Syndromic Surveillance Tracks COVID-19 Cases in University and County Settings: Retrospective Observational Study.

Background: Syndromic surveillance represents a potentially inexpensive supplement to test-based COVID-19 surveillance. By strengthening surveillance of COVID-19-like illness (CLI), targeted and rapid interventions can be facilitated that prevent COVID-19 outbreaks without primary reliance on testing. Objective: This study aims to assess the temporal relationship between confirmed SARS-CoV-2 infections and self-reported and health care provider-reported CLI in university and county settings, respectively. Methods: We collected aggregated COVID-19 testing and symptom reporting surveillance data from Cornell University (2020-2021) and Tompkins County Health Department (2020-2022). We used negative binomial and linear regression models to correlate confirmed COVID-19 case counts and positive test rates with CLI rate time series, lagged COVID-19 cases or rates, and day of the week as independent variables. Optimal lag periods were identified using Granger causality and likelihood ratio tests. Results: In modeling undergraduate student cases, the CLI rate (P=.003) and rate of exposure to CLI (P<.001) were significantly correlated with the COVID-19 test positivity rate with no lag in the linear models. At the county level, the health care provider-reported CLI rate was significantly correlated with SARS-CoV-2 test positivity with a 3-day lag in both the linear (P<.001) and negative binomial model (P=.005). Conclusions: The real-time correlation between syndromic surveillance and COVID-19 cases on a university campus suggests symptom reporting is a viable alternative or supplement to COVID-19 surveillance testing. At the county level, syndromic surveillance is also a leading indicator of COVID-19 cases, enabling quick action to reduce transmission. Further research should investigate COVID-19 risk using syndromic surveillance in other settings, such as low-resource settings like low- and middle-income countries.

Representative Public Health Surveys Pose Several Challenges: Lessons Learned Across 9 Communities During the COVID-19 Pandemic.

Community surveillance surveys offer an opportunity to obtain important and timely public health information that may help local municipalities guide their response to public health threats. The objective of this paper is to present approaches, challenges, and solutions from SARS-CoV-2 surveillance surveys conducted in different settings by 2 research teams. For rapid assessment of a representative sample, a 2-stage cluster sampling design was developed by an interdisciplinary team of researchers at Oregon State University between April 2020 and June 2021 across 6 Oregon communities. In 2022, these methods were adapted for New York communities by a team of veterinary, medical, and public health practitioners. Partnerships were established with local medical facilities, health departments, COVID-19 testing sites, and health and public safety staff. Field staff were trained using online modules, field manuals describing survey methods and safety protocols, and in-person meetings with hands-on practice. Private and secure data integration systems and public awareness campaigns were implemented. Pilot surveys and field previews revealed challenges in survey processes that could be addressed before surveys proceeded. Strong leadership, robust trainings, and university-community partnerships proved critical to successful outcomes. Cultivating mutual trust and cooperation among stakeholders is essential to prepare for the next pandemic.

Integrated Surveillance System for Controlling COVID-19 on a University Campus, 2020‒2021.

To minimize the impacts of COVID-19 and to keep campus open, Cornell University's Ithaca, NY, campus implemented a comprehensive process to monitor COVID-19 spread, support prevention practices, and assess early warning indicators linked to knowledge, behaviors, and attitudes of campus community members. The integrated surveillance approach informed leadership and allowed for prompt adjustments to university policies and practices through evidence-based decisions. This approach enhanced healthy behaviors and promoted the well-being and safety of all community members. (Am J Public Health. 2022;112(7):980-984. https://doi.org/10.2105/AJPH.2022.306838).

Development of a quantitative COVID-19 multiplex assay and its use for serological surveillance in a low SARS-CoV-2 incidence community.

A serological COVID-19 Multiplex Assay was developed and validated using serum samples from convalescent patients and those collected prior to the 2020 pandemic. After initial testing of multiple potential antigens, the SARS-CoV-2 nucleocapsid protein (NP) and receptor-binding domain (RBD) of the spike protein were selected for the human COVID-19 Multiplex Assay. A comparison of synthesized and mammalian expressed RBD proteins revealed clear advantages of mammalian expression. Antibodies directed against NP strongly correlated with SARS-CoV-2 virus neutralization assay titers (rsp = 0.726), while anti-RBD correlation was moderate (rsp = 0.436). Pan-Ig, IgG, IgA, and IgM against NP and RBD antigens were evaluated on the validation sample sets. Detection of NP and RBD specific IgG and IgA had outstanding performance (AUC > 0.90) for distinguishing patients from controls, but the dynamic range of the IgG assay was substantially greater. The COVID-19 Multiplex Assay was utilized to identify seroprevalence to SARS-CoV-2 in people living in a low-incidence community in Ithaca, NY. Samples were taken from a cohort of healthy volunteers (n = 332) in early June 2020. Only two volunteers had a positive result on a COVID-19 PCR test performed prior to serum sampling. Serological testing revealed an exposure rate of at least 1.2% (NP) or as high as 5.7% (RBD), higher than the measured incidence rate of 0.16% in the county at that time. This highly sensitive and quantitative assay can be used for monitoring community exposure rates and duration of immune response following both infection and vaccination.