Dynamically adjusting case reporting policy to maximize privacy and public health utility in the face of a pandemic.

OBJECTIVE: Supporting public health research and the public's situational awareness during a pandemic requires continuous dissemination of infectious disease surveillance data. Legislation, such as the Health Insurance Portability and Accountability Act of 1996 and recent state-level regulations, permits sharing deidentified person-level data; however, current deidentification approaches are limited. Namely, they are inefficient, relying on retrospective disclosure risk assessments, and do not flex with changes in infection rates or population demographics over time. In this paper, we introduce a framework to dynamically adapt deidentification for near-real time sharing of person-level surveillance data. MATERIALS AND METHODS: The framework leverages a simulation mechanism, capable of application at any geographic level, to forecast the reidentification risk of sharing the data under a wide range of generalization policies. The estimates inform weekly, prospective policy selection to maintain the proportion of records corresponding to a group size less than 11 (PK11) at or below 0.1. Fixing the policy at the start of each week facilitates timely dataset updates and supports sharing granular date information. We use August 2020 through October 2021 case data from Johns Hopkins University and the Centers for Disease Control and Prevention to demonstrate the framework's effectiveness in maintaining the PK11 threshold of 0.01. RESULTS: When sharing COVID-19 county-level case data across all US counties, the framework's approach meets the threshold for 96.2% of daily data releases, while a policy based on current deidentification techniques meets the threshold for 32.3%. CONCLUSION: Periodically adapting the data publication policies preserves privacy while enhancing public health utility through timely updates and sharing epidemiologically critical features.

Review of the risk factors for SARS-CoV-2 transmission.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, which has lasted for nearly a year, has made people deeply aware of the strong transmissibility and pathogenicity of SARS-CoV-2 since its outbreak in December 2019. By December 2020, SARS-CoV-2 had infected over 65 million people globally, resulting in more than 1 million deaths. At present, the exact animal origin of SARS-CoV-2 remains unclear and antiviral vaccines are now undergoing clinical trials. Although the social order of human life is gradually returning to normal, new confirmed cases continue to appear worldwide, and the majority of cases are sporadic due to environmental factors and lax self-protective consciousness. This article provides the latest understanding of the epidemiology and risk factors of nosocomial and community transmission of SARS-CoV-2, as well as strategies to diminish the risk of transmission. We believe that our review will help the public correctly understand and cope with SARS-CoV-2.

Risk Factors for Severe Acute Respiratory Syndrome Coronavirus 2 Infection in Hospital Workers: Results From a Screening Study in New Jersey, United States in Spring 2020.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a critical concern among healthcare workers (HCWs). Other studies have assessed SARS-CoV-2 virus and antibodies in HCWs, with disparate findings regarding risk based on role and demographics. METHODS: We screened 3904 employees and clinicians for SARS-CoV-2 virus positivity and serum immunoglobulin (Ig)G at a major New Jersey hospital from April 28 to June 30, 2020. We assessed positive tests in relation to demographic and occupational characteristics and prior coronavirus disease 2019 symptoms using multivariable logistic regression models. RESULTS: Thirteen participants (0.3%) tested positive for virus and 374 (9.6%) tested positive for IgG (total positive: 381 [9.8%]). Compared with participants with no patient care duties, the odds of positive testing (virus or antibodies) were higher for those with direct patient contact: below-median patient contact, adjusted odds ratio (aOR) = 1.71 and 95% confidence interval [CI] = 1.18-2.48; above-median patient contact, aOR = 1.98 and 95% CI = 1.35-2.91. The proportion of participants testing positive was highest for phlebotomists (23.9%), maintenance/housekeeping (17.3%), dining/food services (16.9%), and interpersonal/support roles (13.7%) despite lower levels of direct patient care duties. Positivity rates were lower among doctors (7.2%) and nurses (9.1%), roles with fewer underrepresented minorities. After adjusting for job role and patient care responsibilities and other factors, Black and Latinx workers had 2-fold increased odds of a positive test compared with white workers. Loss of smell, taste, and fever were associated with positive testing. CONCLUSIONS: The HCW categories at highest risk for SARS-CoV-2 infection include support staff and underrepresented minorities with and without patient care responsibilities. Future work is needed to examine potential sources of community and nosocomial exposure among these understudied HCWs.