Can Big Data Be Used to Monitor the Mental Health Consequences of COVID-19?

[...]methodologies, such as de-identification and anonymization, can ensure data protection and privacy by removing personal identifiers. Thereby, dozens of millions of e.g., geo-referenced Twitter tweets, may be analyzed, substantially increasing the statistical power of spatial analyses linking mental health determinants, COVID-19 case counts or regulations, and sentiments of social media users in those locations [10]. [...]Big Data analyses could help identify regional differences and establish correlations with other factors such as incidence rates of COVID-19, lockdown strictness or other policies aimed at containing the pandemic, or hospital overcrowding. [...]real time monitoring of the mental health consequences of COVID-19 may help set up governments to respond rapidly and appropriately to changes in mental health status. [...]Big Data hold potential to strengthen our mental health prevention systems in the context of a global public health crisis.