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.

Solid organ transplant recipients with tuberculosis disease in California, 2010 to 2020.

Using California Tuberculosis (TB) Registry data from 2010-2020, we compared the presentation and outcomes of patients with TB aged >15 years with and without solid organ transplantation (SOT). We matched to the United Network for Organ Sharing registry for 1987-2020 and the estimated time from transplantation to the diagnosis of TB, the incidence of posttransplant TB, and the probability of death and graft failure in SOT recipients with TB, compared to those without TB. From 2010-2020, there were 148 posttransplant TB cases. Patients with posttransplant TB were more likely to have extrapulmonary disease and more than twice as likely to die as TB patients without SOT (relative risk [RR], 2.2; 95% confidence interval [CI], 1.6-2.9). The median time from transplantation to TB diagnosis was 1.2 years, with the shortest time among lung transplant recipients. The incidence of TB disease among Californians with SOT was 56.0 per 100 000 person-years. The risk of death was higher among SOT recipients with posttransplant TB than those without (adjusted hazard ratio, 2.8; 95% CI, 2.0-4.1); the risk of graft failure was higher among kidney transplant recipients with posttransplant TB than those without (adjusted hazard ratio, 3.4; 95% CI, 1.7-6.9). An increased risk of death and graft failure in SOT recipients with posttransplant TB highlights the need for enhanced pretransplant TB prevention.

Comparative Modeling of Tuberculosis Epidemiology and Policy Outcomes in California.

Rationale: Mathematical modeling is used to understand disease dynamics, forecast trends, and inform public health prioritization. We conducted a comparative analysis of tuberculosis (TB) epidemiology and potential intervention effects in California, using three previously developed epidemiologic models of TB.Objectives: To compare the influence of various modeling methods and assumptions on epidemiologic projections of domestic latent TB infection (LTBI) control interventions in California.Methods: We compared model results between 2005 and 2050 under a base-case scenario representing current TB services and alternative scenarios including: 1) sustained interruption of Mycobacterium tuberculosis (Mtb) transmission, 2) sustained resolution of LTBI and TB prior to entry of new residents, and 3) one-time targeted testing and treatment of LTBI among 25% of non-U.S.-born individuals residing in California.Measurements and Main Results: Model estimates of TB cases and deaths in California were in close agreement over the historical period but diverged for LTBI prevalence and new Mtb infections-outcomes for which definitive data are unavailable. Between 2018 and 2050, models projected average annual declines of 0.58-1.42% in TB cases, without additional interventions. A one-time LTBI testing and treatment intervention among non-U.S.-born residents was projected to produce sustained reductions in TB incidence. Models found prevalent Mtb infection and migration to be more significant drivers of future TB incidence than local transmission.Conclusions: All models projected a stagnation in the decline of TB incidence, highlighting the need for additional interventions including greater access to LTBI diagnosis and treatment for non-U.S.-born individuals. Differences in model results reflect gaps in historical data and uncertainty in the trends of key parameters, demonstrating the need for high-quality, up-to-date data on TB determinants and outcomes.

Spatial distribution of tuberculosis incidence in Los Angeles County.

BACKGROUND: In Los Angeles County, the tuberculosis (TB) disease incidence rate is seven times higher among non-U.S.-born persons than U.S.-born persons and varies by country of birth. But translating these findings into public health action requires more granular information, especially considering that Los Angeles County is more than 4000 mile2. Local public health authorities may benefit from data on which areas of the county are most affected, yet these data remain largely unreported in part because of limitations of sparse data. We aimed to describe the spatial distribution of TB disease incidence in Los Angeles County while addressing challenges arising from sparse data and accounting for known cofactors. METHODS: Data on 5447 TB cases from Los Angeles County were combined with stratified population estimates available from the 2005-2011 Public Use Microdata Survey. TB disease incidence rates stratified by country of birth and Public Use Microdata Area were calculated and spatial smoothing was applied using a conditional autoregressive model. We used Bayesian Poisson models to investigate spatial patterns adjusting for age, sex, country of birth and years since initial arrival in the U.S. RESULTS: There were notable differences in the crude and spatially-smoothed maps of TB disease rates for high-risk subgroups, namely persons born in Mexico, Vietnam or the Philippines. Spatially-smoothed maps showed areas of high incidence in downtown Los Angeles and surrounding areas for persons born in the Philippines or Vietnam. Areas of high incidence were more dispersed for persons born in Mexico. Adjusted models suggested that the spatial distribution of TB disease could not be fully explained using age, sex, country of birth and years since initial arrival. CONCLUSIONS: This study highlights areas of high TB incidence within Los Angeles County both for U.S.-born cases and for cases born in Mexico, Vietnam or the Philippines. It also highlights areas that had high incidence rates even when accounting for non-spatial error and country of birth, age, sex, and years since initial arrival in the U.S. Information on spatial distribution provided here complements other descriptions of local disease burden and may help focus ongoing efforts to scale up testing for TB infection and treatment among high-risk subgroups.

