scholarly journals SI epidemic model applied to COVID-19 data in mainland China

2020 ◽  
Vol 7 (12) ◽  
pp. 201878
Author(s):  
J. Demongeot ◽  
Q. Griette ◽  
P. Magal
Keyword(s):  
Phenomenological Model ◽  
Epidemic Model ◽  
Early Stage ◽  
Mainland China ◽  
Numerical Algorithms ◽  
Parameters Identification ◽  
Piecewise Constant ◽  
Constant Rate ◽  
Si Model ◽  
Exponential Fit

The article is devoted to the parameters identification in the SI model. We consider several methods, starting with an exponential fit to the early cumulative data of SARS-CoV2 in mainland China. The present methodology provides a way to compute the parameters at the early stage of the epidemic. Next, we establish an identifiability result. Then we use the Bernoulli–Verhulst model as a phenomenological model to fit the data and derive some results on the parameters identification. The last part of the paper is devoted to some numerical algorithms to fit a daily piecewise constant rate of transmission.

scholarly journals SI epidemic model applied to COVID-19 data in mainland China

2020 ◽  
Author(s):  
J. Demongeot ◽  
Q. Griette ◽  
P. Magal
Keyword(s):  
Phenomenological Model ◽  
Epidemic Model ◽  
Early Stage ◽  
Mainland China ◽  
Numerical Algorithms ◽  
Parameters Identification ◽  
Piecewise Constant ◽  
Constant Rate ◽  
Si Model ◽  
Exponential Fit

AbstractThe article is devoted to the parameters identification in the SI model. We consider several methods, starting with an exponential fit of the early cumulative data of Sars-CoV2 in mainland China. The present methodology provides a way to compute the parameters at the early stage of the epidemic. Next, we establish an identifiability result. Then we use the Bernoulli-Verhulst model as a phenomenological model to fit the data and derive some results on the parameters identification. The last part of the paper is devoted to some numerical algorithms to fit a daily piecewise constant rate of transmission.

scholarly journals SI Epidemic Model Applied to COVID-19 Data in Mainland China

2021 ◽  
Author(s):  
Jacques Demongeot ◽  
Quentin Griette ◽  
Pierre Magal
Keyword(s):  
Epidemic Model ◽  
Mainland China

scholarly journals Spatio-temporal distribution characteristics of COVID-19 in China: a city-level modeling study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Qianqian Ma ◽  
Jinghong Gao ◽  
Wenjie Zhang ◽  
Linlin Wang ◽  
Mingyuan Li ◽  
...  
Keyword(s):  
Spatial Autocorrelation ◽  
Southern China ◽  
Early Stage ◽  
Hot Spot ◽  
Statistical Significance ◽  
Mainland China ◽  
Temporal Distribution ◽  
Distribution Characteristics ◽  
Hotspot Analysis ◽  
Spatio Temporal

Abstract Background The coronavirus disease 2019 (COVID-19) has become a pandemic. Few studies have been conducted to investigate the spatio-temporal distribution of COVID-19 on nationwide city-level in China. Objective To analyze and visualize the spatiotemporal distribution characteristics and clustering pattern of COVID-19 cases from 362 cities of 31 provinces, municipalities and autonomous regions in mainland China. Methods A spatiotemporal statistical analysis of COVID-19 cases was carried out by collecting the confirmed COVID-19 cases in mainland China from January 10, 2020 to October 5, 2020. Methods including statistical charts, hotspot analysis, spatial autocorrelation, and Poisson space–time scan statistic were conducted. Results The high incidence stage of China’s COVID-19 epidemic was from January 17 to February 9, 2020 with daily increase rate greater than 7.5%. The hot spot analysis suggested that the cities including Wuhan, Huangshi, Ezhou, Xiaogan, Jingzhou, Huanggang, Xianning, and Xiantao, were the hot spots with statistical significance. Spatial autocorrelation analysis indicated a moderately correlated pattern of spatial clustering of COVID-19 cases across China in the early phase, with Moran’s I statistic reaching maximum value on January 31, at 0.235 (Z = 12.344, P = 0.001), but the spatial correlation gradually decreased later and showed a discrete trend to a random distribution. Considering both space and time, 19 statistically significant clusters were identified. 63.16% of the clusters occurred from January to February. Larger clusters were located in central and southern China. The most likely cluster (RR = 845.01, P < 0.01) included 6 cities in Hubei province with Wuhan as the centre. Overall, the clusters with larger coverage were in the early stage of the epidemic, while it changed to only gather in a specific city in the later period. The pattern and scope of clusters changed and reduced over time in China. Conclusions Spatio-temporal cluster detection plays a vital role in the exploration of epidemic evolution and early warning of disease outbreaks and recurrences. This study can provide scientific reference for the allocation of medical resources and monitoring potential rebound of the COVID-19 epidemic in China.

