A snapshot of a pandemic: the interplay between social isolation and COVID-19 dynamics in Brazil

SummaryIn response to the COVID-19 pandemic, most governments around the world implemented some kind of social distancing policy in an attempt to block the spreading of the virus within a territory. In Brazil, this mitigation strategy was first implemented in March 2020 and mainly monitored by social isolation indicators built from mobile geolocation data. While it is well known that social isolation has been playing a crucial role in epidemic control, the precise connections between mobility data indicators and epidemic dynamic parameters have a complex interdependence. In this work, we investigate this dependence for several Brazilian cities, looking also at socioeconomic and demographic factors that influence it. As expected, the increase in the social isolation indicator was shown to be related to the decrease in the speed of transmission of the disease, but the relation was shown to depend on the urban hierarchy level of the city, the human development index and also the epidemic curve stage. Moreover, a high social isolation at the beginning of the epidemic relates to a strong positive impact on flattening the epidemic curve, while less efficacy of this mitigation strategy was observed when it has been implemented later. Mobility data plays an important role in epidemiological modeling and decision-making, however, we discuss in this work how a direct relationship between social isolation data and COVID-19 data is hard to be established. Understanding this interplay is a key factor to better modeling, for which we hope this study contributes.

Download Full-text

Visualizing Emergency Department Admission through Data Mining

International Research Journal of Multidisciplinary Technovation ◽

10.34256/irjmt1923 ◽

2019 ◽

Vol 1 (2) ◽

pp. 19-31

Author(s):

Kalaivani S ◽

Shalini Dhiman ◽

Rajagopal T.K.P.

Keyword(s):

Emergency Department ◽

Logistic Regression ◽

Prediction Models ◽

Personal Data ◽

Mobility Data ◽

Novel Approach ◽

Key Factor ◽

Ed Overcrowding ◽

Historic Data ◽

Short Time

Emergency Department (ED) boarding –the inability to transfer emergency patients to inpatient beds- is a key factor contributing to ED overcrowding. This paper presents a novel approach to improving hospital operational efficiency and, therefore, to decreasing ED boarding. Using the historic data of 15,000 patients, admission results and patient information are correlated in order to identify important admission predictor factors. For example, the type of radiology exams prescribed by the ED physician is identified as among the most important predictors of admission. Based on these factors, a real-time prediction model is developed which is able to correctly predict the admission result of four out of every five ED patients. The proposed admission model can be used by inpatient units to estimate the likelihood of ED patients’ admission, and consequently, the number of incoming patients from ED in the near future. Using similar prediction models, hospitals can evaluate their short-time needs for inpatient care more accurately Emergency Department (ED) boarding – the inability to transfer emergency patients to inpatient beds- is a key factor contributing to ED overcrowding. This paper presents a novel approach to improving hospital operational efficiency and, therefore, to decreasing ED boarding. Using the historic data of 15,000 patients, admission results and patient information are correlated in order to identify important admission predictor factors. For example, the type of radiology exams prescribed by the ED physician is identified as among the most important predictors of admission. The proposed admission model can be used by inpatient units to estimate the likelihood of ED patients’ admission, and consequently, the number of incoming patients from ED in the near future. Using similar prediction models, hospitals can evaluate their short-time needs for inpatient care more accurately. We use three algorithms to build the predictive models: (1) logistic regression, (2) decision trees, and Analytic tools (accuracy=80.31%, AUC-ROC=0.859) than the decision tree accuracy=80.06%, AUC-ROC=0.824) and the logistic regression model (accuracy=79.94%, AUC-ROC=0.849). Drawing on logistic regression, we identify several factors related to hospital admissions including hospital site, age, arrival mode, triage category, care group, previous admission in the past month, and previous admission in the past year. From a different perspective, the research focuses on mobility data instead of personal data in general using Structural Equation Modelling analysis method. Based on this research finding, we identified an unexplored factor that can be used to predict the intention to disclose mobility data, and the result also confirmed that context aspects such as demographics and different personal data categories.

