scholarly journals Lagged meteorological impacts on COVID-19 incidence among high-risk counties in the United States—a spatiotemporal analysis

2021 ◽  
Author(s):  
Lung-Chang Chien ◽  
L.-W. Antony Chen ◽  
Ro-Ting Lin
Keyword(s):  
United States ◽  
High Risk ◽  
Relative Humidity ◽  
Weather Forecasting ◽  
Spline Interpolation ◽  
The United States ◽  
Meteorological Factor ◽  
Maximum Temperature ◽  
Minimum Relative Humidity ◽  
Spatial Function

Abstract Background The associations between meteorological factors and coronavirus disease 2019 (COVID-19) have been discussed globally; however, because of short study periods, the lack of considering lagged effects, and different study areas, results from the literature were diverse and even contradictory. Objective The primary purpose of this study is to conduct more reliable research to evaluate the lagged meteorological impacts on COVID-19 incidence by considering a relatively long study period and diversified high-risk areas in the United States. Methods This study adopted the distributed lagged nonlinear model with a spatial function to analyze COVID-19 incidence predicted by multiple meteorological measures from March to October of 2020 across 203 high-risk counties in the United States. The estimated spatial function was further smoothed within the entire continental United States by the biharmonic spline interpolation. Results Our findings suggest that the maximum temperature, minimum relative humidity, and precipitation were the best meteorological predictors. Most significantly positive associations were found from 3 to 11 lagged days in lower levels of each selected meteorological factor. In particular, a significantly positive association appeared in minimum relative humidity higher than 88.36% at 5-day lag. The spatial analysis also shows excessive risks in the north-central United States. Significance The research findings can contribute to the implementation of early warning surveillance of COVID-19 by using weather forecasting for up to two weeks in high-risk counties.

scholarly journals Effects of trees, gardens, and nature trails on heat index and child health: design and methods of the Green Schoolyards Project

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kevin Lanza ◽  
Melody Alcazar ◽  
Deanna M. Hoelscher ◽  
Harold W. Kohl
Keyword(s):  
Physical Activity ◽  
United States ◽  
Relative Humidity ◽  
Air Temperature ◽  
The United States ◽  
Heat Index ◽  
Activity Levels ◽  
Natural Setting ◽  
Physical Activity Levels ◽  
Nature Trails

Abstract Background Latinx children in the United States are at high risk for nature-deficit disorder, heat-related illness, and physical inactivity. We developed the Green Schoolyards Project to investigate how green features—trees, gardens, and nature trails—in school parks impact heat index (i.e., air temperature and relative humidity) within parks, and physical activity levels and socioemotional well-being of these children. Herein, we present novel methods for a) observing children’s interaction with green features and b) measuring heat index and children’s behaviors in a natural setting, and a selection of baseline results. Methods During two September weeks (high temperature) and one November week (moderate temperature) in 2019, we examined three joint-use elementary school parks in Central Texas, United States, serving predominantly low-income Latinx families. To develop thermal profiles for each park, we installed 10 air temperature/relative humidity sensors per park, selecting sites based on land cover, land use, and even spatial coverage. We measured green features within a geographic information system. In a cross-sectional study, we used an adapted version of System for Observing Play and Recreation in Communities (SOPARC) to assess children’s physical activity levels and interactions with green features. In a cohort study, we equipped 30 3rd and 30 4th grade students per school during recess with accelerometers and Global Positioning System devices, and surveyed these students regarding their connection to nature. Baseline analyses included inverse distance weighting for thermal profiles and summing observed counts of children interacting with trees. Results In September 2019, average daily heat index ranged 2.0 °F among park sites, and maximum daily heat index ranged from 103.4 °F (air temperature = 33.8 °C; relative humidity = 55.2%) under tree canopy to 114.1 °F (air temperature = 37.9 °C; relative humidity = 45.2%) on an unshaded playground. 10.8% more girls and 25.4% more boys interacted with trees in September than in November. Conclusions We found extreme heat conditions at select sites within parks, and children positioning themselves under trees during periods of high heat index. These methods can be used by public health researchers and practitioners to inform the redesign of greenspaces in the face of climate change and health inequities.