A Critical Analysis of Legal and Policy Responses to the COVID-19 Pandemic and its Long-term Impacts in Taiwan

2021 ◽  
Vol SI ◽  
pp. 3-10
Author(s):  
Hsing-Hao Wu ◽  
Chih-Wei Chen
Keyword(s):  
Public Health ◽  
Early Stage ◽  
Mainland China ◽  
Legal Framework ◽  
Contact Tracing ◽  
Chinese Government ◽  
Governance System ◽  
Personal Protection Equipment ◽  
Global Pandemic

The COVID-19 pandemic has dramatically impacted public health and economic and social stability worldwide since the WHO’s Public Health Emergency of International Concerns declaration in early March 2020. The COVID-19 virus was first discovered in December 2019 in Wuhan city, China, and eventually resulted in the global pandemic, of which the cumulative cases have reached 181,367,824 at the time of writing. Taiwan encountered severe public health threats because of the frequent travelers as many as 10 million who commuted annually between mainland China and Taiwan. Recognizing the imminent threats arising from an intensive flow of people from mainland China due to the lockdown policy adopted by the Chinese government, Taiwan has adopted strict border control, sophisticated contact tracing and monitoring measures, and most importantly the securing of sufficient Personal Protection Equipment supply for citizens to prevent community spread. Taiwan’s quick and precise COVID-19 response at the early stage of containing the virus has been proven very successful since the outbreak of the COVID-19 global pandemic in late February 2020. Taiwan is now struggling to fight the recent outbreak for lacking sufficient vaccines and testing capacities and shall learn from other country’s experience for countermeasures against a massive epidemic. This article aims to explore the key elements for the early success of containing the COVID-19 virus, including the comprehensive legal framework for preventing infectious disease, highly trained public health officials and governance system, and citizen self-awareness. The article then discusses the potential legal controversies and their long-term impacts on Taiwan. Finally, this article provides the concluding observation and suggestions for fighting massive infectious diseases.

scholarly journals Tracking and forecasting milepost moments of the epidemic in the early-outbreak: framework and applications to the COVID-19

2020 ◽  
Author(s):  
Huiwen Wang ◽  
Yanwen Zhang ◽  
Shan Lu ◽  
Shanshan Wang
Keyword(s):  
Early Stage ◽  
Turning Points ◽  
Mainland China ◽  
Hubei Province ◽  
Reasonable Assumption ◽  
Government Control ◽  
Whole Process ◽  
Number Of Patients ◽  
The Government ◽  
Zero Points

