scholarly journals Reductions of Migrant Population Reduces the Number of COVID-19 Epidemic: A Case Study in China

2020 ◽  
Author(s):  
Lizhen Han ◽  
Jinzhu Jia
Keyword(s):  
Population Density ◽  
Generalized Additive Model ◽  
Hot Spot ◽  
Additive Model ◽  
Hubei Province ◽  
Control Measures ◽  
Cumulative Number ◽  
Migrant Population ◽  
High Prevalence ◽  
The Impact

Abstract Background: The novel coronavirus disease (COVID-19) broke out worldwide in 2020. The purpose of this paper was to find out the impact of migrant population on the epidemic, aiming to provide data support and suggestions for control measures in various epidemic areas. Methods: Generalized additive model was utilized to model the relationship between migrant population and the cumulative number of confirmed cases of COVID-19. The difference of spatial distribution was analyzed through spatial autocorrelation and hot spot analysis. Results: Generalized additive model demonstrated that the cumulative number of confirmed cases was positively correlated with migration index and population density. The predictive results showed that if no travel restrictions are imposed on the migrant population as usual, the total cumulative number of confirmed cases of COVID-19 would have reached 27 483 (95% CI: 16 074, 48 097; the actual number was 23 177). The increase in one city (Jian) would be 577.23% (95% CI: 322.73%, 972.73%) compared to the real confirmed cases of COVID-19. The average increase in 73 cities was 85.53% (95% CI: 19.53%, 189.81%). Among the migration destinations, the number of cases in cities of Hubei province, Chongqing and Beijing was relatively high, and there were large-scale high-prevalence clusters in eastern Hubei province. Meanwhile, without restrictions on migration, the high prevalence areas in Hubei province and its surrounding areas will be further expanded. Conclusions: The reduced population mobility and population density can greatly slow down the spread of the epidemic. All epidemic areas should suspend the transportation between cities, comprehensively and strictly control the population travel and decrease the population density, so as to reduce the spread of COVID-19.

scholarly journals Distribution of the 2019-nCoV Epidemic and Correlation with Population Emigration from Wuhan, China

2020 ◽  
Author(s):  
Zeliang Chen ◽  
Qi Zhang ◽  
Yi Lu ◽  
Zhongmin Guo ◽  
Xi Zhang ◽  
...  
Keyword(s):  
Hot Spot ◽  
Development Program ◽  
Hubei Province ◽  
Control Measures ◽  
Wuhan City ◽  
Spring Festival ◽  
Control And Prevention ◽  
Infection Source ◽  
Highly Correlated ◽  
Case Number

AbstractBACKGROUNDSThe ongoing new coronavirus (2019-nCoV) pneumonia outbreak is spreading in China and has not reached its peak. Five millions of people had emigrated from Wuhan before the city lockdown, which potentially represent a source of virus spreaders. Case distribution and its correlation with population emigration from Wuhan in early epidemic are of great importance for early warning and prevention of future outbreak.METHODSThe officially reported cases of 2019-nCoV pneumonia were collected as of January 30, 2020. Time and location information of these cases were extracted analyzed with ArcGIS and WinBUGS. Population migration data of Wuhan City and Hubei province were extracted from Baidu Qianxi and analyzed for their correlation with case number.FINDINGSThe 2019-nCoV pneumonia cases were predominantly distributed in Hubei and other provinces of South China. Hot spot provinces included Sichuan and Yunnan provinces that are adjacent to Hubei. While Wuhan city has the highest number of cases, the time risk is relatively stable. Numbers of cases in some cities are relatively low, but the time risks are continuously rising. The case numbers of different provinces and cities of Hubei province were highly correlated with the emigrated populations from Wuhan. Lockdown of 19 cities of Hubei province, and implementation of nationwide control measures efficiently prevented the exponential growth of case number.INTERPRETATIONPopulation emigrated from Wuhan was the main infection source for other cities and provinces. Some cities with low case number but were in rapid increase. Due to the upcoming Spring Festival return transport wave, understanding of the trends of risks in different regions is of great significance for preparedness for both individuals and institutions.FUNDINGSNational Key Research and Development Program of China, National Major Project for Control and Prevention of Infectious Disease in China, State Key Program of National Natural Science of China.

scholarly journals The Effect of the COVID-19 Vaccine on Daily Cases and Deaths Based on Global Vaccine Data

