The negative impact of lead exposure on young children and those who become pregnant is well documented but is not well known by those at highest risk from this hazard. Scientific evidence suggests that there is no known safe blood lead level (BLL), because even small amounts of lead can be harmful to a child's developing brain (1). In 2012, CDC introduced the population-based blood lead reference value (BLRV) to identify children exposed to more lead than most other children in the United States. The BLRV should be used as a guide to 1) help determine whether medical or environmental follow-up actions should be initiated for an individual child and 2) prioritize communities with the most need for primary prevention of exposure and evaluate the effectiveness of prevention efforts. The BLRV is based on the 97.5th percentile of the blood lead distribution in U.S. children aged 1-5 years from National Health and Nutrition Examination Survey (NHANES) data. NHANES is a complex, multistage survey designed to provide a nationally representative assessment of health and nutritional status of the noninstitutionalized civilian adult and child populations in the United States (2). The initial BLRV of 5 μg/dL, established in 2012, was based on data from the 2007-2008 and 2009-2010 NHANES cycles. Consistent with recommendations from a former advisory committee, this report updates CDC's BLRV in children to 3.5 μg/dL using NHANES data derived from the 2015-2016 and 2017-2018 cycles and provides helpful information to support adoption by state and local health departments, health care providers (HCPs), clinical laboratories, and others and serves as an opportunity to advance health equity and environmental justice related to preventable lead exposure. CDC recommends that public health and clinical professionals focus screening efforts on populations at high risk based on age of housing and sociodemographic risk factors. Public health and clinical professionals should collaborate to develop screening plans responsive to local conditions using local data. In the absence of such plans, universal BLL testing is recommended. In addition, jurisdictions should follow the Centers for Medicare & Medicaid Services requirement that all Medicaid-enrolled children be tested at ages 12 and 24 months or at age 24-72 months if they have not previously been screened (3).

A sensitive, selective, and quantitative method incorporating high-resolution mass spectrometry was developed for the determination of blood urea nitrogen (BUN) in bronchoalveolar lavage fluid. The method requires no sample cleanup or derivatization prior to analysis. High-performance liquid chromatography (HPLC) on a Hypersil Gold PFP column (100 × 3 mm, 3 μm particle size) connected to a C18 guard column was employed for a 10 min chromatographic separation. The detection of urea was achieved using a Thermo Scientific Q-Exactive Plus instrument incorporating selected ion monitoring (SIM) modes for the protonated adduct of urea. The urea analytical measuring range for the method is 0.047-17.134 mg/dL, resulting in a BUN analytical measurement range of 0.022-8.007 mg/dL, which allows for quantitation over 3 orders of magnitude (R(2) = 0.999). In addition, the method is suitable for small sample volumes (15 μL) with a high level of accuracy, precision, and specificity.

Navajo Nation residents are at risk for exposure to uranium and other co-occurring metals found in abandoned mine waste. The Navajo Birth Cohort Study (NBCS) was initiated in 2010 to address community concerns regarding the impact of chronic environmental exposure to metals on pregnancy and birth outcomes. The objectives of this paper were to 1) evaluate maternal urine concentrations of key metals at enrollment and delivery from a pregnancy cohort; and 2) compare the NBCS to the US general population by comparing representative summary statistical values. Pregnant Navajo women (N = 783, age range 14-45 years) were recruited from hospital facilities on the Navajo Nation during prenatal visits and urine samples were collected by trained staff in pre-screened containers. The U.S. Centers for Disease Control and Prevention (CDC), National Center for Environmental Health's (NCEH) Division of Laboratory Sciences (DLS) analyzed urine samples for metals. Creatinine-corrected urine concentrations of cadmium decreased between enrollment (1st or 2nd trimester) and delivery (3rd trimester) while urine uranium concentrations were not observed to change. Median and 95th percentile values of maternal NBCS urine concentrations of uranium, manganese, cadmium, and lead exceeded respective percentiles for National Health and Nutrition Evaluation Survey (NHANES) percentiles for women (ages 14-45 either pregnant or not pregnant.) Median NBCS maternal urine uranium concentrations were 2.67 (enrollment) and 2.8 (delivery) times greater than the NHANES median concentration, indicating that pregnant Navajo women are exposed to metal mixtures and have higher uranium exposure compared to NHANES data for women. This demonstrates support for community concerns about uranium exposure and suggests a need for additional analyses to evaluate the impact of maternal metal mixtures exposure on birth outcomes.

A number of errors with potentially significant consequences may be introduced at various points in the analytical process which result in skewed, erroneous analytical results. Precautionary procedures such as contamination control, following established sample collection protocols, and having a complete understanding of the long-term stability of the elements of interest can minimize or eliminate these errors. Contamination control is critical in quantification of Cr and Co in human whole blood. Cr and Co levels in most biological samples are low, but these elements occur naturally in the environment and are often found in commercial and consumer products, which increases the risk of contamination. In this paper, we demonstrated that lot screening process in which we pre-screen a sub-set of manufactured lots used in collecting, analyzing, and storing blood samples is a critical step in controlling Cr and Co contamination. Stainless steel needles are often utilized in blood collection but are considered a potential source of introducing metal contamination to the patient sample. We conducted two studies to determine if there is a possibility of Cr or Co leaching into the human whole blood from the needles during blood collection. We analyzed blood collected from 100 donors and blood collected in-vitro in the laboratory from designated vessel containing spiked blood with higher levels of Cr and Co. Two blood tubes were consecutively collected through one needle. In both studies, Cr and Co concentration levels in the two consecutively collected tubes were compared. Based on the results from donor and in-vitro blood collection studies, we concluded there was no Cr and Co leaching from the limited sets of stainless steel needles used in these studies. Further, we demonstrated that Cr and Co human whole blood samples are stable for one year stored at temperatures of -70 degrees C, -20 degrees C, and 4 degrees C, and six months at room temperature.

