Introduction: One major problem in analyzing epidemic data is the lack of data and high dependency among the available data, which is due to the fact that the epidemic process is not directly observable. Methods: One method for epidemic data analysis to estimate the desired epidemic parameters, such as disease transmission rate and recovery rate, is data ...

BACKGROUND It remains unclear whether it is possible to develop a spatiotemporal epidemic prediction model for cryptosporidiosis disease. This paper examined the impact of social economic and weather factors on cryptosporidiosis and explored the possibility of developing such a model using social economic and weather data in Queensland, Australia. METHODS Data on weather variables, notified c...

BACKGROUND Respiratory Syncytial Virus (RSV), a major cause of bronchiolitis, has a large impact on the census of pediatric hospitals during outbreak seasons. Reliable prediction of the week these outbreaks will start, based on readily available data, could help pediatric hospitals better prepare for large outbreaks. METHODS Naïve Bayes (NB) classifier models were constructed using weather da...

Influenza A viruses remain a significant health problem, especially when a novel subtype emerges from the avian population to cause severe outbreaks in humans. Zoonotic viruses arise from the animal population as a result of mutations and reassortments, giving rise to novel strains with the capability to evade the host species barrier and cause human infections. Despite progress in understandin...

Day by day, the accumulative incidence of COVID-19 is rapidly increasing. After spread Corona epidemic and death more than a million people around world countries, scientists researchers have tended to conduct research take advantage modern technologies learn machine help get rid Coronavirus (COVID-19) epidemic. To track predict disease Machine Learning (ML) can be deployed very effectively. ML...