January 28, 2016

New Model Uses Public Health Data to Signal Impending Disease Eradication

Ecologists at the University of Georgia recently published a study in Theoretical Ecology that identifies a potential new tool to fight against infectious diseases.

According to the study, “[s]ustaining momentum near the end of [malaria] elimination programs is often difficult to achieve” and tools that help to monitor the effectiveness of these programs after the initial case reductions are needed. In response to this need, researchers developed a model that used public health surveillance data for malaria to signal when the disease is approaching eradication. The model is based on the theory of “critical slowing down,” which describes statistical patterns that “appear when a system under stress is nearing a tipping point—the point after which it is doomed to eventual extinction.”

Specifically, the researchers looked for evidence of “critical slowing down” with four prevention and control methods: (1) using bed nets, (2) spraying indoor insecticides, (3) administering drug treatments to shorten a malaria patient’s infectious period, and (4) eliminating mosquito habitats. The researchers found that their model revealed patterns indicating impending tipping points, although the strength of the signal depended on the control and statistical methods used to analyze the data.

Click here to read the full study.