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

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.

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THE USE OF LITERATURE-BASED INSTRUCTION TO IMPROVE READING COMPREHENSION AND WRITING ACHIEVEMENTS OF THE EIGHTH GRADE STUDENTS

The Journal of English Literacy Education: The Teaching and Learning of English as a Foreign Language ◽

10.36706/jele.v6i2.9278 ◽

2020 ◽

Vol 6 (2) ◽

pp. 61-73

Author(s):

Ressy Novasyari

Keyword(s):

Reading Comprehension ◽

Eighth Graders ◽

Population Based ◽

Mean Difference ◽

Eighth Grade ◽

Writing Achievement ◽

Eighth Grade Students ◽

Quasi Experimental ◽

Based Instruction ◽

And Control

Abstract: This research aimed to investigate whether or not there were significant differences in reading comprehension and writing achievement between the eighth grade students of SMP Islam Az-Zahra 2 Palembang who were taught by using Literature-Based instruction and those who were not. This study used one of the quasi experimental designs: pretest-posttest design. The sample was selected purposively from the whole population based on their reading comprehension scores. Forty six eighth graders were selected as the sample and equally divided into experimental and control groups. Pretest and posttest were given to both groups. Using paired sample statistics, the results of the experimental group showed that the students’ reading comprehension and writing achievement ? significantly improved. Furthermore, the result of the independent t-test showed that with mean difference of reading comprehension was 8.609, t value 11.111(p<0.05). Moreover, the mean difference of writing achievement was 6.8043, t value 10.478 (p<0.05). Keywords: Literature-based instruction, reading comprehension and writing achievement.

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

10.1101/2020.02.10.20021824 ◽

2020 ◽

Cited By ~ 7

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.

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Highland of COVID-19 outside Hubei: epidemic characteristics, control and projections of Wenzhou, China

10.1101/2020.02.25.20024398 ◽

2020 ◽

Cited By ~ 3

Author(s):

Liangde Xu ◽

Jian Yuan ◽

Yaru Zhang ◽

Guosi Zhang ◽

Fan Lu ◽

...

Keyword(s):

Health Care Workers ◽

Hubei Province ◽

Transmission Model ◽

Unknown Aetiology ◽

Expected Number ◽

Coastal City ◽

Care Workers ◽

Novel Coronavirus ◽

And Control ◽

Epidemiologic Characteristics

In late December 2019, Chinese authorities reported a cluster of pneumonia cases of unknown aetiology in Wuhan, China1. A novel strain of coronavirus named Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was isolated and identified on 2 January 2020 2. Human-to-human transmission have been confirmed by a study of a family cluster and have occurred in health-care workers 3,4. Until 10 February 2020, 42638 cases of 2019 novel coronavirus disease (COVID-19) have been confirmed in China, of which 31728 came from Hubei Province (Figure). Wenzhou, as a southeast coastal city with the most cases outside Hubei Province, its policy control and epidemic projections have certain references for national and worldwide epidemic prevention and control. We described the epidemiologic characteristics of COVID-19 in Wenzhou and made a transmission model to predict the expected number of cases in the coming days.

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Improving Access to Delivery Care and Reducing the Equity Gap Through Voucher Program in Bangladesh: Evidence From Difference-in-Differences Analysis

International Quarterly of Community Health Education ◽

10.1177/0272684x17749568 ◽

2018 ◽

Vol 38 (2) ◽

pp. 137-145

Author(s):

Kaji Tamanna Keya ◽

Benjamin Bellows ◽

Ubaidur Rob ◽

Charlotte Warren

Keyword(s):

Population Based ◽

Public Health Facility ◽

Difference In Differences ◽

Voucher Program ◽

Percentage Points ◽

Null Effect ◽

Demand Side Financing ◽

Quasi Experimental ◽

And Control

To test a statistically significant change in delivery by medically trained providers following introduction of a demand-side financing voucher, a population-based quasi-experimental study was undertaken, with 3,300 mothers in 2010 and 3,334 mothers at follow-up in 2012 in government-implemented voucher program and control areas. Results found that voucher program was significantly associated with increased public health facility use (difference-in-differences (DID) 13.9) and significantly increased delivery complication management care (DID 13.2) at facility although a null effect was found in facility-based delivery increase. A subset analysis of the five well-functioning facilities showed that facility deliveries increased DID 5.3 percentage points. Quintile-based analysis of all facilities showed that facility delivery increased more than threefold in lower quintile households comparing to twofold in control sites. The program needs better targeting to the beneficiaries, ensuring available gynecologist–anesthetist pair and midwives, effective monitoring, and timely fund reimbursements to facilities.

