On March 29, 2021, this report was posted as an MMWR Early Release on the MMWR website (https://www.cdc.gov/mmwr)Messenger RNA (mRNA) BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) COVID-19 vaccines have been shown to be effective in preventing symptomatic COVID-19 in randomized placebo-controlled Phase III trials (1,2); however, the benefits of these vaccines for preventing asymptomatic and symptomatic SARS-CoV-2 (the virus that causes COVID-19) infection, particularly when administered in real-world conditions, is less well understood. Using prospective cohorts of health care personnel, first responders, and other essential and frontline workers* in eight U.S. locations during December 14, 2020-March 13, 2021, CDC routinely tested for SARS-CoV-2 infections every week regardless of symptom status and at the onset of symptoms consistent with COVID-19-associated illness. Among 3,950 participants with no previous laboratory documentation of SARS-CoV-2 infection, 2,479 (62.8%) received both recommended mRNA doses and 477 (12.1%) received only one dose of mRNA vaccine. † Among unvaccinated participants, 1.38 SARS-CoV-2 infections were confirmed by reverse transcription-polymerase chain reaction (RT-PCR) per 1,000 person-days. § In contrast, among fully immunized (≥14 days after second dose) persons, 0.04 infections per 1,000 person-days were reported, and among partially immunized (≥14 days after first dose and * Occupational categories: primary health care personnel (physicians, physician assistants, nurse practitioners, and dentists), other allied health care personnel (nurses, therapists, technicians, medical assistants, orderlies, and all other persons providing clinical support in inpatient or outpatient settings), first responders (firefighters, law enforcement, corrections, and emergency medical technicians), other essential and frontline workers (workers in hospitality, delivery, and retail; teachers; and all other occupations that require contact within 3 feet of the public, customers, or coworkers as a routine part of their job). † An additional five participants received the Janssen COVID-19 vaccine (Johnson & Johnson), resulting in 2,961 vaccinated participants. § Person-days is an estimate of the time-at-risk (to SARS-CoV-2 infection) that each participant contributed to the study.

BackgroundSevere illness due to 2009 pandemic A(H1N1) infection has been reported among persons who are obese or morbidly obese. We assessed whether obesity is a risk factor for hospitalization and death due to 2009 pandemic influenza A(H1N1), independent of chronic medical conditions considered by the Advisory Committee on Immunization Practices (ACIP) to increase the risk of influenza-related complications.Methodology/Principal FindingsWe used a case-cohort design to compare cases of hospitalizations and deaths from 2009 pandemic A(H1N1) influenza occurring between April–July, 2009, with a cohort of the U.S. population estimated from the 2003–2006 National Health and Nutrition Examination Survey (NHANES); pregnant women and children <2 years old were excluded. For hospitalizations, we defined categories of relative weight by body mass index (BMI, kg/m2); for deaths, obesity or morbid obesity was recorded on medical charts, and death certificates. Odds ratio (OR) of being in each BMI category was determined; normal weight was the reference category. Overall, 361 hospitalizations and 233 deaths included information to determine BMI category and presence of ACIP-recognized medical conditions. Among ≥20 year olds, hospitalization was associated with being morbidly obese (BMI≥40) for individuals with ACIP-recognized chronic conditions (OR = 4.9, 95% CI 2.4–9.9) and without ACIP-recognized chronic conditions (OR = 4.7, 95%CI 1.3–17.2). Among 2–19 year olds, hospitalization was associated with being underweight (BMI≤5th percentile) among those with (OR = 12.5, 95%CI 3.4–45.5) and without (OR = 5.5, 95%CI 1.3–22.5) ACIP-recognized chronic conditions. Death was not associated with BMI category among individuals 2–19 years old. Among individuals aged ≥20 years without ACIP-recognized chronic medical conditions death was associated with obesity (OR = 3.1, 95%CI: 1.5–6.6) and morbid obesity (OR = 7.6, 95%CI 2.1–27.9).Conclusions/SignificanceOur findings support observations that morbid obesity may be associated with hospitalization and possibly death due to 2009 pandemic H1N1 infection. These complications could be prevented by early antiviral therapy and vaccination.

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BackgroundGoogle Flu Trends (GFT) uses anonymized, aggregated internet search activity to provide near-real time estimates of influenza activity. GFT estimates have shown a strong correlation with official influenza surveillance data. The 2009 influenza virus A (H1N1) pandemic [pH1N1] provided the first opportunity to evaluate GFT during a non-seasonal influenza outbreak. In September 2009, an updated United States GFT model was developed using data from the beginning of pH1N1.Methodology/Principal FindingsWe evaluated the accuracy of each U.S. GFT model by comparing weekly estimates of ILI (influenza-like illness) activity with the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). For each GFT model we calculated the correlation and RMSE (root mean square error) between model estimates and ILINet for four time periods: pre-H1N1, Summer H1N1, Winter H1N1, and H1N1 overall (Mar 2009–Dec 2009). We also compared the number of queries, query volume, and types of queries (e.g., influenza symptoms, influenza complications) in each model. Both models' estimates were highly correlated with ILINet pre-H1N1 and over the entire surveillance period, although the original model underestimated the magnitude of ILI activity during pH1N1. The updated model was more correlated with ILINet than the original model during Summer H1N1 (r = 0.95 and 0.29, respectively). The updated model included more search query terms than the original model, with more queries directly related to influenza infection, whereas the original model contained more queries related to influenza complications.ConclusionsInternet search behavior changed during pH1N1, particularly in the categories “influenza complications” and “term for influenza.” The complications associated with pH1N1, the fact that pH1N1 began in the summer rather than winter, and changes in health-seeking behavior each may have played a part. Both GFT models performed well prior to and during pH1N1, although the updated model performed better during pH1N1, especially during the summer months.

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