Government Intervention Measures Effectively Control COVID-19 Epidemic in Wuhan,China

The coronavirus disease 2019(COVID-19)outbreak has been brought under control through a nationwide effort,and now it has become a global pandemic and the situation seems grim.We summarized the measures taken in Wuhan and analyzed the effects to comprehensively describe the factors involved in controlling the COVID-19 in China.In China,several measures such as the lockdown of Wuhan,restriction of traffic and communities,increasing hospital beds,nationwide support from medical staff,epidemic prevention equipment and supplies,and establishment of makeshift shelter hospitals have been taken.The lockdown of Wuhan reduced the propagation of cases to other cities in Hubei province and throughout China,traffic and community restrictions reduced the flow of population and the spread of disease,increasing wards and beds and medical personnel reduced the incidence of severe cases and mortality,the establishment of the Fangcang shelter hospitals provided a good isolation and monitoring environment,and further reduced the spread and fatality of the disease.The fact that China was able to control the spread of COVID-19 within three months without a specific drug or vaccine suggests that these measures are more adequate and effective.

Analysis on psychological disorder and related factors in 98 patients with cancer and intervention measures thereon

Objective： The aim of this study was to analyze factors of psychological disorder experienced by 98 cancer patients and to probe into intervention measures in accordance with the corresponding bad psychological factors. Methods： A questionnaire survey was conducted in the test group （n = 98） by filling out a symptom checklist 90 （SCL-90）. And then the survey result was compared with the normal group （n = 1388） contained in relevant references. Results： Except for hostile factor that was similar to normal level （P 〉 0.05）, other 8 factors were higher than in normal group （P 〈 0.01）. And the cancer patients were classified with the survey results. Conclusion： Compared with normal persons, cancer patients have more psychological problems and related intervention measures are sought necessarily to improve the quality of life, to advance the immune function and to prolong the survival time of patients.

Current Situation and Mental Health and Intervention Measures of Left-behind Children

In the Outline of the Twelfth Five-Year Plan for National Economic and Social Development of the People's Republic of China,it proposed of improving distribution and form of urbanization and strengthening urbanization management. With acceleration of the urbanization,numerous rural labors flow to cities,and the number of left-behind children becomes increasingly large,which not only increases burden of family and education,but also gives rise to many mental problems. Due to lack of family education,many left-behind children have mental,emotional and ethical disorder and problem,which creates hidden trouble for building a harmonious society and economic development. This paper analyzed current situation and factors influencing mental health of left-behind children,including family environment,grandparent upbringing,and school environment. Finally,it came up with pertinent intervention measures from changing ideas of parents,improving the relationship between parents and children,and improving mental health education of schools.

Application of Intervention Measures in English Teaching

Students often have problems of one kind or another in the process of learning English.How to solve these problems has always been an important topic in the education field.This paper starts with the analysis of the characteristics of students'learning failure,and then puts forward the preconditions of effective interventions,and finally gives specific interventions.

Diarrhea Disease among Children under 5 Years of Age: A Global Systematic Review

Diarrhea diseases remain the second leading cause of death among children under five years globally. Nearly one in every five child deaths, about 1.6 million each year, are due to diarrhea. Further, diarrhea kills more young children than malaria, measles and Acquired Immunodeficiency Syndrome (AIDS) combined. As a result, better understanding of childhood diarrhea occurrence can perhaps help reduce associated morbidity and mortality rates. Therefore, this study conducted a global systematic review on occurrence of childhood diarrhea. The broad objective of this study was to review present and past researches on childhood diarrhea and most importantly for children under 5 years of age. The review focused on understanding the burden of diarrhea, causes of childhood diarrhea and solutions to the disease. A systematic literature review was conducted using the databases of PubMed, CINAHL, Web of Science and Google Scholar. Search key terms used were childhood diarrhea, risk factors and intervention practices. Journal articles and related reports were filtered and limited from 2005 to 2020. Sixty-one reports and articles that met inclusion criteria were used in this review. Review found that, childhood diarrhea imposes economic costs on the health system and families. Also, repeated bouts of diarrhea can lead to malnutrition, stunting and delayed brain growth later in life and can lead to stress and tension to the affected households. The dependence on open water sources which are often contaminated with fecal materials was found as the major cause of the rising prevalence of childhood diarrhea. Other important factors were poor hygienic practices and lack of sanitation facilities contribute to the spread of diarrhea diseases. Improvements in the quality of drinking water, sanitation facilities and hygiene practices especially in low and middle income countries have been suggested by many studies as an intervention to reduce childhood diarrhea.

