According to the Centers for Disease Control and Prevention (CDC), from 2000 to 2014, reported cases of legionellosis per 100 000 population increased by 300% in the USA, although reports on disease seasonality are inconsistent. Using two national databases, we assessed seasonal patterns of legionellosis in the USA. We created a monthly time series from 1993 to 2015 of reported cases of legionellosis from the CDC, and from 1997 to 2006 of medical claims of legionellosis-related hospitalisation in older adults from the Centers for Medicaid and Medicare Services (CMS). We split the study time interval into two segments (before and after 2003), and applied a Poisson harmonic regression model to each dataset and each segment. The time series of monthly counts exhibited a significant shift of seasonal peaks from mid-September (9.676 ± 0.164 months) before 2003 to mid-August (8.452 ± 0.042 months) after 2003, along with an alarming increase in the amplitude of seasonal peaks in both CDC and CMS data. The lowest monthly reported cases of legionellosis in 2015 (281) exceed the maximum value reported before 2003 (206). We also observed a discrepancy between CDC and CMS data, suggesting that not all cases of legionellosis diagnosed by hospital-based laboratories were reported to the CDC. Improved reporting of legionellosis is required to better inform the public and organise disease prevention.

The carbon intensity (CI) of corn ethanol, the primary renewable fuel used in transportation, has been actively researched and quantified over the last three decades. Reliable estimates of greenhouse gas (GHG) emissions for corn ethanol are important since these values help determine significant policy and market decisions on state, national, and international levels. We reviewed well-to-wheel GHG life cycle analyses (LCAs) for corn ethanol and evaluated models, input data, and results for farming, fuel production, co-product credit, land use change (LUC), transport of feedstock and fuel, tailpipe, and denaturant. Compared to earlier analyses, recent LCAs for corn ethanol contain updates to modeling systems and data that reflect: (a) market-driven changes in corn production that lowered the intensity of fertilizer and fossil fuel use on farms; (b) more efficient use of natural gas and recent electric generation mix data for energy consumed at ethanol refineries, and (c) LUC analyses based on hybrid economic-biophysical models that account for land conversion, land productivity, and land intensification. LCAs that include these latest developments yield a central best estimate of CI for corn ethanol of 51.4 gCO2e MJ−1 (range of 37.6–65.1 gCO2e MJ−1) which is 46% lower than the average CI for neat gasoline. The largest components of total CI are ethanol production (29.6 gCO2e MJ−1, 58% of total) and farming practices net of co-product credit (13.2 gCO2e MJ−1, 26%), while LUC is a minor contributor (3.9 gCO2e MJ−1, 7%). Market conditions that favor greater adoption of precision agriculture systems, retention of soil organic carbon, and demand for co-products from ethanol production may lower the CI of corn ethanol further. Continued refinement of models to account for co-products, conservation of soil carbon, and direct and indirect LUC is expected to produce ever more accurate estimates in the future.

Background: Uptake and completion of the HPV vaccine is suboptimal. This study assessed the feasibility of implementing a one-month Twitter campaign to promote knowledge about the human papillomavirus (HPV) vaccine among low-income women living in public housing. Methods: We recruited a convenience sample (n = 35) of women ages 18-26 years residing in low-come, public housing in Massachusetts. We assessed the feasibility and acceptability of a communication campaign that consisted of daily Twitter messages. Online surveys assessed changes in HPV knowledge, attitudes, and vaccine intentions before and after the campaign. Results: Most believed that Twitter was an acceptable educational strategy and remained engaged with the campaign throughout the intervention. We observed no changes in HPV knowledge, perceived benefits of or barriers to vaccination, decision self-efficacy, or vaccine intentions after the campaign, although perceived risk for cervical cancer decreased. Conclusions: Twitter may be a feasible and acceptable method for promoting knowledge about the HPV vaccine, but more research is needed to understand how best to reach low-income women with low levels of vaccine uptake.

Time series analysis in epidemiological studies is typically conducted on aggregated counts, although data tend to be collected at finer temporal resolutions. The decision to aggregate data is rarely discussed in epidemiological literature although it has been shown to impact model results. We present a critical thinking process for making decisions about data aggregation in time series analysis of seasonal infections. We systematically build a harmonic regression model to characterize peak timing and amplitude of three respiratory and enteric infections that have different seasonal patterns and incidence. We show that irregularities introduced when aggregating data must be controlled during modeling to prevent erroneous results. Aggregation irregularities had a minimal impact on the estimates of trend, amplitude, and peak timing for daily and weekly data regardless of the disease. However, estimates of peak timing of the more common infections changed by as much as 2.5 months when controlling for monthly data irregularities. Building a systematic model that controls for data irregularities is essential to accurately characterize temporal patterns of infections. With the urgent need to characterize temporal patterns of novel infections, such as COVID-19, this tutorial is timely and highly valuable for experts in many disciplines.