SARS-CoV-2 Exposure and Infection Among Health Care Personnel - Minnesota, March 6-July 11, 2020.

Health care personnel (HCP) are at increased risk for infection with SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), as a result of their exposure to patients or community contacts with COVID-19 (1,2). Since the first confirmed case of COVID-19 in Minnesota was reported on March 6, 2020, the Minnesota Department of Health (MDH) has required health care facilities* to report HCP† exposures to persons with confirmed COVID-19 for exposure risk assessment and to enroll HCP with higher-risk exposures into quarantine and symptom monitoring. During March 6-July 11, MDH and 1,217 partnering health care facilities assessed 21,406 HCP exposures; among these, 5,374 (25%) were classified as higher-risk§ (3). Higher-risk exposures involved direct patient care (66%) and nonpatient care interactions (e.g., with coworkers and social and household contacts) (34%). Within 14 days following a higher-risk exposure, nearly one third (31%) of HCP who were enrolled in monitoring reported COVID-19-like symptoms,¶ and more than one half (52%) of enrolled HCP with symptoms received positive SARS-CoV-2 test results. Among all HCP with higher-risk exposures, irrespective of monitoring enrollment, 7% received positive SARS-CoV-2 test results. Compared with HCP with higher-risk exposures working in acute care settings, those working in congregate living or long-term care settings more often returned to work (57%), worked while symptomatic (5%), and received a positive test result (10%) during 14-day postexposure monitoring than did HCP working outside of such settings. These data highlight the need for awareness of nonpatient care SARS-CoV-2 exposure risks and for targeted interventions to protect HCP, in addition to residents, in congregate living and long-term care settings. To minimize exposure risk among HCP, health care facilities need improved infection prevention and control, consistent personal protective equipment (PPE) availability and use, flexible sick leave, and SARS-CoV-2 testing access. All health care organizations and HCP should be aware of potential exposure risk from coworkers, household members, and social contacts.

Postdiarrheal hemolytic uremic syndrome in United States children: clinical spectrum and predictors of in-hospital death.

OBJECTIVE: To assess the clinical spectrum of postdiarrheal hemolytic uremic syndrome (D(+)HUS) hospitalizations and sought predictors of in-hospital death to help identify children at risk of poor outcomes. STUDY DESIGN: We assessed clinical variables collected through population-based surveillance of D(+)HUS in children <18 years old hospitalized in 10 states during 1997-2012 as predictors of in-hospital death by using tree modeling. RESULTS: We identified 770 cases. Of children with information available, 56.5% (430 of 761) required dialysis, 92.6% (698 of 754) required a transfusion, and 2.9% (22 of 770) died; few had a persistent dialysis requirement (52 [7.3%] of 716) at discharge. The tree model partitioned children into 5 groups on the basis of 3 predictors (highest leukocyte count and lowest hematocrit value during the 7 days before to 3 days after the diagnosis of hemolytic uremic syndrome, and presence of respiratory tract infection [RTI] within 3 weeks before diagnosis). Patients with greater leukocyte or hematocrit values or a recent RTI had a greater probability of in-hospital death. The largest group identified (n = 533) had none of these factors and had the lowest odds of death. Many children with RTI had recent antibiotic treatment for nondiarrheal indications. CONCLUSION: Most children with D(+)HUS have good hospitalization outcomes. Our findings support previous reports of increased leukocyte count and hematocrit as predictors of death. Recent RTI could be an additional predictor, or a marker of other factors such as antibiotic exposure, that may warrant further study.

Evaluation of a statewide foodborne illness complaint surveillance system in Minnesota, 2000 through 2006.

Foodborne outbreaks are detected by recognition of similar illnesses among persons with a common exposure or by identification of case clusters through pathogen-specific surveillance. PulseNet USA has created a national framework for pathogen-specific surveillance, but no comparable effort has been made to improve surveillance of consumer complaints of suspected foodborne illness. The purpose of this study was to characterize the complaint surveillance system in Minnesota and to evaluate its use for detecting outbreaks. Minnesota Department of Health foodborne illness surveillance data from 2000 through 2006 were analyzed for this study. During this period, consumer complaint surveillance led to detection of 79% of confirmed foodborne outbreaks. Most norovirus infection outbreaks were detected through complaints. Complaint surveillance also directly led or contributed to detection of 25% of salmonellosis outbreaks. Eighty-one percent of complainants did not seek medical attention. The number of ill persons in a complainant's party was significantly associated with a complaint ultimately resulting in identification of a foodborne outbreak. Outbreak confirmation was related to a complainant's ability to identify a common exposure and was likely related to the process by which the Minnesota Department of Health chooses complaints to investigate. A significant difference (P < 0.001) was found in incubation periods between complaints that were outbreak associated (median, 27 h) and those that were not outbreak associated (median, 6 h). Complaint systems can be used to detect outbreaks caused by a variety of pathogens. Case detection for foodborne disease surveillance in Minnesota happens through a multitude of mechanisms. The ability to integrate these mechanisms and carry out rapid investigations leads to improved outbreak detection.