*Article* **Enhanced Sentinel Surveillance System for COVID-19 Outbreak Prediction in a Large European Dialysis Clinics Network**

**Francesco Bellocchio 1, Paola Carioni 1, Caterina Lonati 2, Mario Garbelli 1, Francisco Martínez-Martínez 3, Stefano Stuard <sup>4</sup> and Luca Neri 1,\*,†**


**Citation:** Bellocchio, F.; Carioni, P.; Lonati, C.; Garbelli, M.; Martínez-Martínez, F.; Stuard, S.; Neri, L. Enhanced Sentinel Surveillance System for COVID-19 Outbreak Prediction in a Large European Dialysis Clinics Network. *Int. J. Environ. Res. Public Health* **2021**, *18*, 9739. https://doi.org/10.3390/ ijerph18189739

Academic Editors: Shang-Ming Zhou and Paul B. Tchounwou

Received: 13 July 2021 Accepted: 11 September 2021 Published: 16 September 2021

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**Abstract:** Accurate predictions of COVID-19 epidemic dynamics may enable timely organizational interventions in high-risk regions. We exploited the interconnection of the Fresenius Medical Care (FMC) European dialysis clinic network to develop a sentinel surveillance system for outbreak prediction. We developed an artificial intelligence-based model considering the information related to all clinics belonging to the European Nephrocare Network. The prediction tool provides risk scores of the occurrence of a COVID-19 outbreak in each dialysis center within a 2-week forecasting horizon. The model input variables include information related to the epidemic status and trends in clinical practice patterns of the target clinic, regional epidemic metrics, and the distance-weighted risk estimates of adjacent dialysis units. On the validation dates, there were 30 (5.09%), 39 (6.52%), and 218 (36.03%) clinics with two or more patients with COVID-19 infection during the 2-week prediction window. The performance of the model was suitable in all testing windows: AUC = 0.77, 0.80, and 0.81, respectively. The occurrence of new cases in a clinic propagates distance-weighted risk estimates to proximal dialysis units. Our machine learning sentinel surveillance system may allow for a prompt risk assessment and timely response to COVID-19 surges throughout networked European clinics.

**Keywords:** SARS-CoV-2; COVID-19; sentinel surveillance system; outbreak prediction; machine learning; artificial intelligence
