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Objectives. To understand the frequency, magnitude, geography, and characteristics of tuberculosis outbreaks in US state prisons. Methods. Using data from the National Tuberculosis Surveillance System, we identified all cases of tuberculosis during 2011 to 2019 that were reported as occurring among individuals incarcerated in a state prison at the time of diagnosis. We used whole-genome sequencing to define 3 or more cases within 2 single nucleotide polymorphisms within 3 years as clustered; we classified clusters with 6 or more cases during a 3-year period as tuberculosis outbreaks. Results. During 2011 to 2019, 566 tuberculosis cases occurred in 41 state prison systems (a median of 3 cases per state). A total of 19 tuberculosis genotype clusters comprising 134 cases were identified in 6 state prison systems; these clusters included a subset of 5 outbreaks in 2 states. Two Alabama outbreaks during 2011 to 2017 totaled 20 cases; 3 Texas outbreaks during 2014 to 2019 totaled 51 cases. Conclusions. Only Alabama and Texas reported outbreaks during the 9-year period; only Texas state prisons had ongoing transmission in 2019. Effective interventions are needed to stop tuberculosis outbreaks in Texas state prisons. (Am J Public Health. 2022;112(8):1170–1179. https://doi.org/10.2105/AJPH.2022.306864 )

Background Although most adults infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) fully recover, a proportion have ongoing symptoms, or post-COVID conditions (PCC), after infection. The objective of this analysis was to estimate the number of United States (US) adults with activity-limiting PCC on 1 November 2021. Methods We modeled the prevalence of PCC using reported infections occurring from 1 February 2020 to 30 September 2021, and population-based, household survey data on new activity-limiting symptoms ≥1 month following SARS-CoV-2 infection. From these data sources, we estimated the number and proportion of US adults with activity-limiting PCC on 1 November 2021 as 95% uncertainty intervals, stratified by sex and age. Sensitivity analyses adjusted for underascertainment of infections and uncertainty about symptom duration. Results On 1 November 2021, at least 3.0–5.0 million US adults, or 1.2%–1.9% of the US adult population, were estimated to have activity-limiting PCC of ≥1 month’s duration. Population prevalence was higher in females (1.4%–2.2%) than males. The estimated prevalence after adjusting for underascertainment of infections was 1.7%–3.8%. Conclusions Millions of US adults were estimated to have activity-limiting PCC. These estimates can support future efforts to address the impact of PCC on the US population.

By November 30, 2021, approximately 130,781 COVID-19-associated deaths, one in six of all U.S. deaths from COVID-19, had occurred in California and New York.* COVID-19 vaccination protects against infection with SARS-CoV-2 (the virus that causes COVID-19), associated severe illness, and death (1,2); among those who survive, previous SARS-CoV-2 infection also confers protection against severe outcomes in the event of reinfection (3,4). The relative magnitude and duration of infection- and vaccine-derived protection, alone and together, can guide public health planning and epidemic forecasting. To examine the impact of primary COVID-19 vaccination and previous SARS-CoV-2 infection on COVID-19 incidence and hospitalization rates, statewide testing, surveillance, and COVID-19 immunization data from California and New York (which account for 18% of the U.S. population) were analyzed. Four cohorts of adults aged ≥18 years were considered: persons who were 1) unvaccinated with no previous laboratory-confirmed COVID-19 diagnosis, 2) vaccinated (14 days after completion of a primary COVID-19 vaccination series) with no previous COVID-19 diagnosis, 3) unvaccinated with a previous COVID-19 diagnosis, and 4) vaccinated with a previous COVID-19 diagnosis. Age-adjusted hazard rates of incident laboratory-confirmed COVID-19 cases in both states were compared among cohorts, and in California, hospitalizations during May 30-November 20, 2021, were also compared. During the study period, COVID-19 incidence in both states was highest among unvaccinated persons without a previous COVID-19 diagnosis compared with that among the other three groups. During the week beginning May 30, 2021, compared with COVID-19 case rates among unvaccinated persons without a previous COVID-19 diagnosis, COVID-19 case rates were 19.9-fold (California) and 18.4-fold (New York) lower among vaccinated persons without a previous diagnosis; 7.2-fold (California) and 9.9-fold lower (New York) among unvaccinated persons with a previous COVID-19 diagnosis; and 9.6-fold (California) and 8.5-fold lower (New York) among vaccinated persons with a previous COVID-19 diagnosis. During the same period, compared with hospitalization rates among unvaccinated persons without a previous COVID-19 diagnosis, hospitalization rates in California followed a similar pattern. These relationships changed after the SARS-CoV-2 Delta variant became predominant (i.e., accounted for50% of sequenced isolates) in late June and July. By the week beginning October 3, compared with COVID-19 cases rates among unvaccinated persons without a previous COVID-19 diagnosis, case rates among vaccinated persons without a previous COVID-19 diagnosis were 6.2-fold (California) and 4.5-fold (New York) lower; rates were substantially lower among both groups with previous COVID-19 diagnoses, including 29.0-fold (California) and 14.7-fold lower (New York) among unvaccinated persons with a previous diagnosis, and 32.5-fold (California) and 19.8-fold lower (New York) among vaccinated persons with a previous diagnosis of COVID-19. During the same period, compared with hospitalization rates among unvaccinated persons without a previous COVID-19 diagnosis, hospitalization rates in California followed a similar pattern. These results demonstrate that vaccination protects against COVID-19 and related hospitalization, and that surviving a previous infection protects against a reinfection and related hospitalization. Importantly, infection-derived protection was higher after the Delta variant became predominant, a time when vaccine-induced immunity for many persons declined because of immune evasion and immunologic waning (2,5,6). Similar cohort data accounting for booster doses needs to be assessed, as new variants, including Omicron, circulate. Although the epidemiology of COVID-19 might change with the emergence of new variants, vaccination remains the safest strategy to prevent SARS-CoV-2 infections and associated complications; all eligible persons should be up to date with COVID-19 vaccination. Additional recommendations for vaccine doses might be warranted in the future as the virus and immunity levels change.

