COVID-19 Surveillance After Expiration of the Public Health Emergency Declaration - United States, May 11, 2023.

On January 31, 2020, the U.S. Department of Health and Human Services (HHS) declared, under Section 319 of the Public Health Service Act, a U.S. public health emergency because of the emergence of a novel virus, SARS-CoV-2.* After 13 renewals, the public health emergency will expire on May 11, 2023. Authorizations to collect certain public health data will expire on that date as well. Monitoring the impact of COVID-19 and the effectiveness of prevention and control strategies remains a public health priority, and a number of surveillance indicators have been identified to facilitate ongoing monitoring. After expiration of the public health emergency, COVID-19-associated hospital admission levels will be the primary indicator of COVID-19 trends to help guide community and personal decisions related to risk and prevention behaviors; the percentage of COVID-19-associated deaths among all reported deaths, based on provisional death certificate data, will be the primary indicator used to monitor COVID-19 mortality. Emergency department (ED) visits with a COVID-19 diagnosis and the percentage of positive SARS-CoV-2 test results, derived from an established sentinel network, will help detect early changes in trends. National genomic surveillance will continue to be used to estimate SARS-CoV-2 variant proportions; wastewater surveillance and traveler-based genomic surveillance will also continue to be used to monitor SARS-CoV-2 variants. Disease severity and hospitalization-related outcomes are monitored via sentinel surveillance and large health care databases. Monitoring of COVID-19 vaccination coverage, vaccine effectiveness (VE), and vaccine safety will also continue. Integrated strategies for surveillance of COVID-19 and other respiratory viruses can further guide prevention efforts. COVID-19-associated hospitalizations and deaths are largely preventable through receipt of updated vaccines and timely administration of therapeutics (1-4).

Correlations and Timeliness of COVID-19 Surveillance Data Sources and Indicators - United States, October 1, 2020-March 22, 2023.

When the U.S. COVID-19 public health emergency declaration expires on May 11, 2023, national reporting of certain categories of COVID-19 public health surveillance data will be transitioned to other data sources or will be discontinued; COVID-19 hospitalization data will be the only data source available at the county level (1). In anticipation of the transition, national COVID-19 surveillance data sources and indicators were evaluated for purposes of ongoing monitoring. The timeliness and correlations among surveillance indicators were analyzed to assess the usefulness of COVID-19-associated hospital admission rates as a primary indicator for monitoring COVID-19 trends, as well as the suitability of other replacement data sources. During April 2022-March 2023, COVID-19 hospital admission rates from the National Healthcare Safety Network (NHSN)† lagged 1 day behind case rates and 4 days behind percentages of positive test results and COVID-19 emergency department (ED) visits from the National Syndromic Surveillance Program (NSSP). In the same analysis, National Vital Statistics System (NVSS) trends in the percentage of deaths that were COVID-19-associated, which is tracked by date of death rather than by report date, were observable 13 days earlier than those from aggregate death count data, which will be discontinued (1). During October 2020-March 2023, strong correlations were observed between NVSS and aggregate death data (0.78) and between the percentage of positive SARS-CoV-2 test results from the National Respiratory and Enteric Viruses Surveillance System (NREVSS) and COVID-19 electronic laboratory reporting (CELR) (0.79), which will also be discontinued (1). Weekly COVID-19 Community Levels (CCLs) will be replaced with levels of COVID-19 hospital admission rates (low, medium, or high) which demonstrated >99% concordance by county during February 2022-March 2023. COVID-19-associated hospital admission levels are a suitable primary metric for monitoring COVID-19 trends, the percentage of COVID-19 deaths is a timely disease severity indicator, and the percentages of positive SARS-CoV-2 test results from NREVSS and ED visits serve as early indicators for COVID-19 monitoring. Collectively, these surveillance data sources and indicators can support monitoring of the impact of COVID-19 and related prevention and control strategies as ongoing public health priorities.

Decreases in COVID-19 Cases, Emergency Department Visits, Hospital Admissions, and Deaths Among Older Adults Following the Introduction of COVID-19 Vaccine - United States, September 6, 2020-May 1, 2021.