CONTEXT: The Lead and Multielement Proficiency (LAMP) program is an external quality assurance program promoting high-quality blood-lead measurements. OBJECTIVES: To investigate the ability of US laboratories, participating in the Centers for Disease Control and Prevention (CDC) LAMP program to accurately measure blood-lead levels (BLL) 0.70 to 47.5 mug/dL using evaluation criteria of +/-2 mug/dL or 10%, whichever is greater. METHODS: The CDC distributes bovine blood specimens to participating laboratories 4 times per year. We evaluated participant performance over 5 challenges on samples with BLL between 0.70 and 47.5 mug/dL. The CDC sent 15 pooled samples (3 samples shipped in 5 rounds) to US laboratories. The LAMP laboratories used 3 primary technologies to analyze lead in blood: inductively coupled plasma mass spectrometry, graphite furnace atomic absorption spectroscopy, and LeadCare technologies based on anodic stripping voltammetry. Laboratories reported their BLL analytical results to the CDC. The LAMP uses these results to provide performance feedback to the laboratories. SETTING: The CDC sent blood samples to approximately 50 US laboratories for lead analysis. PARTICIPANTS: Of the approximately 200 laboratories enrolled in LAMP, 38 to 46 US laboratories provided data used in this report (January 2017 to March 2018). RESULTS: Laboratory precision ranged from 0.26 mug/dL for inductively coupled plasma mass spectrometry to 1.50 mug/dL for LeadCare instruments. All participating US LAMP laboratories reported accurate BLL for 89% of challenge samples, using the +/-2 mug/dL or 10% evaluation criteria. CONCLUSIONS: Laboratories participating in the CDC's LAMP program can accurately measure blood lead using the current Clinical Laboratory Improvement Amendments of 1988 guidance of +/-4 mug/dL or +/-10%, with a success rate of 96%. However, when we apply limits of +/-2 mug/dL or +/-10%, the success rate drops to 89%. When challenged with samples that have target values between 3 and 5 mug/dL, nearly 100% of reported results fall within +/-4 mug/dL, while 5% of the results fall outside of the acceptability criteria used by the CDC's LAMP program. As public health focuses on lower blood lead levels, laboratories must evaluate their ability to successfully meet these analytical challenges surrounding successfully measuring blood lead. In addition proposed CLIA guidelines (+/-2 mug/dL or 10%) would be achievable performance by a majority of US laboratories participating in the LAMP program.

BACKGROUND: Comprehensive information on the effect of time and temperature storage on the measurement of elements in human, whole blood (WB) by inductively coupled plasma-dynamic reaction cell-mass spectrometry (ICP-DRC-MS) is lacking, particularly for Mn and Se. METHODS: Human WB was spiked at 3 concentration levels, dispensed, and then stored at 5 different temperatures: -70 degrees C, -20 degrees C, 4 degrees C, 23 degrees C, and 37 degrees C. At 3 and 5weeks, and at 2, 4, 6, 8, 10, 12, 36months, samples were analyzed for Pb, Cd, Mn, Se and total Hg, using ICP-DRC-MS. We used a multiple linear regression model including time and temperature as covariates to fit the data with the measurement value as the outcome. We used an equivalence test using ratios to determine if results from the test storage conditions, warmer temperature and longer time, were comparable to the reference storage condition of 3weeks storage time at -70 degrees C. RESULTS: Model estimates for all elements in human WB samples stored in polypropylene cryovials at -70 degrees C were equivalent to estimates from samples stored at 37 degrees C for up to 2months, 23 degrees C up to 10months, and -20 degrees C and 4 degrees C for up to 36months. Model estimates for samples stored for 3weeks at -70 degrees C were equivalent to estimates from samples stored for 2months at -20 degrees C, 4 degrees C, 23 degrees C and 37 degrees C; 10months at -20 degrees C, 4 degrees C, and 23 degrees C; and 36months at -20 degrees C and 4 degrees C. This equivalence was true for all elements and pools except for the low concentration blood pool for Cd. CONCLUSIONS: Storage temperatures of -20 degrees C and 4 degrees C are equivalent to -70 degrees C for stability of Cd, Mn, Pb, Se, and Hg in human whole blood for at least 36months when blood is stored in sealed polypropylene vials. Increasing the sample storage temperature from -70 degrees C to -20 degrees C or 4 degrees C can lead to large energy savings. The best analytical results are obtained when storage time at higher temperature conditions (e.g. 23 degrees C and 37 degrees C) is minimized because recovery of Se and Hg is reduced. Blood samples stored in polypropylene vials also lose volume over time and develop clots at higher temperature conditions (e.g., 23 degrees C and 37 degrees C), making them unacceptable for elemental testing after 10months and 2months, respectively.

In 2012, the Centers for Disease Control and Prevention (CDC) adopted its Advisory Committee on Childhood Lead Poisoning Prevention recommendation to use a population-based reference value to identify children and environments associated with lead hazards. The current reference value of 5 mug/dL is calculated as the 97.5th percentile of the distribution of blood lead levels (BLLs) in children 1 to 5 years old from 2007 to 2010 NHANES data. We calculated and updated selected percentiles, including the 97.5th percentile, by using NHANES 2011 to 2014 blood lead data and examined demographic characteristics of children whose blood lead was ≥90th percentile value. The 97.5th percentile BLL of 3.48 microg/dL highlighted analytical laboratory and clinical interpretation challenges of blood lead measurements ≤5 mug/dL. Review of 5 years of results for target blood lead values <11 microg/dL for US clinical laboratories participating in the CDC's voluntary Lead and Multi-Element Proficiency quality assurance program showed 40% unable to quantify and reported a nondetectable result at a target blood lead value of 1.48 microg/dL, compared with 5.5% at a target BLL of 4.60 microg/dL. We describe actions taken at the CDC's Environmental Health Laboratory in the National Center for Environmental Health, which measures blood lead for NHANES, to improve analytical accuracy and precision and to reduce external lead contamination during blood collection and analysis.

