scholarly journals Should internal migrants be held accountable for spreading COVID-19?

2020 ◽  
Vol 52 (4) ◽  
pp. 695-697 ◽  
Author(s):  
Qiujie Shi ◽  
Tao Liu
Keyword(s):  
Internal Migration ◽  
Chinese Spring ◽  
Large Scale ◽  
Hubei Province ◽  
Major Contributor ◽  
Job Seekers ◽  
Business People ◽  
Spring Festival ◽  
Internal Migrants ◽  
Novel Coronavirus

The 2019 novel coronavirus disease (COVID-19) has quickly swept through China, and mass internal migration during the Chinese Spring Festival is now widely blamed for this. This statement, we argue, is misleading. Internal migrants should not be held responsible for the initial spread of COVID-19, as those cities first affected are megacities that connect with the epicentre Wuhan more with regard to business and tourism than migration. The scale of the epidemic can only be partially explained by internal migration. Severe outbreaks are not limited to cities that neighbour Hubei Province and that have large migration to Wuhan. They also occurred in provincial capitals that are neither contiguous with Hubei nor connected with Wuhan in terms of migration. Even though a few cities far away from the epicentre were hit severely by COVID-19 due to migration, the major contributor is not the migrant job seekers but business people. The responsibility of spreading COVD-19 so fast, on such a large scale and so far is by no means fully on internal migrants.

SAGA OF MIGRANT WORKERS IN INDIA: MEASURES TO STRENGTHEN SOCIAL SECURITY

2020 ◽  
pp. 183-195
Author(s):  
Deepa Pillai ◽  
Leena Dam
Keyword(s):  
Social Security ◽  
Internal Migration ◽  
Migrant Workers ◽  
Large Scale ◽  
State Level ◽  
Policy Formulation ◽  
Economic Activities ◽  
Government Interventions ◽  
Internal Migrants ◽  
Security Standards

COVID 19 pandemic has thrown up bitter colors when India witnessed the large scale gory sage of reverse internal migration of unorganized workforce. As compared to intercontinental migration the degree of internal migration is twice. Displacement, lockdowns, loss of employment, starvation and social distancing provoked a frenzied course of mass return for internal migrants in India and other parts of the world. In India there is a peculiar trend of unorganized workforce migration. Out of 29 states and 7 union territories, few states dominate where migrants flock for seeking livelihood. The fleeing of migrants to their inherent origin has weakened the economic activities towards slowdown in the economic growth. This thematic review paper discusses the problems of the internal migrants and their state during and post lockdown announcements in India. The data included extracts of articles, opinions and reviews for which codes were recognized which lead to formulation of research themes. The review also highlights government interventions in addressing the challenges confronted by the internal migrants with social security. This study proposes an arrangement as migrant exchange at state level for efficient policy formulation and accomplishment of social security standards.

scholarly journals Spatiotemporal Exploration of Chinese Spring Festival Population Flow Patterns and Their Determinants Based on Spatial Interaction Model

2020 ◽  
Vol 9 (11) ◽  
pp. 670
Author(s):  
Tao Zhou ◽  
Bo Huang ◽  
Xiaoqian Liu ◽  
Guangqin He ◽  
Qiang Gou ◽  
...  
Keyword(s):  
Urban Development ◽  
Chinese Spring ◽  
Large Scale ◽  
Spatial Interaction ◽  
Value Added ◽  
Flow Patterns ◽  
City Development ◽  
Migration Patterns ◽  
Horizontal Structure ◽  
Spring Festival

Large-scale population flow reshapes the economic landscape and is affected by unbalanced urban development. The exploration of migration patterns and their determinants is therefore crucial to reveal unbalanced urban development. However, low-resolution migration datasets and insufficient consideration of interactive differences have limited such exploration. Accordingly, based on 2019 Chinese Spring Festival travel-related big data from the AMAP platform, we used social network analysis (SNA) methods to accurately reveal population flow patterns. Then, with consideration of the spatial heterogeneity of interactive patterns, we used spatially weighted interactive models (SWIMs), which were improved by the incorporation of weightings into the global Poisson gravity model, to efficiently quantify the effect of socioeconomic factors on migration patterns. These SWIMs generated the local characteristics of the interactions and quantified results that were more regionally consistent than those generated by other spatial interaction models. The migration patterns had a spatially vertical structure, with the city development level being highly consistent with the flow intensity; for example, the first-level developments of Beijing, Shanghai, Chengdu, Guangzhou, Shenzhen, and Chongqing occupied a core position. A spatially horizontal structure was also formed, comprising 16 closely related city communities. Moreover, the quantified impact results indicated that migration pattern variation was significantly related to the population, value-added primary and secondary industry, the average wage, foreign capital, pension insurance, and certain aspects of unbalanced urban development. These findings can help policymakers to guide population migration, rationally allocate industrial infrastructure, and balance urban development.

scholarly journals The impact of traffic isolation in Wuhan on the spread of 2019-nCov