Throughout the COVID-19 pandemic, older U.S. adults have been at increased risk for severe COVID-19-associated illness and death (1). On December 14, 2020, the United States began a nationwide vaccination campaign after the Food and Drug Administration's Emergency Use Authorization of Pfizer-BioNTech COVID-19 vaccine. The Advisory Committee on Immunization Practices (ACIP) recommended prioritizing health care personnel and residents of long-term care facilities, followed by essential workers and persons at risk for severe illness, including adults aged ≥65 years, in the early phases of the vaccination program (2). By May 1, 2021, 82%, 63%, and 42% of persons aged ≥65, 50-64, and 18-49 years, respectively, had received ≥1 COVID-19 vaccine dose. CDC calculated the rates of COVID-19 cases, emergency department (ED) visits, hospital admissions, and deaths by age group during November 29-December 12, 2020 (prevaccine) and April 18-May 1, 2021. The rate ratios comparing the oldest age groups (≥70 years for hospital admissions; ≥65 years for other measures) with adults aged 18-49 years were 40%, 59%, 65%, and 66% lower, respectively, in the latter period. These differential declines are likely due, in part, to higher COVID-19 vaccination coverage among older adults, highlighting the potential benefits of rapidly increasing vaccination coverage.

Antimicrobial resistance incidence and risk factors among Helicobacter pylori-infected persons, United States.

Helicobacter pylori is the primary cause of peptic ulcer disease and an etiologic agent in the development of gastric cancer. H. pylori infection is curable with regimens of multiple antimicrobial agents, and antimicrobial resistance is a leading cause of treatment failure. The Helicobacter pylori Antimicrobial Resistance Monitoring Program (HARP) is a prospective, multicenter U.S. network that tracks national incidence rates of H. pylori antimicrobial resistance. Of 347 clinical H. pylori isolates collected from December 1998 through 2002, 101 (29.1%) were resistant to one antimicrobial agent, and 17 (5%) were resistant to two or more antimicrobial agents. Eighty-seven (25.1%) isolates were resistant to metronidazole, 45 (12.9%) to clarithromycin, and 3 (0.9%) to amoxicillin. On multivariate analysis, black race was the only significant risk factor (p < 0.01, hazard ratio 2.04) for infection with a resistant H. pylori strain. Formulating pretreatment screening strategies or providing alternative therapeutic regimens for high-risk populations may be important for future clinical practice.

Optimization of computer software settings improves accuracy of pulsed-field gel electrophoresis macrorestriction fragment pattern analysis.

Computer-assisted analysis of pulsed-field gel electrophoresis (PFGE) libraries can facilitate comparisons of fragment patterns present on multiple gels. We evaluated the ability of the Advanced Analysis (version 4.01) and Database (version 1.12) modules of the Phoretix gel analysis software package (Nonlinear USA, Inc., Durham, N.C.) to accurately match DNA fragment patterns. Two gels containing 38 lanes of SmaI-digested Enterococcus faecalis OG1RF DNA were analyzed to assess the impact of (i) varying the lane position of the standards, (ii) using gel plugs made at different times, and (iii) normalizing the fragment patterns by using molecular weight (MW) algorithms versus retardation factor (R(f)) algorithms. Two sets of PFGE libraries (one containing SmaI restriction patterns from 62 Enterococcus faecium isolates and the other containing SmaI restriction patterns of 89 Staphylococcus aureus isolates) were analyzed to assess the impact of varying the matching tolerance algorithm (designated as the vector box setting [VBS]) in the Phoretix software. Varying the lane position of standards on a gel and using gel plugs made on different days resulted in different VBSs, although it was not possible to judge whether those differences were statistically significant. Normalization of E. faecalis OG1RF fragment patterns by R(f) and MW methodology yielded no statistically significant differences in variability between the same fragment on different lanes. Suboptimal VBSs decreased the specificity with which related isolates were grouped together in dendrograms. The optimal VBS for analysis of PFGE fragment patterns from E. faecalis isolates differed from that for S. aureus isolates and sometimes was not that recommended by the manufacturer. Thus, computer-assisted analysis of PFGE patterns seemed to compensate for the intra- and intergel variation evaluated in the present study, and optimizing the software for the species to be tested was a critical preliminary step before further PFGE library analysis.