scholarly journals Estimating, monitoring, and forecasting COVID-19 epidemics: a spatiotemporal approach applied to NYC data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Vinicius V. L. Albani ◽  
Roberto M. Velho ◽  
Jorge P. Zubelli
Keyword(s):  
New York ◽  
New York City ◽  
Census Data ◽  
Age Group ◽  
Age Classes ◽  
Basic Model ◽  
Monitoring And Forecasting ◽  
Group Sex ◽  
Age Range ◽  
Spatial Locations

AbstractWe propose a susceptible-exposed-infective-recovered-type (SEIR-type) meta-population model to simulate and monitor the (COVID-19) epidemic evolution. The basic model consists of seven categories, namely, susceptible (S), exposed (E), three infective classes, recovered (R), and deceased (D). We define these categories for n age and sex groups in m different spatial locations. Therefore, the resulting model contains all epidemiological classes for each age group, sex, and location. The mixing between them is accomplished by means of time-dependent infection rate matrices. The model is calibrated with the curve of daily new infections in New York City and its boroughs, including census data, and the proportions of infections, hospitalizations, and deaths for each age range. We finally obtain a model that matches the reported curves and predicts accurate infection information for different locations and age classes.

Phobias and Nervous Symptoms in Childhood and Maturity: Persistence and Associations

1972 ◽  
Vol 120 (556) ◽  
pp. 275-283 ◽  
Author(s):  
K. Abe
Keyword(s):  
New York ◽  
New York City ◽  
Life Time ◽  
Lower Class ◽  
Upper Class ◽  
Age Group ◽  
Falling Asleep ◽  
High Prevalence ◽  
Age Range ◽  
Apparently Healthy

Most people suffer from so-called ‘nervous symptoms' sometime during life, and their activity is influenced in varying degrees by these symptoms. There are a number of works reporting high prevalence of so-called neurotic symptoms: Rennie and his collaborators studied a sample of the population in the age range 20–59 of the central residential area of New York City and found that 75 per cent manifested significant symptoms of anxiety and that only 11 per cent of the lower class and 29 per cent of the upper class were psychiatrically symptom-free respondents (Rennie, Srole, Opler and Langner, 1957). Leighton found the life-time prevalence (after the age of 18) of psychoneurotic symptoms in a small town (population about 3,000) to be 67 per cent (Leighton, 1956). Winter interviewed 200 apparently healthy workers (mean age 36·6 years, 141 males and 59 females) of various social strata of Berlin, and found only 18 per cent free from so-called neurotic symptoms, i.e. anxiety, phobia, insomnia, headache and other psychosomatic symptoms (Winter, 1959). Agras, Sylvester and Oliveau found the prevalence of fear of storms, enclosures and journeying alone in females of Burlington to be 31 per cent, 14 per cent and 10 per cent respectively, and noted that psychiatrists saw only a small percentage of the phobic population (Agras, Sylvester and Oliveau, 1969). In all of these surveys, the authors noted that the majority of those with symptoms appeared to function well in the society. In Japan, a comparable survey is lacking, but Kasahara and Sakamoto investigated by questionnaire 2,481 students who entered Kyoto University in 1967 and found 24·1 per cent suffering from headache and 18 · 5 per cent from difficulty in falling asleep (Kasahara and Sakamoto, 1970). On 30 August 1970, N.H.K. (Japanese Broadcasting Corporation) invited to the studio 100 males who had graduated in 1945 from a single metropolitan all-male middle school for a programme entided ‘Age Forty’, in which health, economical and social status of this age group was enquired into. Among these, 26 ‘often suffered from palpitation and shortness of breath without significant exertion’, and 34 often awoke in the middle of the night or too early in the morning and could not get back to sleep again.

scholarly journals Transmission Dynamics of and Insights from the 2018-2019 Measles Outbreak in New York City: A Modeling Study