The COVID-19 pandemic and subsequent implementation of nonpharmaceutical interventions (e.g., cessation of global travel, mask use, physical distancing, and staying home) reduced transmission of some viral respiratory pathogens (1). In the United States, influenza activity decreased in March 2020, was historically low through the summer of 2020 (2), and remained low during October 2020-May 2021 (

COVID-19 vaccine breakthrough infection surveillance helps monitor trends in disease incidence and severe outcomes in fully vaccinated persons, including the impact of the highly transmissible B.1.617.2 (Delta) variant of SARS-CoV-2, the virus that causes COVID-19. Reported COVID-19 cases, hospitalizations, and deaths occurring among persons aged ≥18 years during April 4-July 17, 2021, were analyzed by vaccination status across 13 U.S. jurisdictions that routinely linked case surveillance and immunization registry data. Averaged weekly, age-standardized incidence rate ratios (IRRs) for cases among persons who were not fully vaccinated compared with those among fully vaccinated persons decreased from 11.1 (95% confidence interval [CI] = 7.8-15.8) to 4.6 (95% CI = 2.5-8.5) between two periods when prevalence of the Delta variant was lower (

Increases in severe respiratory illness and acute flaccid myelitis (AFM) among children and adolescents resulting from enterovirus D68 (EV-D68) infections occurred biennially in the United States during 2014, 2016, and 2018, primarily in late summer and fall. Although EV-D68 annual trends are not fully understood, EV-D68 levels were lower than expected in 2020, potentially because of implementation of COVID-19 mitigation measures (e.g., wearing face masks, enhanced hand hygiene, and physical distancing) (1). In August 2022, clinicians in several geographic areas notified CDC of an increase in hospitalizations of pediatric patients with severe respiratory illness and positive rhinovirus/enterovirus (RV/EV) test results.* Surveillance data were analyzed from multiple national data sources to characterize reported trends in acute respiratory illness (ARI), asthma/reactive airway disease (RAD) exacerbations, and the percentage of positive RV/EV and EV-D68 test results during 2022 compared with previous years. These data demonstrated an increase in emergency department (ED) visits by children and adolescents with ARI and asthma/RAD in late summer 2022. The percentage of positive RV/EV test results in national laboratory-based surveillance and the percentage of positive EV-D68 test results in pediatric sentinel surveillance also increased during this time. Previous increases in EV-D68 respiratory illness have led to substantial resource demands in some hospitals and have also coincided with increases in cases of AFM (2), a rare but serious neurologic disease affecting the spinal cord. Therefore, clinicians should consider AFM in patients with acute flaccid limb weakness, especially after respiratory illness or fever, and ensure prompt hospitalization and referral to specialty care for such cases. Clinicians should also test for poliovirus infection in patients suspected of having AFM because of the clinical similarity to acute flaccid paralysis caused by poliovirus. Ongoing surveillance for EV-D68 is critical to ensuring preparedness for possible future increases in ARI and AFM.

Populations of indigenous persons are frequently associated with pronounced disparities in rates of tuberculosis (TB) disease compared to co-occurring nonindigenous populations. Using data from the National Tuberculosis Surveillance System on TB cases in U.S.-born patients reported in the United States during 2009–2019, we calculated incidence rate ratios and risk ratios for TB risk factors to compare cases in American Indian or Alaska Native (AIAN) and Native Hawaiian or other Pacific Islander (NHPI) TB patients to cases in White TB patients. Annual TB incidence rates among AIAN and NHPI TB patients were on average ≥10 times higher than among White TB patients. Compared to White TB patients, AIAN and NHPI TB patients were 1.91 (95% confidence interval (CI): 1.35–2.71) and 3.39 (CI: 1.44–5.74) times more likely to have renal disease or failure, 1.33 (CI: 1.16–1.53) and 1.63 (CI: 1.20–2.20) times more likely to have diabetes mellitus, and 0.66 (CI: 0.44–0.99) and 0.19 (CI: 0–0.59) times less likely to be HIV positive, respectively. AIAN TB patients were 1.84 (CI: 1.69–2.00) and 1.48 (CI: 1.27–1.71) times more likely to report using excess alcohol and experiencing homelessness, respectively. TB among U.S. indigenous persons is associated with persistent and concerning health disparities.

SARS-CoV-2, the virus that causes COVID-19, is constantly mutating, leading to new variants (1). Variants have the potential to affect transmission, disease severity, diagnostics, therapeutics, and natural and vaccine-induced immunity. In November 2020, CDC established national surveillance for SARS-CoV-2 variants using genomic sequencing. As of May 6, 2021, sequences from 177,044 SARS-CoV-2-positive specimens collected during December 20, 2020-May 6, 2021, from 55 U.S. jurisdictions had been generated by or reported to CDC. These included 3,275 sequences for the 2-week period ending January 2, 2021, compared with 25,000 sequences for the 2-week period ending April 24, 2021 (0.1% and 3.1% of reported positive SARS-CoV-2 tests, respectively). Because sequences might be generated by multiple laboratories and sequence availability varies both geographically and over time, CDC developed statistical weighting and variance estimation methods to generate population-based estimates of the proportions of identified variants among SARS-CoV-2 infections circulating nationwide and in each of the 10 U.S. Department of Health and Human Services (HHS) geographic regions.* During the 2-week period ending April 24, 2021, the B.1.1.7 and P.1 variants represented an estimated 66.0% and 5.0% of U.S. SARS-CoV-2 infections, respectively, demonstrating the rise to predominance of the B.1.1.7 variant of concern† (VOC) and emergence of the P.1 VOC in the United States. Using SARS-CoV-2 genomic surveillance methods to analyze surveillance data produces timely population-based estimates of the proportions of variants circulating nationally and regionally. Surveillance findings demonstrate the potential for new variants to emerge and become predominant, and the importance of robust genomic surveillance. Along with efforts to characterize the clinical and public health impact of SARS-CoV-2 variants, surveillance can help guide interventions to control the COVID-19 pandemic in the United States.

