COVID-19 vaccine effectiveness against hospitalization due to SARS-CoV-2: A test negative design study based on SARI sentinel surveillance in Spain (preprint)

Background: With the emergence of SARS-CoV-2, influenza surveillance systems in Spain were transformed into a new syndromic sentinel surveillance system. The Acute Respiratory Infection Surveillance System (SiVIRA in Spanish) is based on a sentinel network for Acute Respiratory Infection (ARI) surveillance in Primary care, and a network of sentinel hospitals for Severe ARI (SARI) surveillance in hospitals. Methods: Using a test-negative design and data from SARI admissions notified to SiVIRA between January 1 and October 3, 2021, we estimated COVID-19 VE against hospitalization, by age group, vaccine type, time since vaccination and SARS-CoV-2 variant. Results: VE was 89% (95% CI: 83-93) against COVID-19 hospitalization overall in persons aged 20 years and older. VE was higher for mRNA vaccines, and lower for those aged 80 years and older, with a decrease in protection beyond 3 months of completing vaccination, and a further decrease after 5 months. We found no differences between periods with circulation of Alpha or Delta SARS-CoV-2 variants, although variant-specific VE was slightly higher against Alpha. Conclusions: The SiVIRA surveillance system, with a network of sentinel hospitals in Spain was able to describe clinical and epidemiological characteristics of SARI hospitalizations, monitor the circulation of SARS-CoV-2 and other respiratory viruses, and provide data to measure the effectiveness of COVID-19 vaccination in the population under surveillance. Our results add to evidence of high VE of mRNA vaccines against severe COVID-19 and waning protection with time since vaccination.

Near real-time surveillance of the SARS-CoV-2 epidemic with incomplete data (preprint)

Designing public health responses to outbreaks requires close monitoring of population-level health indicators in real-time. Thus an accurate estimation of the epidemic curve is critical. We propose an approach to reconstruct epidemic curves in near real time. We apply this approach to characterize the early SARS-CoV-2 outbreak in two Spanish regions between the months of March and April 2020. We address two data collection problems that affected the reliability of the available real-time epidemiological data, namely, the frequent missing information documenting when a patient first experienced symptoms, and the frequent retrospective revision of historical information (including right censoring). This is done by using a novel back-calculating procedure based on imputing patients dates of symptom onset from reported cases, according to a dynamically-estimated backward reporting delay conditional distribution, and adjusting for right censoring using an existing package, NobBS, to estimate in real time (nowcast) cases by date of symptom onset. This process allows us to obtain an approximation of the time-varying reproduction number (Rt) in real-time. At each step, we evaluate how different assumptions affect the recovered epidemiological events and compare the proposed approach to the alternative procedure of merely using curves of case counts, by report day, to characterize the time-evolution of the outbreak. Finally, we assess how these real-time estimates compare with subsequently documented epidemiological information that is considered more reliable and complete that became available weeks to months later in time. Our approach may help improve accuracy, quantify uncertainty, and evaluate frequently unstated assumptions when recovering the epidemic curves from limited data obtained from public health surveillance systems in other locations.