data4health is a tool developed as part of the HARMONIZE project to facilitate the cleaning, filtering, and aggregation of health data at customised spatiotemporal resolutions. Originally designed for data from Brazil, Colombia, the Dominican Republic, and Peru, the tool is adaptable for any linelist health data.
The R package offers two modes of operation based on the user’s coding experience:
Key features of the R Package:
The latest version of the data4health package is hosted on CRAN and can by installed using the following commands:
install.packages("data4health")
library(data4health)There are two main functionalities of data4health.
For code-experienced users, a series of functions to support health data analysis are provided that users can implement to simplify their existing data pipeline. An overview over how to make use of them can be found in the Overview vignette.
Users with less code experience can employ the graphic user interface to clean and aggregate their data in a user-friendly way by typing the following command and waiting for the a browser window to open:
d4h_ui()Future functionalities of data4health include:
If you have any needs, or suggestions for new functions or new functionalities of current functions, please do not hesitate to create an issue. See CONTRIBUTING.md for details on how to contribute or get in touch.
The data4health website includes detailed guides for each function, example workflows using reported disease cases and instructions on how to access health data.
HARMONIZE is an international consortium co-creating cost-effective and reproducible digital tools for stakeholders in hotspots affected by a changing climate in Latin America & the Caribbean (LAC), including cities, small islands, highlands, and the Amazon rainforest.
The HARMONIZE digital toolkits will allow local researchers and users, including national disease control programs, to link, interrogate and use multi-scale spatiotemporal data, to understand the links between environmental change and infectious disease risk in their local context, and to build robust early warning and response systems in low-resource settings.
The project offers resources and tools developed in conjunction with different teams from Brazil, Colombia, Dominican Republic, Peru and Spain.
Within HARMONIZE, each data category has its own digital toolkit to allow local researchers and users, to prepare, interrogate and eventually merge the data spatially and temporally, to understand the links between environmental change and infectious disease risk in their local context, and to build robust early warning and response systems in low-resource settings. The other HARMONIZE toolkits include:
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GHR Global Health Resilience |
Daniela
Lührsen
Barcelona Supercomputing Center (BSC), Spain
Raquel
Martins Lana, PhD
Barcelona Supercomputing Center (BSC), Spain
Carles Milà,
PhD
Barcelona Supercomputing Center (BSC), Spain
Rachel Lowe,
PhD
Barcelona Supercomputing Center (BSC), Spain
Catalan Institution for Research and Advanced Studies (ICREA), Spain