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Yih, Katherine

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Yih

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Katherine

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Yih, Katherine
Author's Publications: search.filters.isAuthorOfPublication.40dcf92a-ac36-47d6-8bf7-ff75abb91a2a

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    Laboratory-Based Prospective Surveillance for Community Outbreaks of Shigella spp. in Argentina
    (Public Library of Science, 2013) Viñas, María R.; Tuduri, Ezequiel; Galar, Alicia; Yih, Katherine; Pichel, Mariana; Stelling, John; Brengi, Silvina P.; Della Gaspera, Anabella; van der Ploeg, Claudia; Bruno, Susana; Rogé, Ariel; Caffer, María I.; Kulldorff, Martin; Galas, Marcelo
    Background: To implement effective control measures, timely outbreak detection is essential. Shigella is the most common cause of bacterial diarrhea in Argentina. Highly resistant clones of Shigella have emerged, and outbreaks have been recognized in closed settings and in whole communities. We hereby report our experience with an evolving, integrated, laboratory-based, near real-time surveillance system operating in six contiguous provinces of Argentina during April 2009 to March 2012. Methodology To detect localized shigellosis outbreaks timely, we used the prospective space-time permutation scan statistic algorithm of SaTScan, embedded in WHONET software. Twenty three laboratories sent updated Shigella data on a weekly basis to the National Reference Laboratory. Cluster detection analysis was performed at several taxonomic levels: for all Shigella spp., for serotypes within species and for antimicrobial resistance phenotypes within species. Shigella isolates associated with statistically significant signals (clusters in time/space with recurrence interval ≥365 days) were subtyped by pulsed field gel electrophoresis (PFGE) using PulseNet protocols. Principal Findings In three years of active surveillance, our system detected 32 statistically significant events, 26 of them identified before hospital staff was aware of any unexpected increase in the number of Shigella isolates. Twenty-six signals were investigated by PFGE, which confirmed a close relationship among the isolates for 22 events (84.6%). Seven events were investigated epidemiologically, which revealed links among the patients. Seventeen events were found at the resistance profile level. The system detected events of public health importance: infrequent resistance profiles, long-lasting and/or re-emergent clusters and events important for their duration or size, which were reported to local public health authorities. Conclusions/Significance: The WHONET-SaTScan system may serve as a model for surveillance and can be applied to other pathogens, implemented by other networks, and scaled up to national and international levels for early detection and control of outbreaks.
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    The Risk of Febrile Seizures Following Influenza and 13-Valent Pneumococcal Conjugate Vaccines
    (Oxford University Press, 2017) Baker, Meghan; Jankosky, Christopher; Yih, Katherine; Gruber, Susan; Li, Lingling; Cocoros, Noelle; Lipowicz, Hana; Coronel-Moreno, Claudia; Feibelmann, Sandra; Lin, Nancy; McMahill-Walraven, Cheryl; Menschik, David; Selvan, Mano; Selvam, Nandini; Tilney, Rong Chen; Zichittella, Lauren; Lee, Grace; Kawai, Alison Tse
    Abstract Background: Evidence on the risk of febrile seizures (FS) after vaccination with inactivated influenza vaccine (IIV) and 13-valent pneumococcal conjugate vaccine (PCV13) is mixed. Among children 6–23 months, we examined the risk of FS following IIV and PCV13 during the 2013–14 and 2014–15 influenza seasons, for which vaccine virus strains were the same. Methods: We used claims data from 4 large national insurers in the FDA-sponsored Sentinel Initiative, which was developed to monitor the safety of FDA-regulated medical products. With a self-controlled risk interval design, the risk of FS in 0–1 days following IIV and following PCV13 was compared with a comparison interval (14–20 days), adjusting for confounding by age, calendar time, and concomitant vaccination with the other vaccine. In exploratory analyses, we assessed whether the effect of IIV is modified by concomitant administration of PCV13. Results: During the study period, 355,486 children received IIV and 581,868 received PCV13. We observed an incidence rate ratio (IRR) of 1.12 (95% CI 0.80, 1.56) for the risk of FS following IIV after adjustment for age, calendar time and concomitant PCV13. PCV13 was associated with an increased risk of FS (IRR adjusted for age, calendar time and concomitant IIV, 1.80, 95% CI 1.29, 2.52). The attributable risk for PCV13 ranged from 0.33 to 5.16 per 100,000 doses. The age and calendar-time adjusted IRR comparing exposed time to unexposed time was greater for concomitant IIV and PCV13 (IRR 2.80, 95% CI 1.63, 4.83), as compared with that for PCV13 without concomitant IIV (IRR 1.54, 95% CI 1.04, 2.28). However, the formal test assessing for interaction between IIV and PCV13 was not statistically significant. Conclusion: We found an elevated risk of FS after PCV13 vaccine but not after IIV, when adjusting for concomitant administration of the other vaccine. We found some evidence to suggest that concomitant administration of IIV with PCV13 might interact to increase the risk beyond the independent effects of PCV13, but the study was not powered to assess this interaction. The risk of seizures associated with PCV13 is low compared with a child’s lifetime risk of FS. Findings should be interpreted in the context of the importance of preventing influenza and pneumococcal infections in young children. Disclosures L. Li, sanofi pasteur: The author is currently employed by Sanofi Genzyme, which shares the same parent company as sanofi pasteur, the manufacturer of the Flu vaccine. However, the work was done while this author was still employed by Harvard Pilgrim Health Care Institute., No financial benefit received
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    Prospective influenza vaccine safety surveillance using fresh data in the Sentinel System†
    (John Wiley and Sons Inc., 2015) Yih, Katherine; Kulldorff, Martin; Sandhu, Sukhminder K.; Zichittella, Lauren; Maro, Judith; Cole, David V.; Jin, Robert; Kawai, Alison Tse; Baker, Meghan; Liu, Chunfu; McMahill‐Walraven, Cheryl N.; Selvan, Mano S.; Platt, Richard; Nguyen, Michael D.; Lee, Grace
    Abstract Purpose To develop the infrastructure to conduct timely active surveillance for safety of influenza vaccines and other medical countermeasures in the Sentinel System (formerly the Mini‐Sentinel Pilot), a Food and Drug Administration‐sponsored national surveillance system that typically relies on data that are mature, settled, and updated quarterly. Methods: Three Data Partners provided their earliest available (“fresh”) cumulative claims data on influenza vaccination and health outcomes 3–4 times on a staggered basis during the 2013–2014 influenza season, collectively producing 10 data updates. We monitored anaphylaxis in the entire population using a cohort design and seizures in children ≤4 years of age using both a self‐controlled risk interval design (primary) and a cohort design (secondary). After each data update, we conducted sequential analysis for inactivated (IIV) and live (LAIV) influenza vaccines using the Maximized Sequential Probability Ratio Test, adjusting for data‐lag. Results: Most of the 10 sequential analyses were conducted within 6 weeks of the last care‐date in the cumulative dataset. A total of 6 682 336 doses of IIV and 782 125 doses of LAIV were captured. The primary analyses did not identify any statistical signals following IIV or LAIV. In secondary analysis, the risk of seizures was higher following concomitant IIV and PCV13 than historically after IIV in 6‐ to 23‐month‐olds (relative risk = 2.7), which requires further investigation. Conclusions: The Sentinel System can implement a sequential analysis system that uses fresh data for medical product safety surveillance. Active surveillance using sequential analysis of fresh data holds promise for detecting clinically significant health risks early. Limitations of employing fresh data for surveillance include cost and the need for careful scrutiny of signals. © 2015 The Authors. Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd.
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    Telephone Triage Service Data for Detection of Influenza-Like Illness
    (Public Library of Science, 2009) Yih, Katherine; Teates, Kathryn S.; Abrams, Allyson; Kleinman, Kenneth Paul; Kulldorff, Martin; Pinner, Robert; Harmon, Robert; Wang, Stanley; Platt, Richard
    Background: Surveillance for influenza and influenza-like illness (ILI) is important for guiding public health prevention programs to mitigate the morbidity and mortality caused by influenza, including pandemic influenza. Nontraditional sources of data for influenza and ILI surveillance are of interest to public health authorities if their validity can be established. Methods/Principal Findings: National telephone triage call data were collected through automated means for purposes of syndromic surveillance. For the 17 states with at least 500,000 inhabitants eligible to use the telephone triage services, call volume for respiratory syndrome was compared to CDC weekly number of influenza isolates and percentage of visits to sentinel providers for ILI. The degree to which the call data were correlated with either CDC viral isolates or sentinel provider percentage ILI data was highly variable among states. Conclusions: Telephone triage data in the U.S. are patchy in coverage and therefore not a reliable source of ILI surveillance data on a national scale. However, in states displaying a higher correlation between the call data and the CDC data, call data may be useful as an adjunct to state-level surveillance data, for example at times when sentinel surveillance is not in operation or in areas where sentinel provider coverage is considered insufficient. Sufficient population coverage, a specific ILI syndrome definition, and the use of a threshold of percentage of calls that are for ILI would likely improve the utility of such data for ILI surveillance purposes.
