Tuberculosis Diagnoses Following Wildfire Smoke Exposure in California.

Rationale: Wildfires are a significant cause of exposure to ambient air pollution in the United States and other settings. Although indoor air pollution is a known contributor to tuberculosis reactivation and progression, it is unclear whether ambient pollution exposures, including wildfire smoke, similarly increase risk. Objectives: To determine whether tuberculosis diagnosis was associated with recent exposure to acute outdoor air pollution events, including those caused by wildfire smoke. Methods: We conducted a case-crossover analysis of 6,238 patients aged ⩾15 years diagnosed with active tuberculosis disease between 2014 and 2019 in 8 California counties. Using geocoded address data, we characterized individuals' daily exposure to <2.5 µm-diameter particulate matter (PM2.5) during counterfactual risk periods 3-6 months before tuberculosis diagnosis (hazard period) and the same time 1 year previously (control period). We compared the frequency of residential PM2.5 exposures exceeding 35 µg/m3 (PM2.5 events) overall and for wildfire-associated and nonwildfire events during individuals' hazard and control periods. Measurements and Main Results: In total, 3,139 patients experienced 1 or more PM2.5 events during the hazard period, including 671 experiencing 1 or more wildfire-associated events. Adjusted odds of tuberculosis diagnosis increased by 5% (95% confidence interval, 3-6%) with each PM2.5 event experienced over the 6-month observation period. Each wildfire-associated PM2.5 event was associated with 23% (19-28%) higher odds of tuberculosis diagnosis in this time window, whereas no association was apparent for nonwildfire-associated events. Conclusions: Residential exposure to wildfire-associated ambient air pollution is associated with an increased risk of active tuberculosis diagnosis.

COVID-19 Incidence and Mortality Among Unvaccinated and Vaccinated Persons Aged ≥12 Years by Receipt of Bivalent Booster Doses and Time Since Vaccination - 24 U.S. Jurisdictions, October 3, 2021-December 24, 2022.

On September 1, 2022, CDC recommended an updated (bivalent) COVID-19 vaccine booster to help restore waning protection conferred by previous vaccination and broaden protection against emerging variants for persons aged ≥12 years (subsequently extended to persons aged ≥6 months).* To assess the impact of original (monovalent) COVID-19 vaccines and bivalent boosters, case and mortality rate ratios (RRs) were estimated comparing unvaccinated and vaccinated persons aged ≥12 years by overall receipt of and by time since booster vaccination (monovalent or bivalent) during Delta variant and Omicron sublineage (BA.1, BA.2, early BA.4/BA.5, and late BA.4/BA.5) predominance.† During the late BA.4/BA.5 period, unvaccinated persons had higher COVID-19 mortality and infection rates than persons receiving bivalent doses (mortality RR = 14.1 and infection RR = 2.8) and to a lesser extent persons vaccinated with only monovalent doses (mortality RR = 5.4 and infection RR = 2.5). Among older adults, mortality rates among unvaccinated persons were significantly higher than among those who had received a bivalent booster (65-79 years; RR = 23.7 and ≥80 years; 10.3) or a monovalent booster (65-79 years; 8.3 and ≥80 years; 4.2). In a second analysis stratified by time since booster vaccination, there was a progressive decline from the Delta period (RR = 50.7) to the early BA.4/BA.5 period (7.4) in relative COVID-19 mortality rates among unvaccinated persons compared with persons receiving who had received a monovalent booster within 2 weeks-2 months. During the early BA.4/BA.5 period, declines in relative mortality rates were observed at 6-8 (RR = 4.6), 9-11 (4.5), and ≥12 (2.5) months after receiving a monovalent booster. In contrast, bivalent boosters received during the preceding 2 weeks-2 months improved protection against death (RR = 15.2) during the late BA.4/BA.5 period. In both analyses, when compared with unvaccinated persons, persons who had received bivalent boosters were provided additional protection against death over monovalent doses or monovalent boosters. Restored protection was highest in older adults. All persons should stay up to date with COVID-19 vaccination, including receipt of a bivalent booster by eligible persons, to reduce the risk for severe COVID-19.

Severe Acute Respiratory Syndrome Coronavirus 2 and Respiratory Virus Sentinel Surveillance, California, USA, May 10, 2020-June 12, 2021.