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

10.1101/2020.03.02.20030080 ◽

2020 ◽

Cited By ~ 3

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.

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Spatial Statistics and Influencing Factors of the Epidemic of Novel Coronavirus Pneumonia 2019 in Hubei Province, China

10.21203/rs.3.rs-16858/v1 ◽

2020 ◽

Author(s):

Yongzhu Xiong ◽

Yunpeng Wang ◽

Feng Chen ◽

Mingyong Zhu

Keyword(s):

Spatial Autocorrelation ◽

Influencing Factors ◽

Hot Spot ◽

Pearson Correlation ◽

Hubei Province ◽

Land Area ◽

Novel Coronavirus ◽

And Control ◽

Global Spatial Autocorrelation ◽

County Scale

Abstract An in-depth understanding of spatiotemporal dynamic characteristics of infectious diseases could be helpful to an epidemic prevention and control. Based on the novel coronavirus pneumonia (NCP) data published on official websites, GIS spatial statistics and Pearson correlation methods were used to analyze the spatial autocorrelation and influencing factors of the 2019 NCP epidemic from January 30, 2020 to February 18, 2020. The results of the study showed that: (1) During the study period, Hubei Province was the only significant cluster area and hot spot of the cumulative cases confirmed with the NCP infection in China on the provincial scale; (2) The epidemic of the NCP infection in China on the prefecture-city scale had a very significant global spatial autocorrelation, and Wuhan had always been the significant hot spot and cluster city of the cumulative cases confirmed with the NCP infection in the whole country; (3) The cumulative cases confirmed with the NCP infection in Hubei Province on the county scale had a very significant global spatial autocorrelation, and the county-level districts under the jurisdiction of Wuhan and its neighboring Huangzhou district in Huanggang City were the significant hot spots and spatial clusters of the cumulative cases confirmed with the NCP infection; (4) Based on Pearson correlation analysis, the number of the accumulative cases confirmed with the NCP infection in Hubei Province on the prefecture-city scale and also on the county scale had very significant and positive correlations (p < 0.01) with the four indexes of population of registration population, resident population, regional GDP and total retail sales of consumer goods, respectively, during the study period; (5) The number of the cumulative cases confirmed with the NCP infection in Hubei Province on the prefecture-city scale also had a very significant and positive correlation (p < 0.01) with Baidu migration index and population density, respectively, but not with land area, whereas that in Hubei Province on the county scale had a significant and positive correlation (p < 0.05) with land area, but not with population density from January 30, 2020 to February 18, 2020. It is found that the NCP epidemic in Hubei Province has the distinctive characteristics of significantly centralized outbreak, significantly spatial autocorrelation and complex influencing factors and that the spatial scale has a significant effect on the global spatial autocorrelation of the NCP epidemic. The findings help to deepen the understanding of spatial distribution patterns and transmission trends of the NCP epidemic and may also benefit scientific prevention and control of epidemics such as NCP 2019.

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Epidemic Situation of Novel Coronavirus Pneumonia in China mainland

10.1101/2020.02.17.20024034 ◽

2020 ◽

Cited By ~ 3

Author(s):

Youbin Liu ◽

Liming Gong ◽

Baohong Li

Keyword(s):