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    Attitudes of Healthcare Workers in U.S. Hospitals Regarding Smallpox Vaccination
    (BioMed Central, 2003) Yih, Katherine; Lieu, Tracy; Rêgo, Virginia H; O'Brien, Megan A; Shay, David K; Yokoe, Deborah S.; Platt, Richard
    Background: The United States is implementing plans to immunize 500,000 hospital-based healthcare workers against smallpox. Vaccination is voluntary, and it is unknown what factors drive vaccine acceptance. This study's aims were to estimate the proportion of workers willing to accept vaccination and to identify factors likely to influence their decisions. Methods: The survey was conducted among physicians, nurses, and others working primarily in emergency departments or intensive care units at 21 acute-care hospitals in 10 states during the two weeks before the U.S. national immunization program for healthcare workers was announced in December 2002. Of the questionnaires distributed, 1,165 were returned, for a response rate of 81%. The data were analyzed by logistic regression and were adjusted for clustering within hospital and for different number of responses per hospital, using generalized linear mixed models and SAS's NLMIXED procedure. Results: Sixty-one percent of respondents said they would definitely or probably be vaccinated, while 39% were undecided or inclined against it. Fifty-three percent rated the risk of a bioterrorist attack using smallpox in the United States in the next two years as either intermediate or high. Forty-seven percent did not feel well-informed about the risks and benefits of vaccination. Principal concerns were adverse reactions and the risk of transmitting vaccinia. In multivariate analysis, four variables were associated with willingness to be vaccinated: perceived risk of an attack, self-assessed knowledge about smallpox vaccination, self-assessed previous smallpox vaccination status, and gender. Conclusions: The success of smallpox vaccination efforts will ultimately depend on the relative weight in people's minds of the risk of vaccine adverse events compared with the risk of being exposed to the disease. Although more than half of the respondents thought the likelihood of a bioterrorist smallpox attack was intermediate or high, less than 10% of the group slated for vaccination has actually accepted it at this time. Unless new information about the threat of a smallpox attack becomes available, healthcare workers' perceptions of the vaccine's risks will likely continue to drive their ongoing decisions about smallpox vaccination.
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    A Flexibly Shaped Space-time Scan Statistic for Disease Outbreak Detection and Monitoring
    (BioMed Central, 2008) Takahashi, Kunihiko; Kulldorff, Martin; Tango, Toshiro; Yih, Katherine
    Background: Early detection of disease outbreaks enables public health officials to implement disease control and prevention measures at the earliest possible time. A time periodic geographical disease surveillance system based on a cylindrical space-time scan statistic has been used extensively for disease surveillance along with the SaTScan software. In the purely spatial setting, many different methods have been proposed to detect spatial disease clusters. In particular, some spatial scan statistics are aimed at detecting irregularly shaped clusters which may not be detected by the circular spatial scan statistic. Results: Based on the flexible purely spatial scan statistic, we propose a flexibly shaped space-time scan statistic for early detection of disease outbreaks. The performance of the proposed space-time scan statistic is compared with that of the cylindrical scan statistic using benchmark data. In order to compare their performances, we have developed a space-time power distribution by extending the purely spatial bivariate power distribution. Daily syndromic surveillance data in Massachusetts, USA, are used to illustrate the proposed test statistic. Conclusion: The flexible space-time scan statistic is well suited for detecting and monitoring disease outbreaks in irregularly shaped areas.
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    Distributed Data Processing for Public Health Surveillance
    (BioMed Central, 2006) Lazarus, Ross; Yih, Katherine; Platt, Richard
    Background: Many systems for routine public health surveillance rely on centralized collection of potentially identifiable, individual, identifiable personal health information (PHI) records. Although individual, identifiable patient records are essential for conditions for which there is mandated reporting, such as tuberculosis or sexually transmitted diseases, they are not routinely required for effective syndromic surveillance. Public concern about the routine collection of large quantities of PHI to support non-traditional public health functions may make alternative surveillance methods that do not rely on centralized identifiable PHI databases increasingly desirable. Methods: The National Bioterrorism Syndromic Surveillance Demonstration Program (NDP) is an example of one alternative model. All PHI in this system is initially processed within the secured infrastructure of the health care provider that collects and holds the data, using uniform software distributed and supported by the NDP. Only highly aggregated count data is transferred to the datacenter for statistical processing and display. Results: Detailed, patient level information is readily available to the health care provider to elucidate signals observed in the aggregated data, or for ad hoc queries. We briefly describe the benefits and disadvantages associated with this distributed processing model for routine automated syndromic surveillance. Conclusion: For well-defined surveillance requirements, the model can be successfully deployed with very low risk of inadvertent disclosure of PHI – a feature that may make participation in surveillance systems more feasible for organizations and more appealing to the individuals whose PHI they hold. It is possible to design and implement distributed systems to support non-routine public health needs if required.