State and local health departments established the California Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and Respiratory Virus Sentinel Surveillance System to conduct enhanced surveillance for SARS-CoV-2 and other respiratory pathogens at sentinel outpatient testing sites in 10 counties throughout California, USA. We describe results obtained during May 10, 2020‒June 12, 2021, and compare persons with positive and negative SARS-CoV-2 PCR results by using Poisson regression. We detected SARS-CoV-2 in 1,696 (19.6%) of 8,662 specimens. Among 7,851 specimens tested by respiratory panel, rhinovirus/enterovirus was detected in 906 (11.5%) specimens and other respiratory pathogens in 136 (1.7%) specimens. We also detected 23 co-infections with SARS-CoV-2 and another pathogen. SARS-CoV-2 positivity was associated with male participants, an age of 35-49 years, Latino race/ethnicity, obesity, and work in transportation occupations. Sentinel surveillance can provide useful virologic and epidemiologic data to supplement other disease monitoring activities and might become increasingly useful as routine testing decreases.

Application of a life table approach to assess duration of BNT162b2 vaccine-derived immunity by age using COVID-19 case surveillance data during the Omicron variant period.

BACKGROUND: SARS-CoV-2 Omicron variants have the potential to impact vaccine effectiveness and duration of vaccine-derived immunity. We analyzed U.S. multi-jurisdictional COVID-19 vaccine breakthrough surveillance data to examine potential waning of protection against SARS-CoV-2 infection for the Pfizer-BioNTech (BNT162b) primary vaccination series by age. METHODS: Weekly numbers of SARS-CoV-2 infections during January 16, 2022-May 28, 2022 were analyzed by age group from 22 U.S. jurisdictions that routinely linked COVID-19 case surveillance and immunization data. A life table approach incorporating line-listed and aggregated COVID-19 case datasets with vaccine administration and U.S. Census data was used to estimate hazard rates of SARS-CoV-2 infections, hazard rate ratios (HRR) and percent reductions in hazard rate comparing unvaccinated people to people vaccinated with a Pfizer-BioNTech primary series only, by age group and time since vaccination. RESULTS: The percent reduction in hazard rates for persons 2 weeks after vaccination with a Pfizer-BioNTech primary series compared with unvaccinated persons was lowest among children aged 5-11 years at 35.5% (95% CI: 33.3%, 37.6%) compared to the older age groups, which ranged from 68.7%-89.6%. By 19 weeks after vaccination, all age groups showed decreases in the percent reduction in the hazard rates compared with unvaccinated people; with the largest declines observed among those aged 5-11 and 12-17 years and more modest declines observed among those 18 years and older. CONCLUSIONS: The decline in vaccine protection against SARS-CoV-2 infection observed in this study is consistent with other studies and demonstrates that national case surveillance data were useful for assessing early signals in age-specific waning of vaccine protection during the initial period of SARS-CoV-2 Omicron variant predominance. The potential for waning immunity during the Omicron period emphasizes the importance of continued monitoring and consideration of optimal timing and provision of booster doses in the future.

Logically Inferred Tuberculosis Transmission (LITT): A Data Integration Algorithm to Rank Potential Source Cases.

Understanding tuberculosis (TB) transmission chains can help public health staff target their resources to prevent further transmission, but currently there are few tools to automate this process. We have developed the Logically Inferred Tuberculosis Transmission (LITT) algorithm to systematize the integration and analysis of whole-genome sequencing, clinical, and epidemiological data. Based on the work typically performed by hand during a cluster investigation, LITT identifies and ranks potential source cases for each case in a TB cluster. We evaluated LITT using a diverse dataset of 534 cases in 56 clusters (size range: 2-69 cases), which were investigated locally in three different U.S. jurisdictions. Investigators and LITT agreed on the most likely source case for 145 (80%) of 181 cases. By reviewing discrepancies, we found that many of the remaining differences resulted from errors in the dataset used for the LITT algorithm. In addition, we developed a graphical user interface, user's manual, and training resources to improve LITT accessibility for frontline staff. While LITT cannot replace thorough field investigation, the algorithm can help investigators systematically analyze and interpret complex data over the course of a TB cluster investigation. Code available at: https://github.com/CDCgov/TB_molecular_epidemiology/tree/1.0; https://zenodo.org/badge/latestdoi/166261171.