BACKGROUND: To collect information, identify training needs, and assist with influenza capacity building voluntary laboratory capacity assessments were conducted using a standardized tool in CDC cooperative agreement countries. To understand the usefulness of comparing results from repeat assessments and to determine if targeted training supported improvements, this paper details comparison of assessment results of conducting 17 repeat laboratory assessments between 2009 and 2013. METHODS: Laboratory assessments were conducted by SMEs in 17 laboratories (16 countries). We reviewed the quantitative assessment results of the laboratories that conducted both an initial and follow up assessment between 2009 to 2013 using repeated measures of Anova, (Mixed procedure of SAS (9.3)). Additionally, we compared the overall summary scores and the assessor recommendations from the two assessments. RESULTS: We were able to document a statistically significant improvement between the first and second assessments both on an aggregate as well as individual indicator score. Within the international capacity tool three of the eight categories recorded statistically significant improvement (equipment, management, and QA/QC), while the other tool categories (molecular, NIC, specimen, safety and virology) showed improvement in scores although not statistically significant. CONCLUSIONS: We found that using a standardized tool and quantitative framework is useful for documenting capacity and performance improvement in identified areas over time. The use of the tool and standard reports with assessor recommendations assisted laboratories with establishing, maintaining, and improving influenza laboratory practices. On-going assessments and the consistent application of the analytic framework over time will continue to aid in building a measurement knowledge base for laboratory capacity.

The relationship between age, vitamin D status, expression and functionality of the vitamin D receptor (VDR), and key genes in the vitamin D pathway in immune cells is unclear. We enrolled adults 50 to 69 years old (20 subjects) and 70+ (20 subjects) and measured: 1) 25(OH)D levels by liquid chromatography/mass spectrometry; and 2) mRNA expression of VDR, 1alpha-OHase, 1,25D3-MARRS, TREM-1, cathelicidin, RIG-I, and interferon-beta by qRT-PCR. Mean serum 25(OH)D was 30 +/- 4 ng/mL and was not associated with age. Baseline expression of VDR, 1alpha-OHase, 1,25D3-MARRS, TREM-1, and RIG-I also did not differ by age; IFN-beta expression, however, was higher in the 70+ year old group. 25(OH)D3- and 1,25(OH)2D3-induced VDR, TREM-1 and cathelicidin expression were similar between age groups, as was LPS-induced expression of VDR and of 1alpha-OHase. Ligand-induced 1,25D3-MARRS expression was higher in subjects ≥ 70 years. Serum 25(OH)D was inversely associated with LPS-stimulated VDR expression and with baseline or vitamin D-induced TREM-1 expression, adjusting for age, self-rated health, and functional status. In healthy adults ≥ 50 years, the expression and functionality of the VDR, 1alpha-OHase and key vitamin D pathway genes were not consistently associated with age.

BACKGROUND: Influenza-associated illness results in increased morbidity and mortality in the Americas. These effects can be mitigated with an appropriately chosen and timed influenza vaccination campaign. To provide guidance in choosing the most suitable vaccine formulation and timing of administration, it is necessary to understand the timing of influenza seasonal epidemics. OBJECTIVES: Our main objective was to determine if influenza occurs in seasonal patterns in the American tropics, and when these patterns occurred. METHODS: Publicly available, monthly seasonal influenza data from the Pan American Health Organization and WHO, from countries in the American tropics were obtained during 2002-2008 and 2011-2014 (excluding unseasonal pandemic activity during 2009-2010). For each country, we calculated the monthly proportion of samples that tested positive for influenza. We applied the monthly proportion data to a logistic regression model for each country. RESULTS: We analyzed 2002-2008 and 2011-2014 influenza surveillance data from the American tropics and identified 13 (81%) of 16 countries with influenza epidemics that, on average, started during May and lasted 4 months. CONCLUSIONS: The majority of countries in the American tropics have seasonal epidemics that start in May. Officials in these countries should consider the impact of vaccinating persons during April with the Southern Hemisphere formulation.

BACKGROUND: Influenza-associated mortality in subtropical or tropical regions, particularly in developing countries, remains poorly quantified and often underestimated. We analyzed data in Thailand, a middle-income tropical country with good vital statistics and influenza surveillance data. METHODS: We obtained weekly mortality data for all-cause and three underlying causes of death (circulatory and respiratory diseases, and pneumonia and influenza), and weekly influenza virus data, from 2006 to 2011. A negative binomial regression model was used to estimate deaths attributable to influenza in two age groups (<65 and ≥65 years) by incorporating influenza viral data as covariates in the model. RESULTS: From 2006 to 2011, the average annual influenza-associated mortality per 100 000 persons was 4·0 (95% CI: -18 to 26). Eighty-three percent of influenza-associated deaths occurred among persons aged > 65 years. The average annual rate of influenza-associated deaths was 0·7 (95% CI: -8·2 to 10) per 100 000 population for person aged <65 years and 42 (95% CI: -137 to 216) for person aged ≥ 65 years. DISCUSSION: In Thailand, estimated excess mortality associated with influenza was considerable even during non-pandemic years. These data provide support for Thailand's seasonal influenza vaccination campaign. Continued monitoring of mortality data is important to assess impact.