Impact and Effectiveness of State-Level Tuberculosis Interventions in California, Florida, New York, and Texas: A Model-Based Analysis.

The incidence of tuberculosis (TB) in the United States has stabilized, and additional interventions are needed to make progress toward TB elimination. However, the impact of such interventions depends on local demography and the heterogeneity of populations at risk. Using state-level individual-based TB transmission models calibrated to California, Florida, New York, and Texas, we modeled 2 TB interventions: 1) increased targeted testing and treatment (TTT) of high-risk populations, including people who are non-US-born, diabetic, human immunodeficiency virus (HIV)-positive, homeless, or incarcerated; and 2) enhanced contact investigation (ECI) for contacts of TB patients, including higher completion of preventive therapy. For each intervention, we projected reductions in active TB incidence over 10 years (2016-2026) and numbers needed to screen and treat in order to avert 1 case. We estimated that TTT delivered to half of the non-US-born adult population could lower TB incidence by 19.8%-26.7% over a 10-year period. TTT delivered to smaller populations with higher TB risk (e.g., HIV-positive persons, homeless persons) and ECI were generally more efficient but had less overall impact on incidence. TTT targeted to smaller, highest-risk populations and ECI can be highly efficient; however, major reductions in incidence will only be achieved by also targeting larger, moderate-risk populations. Ultimately, to eliminate TB in the United States, a combination of these approaches will be necessary.

Association of Area-Based Socioeconomic Measures with Tuberculosis Incidence in California.

We assessed the association of area-based socio-economic status (SES) measures with tuberculosis (TB) incidence in California. We used TB disease data for 2012-2016 (n = 9901), population estimates, and SES measures to calculate incidence rates, rate ratios, and 95% confidence intervals (95% CI) by SES and birth country. SES was measured by census tract and was categorized by quartiles for education, crowding, and the California Healthy Places Index (HPI)and by specific cutoffs for poverty. The lowest SES areas defined by education, crowding, poverty, and HPI had 39%, 40%, 41%, and 33% of TB cases respectively. SES level was inversely associated with TB incidence across all SES measures and birth countries. TB rates were 3.2 (95% CI 3.0-3.4), 2.1 (95% CI 1.9-2.2), 3.6 (95% CI 3.3-3.8), and 2.0 (95% CI 1.9-2.1) times higher in lowest SES areas vs. highest SES areas as defined by education, crowding, poverty and HPI respectively. Area-based SES measures are associated with TB incidence in California. This information could inform TB prevention efforts in terms of materials, partnerships, and prioritization.

Health insurance, healthcare utilization and language use among populations who experience risk for tuberculosis, California 2014-2017.

BACKGROUND: California tuberculosis (TB) prevention goals include testing more than ten million at-risk Californians and treating two million infected with tuberculosis. Adequate health insurance and robust healthcare utilization are crucial to meeting these goals, but information on these factors for populations that experience risk for TB is limited. METHODS: We used data from the 2014-2017 California Health Interview Survey (n = 82,758), a population-based dual-frame telephone survey to calculate survey proportions and 95% confidence intervals (CI) stratified by country of birth, focusing on persons from countries of birth with the highest number of TB cases in California. Survey proportions for recent doctor's visit, overall health, smoking, and diabetes were age-adjusted. RESULTS: Among 18-64 year-olds, 27% (CI: 25-30) of persons born in Mexico reported being uninsured in contrast with 3% (CI: 1-5) of persons born in India. Report of recent doctor's visit was highest among persons born in the Philippines, 84% (CI: 80-89) and lowest among Chinese-born persons, 70% (CI: 63-76). Persons born in Mexico were more likely to report community clinics as their usual source of care than persons born in China, Vietnam, or the Philippines. Poverty was highest among Mexican-born persons, 56% (CI: 54-58) and lowest among Indian-born persons, 9% (CI: 5-13). Of adults with a medical visit in a non-English language, 96% (CI: 96-97) were non-U.S.-born, but only 42% (CI: 40-44) of non-U.S.-born persons had a visit in a non-English language. DISCUSSION: Many, though not all, of the populations that experience risk for TB had health insurance and used healthcare. We found key differences in usual source of care and language use by country of birth which should be considered when planning outreach to specific providers, clinic systems, insurers and communities for TB prevention and case-finding.

