Introduction Influenza epidemics and pandemics cause significant morbidity and mortality. An effective response to a potential pandemic requires the infrastructure to rapidly detect, characterize, and potentially contain new and emerging influenza strains at a population level. The objective of this study is to use data gathered simultaneously from community and hospital sites to develop a model of how influenza enters and spreads in a population.Methods and Analysis Starting in the 2018-19 season, we have been enrolling individuals with acute respiratory illness from community sites throughout the Seattle metropolitan area, including clinics, childcare facilities, Seattle-Tacoma International Airport, workplaces, college campuses, and homeless shelters. At these sites, we collect clinical data and mid-nasal swabs from individuals with at least two acute respiratory symptoms. Additionally, we collect residual nasal swabs and data from individuals who seek care for respiratory symptoms at four regional hospitals. Samples are tested using a multiplex molecular assay, and influenza whole genome sequencing is performed for samples with influenza detected. Geospatial mapping and computational modeling platforms are in development to characterize the regional spread of influenza and other respiratory pathogens.Ethics and Dissemination The study was approved by the University of Washington’s Institutional Review Board. Results will be disseminated through talks at conferences, peer-reviewed publications, and on the study website (www.seattleflu.org).Strengths and limitations of this study- Large-scale multiple-arm study of respiratory illness characterization with collection of samples from individuals in the community as well as in ambulatory care and hospital settings- Integration of sociodemographic, clinical, and geospatial data on a regional level- Multiplex molecular testing for multiple viral and bacterial pathogens and whole genome sequencing of influenza for detailed molecular epidemiologic characterization and transmission mapping- Geographically and socioeconomically diverse sampling of community-based acute respiratory illnessesCompeting Interest StatementAmanda Adler, Elisabeth Brandstetter, Michael Famulare, Chris D. Frazar, Peter D. Han, Reena K. Gulati, James Hadfield, Michael L. Jackson, Anahita Kiavand, Louise E. Kimball, Kirsten Lacombe, Jennifer Logue, Victoria Lyon, Kira L. Newman, Thomas R. Sibley, Jay Shendure, Lea Starita, Monica L. Zigman Suchsland, and Caitlin Wolf declare no competing interests. Helen Y Chu receives research support from Sanofi, Cepheid, and Genentech/Roche and is a consultant for Merck. Janet Englund receives research support to her institution from Astrazeneca, GlaxoSmithKline, Merck, and Novavax and is a consultant for Sanofi Pasteur and Meissa Vaccines.Funding StatementThe Seattle Flu Study is funded through the Brotman Baty Institute. The funder was not involved in the design of the study, does not have any ownership over the management and conduct of the study, the data, or the rights to publishAuthor DeclarationsAll relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript.YesAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable YesThe data will be accessed only by authorized individuals on the study team. Access to deidentified, aggregated data and analysis code will be publicly available on the study web page (www.seattleflu.org). http://www.seattleflu.org

Granulomatous amebic encephalitis (GAE) from Balamuthia mandrillaris, a free-living ameba, has a case fatality rate exceeding 90 % among recognized cases in the USA. In August 2010, a GAE cluster occurred following transplantation of infected organs from a previously healthy landscaper in Tucson, AZ, USA, who died from a suspected stroke. As B. mandrillaris is thought to be transmitted through soil, a serologic survey of landscapers and a comparison group of blood donors in southern Arizona was performed. Three (3.6 %) of 83 serum samples from landscapers and 11 (2.5 %) of 441 serum samples from blood donors were seropositive (p = 0.47). On multivariable analysis, county of residence was associated with seropositivity, whereas age, sex, and ethnicity were not. Exposure to B. mandrillaris, previously unexamined in North America, appears to be far more common than GAE in Southern Arizona. Risk factors for disease progression and the ameba's geographic range should be examined.

CONTEXT: To target school-aged children (SAC), who were identified as a priority for pandemic 2009 Influenza A (pH1N1) vaccination, Maricopa County (MC) initiated school-based influenza vaccination in 69% of its 706 schools during the 2009-2010 influenza season. OBJECTIVE: To determine factors associated with receipt of pH1N1 monovalent and 2009-2010 seasonal influenza vaccination among SAC and evaluate the association of school-based vaccination with vaccination status of SAC. DESIGN: Random-digit dialing was used to survey 600 MC households with willing adult participants and children grades K-12. Logistic regression was used to identify factors associated with pH1N1 and seasonal vaccine receipt. SETTING: Arizona. PARTICIPANTS: Household adults with children grades K-12. MAIN OUTCOME MEASURE: Characteristics of children, parents, and households were obtained. RESULTS: Among 909 SAC, 402 (44%) received pH1N1 and 436 (48%) received seasonal vaccination. Factors associated with pH1N1 vaccination included vaccine availability at school (adjusted odds ratio [AOR]: 1.6; 95% confidence interval [CI]: 1.0-2.7), high-risk medical condition in child (AOR: 2.4; 95% CI: 1.4-4.0), elementary versus high school attendance (AOR: 1.6; 95% CI: 1.0-2.7), and seasonal influenza vaccination (AOR: 10.0; 95% CI: 6.4-15.6). Factors associated with seasonal vaccination included Hispanic ethnicity (AOR: 2.2; 95% CI: 1.1-4.2), health insurance coverage (AOR: 4.8; 95% CI: 1.7-13.7), elementary versus high school attendance (AOR: 1.5; 95% CI: 1.0-2.5), and pH1N1 vaccination (AOR: 10.5; 95% CI: 6.7-16.6). CONCLUSIONS: Availability of pH1N1 vaccine at school was independently associated with pH1N1 vaccination of MC school-aged children. School-based influenza vaccination campaigns should be considered to increase vaccination among this population.

