Background: We estimated SARS-CoV-2 Delta and Omicron-specific effectiveness of 2 and 3 mRNA COVID-19 vaccine doses in adults against symptomatic illness in US outpatient settings. Method(s): Between October 1, 2021, and February 12, 2022, research staff consented and enrolled eligible participants who had fever, cough, or loss of taste or smell and sought outpatient medical care or clinical SARS-CoV-2 testing within 10 days of illness onset. Using the test-negative design, we compared the odds of receiving 2 or 3 mRNA COVID-19 vaccine doses among SARS-CoV-2 cases versus controls using logistic regression. Regression models were adjusted for study site, age, onset week, and prior SARS-CoV-2 infection. Vaccine effectiveness (VE) was calculated as (1 - adjusted odds ratio) x 100%. Result(s): Among 3847 participants included for analysis, 574 (32%) of 1775 tested positive for SARS-CoV-2 during the Delta predominant period and 1006 (56%) of 1794 participants tested positive during the Omicron predominant period. When Delta predominated, VE against symptomatic illness in outpatient settings was 63% (95% CI: 51% to 72%) among mRNA 2-dose recipients and 96% (95% CI: 93% to 98%) for 3-dose recipients. When Omicron predominated, VE was 21% (95% CI: -6% to 41%) among 2-dose recipients and 62% (95% CI: 48% to 72%) among 3-dose recipients. Conclusion(s): In this adult population, 3 mRNA COVID-19 vaccine doses provided substantial protection against symptomatic illness in outpatient settings when the Omicron variant became the predominant cause of COVID-19 in the U.S. These findings support the recommendation for a 3rd mRNA COVID-19 vaccine dose. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

Hepatitis C virus (HCV) infections are public health problem across the globe, particularly in developing countries. Pakistan has the second highest prevalence of HCV infection worldwide. Limited data exist from Pakistan about persons who inject drugs (PWID) and are at significant risk of exposure to HCV infection and transmission. Serum specimens (n = 110) collected from PWID residing in four provinces were tested for molecular markers of HCV infection. Next generation sequencing (NGS) of the hypervariable region (HVR1) of HCV and Global Hepatitis Outbreak and Surveillance Technology (GHOST) were used to determine HCV genotype, genetic heterogeneity, and construct transmission networks. Among tested specimens, 47.3% were found anti-HCV positive and 34.6% were HCV RNA-positive and belonged to four genotypes, with 3a most prevalent followed by 1a, 1b and 4a. Variants sampled from five cases formed phylogenetic cluster and a transmission network. One case harbored infection with two different genotypes. High prevalence of infections and presence of various genotypes indicate frequent introduction and transmission of HCV among PWID in Pakistan. Identification of a transmission cluster across three provinces, involving 20% of all cases, suggests the existence of a countrywide transmission network among PWIDs. Understanding the structure of this network should assist in devising effective public health strategies to eliminate HCV infection in Pakistan.

During 1995-2011, the overall incidence of hepatitis A decreased by 95% in the United States from 12 cases per 100,000 population during 1995 to 0.4 cases per 100,000 population during 2011, and then plateaued during 2012─2015. The incidence increased by 294% during 2016-2018 compared with the incidence during 2013-2015, with most cases occurring among populations at high risk for hepatitis A infection, including persons who use illicit drugs (injection and noninjection), persons who experience homelessness, and men who have sex with men (MSM) (1-3). Previous outbreaks among persons who use illicit drugs and MSM led to recommendations issued in 1996 by the Advisory Committee on Immunization Practices (ACIP) for routine hepatitis A vaccination of persons in these populations (4). Despite these long-standing recommendations, vaccination coverage rates among MSM remain low (5). In 2017, the New York City Department of Health and Mental Hygiene contacted CDC after public health officials noted an increase in hepatitis A infections among MSM. Laboratory testing* of clinical specimens identified strains of the hepatitis A virus (HAV) that subsequently matched strains recovered from MSM in other states. During January 1, 2017-October 31, 2018, CDC received reports of 260 cases of hepatitis A among MSM from health departments in eight states, a substantial increase from the 16 cases reported from all 50 states during 2013-2015. Forty-eight percent (124 of 258) of MSM patients were hospitalized for a median of 3 days. No deaths were reported. In response to these cases, CDC supported state and local health departments with public health intervention efforts to decrease HAV transmission among MSM populations. These efforts included organizing multistate calls among health departments to share information, providing guidance on developing targeted outreach and managing supplies for vaccine campaigns, and conducting laboratory testing of clinical specimens. Targeted outreach for MSM to increase awareness about hepatitis A infection and improve access to vaccination services, such as providing convenient locations for vaccination, are needed to prevent outbreaks among MSM.

