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Health Domain

Lacuna Fund health datasets reduce health disparities by helping providers and patients make decisions that lead to more equitable healthcare outcomes. These datasets can be used to train chatbots, provide reliable medical information to the public, assist with disease screening and diagnosis, and assess the health and treatment of large populations over time (e.g. maternal health or HIV data). Learn more and download released datasets below.

Equity and Health

Description: This dataset will help in the real-time and remote diagnosis of rabies disease for humans and animals in low-resource settings. A time series approach can be applied to the outbreak dataset to predict the number of rabies cases likely to occur within an area after a given time interval. This approach can help with resource mobilization, too, such as identifying the number of vaccines required in a specific area at a given time. The number of observations from the two datasets is 12,684. There are three datasets for rabies diagnosis for animals and humans, with 7,081 and 4,585 observations, respectively. In the outbreak prediction dataset, 1,018 observations were accounted for. 

Contact: Asa Emmanuel | asakalonga@gmail.com and Kennedy Lushasi | klushasi@ihi.or.tz 

Authors and Affiliations: Asa Emmanuel, Rebecca Chaula, Deogratias Mzurikwao, Joel Changalucha, Kennedy Lushasi 

Dataset: access here.

Contact: Maria Paz Hermosilla | goblab@uai.cl 

Description: This data repository will evaluate factors that contribute to child malnutrition in Chile and childrens’ nutritional status, as well as the associated costs. The focus at this stage is on estimating health costs associated with child malnutrition and identifying biopsychosocial determinants that lead to it.

Authors and Affiliations:  

  • Ministry of Health, Chile  
  • GobLab, School of Government, Adolfo Ibañez University, Chile 
  • FONASA (Public health insurance agency) 
  • Health Superintendency, JUNAEB (national school aid and scholarship board). 

Dataset: Given the sensitive nature of the data contained in this repository, those interested can visit the project website here for controlled access for relevant awarded research projects:  https://goblab.uai.cl/proyecto-reduccion-de-la-malnutricion-infantil-en-chile/. 

Contact: Rose Nakasi | g.nakasi.rose@gmail.com or rose.nakasi@mak.ac.ug 

Description: This dataset will aid in the diagnosis of malaria. The dataset contains annotated images of blood samples collected in Uganda and Ghana with objects of interest, including parasites and white blood cells. It significantly increases the number of available microscopy images — including metadata — by 6,000 thick blood slides and 2,000 thin blood slides for use in object detection research and other areas of inquiry. 

Authors and Affiliations:  

  • Makerere Artificial Intelligence Lab  
  • minoHealth 

Dataset: https://doi.org/10.7910/DVN/VEADSE 

All Lacuna Fund datasets are licensed under the CC-BY 4.0 International license unless otherwise noted.