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During an epidemic, it can be difficult to get an estimate of the actual number of people infected at any given time. This is due to multiple reasons, including some cases being asymptomatic and sick people not seeking healthcare for mild symptoms, among others. Large scale random sampling of the population for testing can be expensive, especially in the early stages of an epidemic, when tests are scarce. Here we show how an adaptive prevalence testing method can be developed to obtain a good estimate of the disease burden by learning to intelligently allocate a small number of tests for random testing of the population. Our approach uses a combination of an agent-based simulation and deep learning in an active sensing paradigm. We show that it is possible to get a good state estimate with relatively minimal prevalence testing, and that the trained system adapts quickly and performs well even if the disease parameters change.
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This content will become publicly available on June 16, 2026
How Removing Overgrown Water Plants Can Help Kids Stay Healthy and Improve The Planet
In Africa, many kids get sick from tiny worms called Schistosoma. These worms can slow children’s growth and development; damage the liver, intestines, and bladder; and sometimes lead to cancer or even death. Schistosoma can keep communities poor by reducing people’s ability to work. Over 800 million people are at risk of infection. People get infected when they play or wash in water filled with certain plants and snails. These plants grow fast because fertilizer from farmers’ fields washes into the water when it rains. We found that removing these plants can reduce Schistosoma. Plants that are removed can be turned into food for animals, compost for farms, or gas for cooking and electricity. This solution helps protect kids from getting sick and can even help to slow climate change. By working together, communities can clean their waterbodies and create a healthier, happier future, which is a win-win for people and nature.
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- PAR ID:
- 10601113
- Publisher / Repository:
- Frontiers Media S.A.
- Date Published:
- Journal Name:
- Frontiers for Young Minds
- Volume:
- 13
- ISSN:
- 2296-6846
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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