scholarly journals Human mobility restrictions and the spread of the Novel Coronavirus (2019-nCoV) in China

2020 ◽  
Vol 191 ◽  
pp. 104272 ◽  
Author(s):  
Hanming Fang ◽  
Long Wang ◽  
Yang Yang
Keyword(s):  
Human Mobility ◽  
The Novel ◽  
Novel Coronavirus

FEAR OF PANDEMICS OR FEAR OF TOURISM: THE CHALLENGES FOR HUMAN MOBILITY

2021 ◽  
Vol 27 (1) ◽  
Author(s):  
Asif Hussain ◽  
Francesc Fusté-Forné ◽  
David Simmons
Keyword(s):  
Human Mobility ◽  
Early Research ◽  
World Health ◽  
Transport Sector ◽  
The Novel ◽  
The Past ◽  
Starting Point ◽  
Tourism And Hospitality ◽  
Novel Coronavirus ◽  
Health Organization

The spread of the novel coronavirus, 'SARS-Cov-2', causing the disease 'COVID-19' has resulted in almost one hundred million cases and two million deaths (World Health Organization 2020). While early research suggested that the virus was not as contagious as SARS and MERS, the rapid increase in human to human transmission showed that the virus was in fact more contagious (Chan et al. 2020; Huang et al. 2020; Wang et al. 2020). On January 23, China announced lockdown in Wuhan to limit people’s movement both within and outside Wuhan (Surveillances 2020). This was the starting point to travel and transport restrictions, which were progressively implemented worldwide, following the virus’ expansion (Hamzelou 2020). In the past few months, research has commenced as part of academics’ rapid response to analyse the impacts and anticipate the consequences of the pandemics for tourism and hospitality (see, for example, Gössling, Scott, and Hall 2020). This paper adds texture to this conversation and critically discusses pandemics’ implications for the hospitality and tourism industries concerning the transport sector.

scholarly journals Early spread of COVID-19 in Romania: imported cases from Italy and human-to-human transmission networks

2020 ◽  
Vol 7 (7) ◽  
pp. 200780 ◽  
Author(s):  
Marian-Gabriel Hâncean ◽  
Matjaž Perc ◽  
Jürgen Lerner
Keyword(s):  
Human Mobility ◽  
Structural Features ◽  
The Novel ◽  
Prevention Measures ◽  
Transmission Networks ◽  
Time Dynamics ◽  
Source Of Infection ◽  
Imported Cases ◽  
Geographical Dispersion ◽  
Novel Coronavirus

We describe the early spread of the novel coronavirus (COVID-19) and the first human-to-human transmission networks, in Romania. We profiled the first 147 cases referring to sex, age, place of residence, probable country of infection, return day to Romania, COVID-19 confirmation date and the probable modes of COVID-19 transmissions. Also, we analysed human-to-human transmission networks and explored their structural features and time dynamics. In Romania, local cycles of transmission were preceded by imported cases, predominantly from Italy. We observed an average of 4.8 days (s.d. = 4.0) between the arrival to a Romanian county and COVID-19 confirmation. Furthermore, among the first 147 COVID-19 patients, 88 were imported cases (64 carriers from Italy), 54 were domestic cases, while for five cases the source of infection was unknown. The early human-to-human transmission networks illustrated a limited geographical dispersion, the presence of super-spreaders and the risk of COVID-19 nosocomial infections. COVID-19 occurred in Romania through case importation from Italy. The largest share of the Romanian diaspora is concentrated especially in the northern parts of Italy, heavily affected by COVID-19. Human mobility (including migration) accounts for the COVID-19 transmission and it should be given consideration while tailoring prevention measures.

scholarly journals Incorporating Human Movement Data to Improve Epidemiological Estimates for 2019-nCoV

2020 ◽  
Author(s):  
Zhidong Cao ◽  
Qingpeng Zhang ◽  
Xin Lu ◽  
Dirk Pfeiffer ◽  
Lei Wang ◽  
...  
Keyword(s):  
Latent Infection ◽  
Human Mobility ◽  
Mainland China ◽  
Human Movement ◽  
Hubei Province ◽  
The Novel ◽  
Movement Data ◽  
Control And Prevention ◽  
Novel Coronavirus ◽  
Reporting Data

AbstractEstimating the key epidemiological features of the novel coronavirus (2019-nCoV) epidemic proves to be challenging, given incompleteness and delays in early data reporting, in particular, the severe under-reporting bias in the epicenter, Wuhan, Hubei Province, China. As a result, the current literature reports widely varying estimates. We developed an alternative geo-stratified debiasing estimation framework by incorporating human mobility with case reporting data in three stratified zones, i.e., Wuhan, Hubei Province excluding Wuhan, and mainland China excluding Hubei. We estimated the latent infection ratio to be around 0.12% (18,556 people) and the basic reproduction number to be 3.24 in Wuhan before the city’s lockdown on January 23, 2020. The findings based on this debiasing framework have important implications to prioritization of control and prevention efforts.One Sentence SummaryA geo-stratified debiasing approach incorporating human movement data was developed to improve modeling of the 2019-nCoV epidemic.