BACKGROUND: Influenza disease is a vaccine-preventable cause of morbidity and mortality. The Pan American Health Organization (PAHO) region has invested in influenza vaccines, but few estimates of influenza burden exist to justify these investments. We estimated influenza-associated deaths for 35 PAHO countries during 2002-2008. METHODS: Annually, PAHO countries report registered deaths. We used respiratory and circulatory (R&C) codes from seven countries with distinct influenza seasonality and high-quality mortality data to estimate influenza-associated mortality rates by age group (0-64, 65-74, and ≥75 years) with a Serfling regression model or a negative binomial model. We calculated the percent of all R&C deaths attributable to influenza by age group in these countries (etiologic fraction) and applied it to the age-specific mortality in 13 countries with good mortality data but poorly defined seasonality. Lastly, we grouped the remaining 15 countries into WHO mortality strata and applied the age and mortality stratum-specific rate of influenza mortality calculated from the 20 countries. We summed each country's estimate to arrive at an average total annual number and rate of influenza deaths in the Americas. RESULTS: For the 35 PAHO countries, we estimated an annual mean influenza-associated mortality rate of 2.1/100 000 among <65-year olds, 31.9/100 000 among those 65-74 years, and 161.8/100 000 among those ≥75 years. We estimated that annually between 40 880 and 160 270 persons (mean, 85 100) die of influenza illness in the PAHO region. CONCLUSION: Influenza remains an important cause of mortality in the Americas.

Infectious diseases in poultry can spread quickly and lead to huge economic losses. In the past decade, on multiple continents, the accelerated spread of highly pathogenic avian Influenza A (H5N1) virus, often through informal trade networks, has led to the death and culling of hundreds of millions of poultry. Endemic poultry diseases like Newcastle disease and fowl typhoid can also be devastating in many parts of the world. Understanding trade networks in unregulated systems can inform policy decisions concerning disease prevention and containment. From June to December 2008 we conducted a cross-sectional survey of backyard farmers, market traders, and middlemen in 5/8 provinces in Kenya. We administered a standardized questionnaire to each type of actor using convenience, random, snowball, and systematic sampling. Questionnaires addressed frequency, volume, and geography of trade, as well as biosecurity practices. We created a network diagram identifying the most important locations for trade. Of 380 respondents, 51% were backyard farmers, 24% were middlemen and 25% were market traders. Half (50%) of backyard farmers said they raised poultry both for household consumption and for sale. Compared to market traders, middlemen bought their poultry from a greater number of villages (median 4.2 villages for middlemen vs. 1.9 for market traders). Traders were most likely to purchase poultry from backyard farmers. Of the backyard farmers who sold poultry, 51% [CI 40-63] reported selling poultry to market traders, and 54% [CI 44-63] sold to middlemen. Middlemen moved the largest volume of poultry on a weekly basis (median purchases: 187 birds/week [IQR 206]; median sales: 188 birds/week [IQR 412.5]). The highest numbers of birds were traded in Nairobi - Kenya's capital city. Nairobi was the most prominent trading node in the network (61 degrees of centrality). Many smaller sub-networks existed as a result of clustered local trade. Market traders were also integral to the network. The informal poultry trade in Kenya is dependent on the sale of backyard poultry to middlemen and market traders. These two actors play a critical role in poultry movement in Kenya; during any type of disease outbreak middlemen should be targeted for control- and containment-related interventions.

BACKGROUND: Little is known about factors associated with maintenance of hemagglutinin inhibition (HAI) antibodies after influenza vaccination in older adults. METHODS: Adults ≥50 years of age were vaccinated prior to the 2009-10 influenza season. Serum was drawn pre-vaccination (S1), 21-28 days post-vaccination (S2), and after the influenza season (S3) for HAI assays. Seroconversion was defined as ≥ 4-fold increase S1 to S2 (or if S1 < 10, by an S2 ≥ 40) and seroprotection was defined as S2 ≥ 40. Maintenance of antibody response was measured in participants with an S2 ≥ 40, and defined as an S3 ≥ 40. RESULTS: We enrolled 510 participants during Fall 2009 at Vanderbilt University Medical Center and Marshfield Clinic Research Foundation. Participants' mean age was 64 years with 62% female and 96% white. Seroconversion and seroprotection rates were lowest for influenza A H1N1 (12% and 26%, respectively), highest for influenza A H3N2 (45% and 82%), and intermediate for influenza B (28% and 72%). Of the participants with an S2 ≥ 40, 36% (46/126), 71% (289/407), and 74% (263/354) maintained an S3 ≥ 40 for H1N1, H3N2, and B influenza vaccine strains, respectively. S1 HAI titer was strongly associated with both post-vaccination seroprotection and maintaining seroprotection at S3 for all three influenza antigens. Age, sex, body mass index, self-reported stress, and vaccination site were not consistently associated with vaccine response or maintenance of response. CONCLUSIONS: Pre-vaccination antibody titer was the only study variable consistently and positively associated with both serologic response to vaccination and maintenance of response. Antibody responses were lowest for the H1N1 vaccine strain. CLINICALTRIALS: gov Identifier: NCT02401893.

BACKGROUND: Excess mortality due to seasonal influenza is substantial, yet quantitative estimates of the benefit of annual vaccination programs on influenza-associated mortality are lacking. METHODS: We estimated the numbers of deaths averted by vaccination in four age groups (0.5 to 4, 5 to 19, 20 to 64 and ≥65 yrs.) for the nine influenza seasons from 2005/6 through 2013/14. These estimates were obtained using a Monte Carlo approach applied to weekly U.S. age group-specific estimates of influenza-associated excess mortality, monthly vaccination coverage estimates and summary seasonal influenza vaccine effectiveness estimates to obtain estimates of the number of deaths averted by vaccination. The estimates are conservative as they do not include indirect vaccination effects. RESULTS: From August, 2005 through June, 2014, we estimated that 40,127 (95% confidence interval [CI] 25,694 to 59,210) deaths were averted by influenza vaccination. We found that of all studied seasons the most deaths were averted by influenza vaccination during the 2012/13 season (9398; 95% CI 2,386 to 19,897) and the fewest during the 2009/10 pandemic (222; 95% CI 79 to 347). Of all influenza-associated deaths averted, 88.9% (95% CI 83 to 92.5%) were in people ≥65 yrs. old. CONCLUSIONS: The estimated number of deaths averted by the US annual influenza vaccination program is considerable, especially among elderly adults and even when vaccine effectiveness is modest, such as in the 2012/13 season. As indirect effects ("herd immunity") of vaccination are ignored, these estimates represent lower bound estimates and are thus conservative given valid excess mortality estimates.

OBJECTIVE: Influenza is the most common vaccine-preventable disease in the United States; however, little is known about the burden of critical illness due to influenza virus infection. Our primary objective was to estimate the proportion of all critical illness hospitalizations that are attributable to seasonal influenza. DESIGN: Retrospective cohort study. SETTING: Arizona, California, and Washington from January 2003 to March 2009. PATIENTS: All adults hospitalized with critical illness, defined by International Classification of Diseases, 9th Edition, Clinical Modification diagnosis and procedure codes for acute respiratory failure, severe sepsis, or in-hospital death. MEASUREMENTS AND MAIN RESULTS: We combined the complete hospitalization discharge databases for three U.S. states, regional influenza virus surveillance, and state census data. Using negative binomial regression models, we estimated the incidence rates of adult influenza-associated critical illness hospitalizations and compared them with all-cause event rates. We also compared modeled outcomes to International Classification of Diseases, 9th Edition, Clinical Modification-coded influenza hospitalizations to assess potential underrecognition of severe influenza disease. During the study period, we estimated that 26,760 influenza-associated critical illness hospitalizations (95% CI, 14,541, 47,464) occurred. The population-based incidence estimate for influenza-associated critical illness was 12.0 per 100,000 person-years (95% CI, 6.6, 21.6) or 1.3% of all critical illness hospitalizations (95% CI, 0.7%, 2.3%). During the influenza season, 3.4% of all critical illness hospitalizations (95% CI, 1.9%, 5.8%) were attributable to influenza. There were only 2,612 critical illness hospitalizations with International Classification of Diseases, 9th Edition, Clinical Modification-coded influenza diagnoses, suggesting influenza is either undiagnosed or undercoded in a substantial proportion of critical illness. CONCLUSIONS: Extrapolating our data to the 2010 U.S. population, we estimate that about 28,000 adults are hospitalized for influenza-associated critical illness annually. Influenza in many of these critically ill patients may be undiagnosed. Critical care physicians should have a high index of suspicion for influenza in the ICU, particularly when influenza is known to be circulating in their communities.

BACKGROUND: Young children are at increased risk of severe outcomes from influenza illness, including hospitalization. We conducted a case-control study to identify risk factors for influenza-associated hospitalizations among children in U.S. Emerging Infections Program sites. METHODS: Cases were children 6-59 months of age hospitalized for laboratory-confirmed influenza infections during 2005-08. Age- and zip-code-matched controls were enrolled. Data on child, caregiver, and household characteristics were collected from parents and medical records. Conditional logistic regression was used to identify independent risk factors for hospitalization. RESULTS: We enrolled 290 (64%) of 454 eligible cases and 1,089 (49%) of 2,204 eligible controls. Risk for influenza hospitalization increased with maternal age <26 years (odds ratio [OR] 1.8, 95% confidence interval [CI] 1.1-2.9); household income below the poverty threshold (OR 2.2, CI 1.4-3.6); smoking by >50% of household members (OR 2.9, CI 1.4-6.6); lack of household influenza vaccination (OR 1.8, CI 1.2-2.5); and presence of chronic illnesses, including hematologic/oncologic (OR 11.8, CI 4.5-31.0), pulmonary (OR 2.9, CI 1.9-4.4), and neurologic (OR 3.8, CI 1.6-9.2) conditions. Full influenza immunization decreased the risk among children aged 6-23 months (OR 0.5, CI 0.3-0.9) but not among those 24-59 months of age (OR 1.5, CI 0.8-3.0; p-value for difference = 0.01). CONCLUSIONS: Chronic illnesses, young maternal age, poverty, household smoking, and lack of household influenza vaccination increased the risk of influenza hospitalization. These characteristics may help providers to identify young children who are at greatest risk for severe outcomes from influenza illness.

BACKGROUND: Each year, the US Influenza Vaccine Effectiveness Network examines the effectiveness of influenza vaccines in preventing medically attended acute respiratory illnesses caused by influenza. METHODS: Patients with acute respiratory illnesses of ≤7 days' duration were enrolled at ambulatory care facilities in 5 communities. Specimens were collected and tested for influenza by real-time reverse-transcriptase polymerase chain reaction. Receipt of influenza vaccine was defined based on documented evidence of vaccination in medical records or immunization registries. Vaccine effectiveness was estimated in adjusted logistic regression models by comparing the vaccination coverage in those who tested positive for influenza with those who tested negative. RESULTS: The 2011-2012 season was mild and peaked late, with circulation of both type A viruses and both lineages of type B. Overall adjusted vaccine effectiveness was 47% (95% confidence interval [CI], 36-56) in preventing medically attended influenza; vaccine effectiveness was 65% (95% CI, 44-79) against type A (H1N1) pdm09 but only 39% (95% CI, 23-52) against type A (H3N2). Estimates of vaccine effectiveness against both type B lineages were similar (overall, 58%; 95% CI, 35-73). An apparent negative effect of prior year vaccination on current year effectiveness estimates was noted, particularly for A (H3N2) outcomes. CONCLUSIONS: Vaccine effectiveness in the 2011-2012 season was modest overall, with lower effectiveness against the predominant A (H3N2) virus. This may be related to antigenic drift, but past history of vaccination might also play a role.

BACKGROUND: Limited data are available from Central and Eastern Europe on risk factors for severe complications of influenza. Such data are essential to prioritize prevention and treatment resources and to adapt influenza vaccination recommendations. OBJECTIVES: To use sentinel surveillance data to identify risk factors for fatal outcomes among hospitalized patients with severe acute respiratory infections (SARI) and among hospitalized patients with laboratory-confirmed influenza. METHODS: Retrospective analysis of case-based surveillance data collected from sentinel hospitals in Romania during the 2009/2010 and 2010/2011 winter influenza seasons was performed to evaluate risk factors for fatal outcomes using multivariate logistic regression. RESULTS: During 2009/2010 and 2010/2011, sentinel hospitals reported 661 SARI patients of which 230 (35%) tested positive for influenza. In the multivariate analyses, infection with influenza A(H1N1)pdm09 was the strongest risk factor for death among hospitalized SARI patients (OR: 6.6; 95% CI: 3.3-13.1). Among patients positive for influenza A(H1N1)pdm09 virus infection (n = 148), being pregnant (OR: 7.1; 95% CI: 1.6-31.2), clinically obese (OR: 2.9;95% CI: 1.6-31.2), and having an immunocompromising condition (OR: 3.7;95% CI: 1.1-13.4) were significantly associated with fatal outcomes. CONCLUSION: These findings are consistent with several other investigations of risk factors associated with influenza A(H1N1)pdm09 virus infections. They also support the more recent 2012 recommendations by the WHO Strategic Advisory Group of Experts on Immunization (SAGE) that pregnant women are an important risk group for influenza vaccination. Ongoing sentinel surveillance can be useful tool to monitor risk factors for complications of influenza virus infections during each influenza season, and pandemics as well.

BACKGROUND: Re-emergence in 2003 of human cases of avian H5N1 and the resultant spread of the disease highlighted the need to improve the capacity of countries to detect and contain novel viruses. To assess development in this capacity, the Centers for Disease Control and Prevention (CDC) produced a tool for assessing a country's capability in 12 critical areas related to pandemic preparedness, including monitoring and identifying novel influenza viruses. OBJECTIVES: Capabilities the CDC tool assesses range from how well a country has planned and is prepared for an outbreak to how prepared a country is to respond when a pandemic occurs. Included in this assessment tool are questions to determine whether a country has a detailed preparedness plan and the laboratory capacity to identify various strains of influenza quickly and accurately. METHODS: The tool was used first in 2008 when 40 countries in collaboration with CDC calculated baseline scores and used a second time in 2010 by 36 of the original 40 countries to determine whether they had improved their preparedness. Using basic mathematical comparison and statistical analyses, we compared data at the aggregate capability level as well as at the indicator and country levels. Additionally, we examined the comments of respondents to the assessment questionnaire for reasons (positive and negative) that would explain changes in scores from 2008 to 2010. RESULTS: Analysis of results of two assessments in 36 countries shows statistically significant improvement in all 12 capabilities on an aggregate level and 47 of 50 indicators.

During 2009-2010, we examined 217 patients hospitalized with laboratory-confirmed pandemic influenza in 9 Influenza Hospitalization Surveillance Network sites and 413 age- and community-matched controls and found that a single dose of monovalent nonadjuvanted influenza A(H1N1)pdm09 vaccine was 50% (95% confidence interval, 13%-71%) effective in preventing hospitalization associated with A(H1N1)pdm09 virus infection.

In order to estimate influenza-associated excess mortality in southern Brazil, we applied Serfling regression models to monthly mortality data from 1980 to 2008 for pneumonia/influenza- and respiratory/circulatory-coded deaths for all ages and for those aged >=60 years. According to viral data, 735% of influenza viruses were detected between April and August in southern Brazil. There was no clear influenza season for northern Brazil. In southern Brazil, influenza-associated excess mortality was 14/100 000 for all ages and 92/100 000 person-years for persons aged >=60 years using underlying pneumonia/influenza-coded deaths and 100/100 000 for all ages and 866/100 000 person-years for persons aged >=60 years using underlying respiratory/circulatory-coded deaths. Influenza-associated excess mortality rates for southern Brazil are similar to those published for other countries. Our data support the need for continued influenza surveillance to guide vaccination campaigns to age groups most affected by this virus in Brazil. Cambridge University Press 2012.

OBJECTIVE: To determine trends in mortality from respiratory disease in several areas of Latin America between 1998 and 2009. METHODS: The numbers of deaths attributed to respiratory disease between 1998 and 2009 were extracted from mortality data from Argentina, southern Brazil, Chile, Costa Rica, Ecuador, Mexico and Paraguay. Robust linear models were then fitted to the rates of mortality from respiratory disease recorded between 2003 and 2009. FINDINGS: Between 1998 and 2008, rates of mortality from respiratory disease gradually decreased in all age groups in most of the study areas. Among children younger than 5 years, for example, the annual rates of such mortality - across all seven study areas - fell from 56.9 deaths per 100 000 in 1998 to 26.6 deaths per 100 000 in 2008. Over this period, rates of mortality from respiratory disease were generally highest among adults older than 65 years and lowest among individuals aged 5 to 49 years. In 2009, mortality from respiratory disease was either similar to that recorded in 2008 or showed an increase - significant increases were seen among children younger than 5 years in Paraguay, among those aged 5 to 49 years in southern Brazil, Mexico and Paraguay and among adults aged 50 to 64 years in Mexico and Paraguay. CONCLUSION: In much of Latin America, mortality from respiratory disease gradually fell between 1998 and 2008. However, this downward trend came to a halt in 2009, probably as a result of the (H1N1) 2009 pandemic.

BACKGROUND: Influenza A (H1N1)pdm09 (2009 H1N1) re-circulated as the predominant virus from January through February 2011 in China. National surveillance of 2009 H1N1 as a notifiable disease was maintained to monitor potential changes in disease severity from the previous season. METHODOLOGY/PRINCIPAL FINDINGS: To describe the characteristics of hospitalized cases with 2009 H1N1 infection and analyze risk factors for severe illness during the 2010-2011 winter season in China, we obtained surveillance data from hospitalized cases with 2009 H1N1 infection from November 2010 through May 2011, and reviewed medical records from 701 hospitalized cases. Age-standardized risk ratios were used to compare the age distribution of patients that were hospitalized and died due to 2009 H1N1 between the 2010-2011 winter season to those during the 2009-2010 pandemic period. During the 2010-2011 winter season, children less than 5 years of age had the highest relative risk of hospitalization and death, followed by adults aged 65 years or older. Additionally, the relative risk of hospitalized cases aged 5-14 and 15-24 years was lower compared to children less than 5 years of age. During the winter season of 2010-2011, the proportions of adults aged 25 years or older for hospitalization and death were significantly higher than those during the 2009-2010 pandemic period. Being male, having a chronic medical condition, delayed hospital admission (≥3 days from onset) or delayed initiation of antiviral treatment (≥5 days from onset) were associated with severe illness among non-pregnant patients ≥2 years of age. CONCLUSIONS/SIGNIFICANCE: We observed a change in high risk groups for hospitalization for 2009 H1N1 during the winter months immediately following the pandemic period compared to the high risk groups identified during the pandemic period. Our nationally notifiable disease surveillance system enabled us to understand the evolving epidemiology of 2009 H1N1 infection after the pandemic period.

BACKGROUND: We estimated rates of influenza-associated deaths and hospitalizations in Argentina, a country that recommends annual influenza vaccination for persons at high risk of complications from influenza illness. METHODS: We identified hospitalized persons and deaths in persons diagnosed with pneumonia and influenza (P&I, ICD-10 codes J10-J18) and respiratory and circulatory illness (R&C, codes I00-I99 and J00-J99). We defined the influenza season as the months when the proportion of samples that tested positive for influenza exceeded the annual median. We used hospitalizations and deaths during the influenza off-season to estimate, using linear regression, the number of excess deaths that occurred during the influenza season. To explore whether excess mortality varied by sex and whether people were age <65 or ≥65 years, we used Poisson regression of the influenza-associated rates. RESULTS: During 2002-2009, 2411 P&I and 8527 R&C mean excess deaths occurred annually from May to October. If all of these excess deaths were associated with influenza, the influenza-associated mortality rate was 6/100 000 person-years (95% CI 4-8/100,000 person-years for P&I and 21/100,000 person-years (95% CI 12-31/100,000 person-years) for R&C. During 2005-2008, we identified an average of 7868 P&I excess hospitalizations and 22,994 R&C hospitalizations per year, resulting in an influenza-associated hospitalization rate of 2/10,000 person-years (95% CI 1-3/10,000 person-years) for P&I and 6/10,000 person-years (95% CI 3-8/10 000 person-years) for R&C. CONCLUSION: Our findings suggest that annual rates of influenza-associated hospitalizations and death in Argentina were substantial and similar to neighboring Brazil.

BACKGROUND: Influenza vaccines may be reformulated annually because of antigenic drift in influenza viruses. However, the relationship between antigenic characteristics of circulating viruses and vaccine effectiveness (VE) is not well understood. We conducted an assessment of the effectiveness of US influenza vaccines during the 2010-2011 season. METHODS: We performed a case-control study comparing vaccination histories between subjects with acute respiratory illness with positive real-time reverse transcription polymerase chain reaction for influenza and influenza test-negative controls. Subjects with acute respiratory illness of ≤7 days duration were enrolled in hospitals, emergency departments, or outpatient clinics in communities in 4 states. History of immunization with the 2010-2011 vaccine was ascertained from vaccine registries or medical records. Vaccine effectiveness was estimated in logistic regression models adjusted for study community, age, race, insurance status, enrollment site, and presence of a high-risk medical condition. RESULTS: A total of 1040 influenza-positive cases and 3717 influenza-negative controls were included from the influenza season, including 373 cases of influenza A(H1N1), 334 cases of influenza A(H3N2), and 333 cases of influenza B. Overall adjusted VE was 60% (95% confidence interval [CI], 53%-66%). Age-specific VE estimates ranged from 69% (95% CI, 56%-77%) in children aged 6 months-8 years to 38% (95% CI, -16% to 67%) in adults aged ≥65 years. CONCLUSIONS: The US 2010-2011 influenza vaccines were moderately effective in preventing medically attended influenza during a season when all 3 vaccine strains were antigenically similar to circulating viruses. Continued monitoring of influenza vaccines in all age groups is important, particularly as new vaccines are introduced.

BACKGROUND: Although, influenza is a vaccine-preventable disease which annually causes substantial disease burden, data on virus activity in tropical countries are limited. We analyzed publicly available influenza data to better understand the global circulation of influenza viruses. METHOD: We reviewed open-source laboratory-confirmed influenza surveillance data. For each country we abstracted data on the percent of samples testing positive for influenza each epidemiologic week from the annual number of samples testing positive for influenza. The start of influenza season was defined as the first week when the proportion of samples that tested positive remained above the annual mean. We assessed the relationship between percent of samples testing positive and average monthly temperature using regression models. FINDINGS: We identified data on laboratory-confirmed influenza virus infection from 85 countries. More than one influenza epidemic period per year was more common in tropical countries (41%) than temperate countries (15%). Year-round activity (i.e., influenza virus identified each week having ≥10 specimens submitted) occurred in 3 (7%) of 43 temperate, one (17%) of six subtropical, and 11 (37%) of 30 tropical countries with available data (p=0.006). Percent positivity was associated with low temperature (p=0.001). INTERPRETATION: Annual influenza epidemics occur in consistent temporal patterns depending upon climate.

BACKGROUND: 18,500 laboratory-confirmed deaths caused by the 2009 pandemic influenza A H1N1 were reported worldwide for the period April, 2009, to August, 2010. This number is likely to be only a fraction of the true number of the deaths associated with 2009 pandemic influenza A H1N1. We aimed to estimate the global number of deaths during the first 12 months of virus circulation in each country. METHODS: We calculated crude respiratory mortality rates associated with the 2009 pandemic influenza A H1N1 strain by age (0-17 years, 18-64 years, and >64 years) using the cumulative (12 months) virus-associated symptomatic attack rates from 12 countries and symptomatic case fatality ratios (sCFR) from five high-income countries. To adjust crude mortality rates for differences between countries in risk of death from influenza, we developed a respiratory mortality multiplier equal to the ratio of the median lower respiratory tract infection mortality rate in each WHO region mortality stratum to the median in countries with very low mortality. We calculated cardiovascular disease mortality rates associated with 2009 pandemic influenza A H1N1 infection with the ratio of excess deaths from cardiovascular and respiratory diseases during the pandemic in five countries and multiplied these values by the crude respiratory disease mortality rate associated with the virus. Respiratory and cardiovascular mortality rates associated with 2009 pandemic influenza A H1N1 were multiplied by age to calculate the number of associated deaths. FINDINGS: We estimate that globally there were 201 200 respiratory deaths (range 105,700-395,600) with an additional 83,300 cardiovascular deaths (46,000-179,900) associated with 2009 pandemic influenza A H1N1. 80% of the respiratory and cardiovascular deaths were in people younger than 65 years and 59% occurred in southeast Asia and Africa. INTERPRETATION: Our estimate of respiratory and cardiovascular mortality associated with the 2009 pandemic influenza A H1N1 was 15 times higher than reported laboratory-confirmed deaths. Although no estimates of sCFRs were available from Africa and southeast Asia, a disproportionate number of estimated pandemic deaths might have occurred in these regions. Therefore, efforts to prevent influenza need to effectively target these regions in future pandemics. FUNDING: None.

BACKGROUND: Age-specific comparisons of influenza and respiratory syncytial virus (RSV) hospitalization rates can inform prevention efforts, including vaccine development plans. Previous US studies have not estimated jointly the burden of these viruses using similar data sources and over many seasons. METHODS: We estimated influenza and RSV hospitalizations in 5 age categories (<1, 1-4, 5-49, 50-64, and ≥65 years) with data for 13 states from 1993-1994 through 2007-2008. For each state and age group, we estimated the contribution of influenza and RSV to hospitalizations for respiratory and circulatory disease by using negative binomial regression models that incorporated weekly influenza and RSV surveillance data as covariates. RESULTS: Mean rates of influenza and RSV hospitalizations were 63.5 (95% confidence interval [CI], 37.5-237) and 55.3 (95% CI, 44.4-107) per 100,000 person-years, respectively. The highest hospitalization rates for influenza were among persons aged ≥65 years (309/100000; 95% CI, 186-1100) and those aged <1 year (151/100,000; 95% CI, 151-660). For RSV, children aged <1 year had the highest hospitalization rate (2350/100,000; 95% CI, 2220-2520) followed by those aged 1-4 years (178/100,000; 95% CI, 155-230). Age-standardized annual rates per 100,000 person-years varied substantially for influenza (33-100) but less for RSV (42-77). CONCLUSIONS: Overall US hospitalization rates for influenza and RSV are similar; however, their age-specific burdens differ dramatically. Our estimates are consistent with those from previous studies focusing either on influenza or RSV. Our approach provides robust national comparisons of hospitalizations associated with these 2 viral respiratory pathogens by age group and over time.

Most estimates of US deaths associated with influenza circulation have been similar despite the use of different approaches. However, a recently published estimate suggested that previous estimates substantially overestimated deaths associated with influenza, and concluded that substantial numbers of deaths during a future pandemic could be prevented because of improvements in medical care. We reviewed the data sources and methods used to estimate influenza-associated deaths. We suggest that discrepancies between the recent estimate and previous estimates of the number of influenza-associated deaths are attributable primarily to the use of different outcomes and methods. We also believe that secondary bacterial infections will likely result in substantial morbidity and mortality during a future influenza pandemic, despite medical progress.