Although most adults infected with SARS-CoV-2 fully recover, a proportion have ongoing symptoms, or post-COVID conditions (PCC), after infection. The objective of this analysis was to estimate the number of US adults with activity-limiting PCC on November 1, 2021.We modeled the prevalence of PCC using reported infections occurring from February 1, 2020 - September 30, 2021, and population-based, household survey data on new activity-limiting symptoms ≥1 month following SARS-CoV-2 infection. From these data sources, we estimated the number and proportion of US adults with activity-limiting PCC on November 1, 2021, as 95% uncertainty intervals, stratified by sex and age. Sensitivity analyses adjusted for under-ascertainment of infections and uncertainty about symptom duration.On November 1, 2021, at least 3.0-5.0 million US adults were estimated to have activity-limiting PCC of ≥1 month duration, or 1.2%-1.9% of US adults. Population prevalence was higher in females (1.4%-2.2%) than males. The estimated prevalence after adjusting for under-ascertainment of infections was 1.7%-3.8%.Millions of US adults were estimated to have activity-limiting PCC. These estimates can support future efforts to address the impact of PCC on the U.S. population.

The four common human coronaviruses (HCoVs), including two alpha (HCoV-NL63 and HCoV-229E) and two beta (HCoV-HKU1 and HCoV-OC43) types, generally cause mild, upper respiratory illness. HCoVs are known to have seasonal patterns and variation in predominant types each year, but defined measures of seasonality are needed. We defined seasonality of HCoVs during July 2014 to November 2021 in the United States using a retrospective method applied to National Respiratory and Enteric Virus Surveillance System (NREVSS) data. In the six HCoV seasons prior to 2020-2021, onsets ranged from October to November, peaks from January to February, and offsets from April to June; most (>93%) HCoV detections occurred within the defined seasonal onsets and offsets. The 2020-2021 HCoV season onset was delayed by 11 weeks compared to prior seasons, likely due to COVID-19 mitigation efforts. Better defining HCoV seasonality can inform clinical preparedness and the expected patterns of emerging HCoVs.Article Summary LineThe typical common HCoV season in the United States starts between October and November, peaks towards the end of January, and ends between April and June, but the 2020-2021 season was markedly delayed compared to prior seasons.

BACKGROUND: Recent evidence suggests transmission of Mycobacterium tuberculosis (Mtb) may be characterized by extreme individual heterogeneity in secondary cases (i.e., few cases account for the majority of transmission). Such heterogeneity implies outbreaks are rarer but more extensive and has profound implications in infectious disease control. However, discrete person-to-person transmission events in tuberculosis (TB) are often unobserved, precluding our ability to directly quantify individual heterogeneity in TB epidemiology. METHODS: We used a modified negative binomial branching process model to quantify the extent of individual heterogeneity using only observed transmission cluster size distribution data (i.e., the simple sum of all cases in a transmission chain) without knowledge of individual-level transmission events. The negative binomial parameter k quantifies the extent of individual heterogeneity (generally, k < 1 indicates extensive heterogeneity, and as k → ∞ transmission becomes more homogenous). We validated the robustness of the inference procedure considering common limitations affecting cluster size data. Finally, we demonstrate the epidemiologic utility of this method by applying it to aggregate US molecular surveillance data from the US Centers for Disease Control and Prevention. RESULTS: The cluster-based method reliably inferred k using TB transmission cluster data despite a high degree of bias introduced into the model. We found that the TB transmission in the United States was characterized by a high propensity for extensive outbreaks ([Formula: see text]; 95% confidence interval = 0.09, 0.10). CONCLUSIONS: The proposed method can accurately quantify critical parameters that govern TB transmission using simple, more easily obtainable cluster data to improve our understanding of TB epidemiology.

Genomic surveillance is a critical tool for tracking emerging variants of SARS-CoV-2 (the virus that causes COVID-19), which can exhibit characteristics that potentially affect public health and clinical interventions, including increased transmissibility, illness severity, and capacity for immune escape. During June 2021-January 2022, CDC expanded genomic surveillance data sources to incorporate sequence data from public repositories to produce weighted estimates of variant proportions at the jurisdiction level and refined analytic methods to enhance the timeliness and accuracy of national and regional variant proportion estimates. These changes also allowed for more comprehensive variant proportion estimation at the jurisdictional level (i.e., U.S. state, district, territory, and freely associated state). The data in this report are a summary of findings of recent proportions of circulating variants that are updated weekly on CDC's COVID Data Tracker website to enable timely public health action.

Previous reports of COVID-19 case, hospitalization, and death rates by vaccination status

Vaccination against SARS-CoV-2, the virus that causes COVID-19, is highly effective at preventing COVID-19-associated hospitalization and death; however, some vaccinated persons might develop COVID-19 with severe outcomes

This study describes characteristics of large tuberculosis (TB) outbreaks in the United States detected using novel molecular surveillance methods during 2014-2016 and followed for 2 years through 2018.We developed 4 genotype-based detection algorithms to identify large TB outbreaks of ≥10 cases related by recent transmission during a 3-year period. We used whole-genome sequencing and epidemiologic data to assess evidence of recent transmission among cases.There were 24 large outbreaks involving 518 cases; patients were primarily U.S.-born (85.1%) racial/ethnic minorities (84.1%). Compared with all other TB patients, patients associated with large outbreaks were more likely to report substance use, homelessness, and having been diagnosed while incarcerated. Most large outbreaks primarily occurred within residences among families and nonfamilial social contacts. A source case with a prolonged infectious period and difficulties in eliciting contacts were commonly reported contributors to transmission.Large outbreak surveillance can inform targeted interventions to decrease outbreak-associated TB morbidity.