Simulation : The National Security Council

1985 ◽  
Vol 47 ◽  
pp. 3-4
Author(s):  
Douglas W. Simon
Keyword(s):  
United States ◽  
High Risk ◽  
National Security ◽  
Security Council ◽  
The United States ◽  
National Security Council ◽  
Gulf Region ◽  
College Course ◽  
Term Papers ◽  
Global Events

In the spring of 1981 I designed and taught what I considered, at the time, a "high risk" seminar for seventeen junior and senior political science majors. There were to be no textbooks, no lectures, no examinations and no term papers, those hallmarks of the traditional college course. Nevertheless, when the thirteen week course was over, the students were exhausted and claimed that they had never worked so hard in their college careers.The adventure that my students (and I) undertook was a semester long simulation of the United States National Security Council (NSC), dealing with actual global events as they happened. As Washington dealt with a problem, we dealt with the same problem. The simulation was initially offered during the deteriorating situation in Iran and instability in the Gulf region.

scholarly journals PIN41 INFLUENZA VACCINATION RATES AMONG HIGH RISK GROUPS IN THE UNITED STATES

2011 ◽  
Vol 14 (3) ◽  
pp. A121
Author(s):  
M. DiBonaventura ◽  
J.S. Wagner ◽  
A. Goren
Keyword(s):  
United States ◽  
High Risk ◽  
Influenza Vaccination ◽  
Risk Groups ◽  
The United States ◽  
Vaccination Rates

Douching Practices Among Women at High Risk of HIV Infection in the United States

2002 ◽  
Vol 29 (7) ◽  
pp. 406-410 ◽  
Author(s):  
BERYL A. KOBLIN ◽  
KENNETH MAYER ◽  
ANTHONY MWATHA ◽  
PAMELA BROWN-PETERSIDE ◽  
RENEE HOLT ◽  
...  
Keyword(s):  
United States ◽  
High Risk ◽  
Hiv Infection ◽  
The United States

scholarly journals Influenza vaccine effectiveness among patients with high-risk medical conditions in the United States, 2012–2016

Vaccine ◽  
2018 ◽  
Vol 36 (52) ◽  
pp. 8047-8053 ◽  
Author(s):  
Mei Shang ◽  
Jessie R. Chung ◽  
Michael L. Jackson ◽  
Lisa A. Jackson ◽  
Arnold S. Monto ◽  
...  
Keyword(s):  
United States ◽  
High Risk ◽  
Influenza Vaccine ◽  
The United States ◽  
Vaccine Effectiveness ◽  
Medical Conditions

scholarly journals Relations between Temperature and Residential Natural Gas Consumption in the Central and Eastern United States

2007 ◽  
Vol 46 (11) ◽  
pp. 1993-2013 ◽  
Author(s):  
Reed P. Timmer ◽  
Peter J. Lamb
Keyword(s):  
United States ◽  
Natural Gas ◽  
Time Scales ◽  
The United States ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
The South ◽  
Northern Regions ◽  
Gas Consumption

Abstract The increased U.S. natural gas price volatility since the mid-to-late-1980s deregulation generally is attributed to the deregulated market being more sensitive to temperature-related residential demand. This study therefore quantifies relations between winter (November–February; December–February) temperature and residential gas consumption for the United States east of the Rocky Mountains for 1989–2000, by region and on monthly and seasonal time scales. State-level monthly gas consumption data are aggregated for nine multistate subregions of three Petroleum Administration for Defense Districts of the U.S. Department of Energy. Two temperature indices [days below percentile (DBP) and heating degree-days (HDD)] are developed using the Richman–Lamb fine-resolution (∼1° latitude–longitude) set of daily maximum and minimum temperatures for 1949–2000. Temperature parameters/values that maximize DBP/HDD correlations with gas consumption are identified. Maximum DBP and HDD correlations with gas consumption consistently are largest in the Great Lakes–Ohio Valley region on both monthly (from +0.89 to +0.91) and seasonal (from +0.93 to +0.97) time scales, for which they are based on daily maximum temperature. Such correlations are markedly lower on both time scales (from +0.62 to +0.80) in New England, where gas is less important than heating oil, and on the monthly scale (from +0.55 to +0.75) across the South because of low January correlations. For the South, maximum correlations are for daily DBP and HDD indices based on mean or minimum temperature. The percentiles having the highest DBP index correlations with gas consumption are slightly higher for northern regions than across the South. This is because lower (higher) relative (absolute) temperature thresholds are reached in warmer regions before home heating occurs. However, these optimum percentiles for all regions are bordered broadly by surrounding percentiles for which the correlations are almost as high as the maximum. This consistency establishes the robustness of the temperature–gas consumption relations obtained. The reference temperatures giving the highest HDD correlations with gas consumption are lower for the colder northern regions than farther south where the temperature range is truncated. However, all HDD reference temperatures greater than +10°C (+15°C) yield similar such correlations for northern (southern) regions, further confirming the robustness of the findings. This robustness, coupled with the very high correlation magnitudes obtained, suggests that potentially strong gas consumption predictability would follow from accurate seasonal temperature forecasts.

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