scholarly journals Modeling risk of infectious diseases: a case of Coronavirus outbreak in four countries

2020 ◽  
Author(s):  
Md. Mazharul Islam ◽  
Md. Monirul Islam ◽  
Md. Jamal Hossain ◽  
Faroque Ahmed
Keyword(s):  
Infectious Disease ◽  
New York ◽  
Risk Index ◽  
New York State ◽  
The Novel ◽  
Identification Rate ◽  
Case Identification ◽  
Calculated Risk ◽  
Using Data ◽  
Novel Coronavirus

AbstractBackgroundThe novel coronavirus (2019-nCOV) outbreak has been a serious concern around the globe. Since people are in tremor due to the massive spread of Coronavirus in the major parts of the world, it requires to predict the risk of this infectious disease. In this situation, we develop a model to measure the risk of infectious disease and predict the risk of 2019-nCOV transmission by using data of four countries—US, Australia, Canada and China.MethodsThe model underlies that higher the population density, higher the risk of transmission of infectious disease from human to human. Besides, population size, case identification rate and travel of infected passengers in different regions are also incorporated in this model.ResultsAccording to the calculated risk index, our study identifies New York State in United States (US) to be the most vulnerable area affected by the novel Coronavirus. Besides, other areas (province/state/territory) such as Hubei (China, 2nd), Massachusetts (US, 3rd), District of Columbia (US, 4th), New Jersey (US, 5th), Quebec (Canada, 20th), Australian Capital Territory (Australia, 29th) are also found as the most risky areas in US, China, Australia and Canada.ConclusionThe study suggests avoiding any kind of mass gathering, maintaining recommended physical distances and restricting inbound and outbound flights of highly risk prone areas for tackling 2019-nCOV transmission.

scholarly journals Age-dependence of mortality from novel coronavirus disease (COVID-19) in highly exposed populations: New York transit workers and residents and Diamond Princess passengers.

2020 ◽  
Author(s):  
Christopher T Leffler ◽  
Matthew C Hogan
Keyword(s):  
New York ◽  
New York City ◽  
New York State ◽  
Age Groups ◽  
The Novel ◽  
Cruise Ship ◽  
Age Dependence ◽  
York State ◽  
Novel Coronavirus ◽  
Available Information

Background. Populations heavily exposed to the novel coronavirus provide an opportunity to estimate the mortality from COVID-19 in different age groups. Methods. The mortality reported by May 13 from COVID-19 among Diamond Princess cruise ship passengers, and New York residents and Metropolitan Transit Authority (MTA) workers was estimated based on publicly available information. Results. The mortality among children (age 0 to 17 yrs) in New York City was 1 in 172,692. The mortality in New York state was 1 in 322,217 for ages 10-19 yrs., and 1 in 36,725 for ages 20-29 yrs. The mortality among New York transit workers was estimated to be 1 in 7,329 for ages 30-39 years; 1 in 1,075 for ages 40-49 yrs.; 1 in 343 for ages 50-59 yrs.; and 1 in 178 for ages 60-69 yrs. Among Diamond Princess passengers, the mortality was estimated to be 1 in 145 for ages 70-79, and 1 in 54 for ages 80-89. Conclusions: Mortality among populations exposed to the novel coronavirus increases with age, ranging from about 1 in 170,000 below the age of 18 years, to 1 in 54 above the age of 80 years.

scholarly journals Racial/Ethnic Residential Segregation and the First Wave of SARS-CoV-2 Infection Rates: A Spatial Analysis of Four U.S. Cities

2021 ◽  
pp. 073112142110419
Author(s):  
Kathryn Freeman Anderson ◽  
Angelica Lopez ◽  
Dylan Simburger
Keyword(s):  
Infectious Disease ◽  
New York ◽  
Infection Rate ◽  
Residential Segregation ◽  
The Novel ◽  
Infection Rates ◽  
Structural Mechanism ◽  
Ethnic Residential Segregation ◽  
Novel Coronavirus ◽  
Racial Ethnic