AbstractBackgroundThe outbreak of the 2019 novel coronavirus (COVID-19) has attracted global attention. In the early stage of the outbreak, the most important question concerns some meaningful milepost moments, including (1) the time when the number of daily confirmed cases decreases, (2) the time when the number of daily confirmed cases becomes smaller than that of the daily removed (recovered and death), (3) the time when the number of daily confirmed cases becomes zero, and (4) the time when the number of patients treated in hospital is zero, which indicates the end of the epidemic. Intuitively, the former two can be regarded as two important turning points which indicate the alleviation of epidemic to some extent, while the latter two as two “zero” points, respectively. Unfortunately, it is extremely difficult to make right and precise prediction due to the limited amount of available data at a early stage of the outbreak.MethodTo address it, in this paper, we propose a flexible framework incorporating the effectiveness of the government control to forecast the whole process of a new unknown infectious disease in its early-outbreak. Specially, we first establish the iconic indicators to characterize the extent of epidemic spread, yielding four periods of the whole process corresponding to the four meaningful milepost moments: two turning points and two “zero” points. Then we develop the tracking and forecasting procedure with mild and reasonable assumption. Finally we apply it to analyze and evaluate the COVID-19 using the public available data for mainland China beyond Hubei Province from the China Centers for Disease Control (CDC) during the period of Jan 29th, 2020, to Feb 29th, 2020, which shows the effectiveness of the proposed procedure.ResultsResults show that our model can clearly outline the development of the epidemic at a very early stage. The first prediction results on Jan 29th reveal that the first and second milepost moments for mainland China beyond Hubei Province would appear on Jan 31st and Feb 14th respectively, which are only one day and three days behind the real world situations. Forecasting results indicate that the number of newly confirmed cases will become zero in the mid-late March, and the number of patients treated in the hospital will become zero between mid-March and mid-April in mainland China beyond Hubei Province. The framework proposed in this paper can help people get a general understanding of the epidemic trends in counties where COVID-19 are raging as well as any other outbreaks of new and unknown infectious diseases in the future.

scholarly journals An epidemic model for non-first-order transmission kinetics

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247512
Author(s):  
Eun-Young Mun ◽  
Feng Geng
Keyword(s):  
Epidemic Model ◽  
Disease Transmission ◽  
Transmission Rate ◽  
Early Stage ◽  
Compartmental Models ◽  
Control Measures ◽  
Chemical Reaction Kinetics ◽  
Rate Law ◽  
First Order ◽  
First Order Kinetics

Compartmental models in epidemiology characterize the spread of an infectious disease by formulating ordinary differential equations to quantify the rate of disease progression through subpopulations defined by the Susceptible-Infectious-Removed (SIR) scheme. The classic rate law central to the SIR compartmental models assumes that the rate of transmission is first order regarding the infectious agent. The current study demonstrates that this assumption does not always hold and provides a theoretical rationale for a more general rate law, inspired by mixed-order chemical reaction kinetics, leading to a modified mathematical model for non-first-order kinetics. Using observed data from 127 countries during the initial phase of the COVID-19 pandemic, we demonstrated that the modified epidemic model is more realistic than the classic, first-order-kinetics based model. We discuss two coefficients associated with the modified epidemic model: transmission rate constant k and transmission reaction order n. While k finds utility in evaluating the effectiveness of control measures due to its responsiveness to external factors, n is more closely related to the intrinsic properties of the epidemic agent, including reproductive ability. The rate law for the modified compartmental SIR model is generally applicable to mixed-kinetics disease transmission with heterogeneous transmission mechanisms. By analyzing early-stage epidemic data, this modified epidemic model may be instrumental in providing timely insight into a new epidemic and developing control measures at the beginning of an outbreak.

scholarly journals Ten years of research and publications about hospice and palliative care in Mainland China: a bibliometric study

2020 ◽  
Author(s):  
Shuang Jin ◽  
Shuo Liu ◽  
Jiaojiao Li ◽  
Xiaohong Ning ◽  
Xiaohong Liu
Keyword(s):  
Palliative Care ◽  
Early Stage ◽  
Mainland China ◽  
Western China ◽  
China National Knowledge Infrastructure ◽  
The Sustainable Development ◽  
Knowledge Infrastructure ◽  
Increasing Demand ◽  
State Of Research ◽  
Hospice And Palliative Care

