scholarly journals Modeling the Spread of Epidemics Based on Cellular Automata

Processes ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 55
Author(s):  
Jindong Dai ◽  
Chi Zhai ◽  
Jiali Ai ◽  
Jiaying Ma ◽  
Jingde Wang ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
Cellular Automata ◽  
Infectious Diseases ◽  
Temporal Evolution ◽  
Control Strategies ◽  
Decision Makers ◽  
Mathematical Methods ◽  
Structure Population ◽  
Social Community

Mathematical modeling is a powerful tool to study the process of the spread of infectious diseases. Among various mathematical methods for describing the spread of infectious diseases, the cellular automaton makes it possible to explicitly simulate both the spatial and temporal evolution of epidemics with intuitive local rules. In this paper, a model is proposed and realized on a cellular automata platform, which is applied to simulate the spread of coronavirus disease 2019 (COVID-19) for different administrative districts. A simplified social community is considered with varying parameters, e.g., sex ratio, age structure, population movement, incubation and treatment period, immunity, etc. COVID-19 confirmation data from New York City and Iowa are adopted for model validation purpose. It can be observed that the disease exhibits different spread patterns in different cities, which could be well accommodated by this model. Then, scenarios under different control strategies in the next 100 days in Iowa are simulated, which could provide a valuable reference for decision makers in identifying the critical factors for future infection control in Iowa.

Ozone Photochemistry in New York City and Baltimore based on Aircraft Observations

2021 ◽  
Author(s):  
Xinrong Ren ◽  
Phillip Stratton ◽  
Hannah Daley ◽  
Russell Dickerson
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Production Efficiency ◽  
Control Strategies ◽  
Scientific Information ◽  
Photochemical Oxidation ◽  
Ozone Production ◽  
Source Regions ◽  
Aircraft Observations

<p>Aircraft observations of ozone, ozone precursors, and meteorological parameters were made over the New York City (NYC) and Baltimore areas during ozone exceedance events in summer 2018-2020.  Despite the continued reduction in anthropogenic emissions, ozone exceedance events still frequently occurred in the NYC area.  Ozone production efficiency, defined as the ratio of the ozone production rate to the NO<sub>x</sub> oxidation rate, calculated using these observations,  was about 14 ppb ozone produced per ppb NOx oxidized. This high ozone production efficiency likely contributes to the persistent ozone exceedance problem over the Long Island Sound and Connecticut coastal area, downwind of NYC under prevailing southwesterly winds.  There is some evidence for a decreasing trend although COVID-19 restrictions had an impact on 2020 emissions.  A box model, constrained by observations, was used to examine atmospheric photochemical oxidation processes.  Ozone production rates and their sensitivity to nitrogen oxides (NO<sub>x</sub>) and volatile organic compounds (VOCs) were calculated based on the model results. In general ozone production is VOC sensitive near emission sources and NOx sensitive away from source regions. While the Baltimore area is predominantly in the NOx sensitive region, the NYC area is transitioning from VOC sensitive to NOx sensitive.  Preliminary results show that controlling both NOx and VOCs reduces ozone production in the NYC area. Reducing VOCs can reduce ozone production in emission source regions and reducing NOx can reduce ozone production farther away from the source regions. The results from this work strengthen our understanding of ozone production and provide scientific information for emission control strategies to reduce air pollution in ozone non-attainment areas.</p>

scholarly journals Contributions of a Local Health Examination Survey to the Surveillance of Chronic and Infectious Diseases in New York City

2009 ◽  
Vol 99 (1) ◽  
pp. 152-159 ◽  
Author(s):  
R. Charon Gwynn ◽  
Renu K. Garg ◽  
Bonnie D. Kerker ◽  
Thomas R. Frieden ◽  
Lorna E. Thorpe
Keyword(s):  
New York ◽  
New York City ◽  
Infectious Diseases ◽  
York City ◽  
Health Examination ◽  
Local Health ◽  
Health Examination Survey

Fred Trump, the Ku Klux Klan and Grassroots Redlining in Interwar America

2019 ◽  
Vol 47 (1) ◽  
pp. 3-28
Author(s):  
Oliver Ayers
Keyword(s):  
New York ◽  
New York City ◽  
Ku Klux Klan ◽  
Decision Makers ◽  
Access To Services ◽  
Political Decision ◽  
Historical Significance ◽  
2016 Election ◽  
History Of ◽  
City State

The arrest of Fred Trump during a Ku Klux Klan (KKK) rally in New York City in 1927 came to light during the 2016 election campaign, but no one grasped its full historical significance. This article sets this contentious episode within the larger history of the Klan and the racial contests that scarred life in the interwar metropolitan fringe to produce a new account of how racially segregated communities were formed. The article finds a decade-long contested process of overlapping layers, driven by debates over race and national identity; tense relationships between community groups; the political machinery of city, state and federal governments; competition between civic groups for access to services; and all set against a turbulent speculative world of interwar real estate. The article argues racially redlined communities were created by a decade-long grassroots battle fought from below just as much as they were imposed from above by political decision-makers.

scholarly journals Infectious Diseases Diagnoses of Children Admitted With Symptoms of Coronavirus Disease 2019 During an Outbreak in New York City

2020 ◽  
Vol 59 (14) ◽  
pp. 1293-1295
Author(s):  
Karen P. Acker ◽  
Katherine Schertz ◽  
Erika L. Abramson ◽  
Patricia DeLaMora ◽  
Christine M. Salvatore ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
Infectious Diseases ◽  
York City

scholarly journals Measuring Racial Discrimination in Algorithms

2021 ◽  
Vol 111 ◽  
pp. 49-54
Author(s):  
David Arnold ◽  
Will Dobbie ◽  
Peter Hull
Keyword(s):  
New York ◽  
New York City ◽  
Race And Ethnicity ◽  
Learning Algorithm ◽  
Decision Makers ◽  
Training Data ◽  
Machine Learning Algorithm ◽  
Experimental Variation ◽  
Quasi Experimental ◽  
Black Defendants

Algorithmic decision-making can lead to discrimination against legally protected groups, but measuring such discrimination is often hampered by a fundamental selection challenge. We develop new quasi-experimental tools to overcome this challenge and measure algorithmic discrimination in pretrial bail decisions. We show that the selection challenge reduces to the challenge of measuring four moments, which can be estimated by extrapolating quasi-experimental variation across as-good-as-randomly assigned decision-makers. Estimates from New York City show that both a sophisticated machine learning algorithm and a simpler regression model discriminate against Black defendants even though defendant race and ethnicity are not included in the training data.

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