COVID-19 Epidemic Prediction Model and Prevention and Control Analysis

In the study of the mid-long-term early warning of landslide, the computational efficiency of the prediction model is critical to the timeliness of landslide prevention and control. Accordingly, enhancing the computational efficiency of the prediction model is of practical implication to the mid-long-term prevention and control of landslides. When the Apriori algorithm is adopted to analyze landslide data based on the MapReduce framework, numerous frequent item-sets will be generated, adversely affecting the computational efficiency. To enhance the computational efficiency of the prediction model, the IAprioriMR algorithm is proposed in this paper to enhance the efficiency of the Apriori algorithm based on the MapReduce framework by simplifying operations of the frequent item-sets. The computational efficiencies of the IAprioriMR algorithm and the original AprioriMR algorithm were compared and analyzed in the case of different data quantities and nodes, and then the efficiency of IAprioriMR algorithm was verified to be enhanced to some extent in processing large-scale data. To verify the feasibility of the proposed algorithm, the algorithm was employed in the mid-long-term early warning study of landslides in the Three Parallel Rivers. Under the same conditions, IAprioriMR algorithm of the same rule exhibited higher confidence than FP-Growth algorithm, which implied that IAprioriMR can achieve more accurate landslide prediction. This method is capable of technically supporting the prevention and control of landslides.

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Epidemiological Investigation and Prevention Control Analysis of the Longitudinal Distribution of COVID-19 in Henan Province, China

mSphere ◽

10.1128/msphere.00867-20 ◽

2020 ◽

Vol 5 (5) ◽

Author(s):

Xianguang Yang ◽

Xuelin Chen ◽

Cuihong Ding ◽

Zhibo Bai ◽

Jingyi Zhu ◽

...

Keyword(s):

Prevention And Control ◽

Henan Province ◽

Control Measures ◽

Longitudinal Distribution ◽

Effective Control ◽

Control Analysis ◽

Female Ratio ◽

Prevention And Control Measures ◽

And Control ◽

Epidemiological Characteristics

ABSTRACT The objective was to analyze the longitudinal distribution, epidemiological characteristics, and local prevention and control measures of coronavirus disease 2019 (COVID-19) in six cities in Henan Province, China, from 21 January 2020 to 17 June 2020: Xinyang City (including Gushi County), Nanyang City (including Dengzhou City), Zhumadian City (including Xincai County), Zhengzhou City (including Gongyi City), Puyang City, and Anyang City (including Hua County). Data were collected and analyzed through the COVID-19 information published on the official websites of the health commissions in the six selected cities of Henan Province. As of 17 June 2020, the cumulative incidence rate of COVID-19 in Henan Province was 1.33/100,000, the cumulative cure rate was 98.27%, the cumulative mortality rate was 1.73%, the age range of diagnosed cases was 5 days to 85 years old, and the male-to-female ratio was 1.09:1. The confirmed cases of COVID-19 in Henan Province were mainly imported cases from Hubei, accounting for 87.74% of all cases, of which the highest proportion was 70.50% in Zhumadian. The contact cases and local cases increased in a fluctuating manner over time. In this paper, epidemiological characteristics of COVID-19 in Henan Province were analyzed from the onset of the outbreak to the effective control within 60 days, and effective and distinctive prevention and control measures in various cities were summarized to provide a favorable useful reference for the further formulation and implementation of epidemic prevention and control and a valuable theoretical basis for effectively avoiding a second outbreak. IMPORTANCE Epidemic prevention and control in China have entered a new stage of normalization. This article analyzes the epidemiological characteristics of COVID-19 in Henan Province and summarizes the effective disease prevention and control means and measures at the prefecture level; the normalized private data provide a theoretical reference for the formulation and conduct of future prevention and control work. At the same time, these epidemic prevention and control findings can also be used for reference in other countries and regions.

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A climate-based prediction model in the high-risk clusters of the Mekong Delta region, Vietnam: towards improving dengue prevention and control

Tropical Medicine & International Health ◽

10.1111/tmi.12754 ◽

2016 ◽

Vol 21 (10) ◽

pp. 1324-1333 ◽

Cited By ~ 11

Author(s):

Dung Phung ◽

Mohammad Radwanur Rahman Talukder ◽

Shannon Rutherford ◽

Cordia Chu

Keyword(s):

High Risk ◽

Prediction Model ◽

Prevention And Control ◽

Mekong Delta ◽

Delta Region ◽

Dengue Prevention ◽

And Control

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Epidemiological investigation and prevention control analysis of longitudinal distribution of COVID-19 in Henan province, China

10.1101/2020.07.25.20161844 ◽

2020 ◽

Author(s):

Xianguang Yang ◽

Xuelin Chen ◽

Cuihong Ding ◽

Zhibo Bai ◽

Jingyi Zhu ◽

...

