Pandemics challenge the capacity and resilience of healthcare systems around the world. A rapid and effective response to the sudden spread of a pathogen is therefore key to minimising the burden of a disease. Epidemic forecasting generates possible future scenarios of disease spread that can inform the decision-making process of public health authorities, leading to the timely implementation of efficient control strategies. Here, we provide an overview of the pathogens that possess the potential to cause future pandemics, the different models, and the data sources that can be employed to generate prognoses about their spread. Existing efforts focus mainly on one or two different sources, failing to account for multiple factors that influence disease transmission. We discuss recent developments that can lead us towards a holistic forecasting system capable of integrating different data sources, which, we argue, is needed to make reliable predictions and ensure a timely response by public health authorities at a global scale.
