Interview Questions for Cornelius Fritz, a Statistician at the University of Munich, Regarding Facebook's Data for Good Initiative
A study led by Cornelius Fritz, a statistician at the University of Munich, has shed light on the role of social connectedness in the spread of COVID-19 within Germany. Utilising data from Facebook's Data for Good programme, the research team analysed mobility and social connectedness data from approximately 10 million Facebook users in the country.
The study, published in January, aimed to improve upon existing forecasting efforts by incorporating three different types of data: colocation maps, a social connectedness index, and geolocation data. This approach allowed the team to identify patterns of people staying put, providing valuable insights into the spread of the virus.
Fritz states that the models developed can be useful for policymakers to evaluate district-level policies, particularly for interventions limiting trans-district movements and concentrating meeting patterns through local lockdowns. These measures, he suggests, could help mitigate further national outbreaks.
The study also revealed a distinction between the former East and West Germany in terms of social ties, even 30 years after reunification. This finding was evident in the graph produced by the study, which showed highly concentrated meeting patterns in the former East Germany, indicating people were mostly meeting with others from their own or nearby districts. In contrast, the former West Germany showed more dispersed meeting patterns.
The model also suggests that the number of infections in a district would likely be lower than the national average if that district was located in the former East Germany. This finding could have significant implications for policymakers, who can use the model as a predictive tool to manage healthcare resources such as hospital beds, respirators, and vaccines.
Fritz emphasises the importance of working with mobility data, stating that it would have been difficult to do their work without Facebook's data due to its granular level. He also suggests that it would be commendable if other companies made their mobility data available to researchers as well.
However, it's worth noting that specific entities or researchers in Germany who have used the mobility data provided by Facebook for COVID-19 research were not identified in the provided search results.
The data was aggregated to the 401 federal administrative districts in Germany to construct a district-level model for meeting patterns. This approach allows for a more nuanced understanding of the spread of COVID-19 within the country, providing valuable insights for policymakers as they navigate the ongoing pandemic.