Keyword(s):

Prevention And Control ◽

Virus Disease ◽

Henan Province ◽

Control Measures ◽

Longitudinal Distribution ◽

Effective Control ◽

Control Analysis ◽

Female Ratio ◽

And Control ◽

Epidemiological Characteristics

Objective: To analyze the vertical distribution of six cities in Henan Province,China from January 21, 2020 to June17, 2020: Xinyang City (including Gushi County), Nanyang City (including Dengzhou City), Zhumadian City (including XincaiCounty), Zhengzhou City (including Gongyi City), Puyang City and Anyang City (including Hua County) corona virus disease 2019(COVID-19) epidemiological characteristics and local prevention and control measures.Methods: Data were collected and analyzed through the COVID-19 information published on the official websites of health commissions of Henan Province and six cities.Results: As of June 17, 2020, the cumulative incidence rate of COVID-19 in Henan province was 1.33/100,000, the cumulative cure rate was 98.27%, the cumulative mortality rate was 1.73%, the age range of diagnosed cases was 5days-85years old, and the male to female ratio was 1.09:1.The confirmed cases of COVID-19 in Henan province were mainly imported cases from Hubei, accounting for 87.74%, of which the highest number was 70.50% in Zhumadian. The contact cases and local cases increased in a fluctuating manner over time.Significance: In this paper, epidemiological characteristics of COVID-19 in Henan province from the outbreak to the effective control within 60 days were analyzed, and effective and distinctive prevention and control measures in various cities were summarized, so as to provide a favorable reference for the further formulation and implementation of epidemic prevention and control and a valuable theoretical basis for effectively avoiding the second outbreak.

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A Continuous Dynamic Prediction Model of Gas Pressure Based on Gas Emission at Excavation Face and its Engineering Application

10.5194/nhess-2015-322 ◽

2016 ◽

Author(s):

Chen Liang ◽

Wang Enyuan

Keyword(s):

Prediction Model ◽

Prevention And Control ◽

Engineering Application ◽

Dynamic Effect ◽

Gas Pressure ◽

Coal And Gas Outburst ◽

Gas Emission ◽

Dynamic Prediction ◽

Gas Outburst ◽

And Control

Abstract. Gas pressure is one of the necessary conditions for the occurrence of coal and gas outburst. Realization of continuous and dynamic gas pressure forecasting is of significance for prevention and control of coal and gas outburst. In this work, we established a gas pressure prediction model based on the source of gas emission with considering fluid-solid coupling process. The verified results showed that the predicted gas pressure was roughly consistent with the actual situation, indicating that the prediction model is correct. And it could meet the need of engineering projects. Coal and gas outburst dynamic phenomenon is successfully predicted in engineering application with the model. Overall, prediction coal and gas outburst with the gas pressure model can achieve the continuous and dynamic effect. It can overcome both the static and sampling shortcomings of traditional methods, and solve the difficulty of coal and gas outburst prediction at the excavation face. With its broad applicability and potential prospect, we believe the model is of great importance for improving prevention and control of gas disasters.

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Prediction of hot spot areas of hemorrhagic fever with renal syndrome in Hunan Province based on an information quantity model and logistical regression model

PLoS Neglected Tropical Diseases ◽

10.1371/journal.pntd.0008939 ◽

2020 ◽

Vol 14 (12) ◽

pp. e0008939

Author(s):

Zixi Chen ◽

Fuqiang Liu ◽

Bin Li ◽

Xiaoqing Peng ◽

Lin Fan ◽

...

Keyword(s):

High Risk ◽

Prediction Model ◽

Prevention And Control ◽

Hot Spot ◽

Hemorrhagic Fever ◽

Hunan Province ◽

Information Quantity ◽

Epidemic Monitoring ◽

Risk Areas ◽

And Control

Background China’s “13th 5-Year Plan” (2016–2020) for the prevention and control of sudden acute infectious diseases emphasizes that epidemic monitoring and epidemic focus surveys in key areas are crucial for strengthening national epidemic prevention and building control capacity. Establishing an epidemic hot spot areas and prediction model is an effective means of accurate epidemic monitoring and surveying. Objective: This study predicted hemorrhagic fever with renal syndrome (HFRS) epidemic hot spot areas, based on multi-source environmental variable factors. We calculated the contribution weight of each environmental factor to the morbidity risk, obtained the spatial probability distribution of HFRS risk areas within the study region, and detected and extracted epidemic hot spots, to guide accurate epidemic monitoring as well as prevention and control. Methods: We collected spatial HFRS data, as well as data on various types of natural and human social activity environments in Hunan Province from 2010 to 2014. Using the information quantity method and logistic regression modeling, we constructed a risk-area-prediction model reflecting the epidemic intensity and spatial distribution of HFRS. Results: The areas under the receiver operating characteristic curve of training samples and test samples were 0.840 and 0.816. From 2015 to 2019, HRFS case site verification showed that more than 82% of the cases occurred in high-risk areas. Discussion This research method could accurately predict HFRS hot spot areas and provided an evaluation model for Hunan Province. Therefore, this method could accurately detect HFRS epidemic high-risk areas, and effectively guide epidemic monitoring and surveyance.

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