scholarly journals Spatial and Temporal Variation in PM 2.5 Chemical Composition in the United States for Health Effects Studies

2007 ◽  
Vol 115 (7) ◽  
pp. 989-995 ◽  
Author(s):  
Michelle L. Bell ◽  
Francesca Dominici ◽  
Keita Ebisu ◽  
Scott L. Zeger ◽  
Jonathan M. Samet
Keyword(s):  
United States ◽  
Chemical Composition ◽  
Temporal Variation ◽  
Health Effects ◽  
The United States ◽  
Spatial And Temporal Variation ◽  
Pm 2.5

scholarly journals The Effect of Stay-at-Home Orders on COVID-19 Infections in the United States

2020 ◽  
Author(s):  
James H. Fowler ◽  
Seth J. Hill ◽  
Remy Levin ◽  
Nick Obradovich
Keyword(s):  
United States ◽  
Temporal Variation ◽  
Fixed Effects ◽  
National Level ◽  
The United States ◽  
Spatial And Temporal Variation ◽  
Full Potential ◽  
County Level ◽  
Fixed Effects Model ◽  
At Home

SummaryBackgroundIn March and April 2020, public health authorities in the United States acted to mitigate transmission of and hospitalizations from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). These actions were not coordinated at the national level, which raises the question of what might have happened if they were. It also creates an opportunity to use spatial and temporal variation to measure their effect with greater accuracy.MethodsWe combine publicly available data sources on the timing of stay-at-home orders and daily confirmed COVID-19 cases at the county level in the United States (N = 124,027). We then derive from the classic SIR model a two-way fixed-effects model and apply it to the data with controls for unmeasured differences between counties and over time. This enables us to estimate the effect of stay-at-home orders while accounting for local variation in factors like health systems and demographics, and temporal variation in national mitigation actions, access to tests, or exposure to media reports that could influence the course of the disease.FindingsMean county-level daily growth in COVID-19 infections peaked at 17.2% just before stay-at-home orders were issued. Two way fixed-effects regression estimates suggest that orders were associated with a 3.9 percentage point (95% CI 1.2 to 6.6) reduction in the growth rate after one week and a 6.9 percentage point (2.4 to 11.5) reduction after two weeks. By day 27 the reduction (22.6 percentage points, 14.8 to 30.5) had surpassed the growth at the peak, indicating that growth had turned negative and the number of new daily infections was beginning to decline. A hypothetical national stay-at-home order issued on March 13, 2020 when a national emergency was declared might have reduced cumulative infections by 63.3%, and might have helped to reverse exponential growth in the disease by April 10.InterpretationAlthough stay-at-home orders impose great costs to society, delayed responses and piecemeal application of these orders generate similar costs without obtaining the full potential benefits suggested by this analysis. The results here suggest that a coordinated nationwide stay-at-home order might have reduced by hundreds of thousands the current number of infections and by tens of thousands the total number of deaths from COVID-19. Future efforts in the United States and elsewhere to control pandemics should coordinate stay-at-home orders at the national level, especially for diseases for which local spread has already occurred and testing availability is delayed. Since stay-at-home orders reduce infection growth rates, early implementation when infection counts are still low would be most beneficial.FundingNone.

scholarly journals Stay-at-home orders associate with subsequent decreases in COVID-19 cases and fatalities in the United States

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0248849
Author(s):  
James H. Fowler ◽  
Seth J. Hill ◽  
Remy Levin ◽  
Nick Obradovich
Keyword(s):  
United States ◽  
Temporal Variation ◽  
National Level ◽  
Local Variation ◽  
The United States ◽  
Spatial And Temporal Variation ◽  
Difference In Differences ◽  
Contagious Diseases ◽  
Incident Cases ◽  
At Home

Governments issue “stay-at-home” orders to reduce the spread of contagious diseases, but the magnitude of such orders’ effectiveness remains uncertain. In the United States these orders were not coordinated at the national level during the coronavirus disease 2019 (COVID-19) pandemic, which creates an opportunity to use spatial and temporal variation to measure the policies’ effect. Here, we combine data on the timing of stay-at-home orders with daily confirmed COVID-19 cases and fatalities at the county level during the first seven weeks of the outbreak in the United States. We estimate the association between stay-at-home orders and alterations in COVID-19 cases and fatalities using a difference-in-differences design that accounts for unmeasured local variation in factors like health systems and demographics and for unmeasured temporal variation in factors like national mitigation actions and access to tests. Compared to counties that did not implement stay-at-home orders, the results show that the orders are associated with a 30.2 percent (11.0 to 45.2) average reduction in weekly incident cases after one week, a 40.0 percent (23.4 to 53.0) reduction after two weeks, and a 48.6 percent (31.1 to 61.7) reduction after three weeks. Stay-at-home orders are also associated with a 59.8 percent (18.3 to 80.2) average reduction in weekly fatalities after three weeks. These results suggest that stay-at-home orders might have reduced confirmed cases by 390,000 (170,000 to 680,000) and fatalities by 41,000 (27,000 to 59,000) within the first three weeks in localities that implemented stay-at-home orders.

scholarly journals Spatial and Temporal Variation of Rainwater Chemistry in Ile-Ife and Its Environ, Osun State, Nigeria

2017 ◽  
Vol 10 (2) ◽  
pp. 203 ◽  
Author(s):  
Aderonke Adetutu Okoya ◽  
Bamikole Walter Osungbemiro ◽  
Temi E. Ologunorisa
Keyword(s):  
Land Use ◽  
Chemical Composition ◽  
Temporal Variation ◽  
Major Ions ◽  
Rain Water ◽  
Spatial And Temporal Variation ◽  
Rainwater Chemistry ◽  
Water Composition ◽  
Physico Chemical ◽  
The Impact

The study of the chemical composition of rain water was conducted in Ile – Ife and environs, an agrarian, commercial, residential and semi-industrialised center of Osun state Nigeria. This was with a view to assessing the impact of land use activities on rain water composition and the temporal variation of rainwater chemistry. Physico-chemical parameters such as Turbidity, pH, TDS, Conductivity, Oxygen parameters, Alkalinity, Acidity, Hardness and Major ions (Ca2+, Mg2+, K+, Na+, NO3-, SO4-, HCO3-) were determined, predominant ions were identified. Turbidity, pH, Conductivity, TDS, D.O B.O.D, Alkalinity, Acidity Hardness ranged between 2.90 - 42.84 NTU, 5.65 - 7.40, 6.71 – 122.33 µScm-1, 4.10 –73.27 mg/L, 3.60 – 10.60 mg/L, 0.13 – 7.20 mg/L, 0.33 – 22.0 mg/L, 2.00 – 15.00 mg/L, 0.04 – 1.23 CaCO3mg/l respectively. The dominant ions detected in the study were HCO3-, Mg2+, Na+ and Ca2+. Generally, the mean concentration of ions as expressed in milli-equivalent per Litre showed order of dominance as HCO3- > NO3- > SO42- for the anions and Mg2+ > Na+ > Ca2+ > K+ for cations. The study concluded that land use activities had influence on all the chemical composition of rain water in the study area but more on pH, alkalinity, acidity, bicarbonate. Except sulphate and Nitrate, all other parameters recorded high values in dry season.

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