The severity of pandemic H1N1 influenza in the United States, from April to July 2009: A Bayesian analysis

Anne M. Presanis, Daniela De Angelis, Angela Hagy, Carrie Reed, Steven Riley, Ben S. Cooper, Lyn Finelli, Paul Biedrzycki, Marc Lipsitch, Joel Ackelsberg, Alys Adamski, Gail Adman, Elisabeth Agbor-Tabi, Christopher Aston, Josephine Atamian, Peter Backman, Sharon Balter, Oxiris Barbot, Sara T. Beatrice, Gary BeaudryElizabeth Begier, Geraldine Bell, Debra Berg, Magdalena Berger, James Betz, Susan Blank, Katherine Bornschlegel, Brooke Bregman, Meghan Burke, Barbara Butts, Liqun Cai, Alejandro Cajigal, Marilyn Campbell, Lorraine Camurati, Shadi Chamany, Dan Cimini, James Cone, Heather Cook, Debra Cook, Catherine Corey, Roseann Costarella, Christiana Coyle, Bindy Crouch, Cherry Ann Da Costa, Alexandria Daniels, Berta Darkins, Arlene DeGrasse, Susanne DeGrechie, Otto Del Cid, Bisram Deocharan, Luis Diaz, Kathleen DiCaprio, Laura DiGrande, Damon Duquaine, James Durrah, Joanna Eavey, Zadkijah Edghill, Barbara Edwin, Joseph Egger, Donna Eisenhower, Martin Evans, Shannon Farley, Richard Feliciano, Marcial Fernandez, Christine Fils-Aime, Anne Fine, Ana Maria Fireteanu, Kelly Fitzgerald, Anne Marie France, Thomas Frieden, Stephen Friedman, Jie Fu, Lawrence Fung, Latchmidat Girdharrie, Michelle Glaser, Christopher Goranson, Francine Griffing, Leena Gupta, Carol Hamilton, Heather Hanson, Scott Harper, Ian Hartman-O'Connell, Qazi Hasnain, Sonia Hedge, Michael Heller, Debra Hendrickson, Arnold Herskovitz, Kinjia Hinterland, Roosevelt Holmes, Jeanne Hom, Jeffrey Hon, Tana Hopke, Jennifer Hsieh, Scott Hughes, Stephen Immerwahr, Anne Marie Incalicchio, John Jasek, Julia Jimenez, Michael Johns, Lucretia Jones, Hannah Jordan, Chrispin Kambili, Jisuk Kang, Deborah Kapell, Adam Karpati, Bonnie Kerker, Kevin Konty, John Kornblum, Gary Krigsman, Fabienne Laraque, Marcelle Layton, Ellen Lee, Lillian Lee, Stephen Lee, Sungwoo Lim, Melissa Marx, Emily McGibbon, Kevin Mahoney, Gilbert Marin, Thomas Matte, Rene McAnanama, Ryan McKay, Carolyn McKay, Katherine McVeigh, Eric Medina, Wanda Medina, Danielle Michelangelo, Juliet Milhofer, Irina Milyavskaya, Mark Misener, Joseph Mizrahi, Linda Moskin, Matt Motherwell, Christa Myers, Hemanth P. Nair, Trang Nguyen, Diana Nilsen, Janet Nival, Jennifer Norton, William Oleszko, Carolyn Olson, Marc Paladini, Lucille Palumbo, Peter Papadopoulos, Hilary Parton, Jacob Paternostro, Lynn Paynter, Krystal Perkins, Sharon Perlman, Haresh Persaud, Charles Peters, Melissa Pfeiffer, Roger Platt, Lindsay Pool, Amado Punsalang, Zahedur Rasul, Valerie Rawlins, Vasudha Reddy, Anne Rinchiuso, Teresa Rodriguez, Ramon Rosal, Maureen Ryan, Michael Sanderson, Allison Scaccia, Amber Levanon Seligson, Jantee Seupersad, Joanne Severe-Dildy, Asma Siddiqi, Ulirike Siemetzki, Tejinder Singh, Sally Slavinski, Meredith Slopen, Timothy Snuggs, David Starr, Catherine Stayton, Alaina Stoute, Jacqueline Terlonge, Alexandra Ternier, Lorna Thorpe, Catherine Travers, Benjamin Tsoi, Kimberly Turner, Joan Tzou, Shameeka Vines, Elizabeth Needham Waddell, Donald Walker, Connie Warner, Isaac Weisfuse, Don Weiss, Antoinette Williams-Akita, Elisha Wilson, Eliza Wilson, Marie Wong, Charles Wu, David Yang, Mohammad Younis, Sulaimon Yusuff, Christopher Zimmerman, Jane Zucker

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Accurate measures of the severity of pandemic (H1N1) 2009 influenza (pH1N1) are needed to assess the likely impact of an anticipated resurgence in the autumn in the Northern Hemisphere. Severity has been difficult to measure because jurisdictions with large numbers of deaths and other severe outcomes have had too many cases to assess the total number with confidence. Also, detection of severe cases may be more likely, resulting in overestimation of the severity of an average case. We sought to estimate the probabilities that symptomatic infection would lead to hospitalization, ICU admission, and death by combining data from multiple sources. Methods and Findings: We used complementary data from two US cities: Milwaukee attempted to identify cases of medically attended infection whether or not they required hospitalization, while New York City focused on the identification of hospitalizations, intensive care admission or mechanical ventilation (hereafter, ICU), and deaths. New York data were used to estimate numerators for ICU and death, and two sources of data - medically attended cases in Milwaukee or self-reported influenza-like illness (ILI) in New York - were used to estimate ratios of symptomatic cases to hospitalizations. Combining these data with estimates of the fraction detected for each level of severity, we estimated the proportion of symptomatic patients who died (symptomatic case-fatality ratio, sCFR), required ICU (sCIR), and required hospitalization (sCHR), overall and by age category. Evidence, prior information, and associated uncertainty were analyzed in a Bayesian evidence synthesis framework. Using medically attended cases and estimates of the proportion of symptomatic cases medically attended, we estimated an sCFR of 0.048% (95% credible interval [CI] 0.026%-0.096%), sCIR of 0.239% (0.134%-0.458%), and sCHR of 1.44% (0.83%-2.64%). Using self-reported ILI, we obtained estimates approximately 7-96lower. sCFR and sCIR appear to be highest in persons aged 18 y and older, and lowest in children aged 5-17 y. sCHR appears to be lowest in persons aged 5-17; our data were too sparse to allow us to determine the group in which it was the highest. Conclusions: These estimates suggest that an autumn-winter pandemic wave of pH1N1 with comparable severity per case could lead to a number of deaths in the range from considerably below that associated with seasonal influenza to slightly higher, but with the greatest impact in children aged 0-4 and adults 18-64. These estimates of impact depend on assumptions about total incidence of infection and would be larger if incidence of symptomatic infection were higher or shifted toward adults, if viral virulence increased, or if suboptimal treatment resulted from stress on the health care system; numbers would decrease if the total proportion of the population symptomatically infected were lower than assumed.

Original languageEnglish (US)
Article number1000207
JournalPLoS Medicine
Volume6
Issue number12
DOIs
StatePublished - Dec 2009

ASJC Scopus subject areas

  • Medicine(all)

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