Flagstaff, Arizona, USA, experienced notable outbreaks of rabies caused by a bat rabies virus variant in carnivore species in 2001, 2004, 2005, 2008, and 2009. The most recent epizootic involved transmission among skunk and fox populations and human exposures. Multiple, wide-ranging control efforts and health communications outreach were instituted in 2009, including a household survey given to community members. Although the Flagstaff community is knowledgeable about rabies and the ongoing outbreaks in general, gaps in knowledge about routes of exposure and potential hosts remain. Future educational efforts should include messages on the dangers of animal translocation and a focus on veterinarians and physicians as valuable sources for outreach. These results will be useful to communities experiencing rabies outbreaks as well as those at current risk.

West Nile virus (WNV) is the leading cause of mosquito-borne disease in the United States; however, risk factors for infection are poorly defined. We performed a case-control study to identify modifiable risk factors for WNV infection. Case-patients (N = 49) had laboratory evidence of recent WNV infection, whereas control-subjects (N = 74) had negative WNV serology. We interviewed participants, surveyed households, and assessed environmental data. WNV infection was associated with living in or near Water District X within Gilbert Township (adjusted odds ratio [aOR] 5.2; 95% confidence interval [95% CI] = 1.5-18.1), having water-holding containers in their yard (aOR 5.0; 95% CI = 1.5-17.3), and not working or attending school outside the home (aOR 2.4; 95% CI = 1.1-5.5). During this outbreak, WNV infection was likely primarily acquired peri-domestically with increased risk associated with potential mosquito larval habitats around the home and neighborhood.

Gibney et al recently reported finding no West Nile virus (WNV) RNA in urine samples collected from 40 patients at 6.5–6.7 years after acute WNV disease [1]. These findings were in contrast to Murray et al, who detected WNV RNA in urine samples collected from 5 of 25 patients (20%) at 1.6–6.7 years after their initial infections [2]. We present results from a prospective evaluation of WNV RNA in urine specimens collected from 63 persons within 5 months after their acute WNV infection. | During the 2010 WNV outbreak in Maricopa County, Arizona, we identified persons with laboratory evidence of acute WNV infection, including detection of WNV immunoglobulin M antibodies in serum or cerebrospinal fluid samples from patients with a clinically compatible illness or WNV RNA in serum samples from asymptomatic blood donors. Information on demographic characteristics, medical history, current medications, and clinical illness was obtained by medical record review and interview with patients or their surrogate. A urine sample was collected during a site visit. The study was approved by the Centers for Disease Control and Prevention (CDC) and Arizona Department of Health Services (ADHS) human subjects review boards, and participants provided informed consent before enrollment.

CONTEXT: Rapid influenza diagnostic tests (RIDTs) are used for influenza screening, clinical decision making, and influenza surveillance. In August 2009, a hospital reported increased false-positive RIDT results to the Arizona Department of Health Services. Because of reported RIDT low sensitivities (40%-62%) for 2009 pandemic influenza A (pH1N1), the hospital's report raised further concerns about the specificity and clinical utility of RIDTs. OBJECTIVE: To determine the positive predictive value (PPV) of RIDTs compared with real-time reverse transcription-polymerase chain reaction assay (rRT-PCR) using Centers for Disease Control and Prevention (CDC) protocols and primers as a standard. DESIGN: A standardized survey collected information including RIDT brand/lot number, training of personnel performing test, type of laboratory, swab and specimen type, time from collection to testing, sample storage, and viral transport medium. SETTING: Arizona. PARTICIPANTS: Seven Arizona laboratories submitted positive RIDT clinical samples to Arizona State Public Health Laboratory (ASPHL) for confirmatory rRT-PCR testing. MAIN OUTCOME MEASURE: The PPV was calculated on the basis of rRT-PCR-positive results for April through October. RESULTS: Results from 600 specimens using 1 of 4 RIDTs were available. Median pH1N1 PPV was 80% (range: 62%-91%) when calculated by RIDT brand. A significant difference in PPV was identified between the 2 largest facilities, which used the same RIDT brand, BinaxNOW Influenza A&B, (Laboratories A, 33% and B, 92%, [P < .01]). The facilities reported similar testing practices except lot numbers used and timing of testing. Laboratory A used lot 003684 and performed testing within 1 hour of collection; Laboratory B used multiple lots, excluding lot 003684, and performed testing within 24 hours. Laboratory A switched RIDT brands and noted a significant PPV increase from 33% to 91% (P < .01). CONCLUSIONS: Wide PPV variability combined with documented low sensitivity among RIDTs for pH1N1 diagnosis increases concerns about their specificity and clinical and epidemiologic utility for influenza.