2020 ◽  
Author(s):  
Gehui Jin ◽  
Jiayu Yu ◽  
Liyuan Han ◽  
Shiwei Duan
Keyword(s):  
Mortality Rate ◽  
Chinese Spring ◽  
Mainland China ◽  
Hubei Province ◽  
Migrant Population ◽  
Migration Index ◽  
Spring Festival ◽  
The Impact

The 2019-nCoV outbreak occurred near the Chinese Spring Festival transport period in Wuhan. As an important transportation center, the migration of Wuhan accelerated the spread of 2019-nCoV across mainland China. Based on the cumulative Baidu migration index (CBMI), we first analyzed the proportion of Wuhan’s migrant population to other cities. Our results confirm that there is a significant correlation between the export population of Wuhan and reported cases in various regions. We subsequently found that the mortality rate in Hubei Province was much higher than that in other regions of mainland China, while the investigation of potential cases in Wuhan was far behind other provinces in Mainland China, which indicates the effectiveness of early isolation.

scholarly journals Prediction of Epidemic Spread of the 2019 Novel Coronavirus Driven by Spring Festival Transportation in China: A Population-Based Study

2020 ◽  
Vol 17 (5) ◽  
pp. 1679 ◽  
Author(s):  
Changyu Fan ◽  
Linping Liu ◽  
Wei Guo ◽  
Anuo Yang ◽  
Chenchen Ye ◽  
...  
Keyword(s):  
Nuclear Family ◽  
Population Based ◽  
Hubei Province ◽  
Social Characteristics ◽  
Doing Business ◽  
Spring Festival ◽  
Quasi Experimental ◽  
Highly Correlated ◽  
Novel Coronavirus ◽  
And Control

After the 2019 novel coronavirus (2019-nCoV) outbreak, we estimated the distribution and scale of more than 5 million migrants residing in Wuhan after they returned to their hometown communities in Hubei Province or other provinces at the end of 2019 by using the data from the 2013–2018 China Migrants Dynamic Survey (CMDS). We found that the distribution of Wuhan’s migrants is centred in Hubei Province (approximately 75%) at a provincial level, gradually decreasing in the surrounding provinces in layers, with obvious spatial characteristics of circle layers and echelons. The scale of Wuhan’s migrants, whose origins in Hubei Province give rise to a gradient reduction from east to west within the province, and account for 66% of Wuhan’s total migrants, are from the surrounding prefectural-level cities of Wuhan. The distribution comprises 94 districts and counties in Hubei Province, and the cumulative percentage of the top 30 districts and counties exceeds 80%. Wuhan’s migrants have a large proportion of middle-aged and high-risk individuals. Their social characteristics include nuclear family migration (84%), migration with families of 3–4 members (71%), a rural household registration (85%), and working or doing business (84%) as the main reason for migration. Using a quasi-experimental analysis framework, we found that the size of Wuhan’s migrants was highly correlated with the daily number of confirmed cases. Furthermore, we compared the epidemic situation in different regions and found that the number of confirmed cases in some provinces and cities in Hubei Province may be underestimated, while the epidemic situation in some regions has increased rapidly. The results are conducive to monitoring the epidemic prevention and control in various regions.

scholarly journals Estimation of local novel coronavirus (COVID-19) cases in Wuhan, China from off-site reported cases and population flow data from different sources

2020 ◽  
Author(s):  
Zian Zhuang ◽  
Peihua Cao ◽  
Shi Zhao ◽  
Yijun Lou ◽  
Shu Yang ◽  
...  
Keyword(s):  
Likelihood Estimation ◽  
Hubei Province ◽  
Flow Data ◽  
Daily Newspaper ◽  
Wuhan City ◽  
Spring Festival ◽  
Log Likelihood ◽  
Novel Coronavirus ◽  
Different Sources

AbstractBackgroundsIn December 2019, a novel coronavirus (COVID-19) pneumonia hit Wuhan, Hubei Province, China and spread to the rest of China and overseas. The emergence of this virus coincided with the Spring Festival Travel Rush in China. It is possible to estimate total number of cases of COVID-19 in Wuhan, by 23 January 2020, given the cases reported in other cities and population flow data between cities.MethodsWe built a model to estimate the total number of cases in Wuhan by 23 January 2020, based on the number of cases detected outside Wuhan city in China, with the assumption that if the same screening effort used in other cities applied in Wuhan. We employed population flow data from different sources between Wuhan and other cities/regions by 23 January 2020. The number of total cases was determined by the maximum log likelihood estimation.FindingsFrom overall cities/regions data, we predicted 1326 (95% CI: 1177, 1484), 1151 (95% CI: 1018, 1292) and 5277 (95% CI: 4732, 5859) as total cases in Wuhan by 23 January 2020, based on different source of data from Changjiang Daily newspaper, Tencent, and Baidu. From separate cities/regions data, we estimated 1059 (95% CI: 918, 1209), 5214 (95% CI: 4659, 5808) as total cases in Wuhan in Wuhan by 23 January 2020, based on different sources of population flow data from Tencent and Baidu.ConclusionSources of population follow data and methods impact the estimates of local cases in Wuhan before city lock down.

scholarly journals Human Mobility Restrictions and the Spread of the Novel Coronavirus (2019-nCoV) in China