2019 ◽  
Author(s):  
Wan Yang
Keyword(s):  
Public Health ◽  
New York ◽  
New York City ◽  
Young Children ◽  
York City ◽  
Vaccine Dose ◽  
Transmission Dynamics ◽  
Age Group ◽  
Measles Outbreak ◽  
The Us

AbstractIn 2018-2019, New York City experienced the largest measles outbreak in the US in nearly three decades. To identify key factors contributing to this outbreak to aid future public health interventions, here we developed a model-inference system to infer the transmission dynamics of measles in the affected community, based on incidence data. Our results indicate that delayed vaccination of young children aged 1-4 years enabled the initial spread of measles and that increased infectious contact among this age group, likely via gatherings intended to expose unvaccinated children (i.e. “measles parties”), further aggravated the outbreak and led to widespread of measles beyond this age group. We found that around half of infants were susceptible to measles by age 1 (the age-limit to receive the first vaccine dose in the US); as such, infants experienced a large number of infections during the outbreak. We showed that without the implemented vaccination campaigns, the outbreak severity including numbers of infections and hospitalizations would be 10 times higher and predominantly affect infants and children under 4. These results suggest that recommending the first vaccine dose before age 1 and the second dose before age 4 could allow pro-vaccine parents to vaccinate and protect infants and young children more effectively, should high level of vaccine hesitancy persist. In addition, enhanced public health education is needed to reduce activities that unnecessarily expose children to measles and other infections.

scholarly journals Modeling between-population variation in COVID-19 dynamics in Hubei, Lombardy, and New York City

2020 ◽  
Vol 117 (41) ◽  
pp. 25904-25910 ◽  
Author(s):  
Bryan Wilder ◽  
Marie Charpignon ◽  
Jackson A. Killian ◽  
Han-Ching Ou ◽  
Aditya Mate ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Age Groups ◽  
Population Variation ◽  
Age Group ◽  
Unknown Parameters ◽  
Individual Level ◽  
Policy Interventions

As the COVID-19 pandemic continues, formulating targeted policy interventions that are informed by differential severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission dynamics will be of vital importance to national and regional governments. We develop an individual-level model for SARS-CoV-2 transmission that accounts for location-dependent distributions of age, household structure, and comorbidities. We use these distributions together with age-stratified contact matrices to instantiate specific models for Hubei, China; Lombardy, Italy; and New York City, United States. Using data on reported deaths to obtain a posterior distribution over unknown parameters, we infer differences in the progression of the epidemic in the three locations. We also examine the role of transmission due to particular age groups on total infections and deaths. The effect of limiting contacts by a particular age group varies by location, indicating that strategies to reduce transmission should be tailored based on population-specific demography and social structure. These findings highlight the role of between-population variation in formulating policy interventions. Across the three populations, though, we find that targeted “salutary sheltering” by 50% of a single age group may substantially curtail transmission when combined with the adoption of physical distancing measures by the rest of the population.

scholarly journals How to Reduce the Transmission Risk of COVID-19 More Effectively in New York City: An Age-Structured Model Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Miaolei Li ◽  
Jian Zu ◽  
Zongfang Li ◽  
Mingwang Shen ◽  
Yan Li ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Age Groups ◽  
Transmission Risk ◽  
Age Group ◽  
Infected People ◽  
Age Structured ◽  
The Impact ◽  
Second Wave

Background: In face of the continuing worldwide COVID-19 epidemic, how to reduce the transmission risk of COVID-19 more effectively is still a major public health challenge that needs to be addressed urgently.Objective: This study aimed to develop an age-structured compartment model to evaluate the impact of all diagnosed and all hospitalized on the epidemic trend of COVID-19, and explore innovative and effective releasing strategies for different age groups to prevent the second wave of COVID-19.Methods: Based on three types of COVID-19 data in New York City (NYC), we calibrated the model and estimated the unknown parameters using the Markov Chain Monte Carlo (MCMC) method.Results: Compared with the current practice in NYC, we estimated that if all infected people were diagnosed from March 26, April 5 to April 15, 2020, respectively, then the number of new infections on April 22 was reduced by 98.02, 93.88, and 74.08%. If all confirmed cases were hospitalized from March 26, April 5, and April 15, 2020, respectively, then as of June 7, 2020, the total number of deaths in NYC was reduced by 67.24, 63.43, and 51.79%. When only the 0–17 age group in NYC was released from June 8, if the contact rate in this age group remained below 61% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC. When both the 0–17 and 18–44 age groups in NYC were released from June 8, if the contact rates in these two age groups maintained below 36% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC.Conclusions: If all infected people were diagnosed in time, the daily number of new infections could be significantly reduced in NYC. If all confirmed cases were hospitalized in time, the total number of deaths could be significantly reduced in NYC. Keeping a social distance and relaxing lockdown restrictions for people between the ages of 0 and 44 could not lead to a second wave of COVID-19 in NYC.