Tuberculosis (TB) control programs use whole-genome sequencing (WGS) of Mycobacterium tuberculosis (Mtb) for detecting and investigating TB case clusters. Existence of few genomic differences between Mtb isolates might indicate TB cases are the result of recent transmission. However, the variable and sometimes long duration of latent infection, combined with uncertainty in the Mtb mutation rate during latency, can complicate interpretation of WGS results. To estimate the association between infection duration and single nucleotide polymorphism (SNP) accumulation in the Mtb genome, we first analyzed pairwise SNP differences among TB cases from Los Angeles County, California, with strong epidemiologic links. We found that SNP distance alone was insufficient for concluding that cases are linked through recent transmission. Second, we describe a well-characterized cluster of TB cases in California to illustrate the role of genomic data in conclusions regarding recent transmission. Longer presumed latent periods were inconsistently associated with larger SNP differences. Our analyses suggest that WGS alone cannot be used to definitively determine that a case is attributable to recent transmission. Methods for integrating clinical, epidemiologic, and genomic data can guide conclusions regarding the likelihood of recent transmission, providing local public health practitioners with better tools for monitoring and investigating TB transmission.

Background Reductions in tuberculosis (TB) transmission have been instrumental in lowering TB incidence in the United States. Sustaining and augmenting these reductions are key public health priorities. Methods We fit mechanistic transmission models to distributions of genotype clusters of TB cases reported to the Centers for Disease Control and Prevention during 2012–2016 in the United States and separately in California, Florida, New York, and Texas. We estimated the mean number of secondary cases generated per infectious case (R0) and individual-level heterogeneity in R0 at state and national levels and assessed how different definitions of clustering affected these estimates. Results In clusters of genotypically linked TB cases that occurred within a state over a 5-year period (reference scenario), the estimated R0 was 0.29 (95% confidence interval [CI], .28–.31) in the United States. Transmission was highly heterogeneous; 0.24% of simulated cases with individual R0 >10 generated 19% of all recent secondary transmissions. R0 estimate was 0.16 (95% CI, .15–.17) when a cluster was defined as cases occurring within the same county over a 3-year period. Transmission varied across states: estimated R0s were 0.34 (95% CI, .3–.4) in California, 0.28 (95% CI, .24–.36) in Florida, 0.19 (95% CI, .15–.27) in New York, and 0.38 (95% CI, .33–.46) in Texas. Conclusions TB transmission in the United States is characterized by pronounced heterogeneity at the individual and state levels. Improving detection of transmission clusters through incorporation of whole-genome sequencing and identifying the drivers of this heterogeneity will be essential to reducing TB transmission.

The COVID-19 pandemic and subsequent implementation of nonpharmaceutical interventions (e.g., cessation of global travel, mask use, physical distancing, and staying home) reduced transmission of some viral respiratory pathogens (1). In the United States, influenza activity decreased in March 2020, was historically low through the summer of 2020 (2), and remained low during October 2020-May 2021 (

Populations of indigenous persons are frequently associated with pronounced disparities in rates of tuberculosis (TB) disease compared to co-occurring nonindigenous populations.Using data from the National Tuberculosis Surveillance System on TB cases in U.S.-born patients reported in the United States during 2009-2019, we calculated incidence rate ratios and risk ratios for TB risk factors to compare cases in American Indian or Alaska Native (AIAN) and Native Hawaiian or other Pacific Islander (NHPI) TB patients to cases in White TB patients.Annual TB incidence rates among AIAN and NHPI TB patients were on average ≥10 times higher than among White TB patients. Compared to White TB patients, AIAN and NHPI TB patients were 1.91 (95% confidence interval (CI): 1.35-2.71) and 3.39 (CI: 1.44-5.74) times more likely to have renal disease or failure, 1.33 (CI: 1.16-1.53) and 1.63 (CI: 1.20-2.20) times more likely to have diabetes mellitus, and 0.66 (CI: 0.44-0.99) and 0.19 (CI: 0-0.59) times less likely to be HIV positive, respectively. AIAN TB patients were 1.84 (CI: 1.69-2.00) and 1.48 (CI: 1.27-1.71) times more likely to report using excess alcohol and experiencing homelessness, respectively.TB among U.S. indigenous persons is associated with persistent and concerning health disparities.

OBJECTIVES: Persons experiencing homelessness (PEH) are disproportionately affected by tuberculosis (TB). We estimate area-specific rates of TB among PEH and characterize the extent to which available data support recent transmission as an explanation of high TB incidence. METHODS: We estimated TB incidence among PEH using National Tuberculosis Surveillance System data and population estimates for the US Department of Housing and Urban Development’s Continuums of Care areas. For areas with TB incidence higher than the national average among PEH, we estimated recent transmission using genotyping and a plausible source-case method. For cases with ≥ 1 plausible source case, we assessed with TB program partners whether available whole-genome sequencing and local epidemiologic data were consistent with recent transmission. RESULTS: During 2011–2016, 3164 TB patients reported experiencing homelessness. National incidence was 36 cases/100,000 PEH. Incidence estimates varied among 21 areas with ≥ 10,000 PEH (9–150 cases/100,000 PEH); 9 areas had higher than average incidence. Of the 2349 cases with Mycobacterium tuberculosis genotyping results, 874 (37%) had ≥ 1 plausible source identified. In the 9 areas, 23%–82% of cases had ≥ 1 plausible source. Of cases with ≥ 1 plausible source, 63% were consistent and 7% were inconsistent with recent transmission; 29% were inconclusive. CONCLUSIONS: Disparities in TB incidence for PEH persist; estimates of TB incidence and recent transmission vary by area. With a better understanding of the TB risk among PEH in their jurisdictions and the role of recent transmission as a driver, programs can make more informed decisions about prioritizing TB prevention strategies.

