Optimising cohort data in Europe

capture, store, manipulate, analyse and interpret relationships, patterns and trends in digital spatial (geographic) and related data. Researchers might use them to track child immunisations or analyse, visualise and map diseases, for instance. Microwave remote sensing techniques are being explored for detecting minute vibrations on the body surface induced by heartbeat and respiration. Examples of remote sensing use cases include surveillance of a patient's movements, monitoring cardiac and respiratory parameters, screening of patients with infections and analysis of environmental factors in air-borne, vector-borne, soil-borne and water-borne diseases. Table 4 shows strengths and weaknesses of data collection associated with geospatial and positioning technologies.

Table 4. Strengths and weaknesses of the use of geospatial and positioning technologies for data collection

Strengths

Weaknesses

− One-time investment that enables rapid data collection. − As these technologies require effective planning and strict monitoring, it enhances more transparency. − High accuracy, leading to better predictions and analysis. − Integrates a wide range of data sources. − Make complex data easy to understand. − Reveals relationships, trends and patterns in maps, charts and more.

− Expensive. − Free publicly available resources often lack basic information. − Results only as accurate as the data. − GIS needs a signal in remote areas. − Issues with data ownership/licencing with the growing data volume and variety.

In a review of technologies used in European/international population cohorts, patients’ cohorts and clinical trials (retrievable on SYNCHROS repository: https://repository. synchros.eu), most studies that use new communication technologies were conducted in US (69 studies) and in Europe (47 studies). Mobile data collection was the technology most frequently used in the studies (in 119 studies) of which smartphones and/or smart apps were used in 112 studies and mobile phones in 42 studies. Nineteen studies used social media for data collection and among them Facebook and/or Twitter was the most popular. Geospatial technology was used in 30 studies (with GPS and remote sensing used in most of the studies) and smart sensors in 9 studies (including 5 studies using ingestible sensors). There were no studies using artificial intelligence, crowdsourcing and crowd seeding techniques or passive data collection.