Living With Inequality: Neighborhood Income Diversity and Perceptions of the Income Gap

2017 ◽  
Vol 47 (2) ◽  
pp. 329-361 ◽  
Author(s):  
Scott L. Minkoff ◽  
Jeffrey Lyons
Keyword(s):  
New York ◽  
New York City ◽  
Income Inequality ◽  
York City ◽  
Census Data ◽  
Income Gap ◽  
Neighborhood Income ◽  
The Rich ◽  
Neighborhood Boundaries ◽  
Lower Educational Attainment

This article explores whether the places where people live—and specifically the diversity of incomes where people live—influence views about income inequality. Using a unique survey of New York City that contains geographic identifiers and questions about attitudes toward inequality, coupled with a rich array of Census data, we assess the degree to which the income diversity within spatially customized neighborhood boundaries influences beliefs about inequality. We find consistent evidence that attitudes about inequality are influenced by the places where people live—those who are exposed to more income diversity near their homes perceive larger gaps between the rich and everybody else, and are more likely to believe that the gap should be smaller. Moreover, this effect appears to be especially pronounced among those with lower educational attainment and at either end of the income spectrum.

scholarly journals Pacing in age group marathoners in the “New York City Marathon”

2017 ◽  
Vol 26 (1) ◽  
pp. 86-99 ◽  
Author(s):  
Pantelis T. Nikolaidis ◽  
Beat Knechtle
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Age Group

West Indians in New York City and London: A Comparative Analysis

1979 ◽  
Vol 13 (2) ◽  
pp. 284-297 ◽  
Author(s):  
Nancy Foner
Keyword(s):  
United States ◽  
New York ◽  
New York City ◽  
Race Relations ◽  
Census Data ◽  
Black Americans ◽  
The United States ◽  
West Indians ◽  
History Of ◽  
Occupational Background

Census data indicate that West Indians in the United States are occupationally more successful than West Indians in Britain. Three factors may help to explain this situation: the history of West Indian migration to Britain and the United States; the occupational background of the migrants; and the structure of race relations in the two receiving areas. Comparing West Indians’ occupational achievements in the United States and Britain may also help to explain why West Indians in New York are more successful than black Americans.

scholarly journals Socioeconomic Disparities in SARS-CoV-2 Serological Testing and Positivity in New York City

2021 ◽  
Author(s):  
Wil Lieberman-Cribbin ◽  
Marta Galanti ◽  
Jeffrey Shaman
Keyword(s):  
New York ◽  
Socioeconomic Status ◽  
New York City ◽  
York City ◽  
Census Data ◽  
Antibody Test ◽  
Credible Interval ◽  
Data Repository ◽  
Antibody Testing ◽  
Socioeconomic Vulnerability

