	Year
Lowest-level	Day
Resolution applicable to use case	Month
Maintenance & Updates
Update frequency	[e.g., ad-hoc / weekly / monthly / annually]
Responsible	[Team member(s)]

2. Data Requirements

Original data shall be uploaded here:

Link: [URL]

Avoid pre-processing original data to match use-case resolution. Instead, provide data at its native resolution. The Data Hub handles aggregation and harmonization automatically, allowing us to apply different strategies depending on the use case
Do not clean your datasets for spatial boundary changes; document any changes you encounter instead (to be added in the Data Layer metadata). The Data Hub is developing centralized handling for spatial mismatches across all layers, so these issues can be addressed consistently platform-wide

Data Requirements	Spatial smallest	Temporal smallest	Study Data	Open Data

EPIDEMIOLOGICAL DATA	NO identifiable/sensitive data!
Dengue cases	District	Year	collection ongoing	`litdata_denv_lim2025`
Dengue transmission suitability	District	Year	--	`litmod_dcz_lim2025`
Aedes-borne virus transmission suitability	District	Year	--	`litmod_denv_lim2025`

DEMOGRAPHIC & SOCIO-ECONOMIC
Population count	District	Year	--	`worldpop_popc`
Population density	District	Year	--	`worldpop_popd`
Wealth index (Gini)	Region	Year	--	`dhs_gini`

ANIMAL DATA	NO identifiable/sensitive data!
Livestock density cattle	District	Year	--	`fao_livestock_cattle`
Livestock density sheep	District	Year	--	`fao_livestock_sheep`
Livestock density goat	District	Year	--	`fao_livestock_goat`

ENTOMOLOGICAL DATA
Aedes aegypti abundance	--	--	--	under review

WEATHER AND CLIMATIC DATA
Temperature max (EO)	District	Day	--	`era5_tmax`
Temperature max (station)	District	Day	--	`meteo_tmax`
Temperature min (EO)	District	Day	--	`era5_tmin`
Temperature min (station)	District	Day	--	`meteo_tmin`
Temperature mean (EO)	District	Day	--	`era5_tavg`
Temperature mean (station)	District	Day	--	`meteo_tavg`
Precipitation sum (EO)	District	Day	--	`era5_prcp`
Precipitation sum (station)	District	Day	--	`meteo_prcp`
ENSO seasons	--	--	--	under review

ENVIRONMENTAL DATA
Geographic area	--	--	--	under review
Elevation	District	Year	--	`worldpop_elevation`
Urban land cover	District	Year	--	`copernicus_built`
Forest land cover	District	Year	--	`copernicus_forest`
Cropland land cover	District	Year	--	`copernicus_crop`
Water bodies land cover	District	Year	--	`copernicus_water`

INFRASTRUCTURE
Health facilities	District	Year	--	`healthsitesio_facilities`
Travel time to nearest health facility	District	Year	--	`malariaatlas_traveltimehc`
Hospital bed capacity	Country	Year	--	`who_physdens`
Physicians capacity	Country	Year	--	`who_hospbeddens`
Nurses and midwifes capacity	Country	Year	--	`who_nursmidwdens`

3. Access Methods


Shapefiles
API	template available for Python and R
Downloables	GeoPackage, GeoJSON, CSV (WKT)
Data Layers
API	template available for Python and R
Downloables	CVS, Excel