On December 14, 2020, the United Kingdom reported a SARS-CoV-2 variant of concern (VOC), lineage B.1.1.7, also referred to as VOC 202012/01 or 20I/501Y.V1.* The B.1.1.7 variant is estimated to have emerged in September 2020 and has quickly become the dominant circulating SARS-CoV-2 variant in England (1). B.1.1.7 has been detected in over 30 countries, including the United States. As of January 13, 2021, approximately 76 cases of B.1.1.7 have been detected in 12 U.S. states.† Multiple lines of evidence indicate that B.1.1.7 is more efficiently transmitted than are other SARS-CoV-2 variants (1-3). The modeled trajectory of this variant in the U.S. exhibits rapid growth in early 2021, becoming the predominant variant in March. Increased SARS-CoV-2 transmission might threaten strained health care resources, require extended and more rigorous implementation of public health strategies (4), and increase the percentage of population immunity required for pandemic control. Taking measures to reduce transmission now can lessen the potential impact of B.1.1.7 and allow critical time to increase vaccination coverage. Collectively, enhanced genomic surveillance combined with continued compliance with effective public health measures, including vaccination, physical distancing, use of masks, hand hygiene, and isolation and quarantine, will be essential to limiting the spread of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19). Strategic testing of persons without symptoms but at higher risk of infection, such as those exposed to SARS-CoV-2 or who have frequent unavoidable contact with the public, provides another opportunity to limit ongoing spread.

Tuberculosis (TB) control programs prevent transmission of Mycobacterium tuberculosis by identifying and treating active cases of TB disease and ensuring that contacts of infectious cases are also identified, screened, and treated for active disease or latent infection. The chapter reviews the use of genotyping to investigate transmission as well as how genotyping methods have been applied to study transmission dynamics, lineage, recurrent TB disease, mixed infections, and laboratory contamination. A common outbreak investigation goal is to combine genotyping data with different sources of clinical, epidemiological, and programmatic data through partnerships that lead investigators to the best conclusions and public health action for control of recent transmission. Although spatial analyses of TB case distributions are common, they are heterogeneous in their methods and findings. The central problem with using genotype clustering to estimate recent transmission has been that clustered cases are not necessarily part of the same chain of transmission.

BACKGROUND Using genotyping techniques that have differentiated Mycobacterium bovis from Mycobacterium tuberculosis since 2005, we review the epidemiology of human tuberculosis caused by M. bovis in the United States and validate previous findings nationally. METHODS All tuberculosis cases with a genotyped M. tuberculosis complex isolate reported during 2006-2013 in the United States were eligible for analysis. We used binomial regression to identify characteristics independently associated with M. bovis disease using adjusted prevalence ratios (aPRs) and corresponding 95% confidence intervals (CIs). RESULTS During 2006-2013, the annual percentages of tuberculosis cases attributable to M. bovis remained consistent nationally (range, 1.3%-1.6%) among all tuberculosis cases (N = 59 273). Compared with adults 25-44 years of age, infants aged 0-4 years (aPR, 1.9 [95% CI, 1.4-2.8]) and children aged 5-14 years (aPR, 4.0 [95% CI, 3.1-5.3]) had higher prevalences of M. bovis disease. Patients who were foreign-born (aPR, 1.4 [95% CI, 1.2-1.7]), Hispanic (aPR, 3.9 [95% CI, 3.0-5.0]), female (aPR, 1.4 [95% CI, 1.3-1.6]), and resided in US-Mexico border counties (aPR, 2.0 [95% CI, 1.7-2.4]) also had higher M. bovis prevalences. Exclusively extrapulmonary disease (aPR, 3.7 [95% CI, 3.3-4.2]) or disease that was both pulmonary and extrapulmonary (aPR, 2.4 [95% CI, 2.1-2.9]) were associated with a higher prevalence of M. bovis disease. CONCLUSIONS Children, foreign-born persons, Hispanics, and females are disproportionately affected by M. bovis, which was independently associated with extrapulmonary disease. Targeted prevention efforts aimed at Hispanic mothers and caregivers are warranted.

Background. In 2011, a multistate outbreak of listeriosis linked to contaminated cantaloupes raised concerns that many pregnant women might have been exposed toListeria monocytogenes. Listeriosis during pregnancy can cause fetal death, premature delivery, and neonatal sepsis and meningitis. Little information is available to guide healthcare providers who care for asymptomatic pregnant women with suspectedL. monocytogenesexposure.Methods. We tracked pregnancy-associated listeriosis cases using reportable diseases surveillance and enhanced surveillance for fetal death using vital records and inpatient fetal deaths data in Colorado. We surveyed 1,060 pregnant women about symptoms and exposures. We developed three methods to estimate how many pregnant women in Colorado ate the implicated cantaloupes, and we calculated attack rates.Results. One laboratory-confirmed case of listeriosis was associated with pregnancy. The fetal death rate did not increase significantly compared to preoutbreak periods. Approximately 6,500–12,000 pregnant women in Colorado might have eaten the contaminated cantaloupes, an attack rate of ~1 per 10,000 exposed pregnant women.Conclusions. Despite many exposures, the risk of pregnancy-associated listeriosis was low. Our methods for estimating attack rates may help during future outbreaks and product recalls. Our findings offer relevant considerations for management of asymptomatic pregnant women with possibleL. monocytogenesexposure.