Vaccines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1328
Author(s):  
Zhiwei Li ◽  
Xiangtong Liu ◽  
Mengyang Liu ◽  
Zhiyuan Wu ◽  
Yue Liu ◽  
...  
Keyword(s):  
Random Effects ◽  
Generalized Additive Model ◽  
Meta Analysis ◽  
Additive Model ◽  
Global Pandemic ◽  
Daily Data ◽  
Fair Distribution ◽  
The Impact ◽  
The Relationship

Background: Coronavirus disease 2019 (COVID-19), a global pandemic, has caused over 216 million cases and 4.50 million deaths as of 30 August 2021. Vaccines can be regarded as one of the most powerful weapons to eliminate the pandemic, but the impact of vaccines on daily COVID-19 cases and deaths by country is unclear. This study aimed to investigate the correlation between vaccines and daily newly confirmed cases and deaths of COVID-19 in each country worldwide. Methods: Daily data on firstly vaccinated people, fully vaccinated people, new cases and new deaths of COVID-19 were collected from 187 countries. First, we used a generalized additive model (GAM) to analyze the association between daily vaccinated people and daily new cases and deaths of COVID-19. Second, a random effects meta-analysis was conducted to calculate the global pooled results. Results: In total, 187 countries and regions were included in the study. During the study period, 1,011,918,763 doses of vaccine were administered, 540,623,907 people received at least one dose of vaccine, and 230,501,824 people received two doses. For the relationship between vaccination and daily increasing cases of COVID-19, the results showed that daily increasing cases of COVID-19 would be reduced by 24.43% [95% CI: 18.89, 29.59] and 7.50% [95% CI: 6.18, 8.80] with 10,000 fully vaccinated people per day and at least one dose of vaccine, respectively. Daily increasing deaths of COVID-19 would be reduced by 13.32% [95% CI: 3.81, 21.89] and 2.02% [95% CI: 0.18, 4.16] with 10,000 fully vaccinated people per day and at least one dose of vaccine, respectively. Conclusions: These findings showed that vaccination can effectively reduce the new cases and deaths of COVID-19, but vaccines are not distributed fairly worldwide. There is an urgent need to accelerate the speed of vaccination and promote its fair distribution across countries.

scholarly journals Land Use and Land Cover Changes and Its Impact on Soil Erosion in Stung Sangkae Catchment of Cambodia

2021 ◽  
Vol 13 (16) ◽  
pp. 9276
Author(s):  
Nareth Nut ◽  
Machito Mihara ◽  
Jaehak Jeong ◽  
Bunthan Ngo ◽  
Gilbert Sigua ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
Water Conservation ◽  
Soil Loss ◽  
Hot Spot ◽  
Control Measures ◽  
Economic Activities ◽  
Mekong River Commission ◽  
The Impact

Agricultural expansion and urban development without proper soil erosion control measures have become major environmental problems in Cambodia. Due to a high population growth rate and increased economic activities, land use and land cover (LULC) changes will cause environmental disturbances, particularly soil erosion. This research aimed to estimate total amounts of soil loss using the Revised Universal Soil Loss Equation (RUSLE) model within a Geographic Information System (GIS) environment. LULC maps of Japan International Cooperation Agency (JICA) 2002 and Mekong River Commission (MRC) 2015 were used to evaluate the impact of LULC on soil erosion loss in Stung Sangkae catchment. LULC dynamics for the study periods in Stung Sangkae catchment showed that the catchment experienced a rapid conversion of forests to paddy rice fields and other croplands. The results indicated that the average soil loss from the catchment was 3.1 and 7.6 t/ha/y for the 2002 and 2015 periods, respectively. The estimated total soil loss in the 2002 and 2015 periods was 1.9 million t/y and 4.5 million t/y, respectively. The soil erosion was accelerated by steep slopes combined with the high velocity and erosivity of stormwater runoff. The spatial distribution of soil loss showed that the highest value (14.3 to 62.9 t/ha/y) was recorded in the central, southwestern and upland parts of the catchment. It is recommended that priority should be given to erosion hot spot areas, and appropriate soil and water conservation practices should be adopted to restore degraded lands.

scholarly journals Estimating the impact of COVID-19 control measures using a Bayesian model of physical distancing

