IBM Malaria Challenge
Use reinforcement learning to determine the optimal combination of interventions to control the transmission of malaria
43 data scientists enrolled, 22 on the leaderboard
HealthReinforcement LearningSDG3
25 August 2019—30 August 2019
6 days

This challenge is open only to participants at the Deep Learning Indaba taking place 25-30 August in Nairobi, Kenya. To enter the challenge, you will need to give your email address in person to an IBM or Zindi representative at the Indaba. You can find us during the practical hackathon track every day of the conference. Check the schedule here.

Malaria is thought to have had the greatest disease burden throughout human history, while it continues to pose a significant and disproportionate global health burden. Participants of this challenge should apply machine learning tools, specifically reinforcement learning, to determine novel solutions which could impact malaria policy in Sub Saharan Africa.

Specifically, challenge participants will submit solutions that will make determinations with respect to how combinations of interventions which control the transmission, prevalence and health outcomes of malaria infection, should be distributed in a simulated human population.

This challenge consists of an in-person live challenge hosted on zindi during the Indaba. Zindi will provide authorised participants with an explanation of the challenge and sample code.

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