State-level prevalence estimates of latent tuberculosis infection in the United States by medical risk factors, demographic characteristics and nativity.

INTRODUCTION: Preventing tuberculosis (TB) disease requires treatment of latent TB infection (LTBI) as well as prevention of person-to-person transmission. We estimated the LTBI prevalence for the entire United States and for each state by medical risk factors, age, and race/ethnicity, both in the total population and stratified by nativity. METHODS: We created a mathematical model using all incident TB disease cases during 2013-2017 reported to the National Tuberculosis Surveillance System that were classified using genotype-based methods or imputation as not attributed to recent TB transmission. Using the annual average number of TB cases among US-born and non-US-born persons by medical risk factor, age group, and race/ethnicity, we applied population-specific reactivation rates (and corresponding 95% confidence intervals [CI]) to back-calculate the estimated prevalence of untreated LTBI in each population for the United States and for each of the 50 states and the District of Columbia in 2015. RESULTS: We estimated that 2.7% (CI: 2.6%-2.8%) of the U.S. population, or 8.6 (CI: 8.3-8.8) million people, were living with LTBI in 2015. Estimated LTBI prevalence among US-born persons was 1.0% (CI: 1.0%-1.1%) and among non-US-born persons was 13.9% (CI: 13.5%-14.3%). Among US-born persons, the highest LTBI prevalence was in persons aged ≥65 years (2.1%) and in persons of non-Hispanic Black race/ethnicity (3.1%). Among non-US-born persons, the highest LTBI prevalence was estimated in persons aged 45-64 years (16.3%) and persons of Asian and other racial/ethnic groups (19.1%). CONCLUSIONS: Our estimations of the prevalence of LTBI by medical risk factors and demographic characteristics for each state could facilitate planning for testing and treatment interventions to eliminate TB in the United States. Our back-calculation method feasibly estimates untreated LTBI prevalence and can be updated using future TB disease case counts at the state or national level.

Modeling the Impact of Recommendations for Primary Care-Based Screening for Latent Tuberculosis Infection in California.

OBJECTIVE: Targeted testing and treatment of persons with latent tuberculosis infection (LTBI) is a critical component of the US tuberculosis (TB) elimination strategy. In January 2016, the California Department of Public Health issued a tool and user guide for TB risk assessment (California tool) and guidance for LTBI testing, and in September 2016, the US Preventive Services Task Force (USPSTF) issued recommendations for LTBI testing in primary care settings. We estimated the epidemiologic effect of adherence to both recommendations in California. METHODS: We used an individual-based Markov micro-simulation model to estimate the number of cases of TB disease expected through 2026 with baseline LTBI strategies compared with implementation of the USPSTF or California tool guidance. We estimated the risk of LTBI by age and country of origin, the probability of being in a targeted population, and the probability of presenting for primary care based on available data. We assumed 100% adherence to testing guidance but imperfect adherence to treatment. RESULTS: Implementation of USPSTF and California tool guidance would result in nearly identical numbers of tests administered and cases of TB disease prevented. Perfect adherence to either recommendation would result in approximately 7000 cases of TB disease averted (40% reduction compared with baseline) by 2026. Almost all of this decline would be driven by a reduction in the number of cases among non-US-born persons. CONCLUSIONS: By focusing on the non-US-born population, adherence to LTBI testing strategies recommended by the USPSTF and the California tool could substantially reduce the burden of TB disease in California in the next decade.

Challenges and solutions to estimating tuberculosis disease incidence by country of birth in Los Angeles County.