2020 ◽  
Author(s):  
Sean C. Anderson ◽  
Andrew M. Edwards ◽  
Madi Yerlanov ◽  
Nicola Mulberry ◽  
Jessica E. Stockdale ◽  
...  
Keyword(s):  
British Columbia ◽  
Control Measures ◽  
Strong Impact ◽  
Contact Rate ◽  
Population Changes ◽  
Epidemic Curve ◽  
Wide Range ◽  
High Prevalence ◽  
The Impact ◽  
Testing Criteria

AbstractExtensive physical distancing measures are currently the primary intervention against coronavirus disease 2019 (COVID-19) worldwide. It is therefore urgent to estimate the impact such measures are having. We introduce a Bayesian epidemiological model in which a proportion of individuals are willing and able to participate in distancing measures, with the timing of these measures informed by survey data on attitudes to distancing and COVID-19. We fit our model to reported COVID-19 cases in British Columbia, Canada, using an observation model that accounts for both underestimation and the delay between symptom onset and reporting. We estimate the impact that physical distancing (also known as social distancing) has had on the contact rate and examine the projected impact of relaxing distancing measures. We find that distancing has had a strong impact, consistent with declines in reported cases and in hospitalization and intensive care unit numbers. We estimate that approximately 0.78 (0.66–0.89 90% CI) of contacts have been removed for individuals in British Columbia practising physical distancing and that this fraction is above the threshold of 0.45 at which prevalence is expected to grow. However, relaxing distancing measures beyond this threshold re-starts rapid exponential growth. Because the extent of underestimation is unknown, the data are consistent with a wide range in the prevalence of COVID-19 in the population; changes to testing criteria over time introduce additional uncertainty. Our projections indicate that intermittent distancing measures—if sufficiently strong and robustly followed— could control COVID-19 transmission, but that if distancing measures are relaxed too much, the epidemic curve would grow to high prevalence.

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 Estimating the population density of the Himalayan Rangeland weed Swertia ciliata (G. Don) Burtt.: An impact of topography and disturbance

2017 ◽  
Vol 7 (1) ◽  
pp. 26-34
Author(s):  
Dil Kumar Limbu ◽  
Zhan-Huan Shang
Keyword(s):  
Population Density ◽  
Control Measures ◽  
Edaphic Factors ◽  
Mountain Ridge ◽  
Weed Population ◽  
Topographic Factors ◽  
Disturbance Intensity ◽  
Average Population ◽  
Line Transects ◽  
The Impact

Swertia ciliata (G. Don) Burtt. is one of the most problematic weeds in the Himalayan rangelands. The main objective of this work is to assess the magnitude of S. ciliata invasion and analyze the impact of topographic factors and the disturbances on the distribution and population density. The work was conducted during August and September 2012 in the Tinjure-Milke mountain ridge at Gupha Pokhari, Nepal. The rangeland aspects (east, south and west) were considered the first level factor; and slopes (≤45 degree and ≥45 degree inclination) and the disturbance intensity were the second and third factors, respectively. Line transects made up 4 m2, 74 quadrats were laid down randomly to enumerate the weed population. The average population density of the S. ciliata was 127 plants m-2. The population density was found significantly different by the effects of the disturbances as well as aspects whereas the effect of the two slopes was found insignificant to the population density. A space is left for further research by ecological and edaphic factors. The study reveals that the infestation degree of S. ciliata is at a considerable level in the Himalayan rangeland and needs immediate control measures.

scholarly journals High prevalence and diversity of Extended-Spectrum β-Lactamase and emergence of Carbapenemase producing Enterobacteriaceae spp in wildlife in Catalonia

2019 ◽  
Author(s):  
Laila Darwich ◽  
Anna Vidal ◽  
Chiara Seminati ◽  
Andreu Albamonte ◽  
Alba Casado ◽  
...  
Keyword(s):  
Selective Pressure ◽  
Control Measures ◽  
Anthropogenic Pressure ◽  
Wild Mammals ◽  
E Coli ◽  
High Prevalence ◽  
Large Panel ◽  
Human Infections ◽  
The Impact ◽  
First Time