Abstract Background Research is a fundamental element in the sustainable development of hospice and palliative care. Mainland China is facing increasing demand for hospice and palliative care and has launched related policies over the past decade. However, the state of research and publications in this field in China remains largely unknown. This study aimed to provide an overall picture of hospice-and palliative care -related research and publications in Mainland China from 2010 to 2019. Methods We searched Web of Science, Scopus, PubMed, CINAHL, OVID, and China National Knowledge Infrastructure for hospice-and palliative care -related publications in English and Chinese for 2010–2019. We analyzed the production, citations and impacts, publishing journals, region and institution of origin, and themes and active topics. Results A total of 3224 publications were identified, and 636 of them were considered of high quality. The production and impacts showed a clear increase—especially after 2016. However, the regional disparity between East and Western China in production was conspicuous and closely linked to economic factors. Beijing and Shanghai were the most productive regions. The hospice providers in the first five pilot regions had no collaboration with leading universities in their publications. Hospice and palliative care for cancer patients was the most common publication topic; some essential themes were rarely explored. Conclusion Research and publications of hospice and palliative care in Mainland China is developing faster than before; however, it remains at an early stage and should be promoted in terms of interregional equity. Collaboration among different disciplines, institutes, and regions should be encouraged.

scholarly journals Ten years of research and publications about hospice and palliative care in Mainland China: a bibliometric study

2020 ◽  
Author(s):  
Shuang Jin ◽  
Shuo Liu ◽  
Jiaojiao Li ◽  
Xiaohong Ning ◽  
Xiaohong Liu
Keyword(s):  
Palliative Care ◽  
Early Stage ◽  
Mainland China ◽  
Western China ◽  
China National Knowledge Infrastructure ◽  
The Sustainable Development ◽  
Knowledge Infrastructure ◽  
Increasing Demand ◽  
State Of Research ◽  
Hospice And Palliative Care

Abstract Objectives: Research is a fundamental element in the sustainable development of hospice and palliative care. Mainland China is facing increasing demand for hospice and palliative care and has launched related policies over the past decade. However, the state of research and publications in this field in China remains largely unknown. This study aimed to provide an overall picture of hospice-and palliative care -related research and publications in Mainland China of the last decade.Methods: We searched Web of Science, Scopus, PubMed, CINAHL, OVID, and China National Knowledge Infrastructure for hospice-and palliative care -related publications in English and Chinese for 2010–2019. We analyzed the production, citations and impacts, publishing journals, region and institution of origin, publication types and topics.Results: A total of 3224 publications were identified, and 636 of them were published in high-quality journals. The production and impacts showed a clear increase—especially after 2016. However, there is no specialized journal of hospice and palliative care in Mainland China. The publications scattered among various journals. The regional disparity between East and Western China in production was conspicuous and closely linked to economic factors. The most prosperous cities in Mainland China, Beijing and Shanghai, were the most productive regions. The hospice providers in the first five pilot regions had no collaboration with leading universities in their publications. Hospice and palliative care for cancer patients was the most common publication topic; some essential topics were rarely explored.Conclusions: Research and publications about hospice and palliative care in Mainland China is developing faster than before; however, it remains at an early stage and should be promoted in terms of interregional equity. Collaboration among different disciplines, institutes, and regions should be encouraged.

scholarly journals Trends in socioeconomic inequalities in smoking in Turkey from 2008 to 2016

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hur Hassoy ◽  
Isil Ergin ◽  
Gorkem Yararbas
Keyword(s):  
Older Women ◽  
Epidemic Model ◽  
Early Stage ◽  
Age Groups ◽  
Socioeconomic Inequalities ◽  
Cross Sectional ◽  
Relative Index ◽  
Younger Women ◽  
Index Of Inequality ◽  
Wealth Inequalities