scholarly journals Does the COVID-19 Pandemic Change Human Mobility Equally Worldwide? Cross-Country Cluster Analysis

Economies ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 182
Author(s):  
Katarzyna Czech ◽  
Anna Davy ◽  
Michał Wielechowski
Keyword(s):  
Human Development Index ◽  
Human Mobility ◽  
Pairwise Comparison ◽  
The Novel ◽  
Mobility Patterns ◽  
Daily Data ◽  
Macroeconomic Factor ◽  
Cross Country ◽  
Stringency Level ◽  
Novel Coronavirus

The paper aims to identify groups of countries characterised by a similar human mobility reaction to COVID-19 and investigate whether the differences between distinguished clusters result from the stringency of government anti-COVID-19 policy or are linked to another macroeconomic factor. We study how COVID-19 affects human mobility patterns, employing daily data of 124 countries. The analysis is conducted for the first and second waves of the novel coronavirus pandemic separately. We group the countries into four clusters in terms of stringency level of government anti-COVID-19 policy and six mobility categories, using k-means clustering. Moreover, by applying the Kruskal–Wallis test and Wilcoxon rank-sum pairwise comparison test, we assess the existence of significant differences between the distinguished clusters. We confirm that the pandemic has caused significant human mobility changes. The study shows that a more stringent anti-COVID-19 policy is related to the greater decline in mobility. Moreover, we reveal that COVID-19-driven mobility changes are also triggered by other factors not related to the pandemic. We find the Human Development Index (HDI) and its components as driving factors of the magnitude of mobility changes during COVID-19. The greater human mobility reaction to COVID-19 refers to the country groups representing higher HDI levels.

scholarly journals Impact of city and residential unit lockdowns on prevention and control of COVID-19

2020 ◽  
Author(s):  
Peng Shao
Keyword(s):  
Human Mobility ◽  
Mortality Rates ◽  
The Novel ◽  
Transmission Characteristics ◽  
Appropriate Treatment ◽  
Residential Units ◽  
Novel Coronavirus ◽  
And Control ◽  
Reduced Mobility ◽  
The Impact

AbstractWith respect to the asymptomatic transmission characteristics of the novel coronavirus that appeared in 2019 (COVID-19), a susceptible-asymptomatic-infected-recovered-death (SAIRD) model that considered human mobility was constructed in this study. The dissemination of COVID-19 was simulated using computational experiments to identify the mechanisms underlying the impact of city and residential lockdowns on controlling the spread of the epidemic. Results: The implementation of measures to lock down cities led to higher mortality rates in these cities, due to reduced mobility. Moreover, implementing city lockdown along with addition of hospital beds led to improved cure and reduced mortality rates. Stringent implementation and early lockdown of residential units effectively controlled the spread of the epidemic, and reduced the number of hospital bed requirements. Collectively, measures to lock down cities and residential units should be taken to prevent the spread of COVID-19. In addition, medical resources should be increased in cities under lockdown. Implementation of these measures would reduce the spread of the virus to other cities and allow appropriate treatment of patients in cities under lockdown.

scholarly journals Monitoring the COVID-19 epidemic with nationwide telecommunication data

2021 ◽  
Vol 118 (26) ◽  
pp. e2100664118
Author(s):  
Joel Persson ◽  
Jurriaan F. Parie ◽  
Stefan Feuerriegel
Keyword(s):  
Large Scale ◽  
Human Mobility ◽  
Human Movement ◽  
Spatiotemporal Analysis ◽  
Decision Makers ◽  
The Novel ◽  
School Closures ◽  
Time Period ◽  
Policy Measures ◽  
Novel Coronavirus

In response to the novel coronavirus disease (COVID-19), governments have introduced severe policy measures with substantial effects on human behavior. Here, we perform a large-scale, spatiotemporal analysis of human mobility during the COVID-19 epidemic. We derive human mobility from anonymized, aggregated telecommunication data in a nationwide setting (Switzerland; 10 February to 26 April 2020), consisting of ∼1.5 billion trips. In comparison to the same time period from 2019, human movement in Switzerland dropped by 49.1%. The strongest reduction is linked to bans on gatherings of more than five people, which are estimated to have decreased mobility by 24.9%, followed by venue closures (stores, restaurants, and bars) and school closures. As such, human mobility at a given day predicts reported cases 7 to 13 d ahead. A 1% reduction in human mobility predicts a 0.88 to 1.11% reduction in daily reported COVID-19 cases. When managing epidemics, monitoring human mobility via telecommunication data can support public decision makers in two ways. First, it helps in assessing policy impact; second, it provides a scalable tool for near real-time epidemic surveillance, thereby enabling evidence-based policies.

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