Download Full-text

How Schools affected COVID-19 Pandemic in Italy: Data Analysis for Lombardy Region, Campania Region, and Emilia Region

10.20944/preprints202103.0623.v1 ◽

2021 ◽

Author(s):

Davide Tosi ◽

Alessandro Siro Campi

Keyword(s):

Geographical Area ◽

Clear Correlation ◽

Campania Region ◽

Lombardy Region ◽

Epidemic Curve ◽

Mobility Data ◽

Emilia Romagna Region ◽

Opening And Closing ◽

The Impact ◽

Second Wave

Background: CoronaVirus Disease 2019 (COVID-19) is the main discussed topic world-wide in 2020 and at the beginning of the Italian epidemic, scientists tried to understand the virus diffusion and the epidemic curve of positive cases with controversial findings and numbers. Objectives: In this paper, a data analytics study on the diffusion of COVID-19 in Lombardy Region and Campania Region is developed in order to identify the driver that sparked the second wave in Italy Methods: Starting from all the available official data collected about the diffusion of COVID-19, we analyzed google mobility data, school data and infection data for two big regions in Italy: Lombardy Region and Campania Region, which adopted two different approaches in opening and closing schools. To reinforce our findings, we also extended the analysis to the Emilia Romagna Region. Results: The paper aims at showing how different policies adopted in school opening / closing may have on the impact on the COVID-19 spread. Conclusions: The paper shows that a clear correlation exists between the school contagion and the subsequent temporal overall contagion in a geographical area.

Download Full-text

Impact of Socioeconomic and Demographic Factors Affecting Child Health in Selected South Asian Countries

Review of Economics and Development Studies ◽

10.26710/reads.v1i2.120 ◽

2015 ◽

Vol 1 (2) ◽

pp. 143-151

Author(s):

Sofia Anwar ◽

Maria Khushbakhet ◽

Aisha Asif ◽

Zahira Batool

Keyword(s):

Child Health ◽

South Asian ◽

Family Size ◽

Healthy Child ◽

Positive Impact ◽

Multinomial Logistic Regression ◽

Nutrition Status ◽

Asian Countries ◽

Related Factors ◽

Socioeconomic And Demographic Factors

Development of any nation is estimated through child health condition. In particular, the fourth millennium development goal out of eight is to reduce the mortality rate. The target set under this goal was to reduce by two-third, between 1990 and 2015, the proportion of child mortality. Maternal BMI is closely associated with child nutritional status. Weak mother having low BMI has low nutrition status which effect child weight. Healthy and balance food of mothers have positive effect on their child. Underweight mother can have impaired and poor growing kids. This study presents impact of some socio-economic demographic and maternal health related factors on health status of children in selected South Asian countries i.e. Pakistan, Bangladesh and Nepal. The study used micro data from demographic and health survey (DHS) of Pakistan, Bangladesh and Nepal. Multinomial logistic regression results revealed that mother education, mother working status, mother health, availability of safe drinking water, family size and vaccination have significant effect on child health. Mother's education is positively associated with healthy child. Working mothers are more likely to have healthy child. Weak and obese children are positively associated with malnourished and overweight mothers respectively. Small family size has positive impact on weak child health. Vaccination and availability of improved and safe water are positively associated with child health.

Download Full-text

Impact of Educational Qualification on Social Support, Social Isolation and Social and Emotional Loneliness: A Study of Senior Citizens

Peshawar Journal of Psychology and Behavioral Sciences (PJPBS) ◽

10.32879/picp.2018.4.2.153 ◽

2019 ◽

Vol 4 (2) ◽

pp. 153-170

Author(s):

Salma Naz Gul ◽

Rabia Chishti ◽

Maher Bano

Keyword(s):