Measuring tuberculosis transmission is exceedingly difficult, given the remarkable variability in the timing of clinical disease after Mycobacterium tuberculosis infection; incident disease can result from either a recent (ie, weeks to months) or a remote (ie, several years to decades) infection event. Although we cannot identify with certainty the timing and location of tuberculosis transmission for individuals, approaches for estimating the individual probability of recent transmission and for estimating the fraction of tuberculosis cases due to recent transmission in populations have been developed. Data used to estimate the probable burden of recent transmission include tuberculosis case notifications in young children and trends in tuberculin skin test and interferon γ–release assays. More recently, M. tuberculosis whole-genome sequencing has been used to estimate population levels of recent transmission, identify the distribution of specific strains within communities, and decipher chains of transmission among culture-positive tuberculosis cases. The factors that drive the transmission of tuberculosis in communities depend on the burden of prevalent tuberculosis; the ways in which individuals live, work, and interact (eg, congregate settings); and the capacity of healthcare and public health systems to identify and effectively treat individuals with infectious forms of tuberculosis. Here we provide an overview of these factors, describe tools for measurement of ongoing transmission, and highlight knowledge gaps that must be addressed.

We assessed characteristics associated with all-cause mortality among US patients with multidrug-resistant tuberculosis. Mortality decreased from 31% during 1993-2002 to 11% during 2003-2013. Directly observed therapy coverage increased from 74% to 95% and was protective against all-cause mortality after accounting for demographics, clinical characteristics, human immunodeficiency virus status, and period of treatment.

Listeriosis is characterized by bacteremia or meningitis. We searched for listeriosis case series and outbreak investigations published in English by 2013, and assessed the strength of evidence for foodborne acquisition among patients who ate hospital food. We identified 30 reports from 13 countries. Among the case series, the median proportion of cases considered to be hospital-acquired was 25% (range, 9%-67%). The median number of outbreak-related illnesses considered to be hospital-acquired was 4.0 (range, 2-16). All patients were immunosuppressed in 18 of 24 (75%) reports with available data. Eight outbreak reports with strong evidence for foodborne acquisition in a hospital implicated sandwiches (3 reports), butter, precut celery, Camembert cheese, sausage, and tuna salad (1 report each). Foodborne acquisition of listeriosis among hospitalized patients is well documented internationally. The number of listeriosis cases could be reduced substantially by establishing hospital policies for safe food preparation for immunocompromised patients and by not serving them higher-risk foods.

Listeria monocytogenes is a leading cause of hospitalization, fetal loss, and death due to foodborne illnesses in the United States. A quantitative assessment of the relative risk of listeriosis associated with the consumption of 23 selected categories of ready-to-eat foods, published by the U.S. Department of Health and Human Services and the U.S. Department of Agriculture in 2003, has been instrumental in identifying the food products and practices that pose the greatest listeriosis risk and has guided the evaluation of potential intervention strategies. Dose-response models, which quantify the relationship between an exposure dose and the probability of adverse health outcomes, were essential components of the risk assessment. However, because of data gaps and limitations in the available data and modeling approaches, considerable uncertainty existed. Since publication of the risk assessment, new data have become available for modeling L. monocytogenes dose-response. At the same time, recent advances in the understanding of L. monocytogenes pathophysiology and strain diversity have warranted a critical reevaluation of the published dose-response models. To discuss strategies for modeling L. monocytogenes dose-response, the Interagency Risk Assessment Consortium (IRAC) and the Joint Institute for Food Safety and Applied Nutrition (JIFSAN) held a scientific workshop in 2011 (details available at http://foodrisk.org/irac/events/). The main findings of the workshop and the most current and relevant data identified during the workshop are summarized and presented in the context of L. monocytogenes dose-response. This article also discusses new insights on dose-response modeling for L. monocytogenes and research opportunities to meet future needs.

Household air pollution is a risk factor for pneumonia, the leading cause of death among children < 5 years of age. From 2008 to 2010, a Kenyan organization sold ~2,500 ceramic cookstoves (upesi jiko) that produce less visible household smoke than 3-stone firepits. During a year-long observational study, we made 25 biweekly visits to 200 homes to determine stove use and observe signs of acute respiratory infection in children < 3 years of age. Reported stove use included 3-stone firepit only (81.8%), upesi jiko only (15.7%), and both (2.3%). Lower, but not statistically significant, percentages of children in upesi jiko-using households than 3-stone firepit-using households had observed cough (1.3% versus 2.9%, rate ratio (RR) 0.48, 95% confidence interval (CI): 0.22-1.03), pneumonia (0.9% versus 1.7%, RR 0.60, 95% CI: 0.24-1.48), and severe pneumonia (0.3% versus 0.6%, RR 0.66, 95% CI: 0.17-2.62). Upesi jiko use did not result in significantly lower pneumonia rates. Further research on the health impact of improved cookstoves is warranted. BACKGROUND Pneumonia is the leading cause of death among children under 5 years of age in developing countries. Annually, ~70% of 1.6 million deaths from pneumonia among children occur in Southeast Asia and sub-Saharan Africa. 1,2 Cooking indoors with open fires, unprocessed biomass fuel, and inad- equate ventilation is common in developing countries and generates high levels of household air pollution (HAP). 3 Women and their young children usually have the greatest expo- sures to HAP, including particulate matter, carbon monoxide, and nitrous oxides. Consequently, they are at greatest risk of adverse health effects from HAP. 4 One study estimated that young children who are exposed to HAP have a nearly 2-fold greater risk of acquiring pneumonia compared with young children without HAP exposure. 5 In 2000, Smith and others 6 estimated that 910,000 deaths from acute respiratory infec- tions in children under 5 years of age were attributable to HAP. To address the public health burden of HAP, a global effort is underway to develop and distribute improved cookstoves that reduce emissions of particulate matter. The Global Alli- ance for Clean Cookstoves, a public-private partnership, was formed in 2010 to encourage the adoption of 100 million

