Scoping future outbreaks: a scoping review on the outbreak prediction of the WHO Blueprint list of priority diseases.

BACKGROUND: The WHO's Research and Development Blueprint priority list designates emerging diseases with the potential to generate public health emergencies for which insufficient preventive solutions exist. The list aims to reduce the time to the availability of resources that can avert public health crises. The current SARS-CoV-2 pandemic illustrates that an effective method of mitigating such crises is the pre-emptive prediction of outbreaks. This scoping review thus aimed to map and identify the evidence available to predict future outbreaks of the Blueprint diseases. METHODS: We conducted a scoping review of PubMed, Embase and Web of Science related to the evidence predicting future outbreaks of Ebola and Marburg virus, Zika virus, Lassa fever, Nipah and Henipaviral disease, Rift Valley fever, Crimean-Congo haemorrhagic fever, Severe acute respiratory syndrome, Middle East respiratory syndrome and Disease X. Prediction methods, outbreak features predicted and implementation of predictions were evaluated. We conducted a narrative and quantitative evidence synthesis to highlight prediction methods that could be further investigated for the prevention of Blueprint diseases and COVID-19 outbreaks. RESULTS: Out of 3959 articles identified, we included 58 articles based on inclusion criteria. 5 major prediction methods emerged; the most frequent being spatio-temporal risk maps predicting outbreak risk periods and locations through vector and climate data. Stochastic models were predominant. Rift Valley fever was the most predicted disease. Diseases with complex sociocultural factors such as Ebola were often predicted through multifactorial risk-based estimations. 10% of models were implemented by health authorities. No article predicted Disease X outbreaks. CONCLUSIONS: Spatiotemporal models for diseases with strong climatic and vectorial components, as in River Valley fever prediction, may currently best reduce the time to the availability of resources. A wide literature gap exists in the prediction of zoonoses with complex sociocultural and ecological dynamics such as Ebola, COVID-19 and especially Disease X.

Human Induced Pluripotent Stem Cell-Derived Astrocytes Are Differentially Activated by Multiple Sclerosis-Associated Cytokines.

Recent studies highlighted the importance of astrocytes in neuroinflammatory diseases, interacting closely with other CNS cells but also with the immune system. However, due to the difficulty in obtaining human astrocytes, their role in these pathologies is still poorly characterized. Here, we develop a serum-free protocol to differentiate human induced pluripotent stem cells (hiPSCs) into astrocytes. Gene expression and functional assays show that our protocol consistently yields a highly enriched population of resting mature astrocytes across the 13 hiPSC lines differentiated. Using this model, we first highlight the importance of serum-free media for astrocyte culture to generate resting astrocytes. Second, we assess the astrocytic response to IL-1ß, TNF-α, and IL-6, all cytokines important in neuroinflammation, such as multiple sclerosis. Our study reveals very specific profiles of reactive astrocytes depending on the triggering stimulus. This model provides ideal conditions for in-depth and unbiased characterization of astrocyte reactivity in neuroinflammatory conditions.