Social Support ◽

Social Isolation ◽

Rural Areas ◽

Positive Impact ◽

Senior Citizens ◽

Sampling Technique ◽

Educational Qualification ◽

Social And Emotional ◽

Emotional Loneliness ◽

The Impact

The present study aims to investigate the impact of educational qualification on social support, social isolation, and loneliness (social and emotional) among Senior Citizens. De Jong Gierveld Loneliness Scale (1985),Social Support Scale developed by Malik (2002), and Friendship Scale developed by Hawthorne (2006) were used to measure the pertinent constructs of present study. Purposive convenient sampling technique was used to draw the sample of older adults (N = 500) aged 60 to 90 years (M = 67.59, SD = 7.54) from both urban and rural areas of various districts of Khyber Pakhtunkhwa province of Pakistan. Alpha coefficients, for all the variables were computed, which ranged between .60 for social loneliness to .96 for social support total scale. Study found significant differences among the variables. Findings revealed that educational qualification of the sample had a positive impact on their social support and they were less socially isolated as compared to uneducated senior citizens.

Download Full-text

Qualitative and Quantitative Analyses of COVID-19 Dynamics

Axioms ◽

10.3390/axioms10030210 ◽

2021 ◽

Vol 10 (3) ◽

pp. 210

Author(s):

Taye Samuel Faniran ◽

Leontine Nkague Nkamba ◽

Thomas Timothee Manga

Keyword(s):

High Risk ◽

General Public ◽

Deterministic Model ◽

Negative Impact ◽

Positive Impact ◽

Transmission Rate ◽

Low Risk ◽

Contact Tracing ◽

Epidemic Curve ◽

Underlying Diseases

COVID-19 is a highly contagious disease which has spread across the world. A deterministic model that considers an important component of individuals with vertically transmitted underlying diseases (high-risk susceptible individuals), rather than the general public, is formulated in this paper. We also consider key parameters that are concerned with the disease. An epidemiological threshold, R0, is computed using next-generation matrix approach. This is used to establish the existence and global stability of equilibria. We identify the most sensitive parameters which effectively contribute to change the disease dynamics with the help of sensitivity analysis. Our results reveal that increasing contact tracing of the exposed individuals who are tested for COVID-19 and hospitalizing them, largely has a negative impact on R0. Results further reveal that transmission rate between low-risk/high-risk susceptible individuals and symptomatic infectious individuals β and incubation rate of the exposed individuals σ have positive impact on R0. Numerical simulations show that there are fewer high-risk susceptible individuals than the general public when R0<1. This may be due to the fact that high-risk susceptible individuals may prove a bit more difficult to control than the low-risk susceptible individuals as a result of inherited underlying diseases present in them. We thus conclude that high level of tracing and hospitalizing the exposed individuals, as well as adherence to standard precautions and wearing appropriate Personal Protective Equipment (PPE) while handling emergency cases, are needed to flatten the epidemic curve.

Download Full-text

The UK Covid-19 lockdown weakened in April and May 2020: implications for the size of the epidemic and for outcomes had lockdown been earlier

10.1101/2020.07.04.20146340 ◽

2020 ◽

Author(s):

Anthony D Lander

Keyword(s):