Listeria monocytogenes (Lm) causes severe foodborne illness (listeriosis). Previous molecular subtyping methods, such as pulsed-field gel electrophoresis (PFGE), were critical in detecting outbreaks that led to food safety improvements and declining incidence, but PFGE provides limited genetic resolution. A multiagency collaboration began performing real-time, whole-genome sequencing (WGS) on all US Lm isolates from patients, food, and the environment in September 2013, posting sequencing data into a public repository. Compared with the year before the project began, WGS, combined with epidemiologic and product trace-back data, detected more listeriosis clusters and solved more outbreaks (2 outbreaks in pre-WGS year, 5 in WGS year 1, and 9 in year 2). Whole-genome multilocus sequence typing and single nucleotide polymorphism analyses provided equivalent phylogenetic relationships relevant to investigations; results were most useful when interpreted in context of epidemiological data. WGS has transformed listeriosis outbreak surveillance and is being implemented for other foodborne pathogens.

BACKGROUND Listeria monocytogenes causes often-fatal infections affecting mainly immunocompromised persons. Sources of hospital-acquired listeriosis outbreaks can be difficult to identify. We investigated a listeriosis outbreak spanning 7 months and involving 5 hospitals. METHODS Outbreak-related cases were identified by pulsed-field gel electrophoresis (PFGE) and confirmed by multiple-locus variable-number tandem-repeat analysis (MLVA). We conducted patient interviews, medical records reviews, and hospital food source evaluations. Food and environmental specimens were collected at a hospital (hospital A) where 6 patients had been admitted before listeriosis onset; these specimens were tested by culture, polymerase chain reaction (PCR), and PFGE. We collected and tested food and environmental samples at the implicated processing facility. RESULTS Ten outbreak-related patients were immunocompromised by ≥1 underlying conditions or treatments; 5 died. All patients had been admitted to or visited an acute-care hospital during their possible incubation periods. The outbreak strain of L. monocytogenes was isolated from chicken salad and its diced celery ingredient at hospital A, and in 19 of >200 swabs of multiple surfaces and in 8 of 11 diced celery products at the processing plant. PCR testing detected Listeria in only 3 of 10 environmental and food samples from which it was isolated by culturing. The facility was closed, products were recalled, and the outbreak ended. CONCLUSIONS Contaminated diced celery caused a baffling, lengthy outbreak of hospital-acquired listeriosis. PCR testing often failed to detect the pathogen, suggesting its reliability should be further evaluated. Listeriosis risk should be considered in fresh produce selections for immunocompromised patients.

Opportunities for improved disease reporting are identified by describing physicians' reporting knowledge and practices as well as reporting knowledge and specimen referral patterns among clinical laboratories in the state of Georgia. In 2005, a sample of physicians(n = 177) and all Georgia clinical laboratories (n = 139) were surveyed about reporting knowledge and practices. Knowledge was greater among physicians who received their medical degree before 1980 (P = .04), accessed e-mail (P< .01), used the Internet to obtain public health information (P < .01), and reported frequently (P= .06). Increased knowledge was not associated with training in reporting (P = .14). Physicians were often unaware of reporting procedures and mechanisms and often did not report because they believed others would report (52%). Laboratory representatives (56%) more often received training on disease reporting than physicians (32%). All laboratories sent some specimens for diagnostic testing at reference laboratories and 35% sent the specimens outside of Georgia. Physicians'characteristics may affect reporting knowledge independent of training on disease reporting, and increased knowledge is associated with increased reporting. Investigation of physician characteristics that contribute to improved reporting, such as an active engagement with public health, could help to guide changes to reporting-related training and technology. Reporting by other health care providers and physicians' perceptions that others will report both indicate that studies of all reporting stakeholders and clear delineation of reporting responsibilities are needed. Extensive specimen referral by laboratories suggests the need for coordination of reporting regulations and responsibilities beyond local boundaries.

We used whole-genome sequencing to determine evolutionary relationships among 20 outbreak-associated clinical isolates of Listeria monocytogenes serotypes 1/2a and 1/2b. Isolates from 6 of 11 outbreaks fell outside the clonal groups or “epidemic clones” that have been previously associated with outbreaks, suggesting that epidemic potential may be widespread in L. monocytogenes and is not limited to the recognized epidemic clones. Pairwise comparisons between epidemiologically related isolates within clonal complexes showed that genome-level variation differed by 2 orders of magnitude between different comparisons, and the distribution of point mutations (core versus accessory genome) also varied. In addition, genetic divergence between one closely related pair of isolates from a single outbreak was driven primarily by changes in phage regions. The evolutionary analysis showed that the changes could be attributed to horizontal gene transfer; members of the diverse bacterial community found in the production facility could have served as the source of novel genetic material at some point in the production chain. The results raise the question of how to best utilize information contained within the accessory genome in outbreak investigations. The full magnitude and complexity of genetic changes revealed by genome sequencing could not be discerned from traditional subtyping methods, and the results demonstrate the challenges of interpreting genetic variation among isolates recovered from a single outbreak. Epidemiological information remains critical for proper interpretation of nucleotide and structural diversity among isolates recovered during outbreaks and will remain so until we understand more about how various population histories influence genetic variation.

