An app for dengue

Dengue is a debilitating viral infection transmitted by mosquitoes. It has become the world's fastest-growing mosquito-borne disease, putting half of the global population at risk. In high-risk areas, an estimated 100–400 million people  become infected each year, straining healthcare systems. A study published in Multimedia Tools and Applications, by researchers at the Universiti Malaysia Sarawak (UNIMAS), describes the development, design, and implementation of the hotspot detector app MozzHub.

Dengue is a major public health challenge in Malaysia, and traditional control methods such as spraying and fogging have been ineffective. The difficulty lies in accurately identifying the source of infection. Despite a 30.3% reduction in cases in 2020, attributed to a COVID-19-related movement control order, studies suggest that control measures should not focus solely on residential areas. Instead, it is crucial to consider the movement history of dengue patients two weeks before their symptoms start, to identify likely sources of infection. Unlike most early warning systems for dengue that lack real-time functionality, a system that considers the variations in human impact on the environment and the places they visit is needed.

Did you know? 
Dengue is the world's fastest growing mosquito-borne disease.
Half the world's population is at risk.

“The usual methods for finding dengue hotspots often rely on mere prediction that fail to focus on where the disease might actually spread," explains Jane Labadin, a professor and research fellow at UNIMAS. “Some of the methods that try to predict its spread need a lot of information and mostly look at large geographical areas.” She adds that the smaller details needed to control the mosquitoes spreading the disease are missed by these methods.

To tackle this problem, Labadin and her colleagues created MozzHub as a user-friendly web app built on an existing dengue model. Unlike the other methods, MozzHub considers how people move around, especially in smaller areas within a 400-metre radius. The model can identify the most probable sources of dengue infection based on patients’ movements and environmental factors, including temperature and humidity.