Stochastic Model ◽

Case Fatality Rate ◽

Case Fatality ◽

Fatality Rate ◽

Daily Mortality ◽

Mortality Curve ◽

Epidemic Curve ◽

Mobility Data ◽

The Uk ◽

Low Prevalence

The number of active cases in the UK Covid-19 epidemic, the case fatality rate, the susceptible proportion of the population, and how well the lockdown was maintained during April-May 2020 are unknown. These four have a relationship with the shape of the daily mortality curve once one considers the intervals from infection to death or recovery. Without an understanding of this relationship we cannot say that an earlier lockdown would have saved lives. Using a small stochastic model, the lockdown had to be weakened, in April and May, for simulated deaths to match ongoing actual daily deaths. Google mobility data was found to be consistent with the weakening required in the model with similar changes from baseline in time and magnitude. If in an earlier lockdown, mobility and interactions would have followed a similar course, then with a large epidemic curve an earlier lockdown might be associated with many more deaths than some currently believe. This was confirmed in the stochastic model and in two modified SIR models of epidemics of various sizes. The first SIR model had a fixed period to recovery and the second used random periods, both models had random periods to death. Weakening of the mitigations was required to tune the output in large but not in small epidemics. This gives weight to the epidemic having affected many more individuals than some reports currently suggest. In both one and two-week earlier lockdowns, total deaths were found to depend on the size of the epidemic and to vary from 2,000-49,000 deaths. There was a linear relationship between the peak proportion of the population infected and the reciprocal of the case fatality rate. This work questions the low prevalence of < 0.1%, reported by the Office for National Statistics in May and June 2020, since to accommodate a weakening lockdown, the shape of the daily mortality curve, and an acceptable case fatality rate a much larger epidemic curve is required.

Download Full-text

Japan's Covid mitigation strategy and its epidemic prediction

10.1101/2021.05.06.21256476 ◽

2021 ◽

Author(s):

Yasuharu Tokuda ◽

Toshikazu Kuniya

Keyword(s):

Curve Fitting ◽

Urban Areas ◽

Compartmental Model ◽

Mitigation Strategy ◽

State Of Emergency ◽

Epidemic Curve ◽

Epidemic Prediction ◽

One Year ◽

Reported Data ◽

Original Virus

The COVID-19 epidemic curve in Japan was constructed based on daily reported data from January 14, 2020 until April 20, 2021. A SEIR compartmental model was used for the curve fitting by updating the estimation per wave. In the current vaccination pace of 1/1000, restrictions (state of emergency in Japan) would be repeated 4 times until the end of next March. In the case of 1/500, another round of restriction would be required in the summer 2021, after which the infection would be mitigated. In the case of 1/250, there would be no need for restriction after the current spring restriction. The scenario of completing the vaccination of 110 million people by the end of March 2020 corresponds to the case of 1/250 in this curve. When considering the likely spread of variant with greater infectiousness (here we assume 1.3 times greater than the original virus), 1/500 pace of vaccination would not be enough to contain it and need several series of restrictions. There are currently several variants of concern that are already spreading in urban areas in this country. In the new stage of the replacement of variants, if the vaccination pace could not be quadrupled from the current pace, Japan could not become a zero covid (zero corona) country at least one year.

Download Full-text

Determinants of the result of new rural development program in Vietnam

Journal of Economics and Development ◽

10.1108/jed-12-2019-0076 ◽

2020 ◽

Vol 22 (1) ◽

pp. 81-90

Author(s):

Quang Vu Hoang

Keyword(s):

Positive Impact ◽

Development Program ◽

High Growth ◽

Ordinary Least Squares ◽

Content Type ◽

Stratification Method ◽

Key Factor ◽

Rural Development Program ◽

Capita Income Growth ◽

Practical Implications

PurposeThe purpose of this paper is to identify the determinants of the proportion of communes that met all national new rural criteria (hereafter NRD communes).Design/methodology/approachFirst, the method of propensity score (PS) stratification is used to classify 63 provinces into the subgroups. Second, the ordinary least squares (OLS) model is used with the subgroups classified from the PS stratification method as one of explicative variables. The dependent variable in the OLS model is the proportion of NRD communes.FindingsWith the sample of 63 provinces of Vietnam, the author found that per capita income growth rate, high growth of gross regional domestic product (GRDP) and effort of the provincial authority have positive impact on the proportion of NRD communes.Practical implicationsThis research suggests that the provincial authority should actively participate in the NRD program, and the economic development is key factor for success implementation of the NRD program.Originality/valueThis research contributes to understand the factors impacting the result of the NRD program and then help to identify the measures to support this program.