BACKGROUND: Molecular surveillance and outbreak investigation are important for elimination of hepatitis C virus (HCV) infection in the United States. A web-based system, Global Hepatitis Outbreak and Surveillance Technology (GHOST), has been developed using Illumina MiSeq-based amplicon sequence data derived from the HCV E1/E2-junction genomic region to enable public health institutions to conduct cost-effective and accurate molecular surveillance, outbreak detection and strain characterization. However, as there are many factors that could impact input data quality to which the GHOST system is not completely immune, accuracy of epidemiological inferences generated by GHOST may be affected. Here, we analyze the data submitted to the GHOST system during its pilot phase to assess the nature of the data and to identify common quality concerns that can be detected and corrected automatically. RESULTS: The GHOST quality control filters were individually examined, and quality failure rates were measured for all samples, including negative controls. New filters were developed and introduced to detect primer dimers, loss of specimen-specific product, or short products. The genotyping tool was adjusted to improve the accuracy of subtype calls. The identification of "chordless" cycles in a transmission network from data generated with known laboratory-based quality concerns allowed for further improvement of transmission detection by GHOST in surveillance settings. Parameters derived to detect actionable common quality control anomalies were incorporated into the automatic quality control module that rejects data depending on the magnitude of a quality problem, and warns and guides users in performing correctional actions. The guiding responses generated by the system are tailored to the GHOST laboratory protocol. CONCLUSIONS: Several new quality control problems were identified in MiSeq data submitted to GHOST and used to improve protection of the system from erroneous data and users from erroneous inferences. The GHOST system was upgraded to include identification of causes of erroneous data and recommendation of corrective actions to laboratory users.

BACKGROUND: Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections associated with unsafe injection practices, drug diversion, and other exposures to blood are difficult to detect and investigate. Effective HCV outbreak investigation requires comprehensive surveillance and robust case investigation. We previously developed and validated a methodology for the rapid and cost-effective identification of HCV transmission clusters. Global Hepatitis Outbreak and Surveillance Technology (GHOST) is a cloud-based system enabling users, regardless of computational expertise, to analyze and visualize transmission clusters in an independent, accurate and reproducible way. RESULTS: We present and explore performance of several GHOST implemented algorithms using next-generation sequencing data experimentally obtained from hypervariable region 1 of genetically related and unrelated HCV strains. GHOST processes data from an entire MiSeq run in approximately 3 h. A panel of seven specimens was used for preparation of six repeats of MiSeq libraries. Testing sequence data from these libraries by GHOST showed a consistent transmission linkage detection, testifying to high reproducibility of the system. Lack of linkage among genetically unrelated HCV strains and constant detection of genetic linkage between HCV strains from known transmission pairs and from follow-up specimens at different levels of MiSeq-read sampling indicate high specificity and sensitivity of GHOST in accurate detection of HCV transmission. CONCLUSIONS: GHOST enables automatic extraction of timely and relevant public health information suitable for guiding effective intervention measures. It is designed as a virtual diagnostic system intended for use in molecular surveillance and outbreak investigations rather than in research. The system produces accurate and reproducible information on HCV transmission clusters for all users, irrespective of their level of bioinformatics expertise. Improvement in molecular detection capacity will contribute to increasing the rate of transmission detection, thus providing opportunity for rapid, accurate and effective response to outbreaks of hepatitis C. Although GHOST was originally developed for hepatitis C surveillance, its modular structure is readily applicable to other infectious diseases. Worldwide availability of GHOST for the detection of HCV transmissions will foster deeper involvement of public health researchers and practitioners in hepatitis C outbreak investigation.