BACKGROUND: Among U.S. residents, tuberculosis (TB) disease disproportionally affects non-U.S.-born persons and varies substantially by country of birth. Yet TB disease incidence rates by country of birth are not routinely reported despite these large, known health disparities. This is in part due to the technical challenges of using standard regression analysis with a communicable disease. Here, we estimate tuberculosis disease incidence rates by country of birth and demonstrate methods for overcoming these challenges using TB surveillance data from Los Angeles County which has more than 3.5 million non-U.S.-born residents. METHODS: Cross-sectional data on 5,447 cases of TB disease from Los Angeles County were combined with population estimates from the American Community Survey to calculate TB disease incidence rates for 2005 through 2011. Adjusted incidence rates were modelled using Poisson and negative binomial regressions. Bayesian models were used to account for the uncertainty in population estimates. RESULTS: The unadjusted incidence rate among non-U.S.-born persons was 15 per 100,000 person-years in contrast to the rate among U.S-born persons, 2 per 100,000. The unadjusted incidence rates were 44 and 12 per 100,000 person-years among persons born in the Philippines and Mexico, respectively. In adjusted analysis, persons born in the Philippines were 2.6 (95% CI: 2.3-3.1) times as likely to be reported as a TB case than persons born in Mexico. Bayesian models showed similar results. CONCLUSION: This study confirms substantial disparities in TB disease by country of birth in Los Angeles County. Accounting for age, gender, years in residence and year of diagnosis, persons from the Philippines, Vietnam and several other countries had much higher rates of reported TB disease than other foreign countries. We demonstrated that incidence rates by country of birth can be estimated using available data despite technical challenges.

Applications of electronic health information in public health: uses, opportunities & barriers.

Electronic health information systems can reshape the practice of public health including public health surveillance, disease and injury investigation and control, decision making, quality assurance, and policy development. While these opportunities are potentially transformative, and the federal program for the Meaningful Use (MU) of electronic health records (EHRs) has included important public health components, significant barriers remain. Unlike incentives in the clinical care system, scant funding is available to public health departments to develop the necessary information infrastructure and workforce capacity to capitalize on EHRs, personal health records, or Big Data. Current EHR systems are primarily built to serve clinical systems and practice rather than being structured for public health use. In addition, there are policy issues concerning how broadly the data can be used by public health officials. As these issues are resolved and workable solutions emerge, they should yield a more efficient and effective public health system.

Transmitted antiretroviral drug resistance in New York State, 2006-2008: results from a new surveillance system.

BACKGROUND: HIV transmitted drug resistance (TDR) is a public health concern because it has the potential to compromise antiretroviral therapy (ART) at the population level. In New York State, high prevalence of TDR in a local cohort and a multiclass resistant case cluster led to the development and implementation of a statewide resistance surveillance system. METHODOLOGY: We conducted a cross-sectional analysis of the 13,109 cases of HIV infection that were newly diagnosed and reported in New York State between 2006 and 2008, including 4,155 with HIV genotypes drawn within 3 months of initial diagnosis and electronically reported to the new resistance surveillance system. We assessed compliance with DHHS recommendations for genotypic resistance testing and estimated TDR among new HIV diagnoses. PRINCIPAL FINDINGS: Of 13,109 new HIV diagnoses, 9,785 (75%) had laboratory evidence of utilization of HIV-related medical care, and 4,155 (43%) had a genotype performed within 3 months of initial diagnosis. Of these, 11.2% (95% confidence interval [CI], 10.2%-12.1%) had any evidence of TDR. The proportion with mutations associated with any antiretroviral agent in the NNRTI, NRTI or PI class was 6.3% (5.5%-7.0%), 4.3% (3.6%-4.9%) and 2.9% (2.4%-3.4%), respectively. Multiclass resistance was observed in <1%. TDR did not increase significantly over time (p for trend = 0.204). Men who have sex with men were not more likely to have TDR than persons with heterosexual risk factor (OR 1.0 (0.77-1.30)). TDR to EFV+TDF+FTC and LPV/r+TDF+FTC regimens was 7.1% (6.3%-7.9%) and 1.4% (1.0%-1.8%), respectively. CONCLUSIONS/SIGNIFICANCE: TDR appears to be evenly distributed and stable among new HIV diagnoses in New York State; multiclass TDR is rare. Less than half of new diagnoses initiating care received a genotype per DHHS guidelines.