Previous research has linked racial/ethnic residential segregation to a number of poor health conditions, including infectious disease. Here, we examine how racial/ethnic residential segregation is related to the novel coronavirus, SARS-CoV-2. We examine infection rates by zip code level segregation in four major cities across the U.S.: New York City, Chicago, Houston, and San Diego. We also include a number of area-level Census variables in order to analyze how other factors may help account for the infection rate. We find that both Black and Latino residential clustering are significantly and positively related to a higher SARS-CoV-2 infection rate across all four cities, and that this effect is strong even when accounting for a number of other social conditions and factors that are salient to the transmission of infectious disease. As a result, we argue that neighborhood-level racial/ethnic patterning may serve as an important structural mechanism for disparities in SARS-CoV-2 infection.

scholarly journals Digital Tracing during the COVID-19 Pandemic: User Appraisal, Emotion, and Continuance Intention

2021 ◽  
Vol 13 (2) ◽  
pp. 608
Author(s):  
Ayoung Suh ◽  
Mengjun Li
Keyword(s):  
Mobile Apps ◽  
Contact Tracing ◽  
The Novel ◽  
Personal Privacy ◽  
Continuance Intention ◽  
Infectious Disease Outbreak ◽  
Using Data ◽  
Novel Coronavirus ◽  
Technological Affordances ◽  
Method Approach

This study explores how people appraise the use of contact tracing apps during the novel coronavirus (COVID-19) pandemic in South Korea. Despite increasing attention paid to digital tracing for health disasters, few studies have empirically examined user appraisal, emotion, and their continuance intention to use contact tracing apps for disaster management during an infectious disease outbreak. A mixed-method approach combining qualitative and quantitative inquiries was employed. In the qualitative study, by conducting interviews with 25 people who have used mobile apps for contact tracing, the way users appraise contact tracing apps for COVID-19 was explored. In the quantitative study, using data collected from 506 users of the apps, the interplay among cognitive appraisal (threats and opportunities) and its association with user emotion, and continuance intention was examined. The findings indicate that once users experience loss emotions, such as anger, frustration, and disgust, they are not willing to continue using the apps. App designers should consider providing technological affordances that enable users to have a sense of control over the technology so that they do not experience loss emotions. Public policymakers should also consider developing measures that can balance public health and personal privacy.

Sick on the Frontlines:A Cross Sectional Study on COVID-19 Infection, Symptom Severity Amongst Emergency Medicine Residents and Fellows in Urban Academic Hospital Settings (Preprint)

2021 ◽  
Author(s):  
Stacey Frisch ◽  
Sarah Jones ◽  
James Willis ◽  
Richard Sinert
Keyword(s):  
New York ◽  
Emergency Medicine ◽  
Cross Sectional Study ◽  
The Novel ◽  
Academic Hospital ◽  
Cross Sectional ◽  
Time Period ◽  
High Infection ◽  
Novel Coronavirus ◽  
Specific Symptoms

BACKGROUND COVID-19, an illness caused by the novel coronavirus SARS-CoV-2, affected many aspects of healthcare worldwide in 2020. From March to May of 2020, New York City (NYC) experienced a large surge of cases. OBJECTIVE The authors aimed to characterize the amount of illness experienced by residents and fellows in 2 NYC hospitals during this time period. METHODS This was a cross-sectional observational study. An IRB-exempt survey was distributed to emergency medicine housestaff in May 2020 and submissions were accepted through August 2020. RESULTS 64 residents and fellows responded to our survey (a 62% response rate). 42% of responders tested positive for SARS-CoV-2 antibodies. Most residents experienced symptoms that could be consistent with COVID-19 however few received PCR testing. Fevers and/or chills along with loss of smell and/or taste were the most specific symptoms for COVID-19, with p-values <0.05. All 13 housestaff who reported no symptoms during the study period tested negative for SARS-CoV-2 antibodies. CONCLUSIONS Our study demonstrated that the rate of COVID-19 illness among emergency department housestaff is much higher than previously reported. Further studies are needed to characterize illness among medical staff in emergency departments across the nation. The high infection rate among emergency medicine trainees stresses the importance of supplying adequate PPE for healthcare professionals.

scholarly journals Investigation of the genetic variation in ACE2 on the structural recognition by the novel coronavirus (SARS-CoV-2)

