Research about the optimal strategies for prevention and control of varicella outbreak in a school in a central city of China: based on an SEIR dynamic model

Abstract Varicella is an acute respiratory infectious diseases, with high transmissibility and quick dissemination. In this study, an SEIR (susceptible-exposed-infected-recovered) dynamic model was established to explore the optimal prevention and control measures according to the epidemiological characteristics about varicella outbreak in a school in a central city of China. Berkeley Madonna 8.3.18 and Microsoft Office Excel 2010 software were employed for the model simulation and data management, respectively. The result showed that the simulated result of SEIR model agreed well with the reported data when β (infected rate) equal to 0.067. Models showed that the cumulative number of cases was only 13 when isolation adopted when the infected individuals were identified (assuming isolation rate was up to 100%); the cumulative number of cases was only two and the TAR (total attack rate) was 0.56% when the vaccination coefficient reached 50%. The cumulative number of cases did not change significantly with the change of efficiency of ventilation and disinfection, but the peak time was delayed; when δ (vaccination coefficient) = 0.1, m (ventilation efficiency) = 0.7 or δ = 0.2, m = 0.5 or δ = 0.3, m = 0.1 or δ = 0.4 and above, the cumulative number of cases would reduce to one case and TAR would reduce to 0.28% with combined interventions. Varicella outbreak in school could be controlled through strict isolation or vaccination singly; combined interventions have been adopted when the vaccination coefficient was low.

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Policy disparities in response to COVID-19 between Singapore and China

International Journal for Equity in Health ◽

10.1186/s12939-021-01525-z ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Xiaohan Wang ◽

Leiyu Shi ◽

Yuyao Zhang ◽

Haiqian Chen ◽

Gang Sun

Keyword(s):

Public Health ◽

Urban Communities ◽

Prevention And Control ◽

Central Government ◽

Control Measures ◽

Cumulative Number ◽

Control Policies ◽

Response Strategies ◽

Set Up ◽

And Control

Abstract Objective The study analyzed the common points and discrepancies of COVID-19 control measures of the two countries in order to provide appropriate coping experiences for countries all over the world. