New Mexico Emerging Infections Program

New York City, United States

New Mexico Emerging Infections Program

New York City, United States
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Haley C.C.,Workforce and Career Development | Haley C.C.,Oregon Public Health Division | Ong K.L.,Centers for Disease Control and Prevention | Ong K.L.,U.S. Department of Agriculture | And 12 more authors.
Foodborne Pathogens and Disease | Year: 2010

Background: An estimated 450,000 cases of shigellosis occur annually in the United States. Outbreaks have been associated with food, water, child daycare centers, and men who have sex with men. However, for sporadic infections, which account for the majority of cases, risk exposures are poorly characterized. Methods: Foodborne Diseases Active Surveillance Network (FoodNet) conducts active, laboratory-based shigellosis surveillance in 10 US sites. We interviewed cases with illness onset during 2005 about exposures during the week before symptom onset using a standardized questionnaire. The proportion of patients who denied nonfood risks was used to estimate the burden attributable to foodborne transmission. Results: Overall, 1494 cases were identified. The approximate incidence was 3.9/100,000, with the highest rates among children aged 1-4 years (16.4) and Hispanics (8.4). Of the 929 cases interviewed, 223 (24%) reported international travel in the week before symptom onset. Of the 626 nontraveling cases with complete risk factor information, 298 (48%) reported exposure to daycare or a household member with diarrhea; 99 (16%) reported drinking untreated water or recreational exposure to water; and 16 (3%) reported sexual contact with a person with diarrhea. Two hundred and fifty-nine (41%) denied all nonfood exposures examined. Conclusions: Sporadic shigellosis is most common among young children and Hispanics. Common exposures include international travel and contact with ill persons or daycare. However, more than one-third of US shigellosis cases annually might be due to food consumed in the United States. © 2010, Mary Ann Liebert, Inc.


Dao C.N.,Centers for Disease Control and Prevention | Kamimoto L.,Centers for Disease Control and Prevention | Nowell M.,Centers for Disease Control and Prevention | Reingold A.,California Emerging Infections Program | And 11 more authors.
Journal of Infectious Diseases | Year: 2010

Background: Rates of influenza-associated hospitalizations in the United States have been estimated using modeling techniques with data from pneumonia and influenza hospitalization discharge diagnoses, but they have not been directly estimated from laboratory-positive cases. Methods: We calculated overall, age-specific, and site-specific rates of laboratory-positive, influenza-associated hospitalization among adults and compared demographic and clinical characteristics and outcomes of hospitalized cases by season with use of data collected by the Emerging Infections Program Network during the 2005-2006 through 2007-2008 influenza seasons. Results: Overall rates of adult influenza-associated hospitalization per 100,000 persons were 9.9 during the 2005-2006 season, 4.8 during the 2006-2007 season, and 18.7 during the 2007-2008 season. Rates of hospitalization varied by Emerging Infections Program site and increased with increasing age. Higher overall and age-specific rates of hospitalization were observed during influenza A (H3) predominant seasons and during periods of increased circulation of influenza B. More than 80% of hospitalized persons each season had≥1 underlying medical condition, including chronic cardiovascular and metabolic diseases. Conclusions: Rates varied by season, age, geographic location, and type/subtype of circulating influenza viruses. Influenza-associated hospitalization surveillance is essential for assessing the relative severity of influenza seasons over time and the burden of influenza-associated complications. © 2010 by the Infectious Diseases Society of America. All rights reserved.


Gould L.H.,Centers for Disease Control and Prevention | Mody R.K.,Centers for Disease Control and Prevention | Ong K.L.,Centers for Disease Control and Prevention | Clogher P.,Connecticut Emerging Infections Program | And 8 more authors.
Foodborne Pathogens and Disease | Year: 2013

Background: Shiga toxin-producing Escherichia coli (STEC) are an important cause of diarrhea and the major cause of postdiarrheal hemolytic uremic syndrome. Non-O157 STEC infections are being recognized with greater frequency because of changing laboratory practices. Methods: Foodborne Diseases Active Surveillance Network (FoodNet) site staff conducted active, population-based surveillance for laboratory-confirmed STEC infections. We assessed frequency and incidence of STEC infections by serogroup and examined and compared demographic factors, clinical characteristics, and frequency of international travel among patients. Results: During 2000-2010, FoodNet sites reported 2006 cases of non-O157 STEC infection and 5688 cases of O157 STEC infections. The number of reported non-O157 STEC infections increased from an incidence of 0.12 per 100,000 population in 2000 to 0.95 per 100,000 in 2010; while the rate of O157 STEC infections decreased from 2.17 to 0.95 per 100,000. Among non-O157 STEC, six serogroups were most commonly reported: O26 (26%), O103 (22%), O111 (19%), O121 (6%), O45 (5%), and O145 (4%). Non-O157 STEC infections were more common among Hispanics, and infections were less severe than those caused by O157 STEC, but this varied by serogroup. Fewer non-O157 STEC infections were associated with outbreaks (7% versus 20% for O157), while more were associated with international travel (14% versus 3% for O157). Conclusions: Improved understanding of the epidemiologic features of non-O157 STEC infections can inform food safety and other prevention efforts. To detect both O157 and non-O157 STEC infections, clinical laboratories should routinely and simultaneously test all stool specimens submitted for diagnosis of acute community-acquired diarrhea for O157 STEC and for Shiga toxin and ensure that isolates are sent to a public health laboratory for serotyping and subtyping. © Mary Ann Liebert, Inc.


Thompson N.D.,Centers for Disease Control and Prevention | LaPlace L.,Centers for Disease Control and Prevention | Epstein L.,Centers for Disease Control and Prevention | Thompson D.,New Mexico Emerging Infections Program | And 4 more authors.
Journal of the American Medical Directors Association | Year: 2016

Objectives: To describe the prevalence and epidemiology of antimicrobial use (AU) in nursing home residents. Design: One-day point prevalence survey. Setting and participants: Nine nursing homes in four states; 1,272 eligible residents. Measurement: Frequency of antimicrobials prescribed, drug name, start date, duration, route, rationale, and treatment site. AU prevalence per 100 residents overall and by resident characteristic. Results: AU prevalence was 11.1% (95% confidence interval, 9.4%-12.9%) and varied by resident characteristics. Most (32%) antimicrobials were given for urinary tract infection. For 38% of AU, key prescribing information was not documented. Conclusion: Opportunities to improve AU documentation and prescribing exist in nursing homes. © 2016.


Reed C.,Centers for Disease Control and Prevention | Chaves S.S.,Centers for Disease Control and Prevention | Kirley P.D.,California Emerging Infections Program | Emerson R.,California Emerging Infections Program | And 9 more authors.
PLoS ONE | Year: 2015

Annual estimates of the influenza disease burden provide information to evaluate programs and allocate resources. We used a multiplier method with routine population-based surveillance data on influenza hospitalization in the United States to correct for under-reporting and estimate the burden of influenza for seasons after the 2009 pandemic. Five sites of the Influenza Hospitalization Surveillance Network (FluSurv-NET) collected data on the frequency and sensitivity of influenza testing during two seasons to estimate under-detection. Population-based rates of influenza-associated hospitalization and Intensive Care Unit admission from 2010-2013 were extrapolated to the U.S. population from FluSurv-NET and corrected for under-detection. Influenza deaths were calculated using a ratio of deaths to hospitalizations. We estimated that influenza-related hospitalizations were under-detected during 2010-11 by a factor of 2.1 (95%CI 1.7-2.9) for age < 18 years, 3.1 (2.4-4.5) for ages 18-64 years, and 5.2 (95%CI 3.8-8.3) for age 65+. Results were similar in 2011-12. Extrapolated estimates for 3 seasons from 2010-2013 included: 114,192-624,435 hospitalizations, 18,491-95,390 ICU admissions, and 4,915-27,174 deaths per year; 54-70% of hospitalizations and 71-85% of deaths occurred among adults aged 65+. Influenza causes a substantial disease burden in the U.S. that varies by age and season. Periodic estimation of multipliers across multiple sites and age groups improves our understanding of influenza detection in sentinel surveillance systems. Adjusting surveillance data using a multiplier method is a relatively simple means to estimate the impact of influenza and the subsequent value of interventions to prevent influenza.


Luna-Gierke R.E.,Centers for Disease Control and Prevention | Wymore K.,California Emerging Infections Program | Clogher P.,Connecticut Emerging Infections Program | Gierke R.W.,Georgia Emerging Infections Program | And 6 more authors.
Zoonoses and Public Health | Year: 2014

Summary: We describe multiple-aetiology infections involving non-O157 Shiga toxin-producing Escherichia coli (STEC) identified through laboratory-based surveillance in nine FoodNet sites from 2001 to 2010. A multiple-aetiology infection (MEI) was defined as isolation of non-O157 STEC and laboratory evidence of any of the other nine pathogens under surveillance or isolation of >1 non-O157 STEC serogroup from the same person within a 7-day period. We compared exposures of patients with MEI during 2001-2010 with those of patients with single-aetiology non-O157 STEC infections (SEI) during 2008-2009 and with those of the FoodNet population from a survey conducted during 2006-2007. In total, 1870 non-O157 STEC infections were reported; 68 (3.6%) were MEI; 60 included pathogens other than non-O157 STEC; and eight involved >1 serogroup of non-O157 STEC. Of the 68 MEI, 21 (31%) were part of six outbreaks. STEC O111 was isolated in 44% of all MEI. Of patients with MEI, 50% had contact with farm animals compared with 29% (P < 0.01) of persons with SEI; this difference was driven by infections involving STEC O111. More patients with non-outbreak-associated MEI reported drinking well water (62%) than respondents in a population survey (19%) (P < 0.01). Drinking well water and having contact with animals may be important exposures for MEI, especially those involving STEC O111. © 2014 Blackwell Verlag GmbH.


Clogher P.,Yale University | Hurd S.,Yale University | Hoefer D.,New York State Department of Health | Hadler J.L.,Yale University | And 6 more authors.
Clinical Infectious Diseases | Year: 2012

Background.Shiga toxin-producing Escherichia coli (STEC) infections cause acute diarrheal illness and sometimes life-threatening hemolytic uremic syndrome (HUS). Escherichia coli O157 is the most common STEC, although the number of reported non-O157 STEC infections is growing with the increased availability and use of enzyme immunoassay testing, which detects the presence of Shiga toxin in stool specimens. Prompt and accurate diagnosis of STEC infection facilitates appropriate therapy and may improve patient outcomes.Methods.We mailed 2400 surveys to physicians in 8 Foodborne Diseases Active Surveillance Network (FoodNet) sites to assess their knowledge and practices regarding STEC testing, treatment, and reporting, and their interpretation of Shiga toxin test results.Results.Of 1102 completed surveys, 955 were included in this analysis. Most (83%) physicians reported often or always ordering a culture of bloody stool specimens; 49% believed that their laboratory routinely tested for STEC O157, and 30% believed that testing for non-O157 STEC was also included in a routine stool culture. Forty-two percent of physicians were aware that STEC, other than O157, can cause HUS, and 34% correctly interpreted a positive Shiga toxin test result. All STEC knowledge-related factors were strongly associated with correct interpretation of a positive Shiga toxin test result.Conclusions. Identification and management of STEC infection depends on laboratories testing for STEC and physicians ordering and correctly interpreting results of Shiga toxin tests. Although overall knowledge of STEC was low, physicians who had more knowledge were more likely to correctly interpret a Shiga toxin test result. Physician knowledge of STEC may be modifiable through educational interventions. © 2012 The Author.


Mody R.K.,Centers for Disease Control and Prevention | Gu W.,Centers for Disease Control and Prevention | Griffin P.M.,Centers for Disease Control and Prevention | Shiferaw B.,Oregon Public Health Division | And 6 more authors.
Journal of Pediatrics | Year: 2015

Objective To assess the clinical spectrum of postdiarrheal hemolytic uremic syndrome (D+HUS) hospitalizations and sought predictors of in-hospital death to help identify children at risk of poor outcomes. Study design We assessed clinical variables collected through population-based surveillance of D+HUS in children <18 years old hospitalized in 10 states during 1997-2012 as predictors of in-hospital death by using tree modeling. Results We identified 770 cases. Of children with information available, 56.5% (430 of 761) required dialysis, 92.6% (698 of 754) required a transfusion, and 2.9% (22 of 770) died; few had a persistent dialysis requirement (52 [7.3%] of 716) at discharge. The tree model partitioned children into 5 groups on the basis of 3 predictors (highest leukocyte count and lowest hematocrit value during the 7 days before to 3 days after the diagnosis of hemolytic uremic syndrome, and presence of respiratory tract infection [RTI] within 3 weeks before diagnosis). Patients with greater leukocyte or hematocrit values or a recent RTI had a greater probability of in-hospital death. The largest group identified (n = 533) had none of these factors and had the lowest odds of death. Many children with RTI had recent antibiotic treatment for nondiarrheal indications. Conclusion Most children with D+HUS have good hospitalization outcomes. Our findings support previous reports of increased leukocyte count and hematocrit as predictors of death. Recent RTI could be an additional predictor, or a marker of other factors such as antibiotic exposure, that may warrant further study.


Mody R.K.,Centers for Disease Control and Prevention | Luna-Gierke R.E.,Centers for Disease Control and Prevention | Hurd S.,Connecticut Emerging Infections Program | Lathrop S.,New Mexico Emerging Infections Program | And 6 more authors.
Archives of Pediatrics and Adolescent Medicine | Year: 2012

Objective: To describe pathogens identified through routine clinical practice and factors associated with identifying Shiga toxin-producing Escherichia coli (STEC) infection in patients with postdiarrheal hemolytic uremic syndrome (D+HUS). Design : Population-based active surveillance. Setting: Hospitals in the FoodNet surveillance areas from 2000 through 2010. Participants : Children younger than 18 years with D+HUS. Main Exposures: Testing for STEC and demographic and clinical characteristics. Main Outcome Measures: Percentage of patients with evidence of infection with likely HUS-causing agents and associations between exposures and evidence of STEC infection. Results: Of 617 patients, 436 (70.7%) had evidence of infection with likely HUS-causing agents: STEC O157 (401 patients), non-O157 STEC (21 patients), O157 and non-O157 STEC (1 patient), Streptococcus pneumoniae (11 patients), and other pathogens (2 patients). Among patients without microbiological evidence of STEC, 76.9% of those tested had serologic evidence of STEC infection. Children more likely to have evidence of STEC infections included those patients tested for STEC less than 4 days after diarrhea onset, 12 months or older (71.6% vs 27.8% if <12 months of age), with infections as part of an outbreak (94.3% vs 67.3%), with bloody diarrhea (77.2% vs 40.4%), with onset during June through September (76.9% vs 60.1%), with a leukocyte count greater than 18 000/μL (to convert to X109/L, multiply by 0.001) (75.7% vs 65.3%), or with only moderate anemia (hemoglobin >7.0 g/dL [to convert to grams per liter, multiply by 10] or hematocrit greater than 20% [to convert to a proportion of 1, multiply by 0.01]) (75.1% vs 66.3%). However, many of these associations were weaker among children with thorough STEC testing. Conclusions: Early stool collection for E coli O157 culture and Shiga toxin testing of all children with possible bacterial enteric infection will increase detection of STEC strains causing HUS. In the absence of microbiological evidence of STEC, serologic testing should be performed. ©2012 American Medical Association. All rights reserved.


PubMed | California Emerging Infections Program, Centers for Disease Control and Prevention, Oregon Public Health Division, New Mexico Emerging Infections Program and University of Rochester
Type: Journal Article | Journal: PloS one | Year: 2015

Annual estimates of the influenza disease burden provide information to evaluate programs and allocate resources. We used a multiplier method with routine population-based surveillance data on influenza hospitalization in the United States to correct for under-reporting and estimate the burden of influenza for seasons after the 2009 pandemic. Five sites of the Influenza Hospitalization Surveillance Network (FluSurv-NET) collected data on the frequency and sensitivity of influenza testing during two seasons to estimate under-detection. Population-based rates of influenza-associated hospitalization and Intensive Care Unit admission from 2010-2013 were extrapolated to the U.S. population from FluSurv-NET and corrected for under-detection. Influenza deaths were calculated using a ratio of deaths to hospitalizations. We estimated that influenza-related hospitalizations were under-detected during 2010-11 by a factor of 2.1 (95%CI 1.7-2.9) for age < 18 years, 3.1 (2.4-4.5) for ages 18-64 years, and 5.2 (95%CI 3.8-8.3) for age 65+. Results were similar in 2011-12. Extrapolated estimates for 3 seasons from 2010-2013 included: 114,192-624,435 hospitalizations, 18,491-95,390 ICU admissions, and 4,915-27,174 deaths per year; 54-70% of hospitalizations and 71-85% of deaths occurred among adults aged 65+. Influenza causes a substantial disease burden in the U.S. that varies by age and season. Periodic estimation of multipliers across multiple sites and age groups improves our understanding of influenza detection in sentinel surveillance systems. Adjusting surveillance data using a multiplier method is a relatively simple means to estimate the impact of influenza and the subsequent value of interventions to prevent influenza.

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