Download Full-text

Turning home boredom during the outbreak of COVID-19 into thriving at home and career self-management: the role of online leisure crafting

International Journal of Contemporary Hospitality Management ◽

10.1108/ijchm-06-2020-0580 ◽

2020 ◽

Vol 32 (11) ◽

pp. 3645-3663

Author(s):

I-Shuo Chen

Keyword(s):

Social Isolation ◽

Positive Impact ◽

Leisure Activities ◽

Mainland China ◽

Self Management ◽

Content Type ◽

Hospitality Managers ◽

The Impact ◽

At Home

Purpose This paper studied whether boredom at home due to social isolation during the COVID-19 pandemic may motivate individuals to engage in online leisure crafting, thereby contributing to their thriving at home and career self-management. This paper aims to examine whether individuals’ growth need strength influences the impact of home boredom on online leisure crafting. Design/methodology/approach This paper performed a two-wave longitudinal study involving a group of employees from the hospitality industry (N = 340) in Mainland China. This paper evaluated home boredom, online leisure crafting and growth need strength at Time 1 and thriving at home and career self-management two months later at Time 2. Findings The respondents’ experience of home boredom had a time-lagged effect on their thriving at home and career self-management via online leisure crafting. Additionally, their growth need strength amplified the positive impact of home boredom on online leisure crafting. Practical implications Hospitality managers can motivate employees to engage in crafting online leisure activities at home when they experience home boredom during the outbreak of COVID-19, which may further allow them to experience thriving at home and engage in career self-management. Additionally, managers can develop managerial interventions to improve the growth need strength of employees with low growth needs, which may, in turn, render these employees less likely to tolerate home boredom, thereby increasing the positive impact of home boredom on their online leisure crafting. Originality/value This paper offer insights for the boredom literature regarding how individuals’ home boredom caused by social isolation during the COVID-19 pandemic might lead to their thriving at home through online leisure crafting. This paper also provides insights for the leisure crafting literature regarding the role of online leisure crafting in individuals’ thriving at home. This paper reveals the role of growth need strength in the impact of home boredom on thriving at home through online leisure crafting.

Download Full-text

The impact of industrial clusters on human resource and firms performance

Journal of Modelling in Management ◽

10.1108/jm2-11-2012-0038 ◽

2014 ◽

Vol 9 (2) ◽

pp. 141-159 ◽

Cited By ~ 6

Author(s):

Maw-Shin Hsu ◽

Yung-Lung Lai ◽

Feng-Jhy Lin

Keyword(s):

Human Resources ◽

Positive Impact ◽

Industrial Cluster ◽

Industrial Clusters ◽

Global Market ◽

Content Type ◽

Key Factor ◽

The Face ◽

Processing Zone ◽

The Impact

Purpose – The purpose of this study was to explore the impact of the formation of industrial clusters on the obtainment of professional human resources, to verify the impact of human resources on clustering relationships and firm’s performance and to understand whether the formation of clusters can contribute to the obtainment of professional human resources and the improvement of competitiveness of enterprises. It was expected that solutions could be found to make new contributions through the verification of special economic zones (SEZs). Design/methodology/approach – Using manufacturers in Taiwan’s SEZs as the subjects, this study explored the impact on the obtainment of professional human resources after the formation of industrial clusters in SEZs, through conducting and empirical study with a questionnaire survey. Findings – The professional human resources are the essential factor for the formation of industrial clusters and the improvement of competitiveness. This study also confirmed that industries can have professional human resources by industrial clustering and that this will produce a positive impact on the enterprise clustering relationships, which can also have a positive impact on firm’s performance and can enhance the enterprise’s competitive advantage. Practical implications – Industrial clustering is the key factor to attract professional human resources; industrial clusters can enhance firm’s performance; and professional human resources affect firm’s performance of enterprises. Originality/value – No study has discussed the topic of clusters from the perspective of SEZs also including six export processing zone (EPZ) parks in Taiwan. This study discussed the topic using theories relating to clustering and human resources. The formation of industrial clusters can result in higher competitiveness in the face of the global market. The EPZ industrial cluster provides an excellent investment environment. Coupled with one-stop express services and geographic advantage, the land-use rate is up to 97 per cent and the per hectare output value amounts to NTD 3.2 billion, setting a successful example of an industrial cluster.

Download Full-text