AbstractIn wildlife, most of the studies focused on antimicrobial resistance (AMR) describe Escherichia coli as the principal indicator of the selective pressure. In the present study, new species of Enterobacteriaceae with a large panel of cephalosporin resistant (CR) genes have been isolated from wildlife in Catalonia. A total of 307 wild animals were examined to determine CR enterobacteria prevalence, AMR phenotypes and common carbapenem and CR gene expression. The overall prevalence of CR-phenotype was 13% (40/307): 17.3% in wild mammals (18/104) and 11.5% in wild birds (22/191) (p<0.01)). Hedgehogs presented the largest prevalence with 13.5% (14/104) of the mammal specimens, followed by raptors with 7.3% (14/191) of the total bird specimens. Although CR E. coli was obtained most frequently (45%), other CR-Enterobacteriaceae spp like Klebsiella pneumoniae (20%), Citrobacter freundii (15%), Enterobacter cloacae (5%), Proteus mirabilis (5%), Providencia spp (5%) and Serratia marcescens (2.5%) were isolated. A high diversity of CR genes was identified among the isolates, with 50% yielding blaCMY-2, 23% blaSHV-12, 20% blaCMY-1 and 18% blaCTX-M-15. Additionally, new CR-gene variants and resistance to carbapenems associated to OXA-48 were found. Most of the CR isolates, principally K. pneumoniae and C. freundii, were multiresistant with co-resistance to fluoroquinolones, tetracycline, sulphonamides and aminoglycosides. This study describes for the first time in wildlife a high prevalence of Enterobacteriaceae spp harbouring a large variety of carbapenem and CR genes frequently associated to nosocomial human infections. Implementation of control measures to reduce the impact of anthropogenic pressure in the environment is urgently needed.

scholarly journals Time-Varying Spatial Memory Model and Its Impact on Virus Spreading

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Mingyue Xu ◽  
Dingding Han ◽  
Kaidi Zhao ◽  
Qingqing Yao
Keyword(s):  
Spatial Memory ◽  
Management Control ◽  
Control Measures ◽  
Floating Population ◽  
Memory Model ◽  
Cumulative Number ◽  
Time Varying ◽  
Epidemic Spreading ◽  
Virus Spreading ◽  
The Impact

The models of time-varying network have a profound impact on the study of virus spreading on the networks. On the basis of an activity-driven memory evolution model, a time-varying spatial memory model (TSM) is proposed. In the TSM model, the cumulative number of connections between nodes is recorded, and the spatiality of nodes is considered at the same time. Therefore, the active nodes tend to connect the nodes with high intimacy and close proximity. Then, the TSM model is applied to epidemic spreading, and the epidemic spreading on different models is compared. To verify the universality of the TSM model, this model is also applied to rumor spreading, and it is proved that it can also play a good inhibiting effect. We find that, in the TSM network, the introduction of spatiality and memory can slow down the propagation speed and narrow the propagation scope of disease or rumor, and memory is more important. We then explore the impact of different prevention and control methods on pandemic spreading to provide reference for COVID-19 management control and find when the activity of node is restricted, the spreading will be controlled. As floating population has been acknowledged as a key parameter that affects the situation of COVID-19 after work resumption, the factor of population mobility is introduced to calculate the interregional population interaction rate, and the time-varying interregional epidemic model is established. Finally, our results of infectious disease parameters based on daily cases are in good agreement with the real data, and the effectiveness of different control measures is evaluated.

scholarly journals Policy and Law Assessment of COVID-19 Based on Smooth Transition Autoregressive Model

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jieqi Lei ◽  
Xuyuan Wang ◽  
Yiming Zhang ◽  
Lian Zhu ◽  
Lin Zhang
Keyword(s):  
Prevention And Control ◽  
Control Measures ◽  
Smooth Transition ◽  
Cumulative Number ◽  
Star Model ◽  
The World ◽  
Transition Points ◽  
And Control ◽  
The Impact ◽  
Smooth Transition Autoregressive

As of the end of October 2020, the cumulative number of confirmed cases of COVID-19 has exceeded 45 million and the cumulative number of deaths has exceeded 1.1 million all over the world. Faced with the fatal pandemic, countries around the world have taken various prevention and control measures. One of the important issues in epidemic prevention and control is the assessment of the prevention and control effectiveness. Changes in the time series of daily new confirmed cases can reflect the impact of policies in certain regions. In this paper, a smooth transition autoregressive (STAR) model is applied to investigate the intrinsic changes during the epidemic in certain countries and regions. In order to quantitatively evaluate the influence of the epidemic control measures, the sequence is fitted to the STAR model; then, comparisons between the dates of transition points and those of releasing certain policies are applied. Our model well fits the data. Moreover, the nonlinear smooth function within the STAR model reveals that the implementation of prevention and control policies is effective in some regions with different speeds. However, the ineffectiveness is also revealed and the threat of a second wave had already emerged.

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