scholarly journals Use Crow-AMSAA Method to predict the cases of the Coronavirus 19 in Michigan and U.S.A

2020 ◽  
Author(s):  
Yanshuo Wang
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Complex Problem ◽  
Mitigation Strategies ◽  
Homogeneous Poisson Process ◽  
Ca Model ◽  
The Government ◽  
Reported Data ◽  
Non Homogeneous Poisson Process

AbstractThe Crow-AMSAA method is used in engineering reliability world to predict the failures and evaluate the reliability growth. The author intents to use this model in the prediction of the Coronavirus 19 (COVID19) cases by using the daily reported data from Michigan, New York City, U.S.A and other countries. The piece wise Crow-AMSAA (CA) model fits the data very well for the infected cases and deaths at different phases while the COVID19 outbreak starting. The slope β of the Crow-AMSAA line indicates the speed of the transmission or death rate. The traditional epidemiological model is based on the exponential distribution, but the Crow-AMSAA is the Non Homogeneous Poisson Process (NHPP) which can be used to modeling the complex problem like COVID19, especially when the various mitigation strategies such as social distance, isolation and locking down were implemented by the government at different places.SummaryThis paper is to use piece wise Crow-AMSAA method to fit the COVID19 confirmed cases in Michigan, New York City, U.S.A and other countries.

scholarly journals Predict new cases of the Coronavirus 19; in Michigan, U.S.A. or other countries using Crow-AMSAA Method (Preprint)

2020 ◽  
Author(s):  
Yanshuo Wang
Keyword(s):  
New York ◽  
New York City ◽  
Social Distance ◽  
York City ◽  
Death Rate ◽  
Transmission Rate ◽  
Complex Problem ◽  
Mitigation Strategies ◽  
Summary Table ◽  
The Government

BACKGROUND Statistical predictions are useful to predict events based on statistical models. The data is useful to determine outcomes based on inputs and calculations. The Crow-AMSAA method will be explored to predict new cases of Coronavirus 19 (COVID19). This method is currently used within engineering reliability design to predict failures and evaluate the reliability growth. The author intents to use this model to predict the COVID19 cases by using daily reported data from Michigan, New York City, U.S.A and other countries. The piece wise Crow-AMSAA (CA) model fits the data very well for the infected cases and deaths at different phases during the start of the COVID19 outbreak. The slope β of the Crow-AMSAA line indicates the speed of the transmission or death rate. The traditional epidemiological model is based on the exponential distribution, but the Crow-AMSAA is the Non Homogeneous Poisson Process (NHPP) which can be used to modeling the complex problem like COVID19, especially when the various mitigation strategies such as social distance, isolation and locking down were implemented by the government at different places. OBJECTIVE This paper is to use piece wise Crow-AMSAA method to fit the COVID19 confirmed cases in Michigan, New York City, U.S.A and other countries. METHODS piece wise Crow-AMSAA method to fit the COVID19 confirmed cases RESULTS From the Crow-AMSAA analysis above, at the beginning of the COVID 19, the infectious cases did not follow the Crow-AMSAA prediction line, but during the outbreak start, the confirmed cases does follow the CA line, the slope β value indicates the pace of the transmission rate or death rate in each case. The piece wise Crow-AMSAA describes the different phases of spreading. This indicates the speed of the transmission rate could change according to the government interference, social distance order or other factors. Comparing the piece wise CA β slopes (β: 1.683-- 0.834--0.092) in China and in U.S.A (β:5.138--10.48--5.259), the speed of infectious rate in U.S.A is much higher than the infectious rate in China. From the piece wise CA plots and summary table 1 of the CA slope βs, the COVID19 spreading has the different behavior at different places and countries where the government implemented the different policy to slow down the spreading. CONCLUSIONS From the analysis of data and conclusions from confirmed cases and deaths of COVID 19 in Michigan, New York city, U.S.A, China and other countries, the piece wise Crow-AMSAA method can be used to modeling the spreading of COVID19.

scholarly journals A Modification to the NOAH LSM to Simulate Heat Mitigation Strategies in the New York City Metropolitan Area

2009 ◽  
Vol 48 (2) ◽  
pp. 199-216 ◽  
Author(s):  
Barry H. Lynn ◽  
Toby N. Carlson ◽  
Cynthia Rosenzweig ◽  
Richard Goldberg ◽  
Leonard Druyan ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
Thermal Stress ◽  
York City ◽  
Atmospheric Model ◽  
Mitigation Strategies ◽  
Local Exchange ◽  
Street Level ◽  
Air Temperatures ◽  
Roughness Lengths