2020 ◽  
Author(s):  
Xingyi Guo ◽  
Zhishan Chen ◽  
Yumin Xia ◽  
Weiqiang Lin ◽  
Hongzhi Li
Keyword(s):  
Genetic Variation ◽  
The Novel ◽  
S Protein ◽  
Angiotensin Converting Enzyme 2 ◽  
Missense Variants ◽  
Catalytic Metal ◽  
Using Data ◽  
Novel Coronavirus ◽  
Insight Into

Abstract Background: The outbreak of coronavirus disease (COVID-19) was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), through its surface spike glycoprotein (S-protein) recognition on the receptor Angiotensin-converting enzyme 2 (ACE2) in humans. However, it remains unclear how genetic variations in ACE2 may affect its function and structure, and consequently alter the recognition by SARS-CoV-2. Methods: We have systemically characterized missense variants in the gene ACE2 using data from the Genome Aggregation Database (gnomAD; N = 141,456). To investigate the putative deleterious role of missense variants, six existing functional prediction tools were applied to evaluate their impact. We further analyzed the structural flexibility of ACE2 and its protein-protein interface with the S-protein of SARS-CoV-2 using our developed Legion Interfaces Analysis (LiAn) program.Results: Here, we characterized a total of 12 ACE2 putative deleterious missense variants. Of those 12 variants, we further showed that p.His378Arg could directly weaken the binding of catalytic metal atom to decrease ACE2 activity and p.Ser19Pro could distort the most important helix to the S-protein. Another seven missense variants may affect secondary structures (i.e. p.Gly211Arg; p.Asp206Gly; p.Arg219Cys; p.Arg219His, p.Lys341Arg, p.Ile468Val, and p.Ser547Cys), whereas p.Ile468Val with AF = 0.01 is only present in Asian.Conclusions: We provide strong evidence of putative deleterious missense variants in ACE2 that are present in specific populations, which could disrupt the function and structure of ACE2. These findings provide novel insight into the genetic variation in ACE2 which may affect the SARS-CoV-2 recognition and infection, and COVID-19 susceptibility and treatment.

scholarly journals Heterogeneous Impact of Geographic Barriers on Provider Choice Evidence from New York County’s Health Market

2018 ◽  
Vol 33 (3) ◽  
pp. 23-45
Author(s):  
Lee Jae Bok ◽  
Roh Chul-young ◽  
Woolley Jonathan A
Keyword(s):  
New York ◽  
Low Socioeconomic Status ◽  
Health Informatics ◽  
Choice Model ◽  
New York State ◽  
Low Socioeconomic ◽  
Geographic Barriers ◽  
Health Market ◽  
York County ◽  
Using Data

Health services should be accessible regardless of citizens’ gender, age, race, or insurance type, and geographic barriers should not interfere with this access. This article aims to assess the heterogeneous impacts of geographic barriers on inpatients’ hospital choices and to examine whether they vary according inpatients’ socioeconomic or insurance status. Using data on providers and inpatients obtained from the New York State Bureau of Health Informatics Office of Quality and Patient Safety for New York County (New York City’s borough of Manhattan) for 2009, we employed a discrete choice model. Our findings reveal that geographic barriers limit inpatients’ choices of hospitals more when they are of low socioeconomic status.

scholarly journals Forecasting COVID-19 cases in Algeria using logistic growth and polynomial regression models

2021 ◽  
Author(s):  
Mohamed LOUNIS ◽  
Babu Malavika
Keyword(s):  
Regression Model ◽  
Logistic Model ◽  
Polynomial Regression ◽  
Logistic Growth ◽  
The Novel ◽  
Logistic Growth Model ◽  
Polynomial Regression Models ◽  
Using Data ◽  
Novel Coronavirus ◽  
Polynomial Regression Model

Abstract The novel Coronavirus respiratory disease 2019 (COVID-19) is still expanding through the world since it started in Wuhan (China) on December 2019 reporting a number of more than 84.4 millions cases and 1.8 millions deaths on January 3rd 2021.In this work and to forecast the COVID-19 cases in Algeria, we used two models: the logistic growth model and the polynomial regression model using data of COVID-19 cases reported by the Algerian ministry of health from February 25th to December 2nd, 2020. Results showed that the polynomial regression model fitted better the data of COVID-19 in Algeria the Logistic model. The first model estimated the number of cases on January, 19th 2021 at 387673 cases. This model could help the Algerian authorities in the fighting against this disease.

