The complex, unpredictable nature of pathogen occurrence has required substantial efforts
to accurately predict infectious diseases (IDs). With rising popularity of Machine Learning …

Recent decades have witnessed several infectious disease outbreaks, including the
coronavirus disease (COVID-19) pandemic, which had catastrophic impacts on societies …

Dengue fever is an acute mosquito-borne disease that mostly spreads within urban or semi-
urban areas in warm climate zones. The dengue-related risk map is one of the most practical …

Simple Summary Forecasting dengue cases often face challenges from (1) time-
effectiveness due to time-consuming satellite data downloading and processing,(2) weak …

Dengue is recognized as a health problem that causes significant socioeconomic impacts
throughout the world, affecting millions of people each year. A commonly used method for …

With advancements in big geospatial data and artificial intelligence, multi-source data and
diverse data-driven methods have become common in dengue risk prediction …

Predicting the specific magnitude and the temporal peak of the epidemic of individual local
outbreaks is critical for infectious disease control. Previous studies have indicated that …

Infectious disease prevention, control and forecasting rely on sentinel observations;
however, many locations lack the capacity for routine surveillance. Here we show that, by …

The application of artificial intelligence (AI) in entomological research has gained significant
attention in recent years. This review summarizes the current state of research on the …

Arboviruses are a group of diseases that are transmitted by an arthropod vector. Since they
are part of the Neglected Tropical Diseases that pose several public health challenges for …