Prevention And Control ◽

Turning Point ◽

Hubei Province ◽

Wuhan City ◽

Novel Coronavirus ◽

China Mainland ◽

And Control

AbstractObjectiveAnalyze the occurrence of novel coronavirus pneumonia(NCP) in China mainland, explore the epidemiological rules, and evaluate the effect of prevention and control.MethodsFrom December 1, 2019 to March 4, 2020, Analysis of 80,409 confirmed cases of NCP in China mainland.ResultsFrom December 1, 2019 to March 4, 2020, a total of 80,409 cases of NCP were confirmed in China mainland, a total of 67,466 cases were confirmed in Hubei Province, a total of 49,671 cases were confirmed in Wuhan city. From December 1, 2019 to March 4, 2020, a total of 3,012 cases of NCP deaths in China mainland, the mortality was 3.75% (3012/80,409); A total of 52045 cases of cured in China mainland; The turning point of the epidemic have been reached since February 18.2020 in China mainland; The spread index of NCP gradually declined since January 27. 2020, and the extinction index of NCP rose little by little since January 29, 2020.ConclusionFrom December 1, 2019 to March 4, 2020, NCP is under control, and the trend of the epidemic will eventually disappear; The turning point of an epidemic that I’ve created is a great indicator that can calculate the turning date of an outbreak and provide a basis for scientific prevention.

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Spatial statistics and influencing factors of the novel coronavirus pneumonia 2019 epidemic in Hubei Province, China

10.21203/rs.3.rs-16858/v2 ◽

2020 ◽

Cited By ~ 2

Author(s):

Yongzhu Xiong ◽

Yunpeng Wang ◽

Feng Chen ◽

Mingyong Zhu

Keyword(s):

Spatial Autocorrelation ◽

Influencing Factors ◽

Pearson Correlation ◽

Hubei Province ◽

County Level ◽

The Novel ◽

Land Area ◽

Novel Coronavirus ◽

And Control ◽

Global Spatial Autocorrelation

Abstract An in-depth understanding of the spatiotemporal dynamic characteristics of infectious diseases could be helpful for epidemic prevention and control. Based on the novel coronavirus pneumonia (NCP) data published on official websites, GIS spatial statistics and Pearson correlation methods were used to analyze the spatial autocorrelation and influencing factors of the 2019 NCP epidemic from January 30, 2020 to February 18, 2020. The following results were obtained. (1) During the study period, Hubei Province was the only significant cluster area and hotspot of cumulative confirmed cases of NCP infection at the provincial level in China. (2) The NCP epidemic in China had a very significant global spatial autocorrelation at the prefecture-city level, and Wuhan was the significant hotspot and cluster city for cumulative confirmed NCP cases in the whole country. (3) The cumulative confirmed NCP cases had a very significant global spatial autocorrelation at the county level in Hubei Province, and the county-level districts under the jurisdiction of Wuhan and neighboring Huangzhou district in Huanggang City were the significant hotspots and spatial clusters of cumulative confirmed NCP cases. (4) Based on Pearson correlation analysis, the number of cumulative confirmed NCP cases in Hubei Province had very significant and positive correlations (p<0.01) at the prefecture-city and the county levels with four population indexes (registered population, resident population, regional GDP and total retail sales of consumer goods) during the study period. (5) The number of the cumulative confirmed NCP cases in Hubei Province also had a very significant and positive correlation (p<0.01) on the prefecture-city scale with the Baidu migration index and population density but not with land area, whereas that in Hubei Province had a significant and positive correlation (p<0.05) at the county level with land area but not with population density from January 30, 2020, to February 18, 2020. It was found that the NCP epidemic in Hubei Province had distinctive characteristics of a significant centralized outbreak, significant spatial autocorrelation and complex influencing factors and that the spatial scale had a significant effect on the global spatial autocorrelation of the NCP epidemic. The findings help to deepen the understanding of spatial distribution patterns and transmission trends of the NCP epidemic and may also benefit scientific prevention and control of epidemics such as COVID-19.

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Population-based organized screening by faecal immunochemical testing and colorectal cancer mortality: a natural experiment

International Journal of Epidemiology ◽

10.1093/ije/dyaa166 ◽

2020 ◽

Author(s):

Matthew Thomas Keys ◽

Miquel Serra-Burriel ◽

Natalia Martínez-Lizaga ◽

Maria Pellisé ◽

Francesc Balaguer ◽

...