Abstract Background Smoking inequalities in Turkey were previously demonstrated in an early stage of the smoking epidemic model. This paper aimed to assess the trends for socioeconomic inequalities in smoking in Turkey over the years in the context of the smoking epidemic model using data from the Global Adult Tobacco Survey (GATS) Turkey 2008–2012-2016. Methods Cross-sectional data were analyzed to calculate the association of smoking with, wealth, education, occupation and place of residence using age-standardized prevalence rates, odds ratios, relative index of inequality (RII) and slope index of inequality (SII). The analysis was performed separately for age groups (younger: 20–39 years/older: 40 and above years) and sex. Results Younger women with higher wealth and older women with higher wealth and education smoked more. For both age groups, smoking was increased for working class and urban women. Relative wealth inequalities in smoking narrowed and then showed a reversal for younger women (RII2008 = 3.37; 95% CI:1.64–3.40; RII2012 = 2.19; 95% CI:1.48–3.24; RII2016 = 0.80; 95% CI:0.58–1.10, p-for trend < 0.0001). Relative educational inequalities in smoking for older women also showed a narrowing (RII2008 = 21.45; 95% CI:11.74–39.19; RII2012 = 15.25; 95% CI:9.10–25.55; and RII2016 = 5.48; 95% CI:3.86–7.78, p-for trend < 0.0001). For older women, a similar narrowing was observed for wealth (RII2008 = 3.94; 95% CI:2.38–6.53; RII2012 = 2.79; 95% CI:1.80–4.32; and RII2016 = 1.34; 95% CI:0.94–1.91, p-for trend = 0.0001). The only significant trend for absolute inequalities was for younger women by wealth. This trend showed a narrowing and then a reversal (SII2008 = 0.14; 95% CI:0.09–1.20; SII2012 = 0.12; 95% CI:0.06–0.18; and SII2016 = -0.05; 95% CI:-0.12–0.02, p-for trend = 0.0001). Unlike women, smoking in men showed inverse associations for wealth and education, although not statistically confirmed for all years. Smoking was increased in working classes and unemployed men in 2012 and 2016. Inequalities did not show a trend in relative and absolute terms for men. Conclusions For smoking inequalities in Turkey, a transition to the next stage was observed, although the previously defined Southern European pattern also existed. Low socioeconomic women deserve special attention as well as stressors at work and drivers of smoking at urban settings.

scholarly journals Analysis of Collective Response Reveals that COVID-19-Related Activities Start From the End of 2019 in Mainland China

2020 ◽  
Author(s):  
Ji Liu ◽  
Tongtong Huang ◽  
Haoyi Xiong ◽  
Jizhou Huang ◽  
Jingbo Zhou ◽  
...  
Keyword(s):  
Early Stage ◽  
Human Mobility ◽  
Mainland China ◽  
Global Scale ◽  
Time Warping ◽  
Mobility Data ◽  
Collective Response ◽  
Cross Correlation Analysis ◽  
The Usa ◽  
Dynamic Time

While the COVID-19 outbreak is making an impact at a global scale, the collective response to the pandemic becomes the key to analyzing past situations, evaluating current measures, and formulating future predictions. In this paper, we analyze the public reactions to the pandemic using search engine data and mobility data from Baidu Search and Baidu Maps respectively, where we particularly pay attentions to the early stage of pandemics and find early signals from the collective response to COVID-19. First, we correlate the number of confirmed cases per day to daily search queries of a large number of keywords through Dynamic Time Warping (DTW) and Detrended Cross-Correlation Analysis (DCCA), where the keywords top in the most critical days are believed the most relevant to the pandemic. We then categorize the ranking lists of keywords according to the specific regions of the search, such as Wuhan, Mainland China, the USA, and the whole world. Through the analysis on search, we succeed in identifying COVID-19 related collective response would not be earlier than the end of 2019 in Mainland China. Finally, we confirm this observation again using human mobility data, where we specifically compare the massive mobility traces, including the real-time population densities inside key hospitals and inter-city travels departing from/arriving in Wuhan, from 2018 to 2020. No significant changes have been witnessed before December, 2019.

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