Abstract A new approach to simulating the urban environment with a mesocale model has been developed to identify efficient strategies for mitigating increases in surface air temperatures associated with the urban heat island (UHI). A key step in this process is to define a “global” roughness for the cityscape and to use this roughness to diagnose 10-m temperature, moisture, and winds within an atmospheric model. This information is used to calculate local exchange coefficients for different city surface types (each with their own “local roughness” lengths); each surface’s energy balances, including surface air temperatures, humidity, and wind, are then readily obtained. The model was run for several summer days in 2001 for the New York City five-county area. The most effective strategy to reduce the surface radiometric and 2-m surface air temperatures was to increase the albedo of the city (impervious) surfaces. However, this caused increased thermal stress at street level, especially noontime thermal stress. As an alternative, the planting of trees reduced the UHI’s adverse effects of high temperatures and also reduced noontime thermal stress on city residents (and would also have reduced cooling energy requirements of small structures). Taking these results together, the analysis suggests that the best mitigation strategy is planting trees at street level and increasing the reflectivity of roofs.

scholarly journals EXPLORING DRIVING FACTORS OF HIGHER PAID TAXI TRIPS USING ORIGIN–DESTINATION GPS DATA (CASE STUDY: GREEN TAXIS OF NEW YORK CITY)

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 745-748
Author(s):  
P. Mojtabaee ◽  
M. Molavi ◽  
M. Taleai
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Driving Forces ◽  
Influential Factors ◽  
Driving Factors ◽  
Population Number ◽  
Factors Affecting ◽  
Explanatory Variables ◽  
The Government

Abstract. Investigating the influential factors of the areas where people use taxis is a crucial step in understanding the taxi demand dynamics. In this study, we intend to analyze higher-paying taxi trips by putting forward an approach to explore a dataset of green taxi trips in New York City in January 2015 together with some demographic, housing, social and economic data. The final goal is to find out whether the chosen factors are statistically significant to be considered as potential driving forces of demand location for trips with a higher-paid fare. Since airports are major attracting sources for taxi travels, all the steps are taken separately for three scenarios that the trip drop-offs are in 1) LaGuardia Airport, 2) John F Kennedy Airport or 3) other areas. First, the spatial pick-up distribution of these higher-paying trips is mapped to enable visual comparison of the urban movement patterns. Then, taking into account the pick-up density as the response variable, the densities of: foreign-born’s population, number of houses with no vehicles, the private wage and salary workers’ population, the government workers’ population and the self-employed workers’ population in own not incorporate business were considered as the explanatory variables. These variables were examined to find important factors affecting the demand in each neighborhood and different results in each of the three scenarios were discussed. This study gives a better insight into discovering driving factors of higher-paid taxi trips when considering airports as destinations which attract travels with potentially different characteristics.

Excess Deaths in Mexico City and New York City During the COVID-19 Pandemic, March to August 2020

2021 ◽  
pp. e1-e4
Author(s):  
Martín Lajous ◽  
Rodrigo Huerta-Gutiérrez ◽  
Joseph Kennedy ◽  
Donald R. Olson ◽  
Daniel M. Weinberger
Keyword(s):  
Public Health ◽  
New York ◽  
New York City ◽  
Mexico City ◽  
York City ◽  
Excess Mortality ◽  
Negative Binomial ◽  
Age Groups ◽  
Mitigation Strategies ◽  
Excess Deaths

Objectives. To estimate all-cause excess deaths in Mexico City (MXC) and New York City (NYC) during the COVID-19 pandemic. Methods. We estimated expected deaths among residents of both cities between March 1 and August 29, 2020, using log-linked negative binomial regression and compared these deaths with observed deaths during the same period. We calculated total and age-specific excess deaths and 95% prediction intervals (PIs). Results. There were 259 excess deaths per 100 000 (95% PI = 249, 269) in MXC and 311 (95% PI = 305, 318) in NYC during the study period. The number of excess deaths among individuals 25 to 44 years old was much higher in MXC (77 per 100 000; 95% PI = 69, 80) than in NYC (34 per 100 000; 95% PI = 30, 38). Corresponding estimates among adults 65 years or older were 1263 (95% PI = 1199, 1317) per 100 000 in MXC and 1581 (95% PI = 1549, 1621) per 100 000 in NYC. Conclusions. Overall, excess mortality was higher in NYC than in MXC; however, the excess mortality rate among young adults was higher in MXC. Public Health Implications. Excess all-cause mortality comparisons across populations and age groups may represent a more complete measure of pandemic effects and provide information on mitigation strategies and susceptibility factors. (Am J Public Health. Published online ahead of print September 9, 2021: e1–e4. https://doi.org/10.2105/AJPH.2021.306430 )

scholarly journals Can the Government Deter Discrimination? Evidence from a Randomized Intervention in New York City