Prediction of epidemics dynamics on networks with partial differential equations:A case study for COVID-19 in China

Since December 2019,the COVID-19 epidemic has repeatedly hit countries around the world due to various factors such as trade,national policies and the natural environment.To closely monitor the emergence of new COVID-19 clusters and ensure high prediction accuracy,we develop a new prediction framework for studying the spread of epidemic on networks based on partial differential equations(PDEs),which captures epidemic diffusion along the edges of a network driven by population flow data.In this paper,we focus on the effect of the population movement on the spread of COVID-19 in several cities from different geographic regions in China for describing the transmission characteristics of COVID-19.Experiment results show that the PDE model obtains relatively good prediction results compared with several typical mathematical models.Furthermore,we study the effectiveness of intervention measures,such as traffic lockdowns and social distancing,which provides a new approach for quantifying the effectiveness of the government policies toward controlling COVID-19 via the adaptive parameters of the model.To our knowledge,this work is the first attempt to apply the PDE model on networks with Baidu Migration Data for COVID-19 prediction.

Risk estimation and prediction of the transmission of coronavirus disease-2019(COVID-19)in the mainland of China excluding Hubei province

Background In December 2019,an outbreak of coronavirus disease(later named as COVID-19)was identified in Wuhan,China and,later on,detected in other parts of China.Our aim is to evaluate the effectiveness of the evolution of interventions and self-protection measures,estimate the risk of partial lifting control measures and predict the epidemic trend of the virus in the mainland of China excluding Hubei province based on the published data and a novel mathematical model.Methods A novel COVID-19 transmission dynamic model incorporating the intervention measures implemented in China is proposed.COVID-19 daily data of the mainland of China excluding Hubei province,including the cumulative confirmed cases,the cumulative deaths,newly confirmed cases and the cumulative recovered cases between 20 January and 3 March 2020,were archived from the National Health Commission of China(NHCC).We parameterize the model by using the Markov Chain Monte Carlo(MCMC)method and estimate the control reproduction number(Rc),as well as the effective daily reproduction ratio-Re(t),of the disease transmission in the mainland of China excluding Hubei province.Results The estimation outcomes indicate that Rc is 3.36(95%CI:3.20–3.64)and Re(t)has dropped below 1 since 31 January 2020,which implies that the containment strategies implemented by the Chinese government in the mainland of China are indeed effective and magnificently suppressed COVID-19 transmission.Moreover,our results show that relieving personal protection too early may lead to a prolonged disease transmission period and more people would be infected,and may even cause a second wave of epidemic or outbreaks.By calculating the effective reproduction ratio,we prove that the contact rate should be kept at least less than 30%of the normal level by April,2020.Conclusions To ensure the pandemic ending rapidly,it is necessary to maintain the current integrated restrict interventions and self-protection measures,including travel restriction,quarantine of entry,contact tracing followed by quarantine and isolation and reduction of contact,like wearing masks,keeping social distance,etc.People should be fully aware of the real-time epidemic situation and keep sufficient personal protection until April.If all the above conditions are met,the outbreak is expected to be ended by April in the mainland of China apart from Hubei province.

An evaluation of mathematical models for the outbreak of COVID-19

Mathematical modelling performs a vital part in estimating and controlling the recent outbreak of coronavirus disease 2019(COVID-19).In this epidemic,most countries impose severe intervention measures to contain the spread of COVID-19.The policymakers are forced to make difficult decisions to leverage between health and economic development.How and when tomake clinical and public health decisions in an epidemic situation is a challenging question.The most appropriate solution is based on scientific evidence,which is mainly dependent on data and models.So one of the most critical problems during this crisis is whether we can develop reliable epidemiological models to forecast the evolution of the virus and estimate the effectiveness of various intervention measures and their impacts on the economy.There are numerous types of mathematical model for epidemiological diseases.In this paper,we present some critical reviews on mathematical models for the outbreak of COVID-19.Some elementary models are presented as an initial formulation for an epidemic.We give some basic concepts,notations,and foundation for epidemiological modelling.More related works are also introduced and evaluated by considering epidemiological features such as disease tendency,latent effects,susceptibility,basic reproduction numbers,asymptomatic infections,herd immunity,and impact of the interventions.