scholarly journals Vertical Transmission

2020 ◽  
Vol 41 (1) ◽  
pp. 2
Author(s):  
Dena Lyras
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Vertical Transmission ◽  
Racial Groups ◽  
The Novel ◽  
Local Part ◽  
Rapid Dissemination ◽  
Novel Coronavirus ◽  
The Impact

As we begin 2020, Microbiology is dominating the news with the emergence and rapid dissemination of the novel coronavirus COVID-19. The impact of COVID-19 on public health, with significant financial, logistical and social repercussions, has quickly become apparent. As microbiologists we have an important role to play during this time because we can use our knowledge, expertise and experience to educate the community around us, and to reduce the panic that results from fear and misinformation. It is also critical that we ensure that racial groups are not stigmatised because of an infectious disease. A co-ordinated global effort is required to tackle this new infectious threat, and we are an important local part of this effort. It is also important to develop strategies that can be deployed when the next threat emerges, as it surely will.

Seeing Blue: A Police-Centered Explanation of Protest Policing

2006 ◽  
Vol 11 (2) ◽  
pp. 145-164 ◽  
Author(s):  
Jennifer Earl ◽  
Sarah Soule
Keyword(s):  
New York ◽  
New York State ◽  
State Repression ◽  
Law Enforcement Agencies ◽  
Local Law Enforcement ◽  
Protest Policing ◽  
Public Protest ◽  
Police Presence ◽  
Using Data

Existing explanations of repression and the policing of protest focus on the interests of political elites, with research indicating that a chief predictor of state repression is the level of threat protesters pose to elite interests. However, prior research has only paid sporadic attention to how the institutional and organizational characteristics of local law enforcement agencies shape the character of protest policing. This article addresses this significant theoretical gap by developing a police-centered, or "blue," approach to protest policing. Using data on the policing of public protest events in New York State between 1968 and 1973, this article finds support for the blue approach. Specifically, the situational threats posed by protesters to those agents who actually perform repression-local police-are critical predictors of police presence and action. Results also show some residual support for the role of elite threats in structuring repression.

scholarly journals Situation analysis of novel Coronavirus (2019-nCoV) cases in Nepal

2020 ◽  
Vol 1 (1) ◽  
pp. 9-14
Author(s):  
Kiran Paudel ◽  
Prashamsa Bhandari ◽  
Yadav Prasad Joshi
Keyword(s):  
South Asian ◽  
Case Fatality ◽  
Cumulative Number ◽  
The Novel ◽  
Asian Countries ◽  
Primary Case ◽  
The Status ◽  
Exponential Trend ◽  
Using Data ◽  
Novel Coronavirus

The Novel Coronavirus (2019-nCoV) is currently a major threat to global health in an unprecedented manner. The global pandemic of COVID-19 has affected 215 countries and territories including Nepal. Until 1st June 2020, altogether 1,811 COVID-19 positive cases were diagnosed using RT-PCR. This study aimed to analyze the status of COVID-19 cases in Nepal and South Asian countries. A retrospective study from 23rd January to 1st June 2020 was conducted using data of the Ministry of Home Affairs, Nepal and Worldometer homepages. The primary case records during the pre and post lockdown periods were examined. Spatial distribution was observed. An exponential trend line was plotted and COVID-19 situation in South Asian countries was assessed. Of 1,811 COVID-19 cases, the highest number (38.3%) was reported in Province 2. Out of 77 districts, 59 were affected. In Fifty-eight districts, primary cases appeared during the lockdown period. The cumulative number of COVID-19 cases showed the exponential pattern of distribution in Nepal. In South Asian countries, India had the highest number of cases and case fatality rate (CFR). There were no cases of CFR in Bhutan. The Novel Coronavirus emergence in Nepal has become a serious challenge to the various sectors including public health. The emergence of primary cases even in the lockdown period needs a detailed study in the future.

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