2019 ◽  
Vol 81 (1) ◽  
pp. 127-141 ◽  
Author(s):  
Albert H. Fang ◽  
Andrew M. Guess ◽  
Macartan Humphreys
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Randomized Intervention ◽  
The Government

scholarly journals Retrospective Analyses of Interventions to Epidemics using a Continuously Updated Model, with Application to the COVID-19 Crisis in New York City

2020 ◽  
Author(s):  
Jenna Osborn ◽  
Shayna Berman ◽  
Sara Bender-Bier ◽  
Gavin D’Souza ◽  
Matthew Myers
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Cost Benefit ◽  
Filtration Efficiency ◽  
Mitigation Strategies ◽  
Infection Dynamics ◽  
Spread Function ◽  
Turn Around Time ◽  
The Cost

AbstractRetrospective analyses of interventions to epidemics, in which the effectiveness of strategies implemented are compared to hypothetical alternatives, are valuable for performing the cost-benefit calculations necessary to optimize infection countermeasures. SIR (susceptible-infected-removed) models are useful in this regard but are limited by the challenge of deciding how and when to update the numerous parameters as the epidemic progresses. We present a method that uses a “dynamic spread function” to systematically capture the continuous variation in the population behavior throughout an epidemic. There is no need to update parameters as the effects of interventions are gradually manifested in the infection dynamics. We use the tool to quantify the reduction in infection rate realizable from the population of New York City adopting different facemask strategies during COVID-19. Assuming a baseline facemask of 67% filtration efficiency, calculations show that increasing the efficiency to 75% could reduced the roughly 5000 new infections per day occurring at the peak of the epidemic by about 40%. The turn-around time for the epidemic decreases from around 37 days to 31 days. Mitigation strategies that may not be varied as part of the retrospective analysis, such as social distancing, are automatically captured as part of the calibration of the dynamic spread function.

Guyanese remittance motivations: altruistic?

2014 ◽  
Vol 41 (3) ◽  
pp. 201-212 ◽  
Author(s):  
Tilokie Depoo
Keyword(s):  
New York ◽  
Economic Development ◽  
New York City ◽  
York City ◽  
Positive Impact ◽  
Altruistic Motive ◽  
Content Type ◽  
The Usa ◽  
The Government ◽  
Remittance Behavior

Purpose – This paper aims to examine the remittance behavior of Guyanese immigrants living in three communities of New York City, USA to assess their remittance behavior and if these are motivated by altruism or the intent to return to live in Guyana. Over the last two decades, remittances accounted for approximately 17 percent of the GDP of the Guyanese economy and continue to grow. The bulk of these remittances are significant from its native sons and daughters residing in the USA. Design/methodology/approach – This case study uses non-experimental survey research design with survey data collected from 300 participants living in New York, with 236 selected for analysis. Findings – Guyanese living in New York City remit monies to Guyana because of a pure altruistic motive as well as believing that their contributions have a positive impact on the economic development of their nations regardless of their intention to return to Guyana. These findings support the altruistic model on remittance motivation. Research limitations/implications – The data gathered for this survey are restricted to three communities in the USA where Guyanese are significant in numbers, thus limiting generalizations and findings to other countries such as Canada, England, where there are significant enclaves of Guyanese immigrants. Practical implications – New York-based Guyanese deem their remittances as contributing to the economic development of their country. This suggest that there may room for a coordinated policy on the part of the Government of Guyana to develop a coordinated plan to engage overseas-based Guyanese to remit more to help with Guyana economic development efforts. Originality/value – This is the first study to survey Guyanese in their host countries to gather information on remittances motivation and the perceived impact of these remittances from the sender's perspective. The paper highlights the significant remittance contributions of US-based Guyanese and their net private flows to Guyana.

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