Keyword(s):

Colorectal Cancer ◽

Cancer Mortality ◽

Population Based ◽

Incidence Rates ◽

Average Risk ◽

Synthetic Control ◽

Quasi Experimental ◽

Immunochemical Test ◽

And Control ◽

Colorectal Cancer Mortality

Abstract Background Population-based organized screening programmes for colorectal cancer (CRC) are underway worldwide, with many based on the faecal immunochemical test (FIT). No clinical trials assessing FIT compared with no screening are planned, and few studies have assessed the population impact of such programmes. Methods Before 2010, 11 out of 50 Spanish provinces initiated population-based organized screening programmes with FIT for an average-risk population aged 50–69 years. We used a quasi-experimental design across Spanish provinces between 1999 and 2016 to evaluate their impact on population age-standardized mortality and incidence rates due to CRC. Difference-in-differences and synthetic control analyses were performed to test for validation of statistical assumptions and to assess the dynamics of screening-associated changes in outcomes over time. Results No differences in outcome trends between exposed (n = 11) and control (n = 36) provinces were observed for up to 7 years preceding the implementation of screening. Relative to controls, exposed provinces experienced a mean increase in age-standardized incidence of 10.08% [95% confidence interval (CI) (5.09, 15.07)] 2 years after implementation, followed by a reduction in age-standardized mortality rates due to CRC of 8.82% [95% CI (3.77, 13.86)] after 7 years. Results were similar for both women and men. No associated changes were observed in adjacent age bands not targeted by screening, nor for 10 other major causes of death in the exposed provinces. Conclusions FIT-based organized screening in Spain was associated with reductions in population colorectal cancer mortality. Further research is warranted in order to assess the replicability and external validity of our findings, and on gender-specific use of FIT in organized screening.

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Population Mobility and the Transmission Risk of the COVID-19 in Wuhan, China

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10060395 ◽

2021 ◽

Vol 10 (6) ◽

pp. 395

Author(s):

Minghai Luo ◽

Sixian Qin ◽

Bo Tan ◽

Mingming Cai ◽

Yufeng Yue ◽

...

Keyword(s):

Infection Risk ◽

Control Measures ◽

Transmission Risk ◽

Medical Services ◽

Population Mobility ◽

Wholesale Market ◽

Spring Festival ◽

Prevention And Control Measures ◽

Novel Coronavirus ◽

And Control

At the beginning of 2020, a suddenly appearing novel coronavirus (COVID-19) rapidly spread around the world. The outbreak of the COVID-19 pandemic in China occurred during the Spring Festival when a large number of migrants traveled between cities, which greatly increased the infection risk of COVID-19 across the country. Financially supported by the Wuhan government, and based on cellphone signaling data from Unicom (a mobile phone carrier) and Baidu location-based data, this paper analyzed the effects that city dwellers, non-commuters, commuters, and people seeking medical services had on the transmission risk of COVID-19 in the early days of the pandemic in Wuhan. The paper also evaluated the effects of the city lockdown policy on the spread of the pandemic outside and inside Wuhan. The results show that although the daily business activities in the South China Seafood Wholesale Market and nearby commuters’ travel behaviors concentrated in the Hankou area, a certain proportion of these people were distributed in the Wuchang and Hanyang areas. The areas with relatively high infection risks of COVID-19 were scattered across Wuhan during the early outbreak of the pandemic. The lockdown in Wuhan closed the passageways of external transport at the very beginning, largely decreasing migrant population and effectively preventing the spread of the pandemic to the outside. However, the Wuhan lockdown had little effect on preventing the spread of the pandemic within Wuhan at that time. During this period, a large amount of patients who went to hospitals for medical services were exposed to a high risk of cross-infection without precaution awareness. The pandemic kept dispersing in three towns until the improvement of the capacity of medical treatment, the management of closed communities, the national support to Wuhan, and the implementation of a series of emergency responses at the same time. The findings in this paper reveal the spatiotemporal features of the dispersal of infection risk of COVID-19 and the effects of the prevention and control measures during the early days of the pandemic. The findings were adopted by the Wuhan government to make corresponding policies and could also provide supports to the control of the pandemic in the other regions and countries.

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