2020 ◽  
Author(s):  
Hanming Fang ◽  
Long Wang ◽  
Yang Yang
Keyword(s):  
Human Mobility ◽  
Hubei Province ◽  
The Novel ◽  
Chinese Cities ◽  
Social Distancing ◽  
Spring Festival ◽  
The Social ◽  
Novel Coronavirus ◽  
The Impact ◽  
The City

AbstractWe quantify the causal impact of human mobility restrictions, particularly the lockdown of the city of Wuhan on January 23, 2020, on the containment and delay of the spread of the Novel Coronavirus (2019-nCoV). We employ a set of difference-in-differences (DID) estimations to disentangle the lockdown effect on human mobility reductions from other confounding effects including panic effect, virus effect, and the Spring Festival effect. We find that the lockdown of Wuhan reduced inflow into Wuhan by 76.64%, outflows from Wuhan by 56.35%, and within-Wuhan movements by 54.15%. We also estimate the dynamic effects of up to 22 lagged population inflows from Wuhan and other Hubei cities, the epicenter of the 2019-nCoV outbreak, on the destination cities’ new infection cases. We find, using simulations with these estimates, that the lockdown of the city of Wuhan on January 23, 2020 contributed significantly to reducing the total infection cases outside of Wuhan, even with the social distancing measures later imposed by other cities. We find that the COVID-19 cases would be 64.81% higher in the 347 Chinese cities outside Hubei province, and 52.64% higher in the 16 non-Wuhan cities inside Hubei, in the counterfactual world in which the city of Wuhan were not locked down from January 23, 2020. We also find that there were substantial undocumented infection cases in the early days of the 2019-nCoV outbreak in Wuhan and other cities of Hubei province, but over time, the gap between the officially reported cases and our estimated “actual” cases narrows significantly. We also find evidence that enhanced social distancing policies in the 63 Chinese cities outside Hubei province are effective in reducing the impact of population inflows from the epi-center cities in Hubei province on the spread of 2019-nCoV virus in the destination cities elsewhere.JEL CodesI18, I10.

Current updates on COVID-19 - A review

2020 ◽  
Vol 10 (1) ◽  
pp. 1-8
Author(s):  
Ghotekar D S ◽  
Vishal N Kushare ◽  
Sagar V Ghotekar
Keyword(s):  
World Health Organization ◽  
Common Cold ◽  
Respiratory Diseases ◽  
Gastrointestinal Diseases ◽  
Hubei Province ◽  
World Health ◽  
The World ◽  
The Common ◽  
Novel Coronavirus ◽  
Health Organization

Coronaviruses are a family of viruses that cause illness such as respiratory diseases or gastrointestinal diseases. Respiratory diseases can range from the common cold to more severe diseases. A novel coronavirus outbreak was first documented in Wuhan, Hubei Province, China in December 2019. The World Health Organization (WHO) has declared the coronavirus disease 2019 (COVID-19) a pandemic. A global coordinated effort is needed to stop the further spread of the virus. A novel coronavirus (nCoV) is a new strain that has not been identified in humans previously. Once scientists determine exactly what coronavirus it is, they give it a name (as in the case of COVID-19, the virus causing it is SARS-CoV-2).

The Risk of Death in 2019 Novel Coronavirus Disease (COVID-19) in Hubei Province

2020 ◽  
Author(s):  
Vincent Yi Fong Su ◽  
Yao-Hsu Yang ◽  
Kuang-Yao Yang ◽  
Kun-Ta Chou ◽  
Wei-Juin Su ◽  
...  
Keyword(s):  
Hubei Province ◽  
Risk Of Death ◽  
Novel Coronavirus

scholarly journals Multi-Objective Optimization of Integrated Civilian-Military Scheduling of Medical Supplies for Epidemic Prevention and Control

Healthcare ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 126
Author(s):  
Hai-Feng Ling ◽  
Zheng-Lian Su ◽  
Xun-Lin Jiang ◽  
Yu-Jun Zheng
Keyword(s):  
Prevention And Control ◽  
Large Scale ◽  
Medical Services ◽  
The Novel ◽  
Multi Objective ◽  
Medical Supplies ◽  
Problem Instances ◽  
Novel Coronavirus ◽  
And Control ◽  
Minimum Ratio

In a large-scale epidemic, such as the novel coronavirus pneumonia (COVID-19), there is huge demand for a variety of medical supplies, such as medical masks, ventilators, and sickbeds. Resources from civilian medical services are often not sufficient for fully satisfying all of these demands. Resources from military medical services, which are normally reserved for military use, can be an effective supplement to these demands. In this paper, we formulate a problem of integrated civilian-military scheduling of medical supplies for epidemic prevention and control, the aim of which is to simultaneously maximize the overall satisfaction rate of the medical supplies and minimize the total scheduling cost, while keeping a minimum ratio of medical supplies reservation for military use. We propose a multi-objective water wave optimization (WWO) algorithm in order to efficiently solve this problem. Computational results on a set of problem instances constructed based on real COVID-19 data demonstrate the effectiveness of the proposed method.

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