Abstract Background We characterized SARS-CoV-2 antibody test prevalence and positive test prevalence across New York City (NYC) in order to investigate disparities in testing outcomes by race and socioeconomic status (SES). Methods Serologic data were downloaded from the NYC Coronavirus data repository (August 2020–December 2020). Area-level characteristics for NYC neighborhoods were downloaded from U.S. census data and a socioeconomic vulnerability index was created. Spatial generalized linear mixed models were performed to examine the association between SES and antibody testing and positivity. Results The proportion of Hispanic population (Posterior Median: 0.001, 95% Credible Interval: 0.0003-0.002), healthcare workers (0.003, 0.0001-0.006), essential workers (0.003, 0.001-0.005), age ≥ 65 years (0.003, 0.00002-0.006), and high SES (SES quartile 3 vs 1: 0.034, 0.003-0.062) were positively associated with antibody tests per 100,000 residents. The White proportion (-0.002, -0.003- -0.001), SES index (quartile 3 vs 1: -0.068, -0.115- -0.017; quartile 4 vs 1: -0.077- -0.134, -0.018) and age ≥ 65 years (-0.005, -0.009- -0.002) were inversely associated with positivity, whereas the Hispanic (0.004, 0.002-0.006), and essential worker proportions (0.008, 0.003-0.012) had positive coefficients. Conclusions Disparities in serologic testing and seropositivity exist on socioeconomic status and race/ethnicity across NYC, indicative of excess COVID-19 burden in vulnerable and marginalized populations.

scholarly journals Monitoring child mental health related emergency department visits in New York City

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Don Olson ◽  
Willem Van der Mei ◽  
Sungwoo Lim ◽  
Carol Yoon ◽  
Melissa Kull ◽  
...  
Keyword(s):  
Mental Health ◽  
Emergency Department ◽  
New York ◽  
New York City ◽  
York City ◽  
Syndromic Surveillance ◽  
Surveillance Data ◽  
Age Group ◽  
Health Related ◽  
Ed Visits

ObjectiveTo assess the use of syndromic surveillance to assess trends inmental health-related emergency department (ED) visits amongschool-aged children and adolescents in New York City (NYC).IntroductionFrom 2001-2011, mental health-related hospitalizations and EDvisits increased among United States children nationwide [1]. Duringthis period, mental health-related hospitalizations among NYCchildren increased nearly 23% [2]. To estimate mental health-relatedED visits in NYC and assess the use of syndromic surveillance chiefcomplaint data to monitor these visits, we compared trends from anear real-time syndromic system with those from a less timely, codedED visit database.MethodsThe NYC ED syndromic surveillance system receives anonymizedpatient chief complaint and basic demographic data for nearly everyED visit citywide to provide timely surveillance information tohealth authorities. Using NYC ED syndromic surveillance datafrom 2003-2015, we applied previously developed definitions forgeneral psychiatric syndromes. We aggregated ED visits by agegroup (5-12 years, 13-17 years, and 18-20 years), geography, andtemporality. Syndromic data were compared with Statewide Planningand Research Collaborative System (SPARCS) data from 2006-2014which reported mental health diagnosis (ICD-9), treatment, service,and basic demographics for patients visiting facilities in NYC. Usingthese two data sources, we compared daily visit patterns and annualtrends overall as well as stratified by age group, area-based poverty(ZIP code), and time of visit.ResultsBoth syndromic surveillance and SPARCS data for NYC showedan increasing trend during the period. While both showed relativeincreases with similar slopes, mental health-related chief complaintdata captured fewer overall visits than the ICD-9 coded SPARCSdata. Trends in syndromic data during 2003-2015 differed by age-group and area-based poverty, e.g., among children ages 5-12 yearsthe annual proportion of mental health-related ED visits increasedroughly 3-fold from 1.2% to 3.8% in the poorest areas, which wasgreater than the increase in the richest areas (1.7% to 2.6%). Seasonal,day-of-week, and school holiday patterns found far fewer visits duringthe periods of NYC public school breaks (Figure).ConclusionsWe conclude that syndromic surveillance data can provide areliable indicator of mental health-related ED visit trends. Thesefindings suggest potential benefit of syndromic surveillance data asthey may help capture temporal and spatial clustering of events in amuch more timely manner than the >1 year delay in availability ofED discharge data. Next steps include a qualitative study exploringthe causes of these patterns and the role of various factors drivingthem, as well as use of patient disposition and matched data to bettercharacterize ED visit patient outcomes.

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