Summary Mycobacterium tuberculosis is recognised as the primary cause of human tuberculosis worldwide. However, substantial evidence suggests that the burden of Mycobacterium bovis , the cause of bovine tuberculosis, might be underestimated in human beings as the cause of zoonotic tuberculosis. In 2013, results from a systematic review and meta-analysis of global zoonotic tuberculosis showed that the same challenges and concerns expressed 15 years ago remain valid. These challenges faced by people with zoonotic tuberculosis might not be proportional to the scientific attention and resources allocated in recent years to other diseases. The burden of zoonotic tuberculosis in people needs important reassessment, especially in areas where bovine tuberculosis is endemic and where people live in conditions that favour direct contact with infected animals or animal products. As countries move towards detecting the 3 million tuberculosis cases estimated to be missed annually, and in view of WHO's end TB strategy endorsed by the health authorities of WHO Member States in 2014 to achieve a world free of tuberculosis by 2035, we call on all tuberculosis stakeholders to act to accurately diagnose and treat tuberculosis caused by M bovis in human beings.

SUMMARYListeria monocytogenesis a foodborne pathogen that can cause bacteraemia, meningitis, and complications during pregnancy. In July 2012, molecular subtyping identified indistinguishableL. monocytogenesisolates from six patients and two samples of different cut and repackaged cheeses. A multistate outbreak investigation was initiated. Initial analyses identified an association between eating soft cheese and outbreak-related illness (odds ratio 17·3, 95% confidence interval 2·0–825·7) but no common brand. Cheese inventory data from locations where patients bought cheese and an additional location where repackaged cheese yielded the outbreak strain were compared to identify cheeses for microbiological sampling. Intact packages of imported ricotta salata yielded the outbreak strain. Fourteen jurisdictions reported 22 cases from March–October 2012, including four deaths and a fetal loss. Six patients ultimately reported eating ricotta salata; another reported eating cheese likely cut with equipment also used for contaminated ricotta salata, and nine more reported eating other cheeses that might also have been cross-contaminated. An FDA import alert and US and international recalls followed. Epidemiology-directed microbiological testing of suspect cheeses helped identify the outbreak source. Cross-contamination of cheese highlights the importance of using validated disinfectant protocols and routine cleaning and sanitizing after cutting each block or wheel.

In Georgia, most individuals reported with West Nile virus (WNV) disease have been diagnosed with West Nile neuroinvasive disease (WNND). Relatively few cases of West Nile Fever (WNF) are reported, and the burden of illness due to WNV is likely underestimated. From July through October 2003, WNV serologic testing was performed on enrolled patients>or=18 years of age with fever admitted to a large, urban hospital in Atlanta, Georgia through the emergency department (ED). Patients' history, clinical, and laboratory data were recorded. Residual blood drawn in the ED was tested to determine the presence of WNV IgG and IgM antibodies. Of 254 patients tested for WNV, four (1.6%) patients were positive for WNV IgM and IgG antibodies, and had a clinical illness compatible with WNV. None of the four positive patients were clinically suspected of having WNV infection; discharge diagnoses included pneumonia, migraine, stroke, and gout. These four patients accounted for 80% of all WNV diagnosed in this hospital, 44% of all cases in Fulton County, and 7% of all cases reported in Georgia in 2003. The occurrence of WNV disease may be substantially greater than currently reflected in disease statistics in Georgia and many other states. When indicators of WNV activity are present and patients are likely to have had intensive mosquito exposure, WNV should be considered in the differential diagnosis of seriously ill, febrile patients.

Notifiable disease surveillance systems provide essential data for infectious disease prevention and control programs at the local, state, and national levels. Given that reporting completeness is known to vary considerably, this review identifies methods that can reliably enhance completeness of reporting. These surveillance-related activities include initiating active surveillance when appropriate; implementing automated, electronic laboratory-based reporting; strengthening ties with clinicians and other key partners in notifiable disease reporting; and increasing the use of laboratory diagnostic tests in identifying new cases. Despite ample data in support of these strategies, notifiable disease surveillance continues to receive insufficient attention and resources. Recent attention to public health preparedness provides an opportunity to strengthen notifiable disease surveillance and enhance completeness of reporting.

Objective Emergency department (ED)-based syndromic surveillance systems are being used by public health departments to monitor for outbreaks of infectious diseases, including bioterrorism; however, few systems have been validated. The authors evaluated a "drop-in" syndromic surveillance system by comparing syndrome categorization in the ED with chief complaints and ED discharge diagnoses from medical record review. Methods A surveillance form was completed for each ED visit at 15 participating Arizona hospitals between October 27 and November 18, 2001. Each patient visit was assigned one of ten clinical syndromes or "none." For six of 15 EDs, kappa statistics were used to compare syndrome agreement between surveillance forms and syndrome categorization with chief complaint and ED discharge diagnosis from medical record review. Results Overall, agreement between surveillance forms and ED discharge diagnoses (kappa = 0.55; 95% confidence interval [CI] = 0.52 to 0.59) was significantly higher than between surveillance forms and chief complaints (kappa = 0.48; 95% CI = 0.44 to 0.52). Agreement between chief complaints and ED discharge diagnoses was poor for respiratory tract infection with fever (kappa = 0.33; 95% CI = 0.27 to 0.39). Furthermore, pediatric chief complaints showed lower agreement for respiratory tract infection with fever when compared with adults (kappa = 0.34 [95% CI = 0.20 to 0.47] vs. kappa = 0.44 [95% CI = 0.28 to 0.59], respectively). Conclusions In general, this syndromic surveillance system classified patients into appropriate syndrome categories with fair to good agreement compared with chief complaints and discharge diagnoses. The present findings suggest that use of ED discharge diagnoses, in addition to or instead of chief complaints, may increase surveillance validity for both automated and drop-in syndromic surveillance systems.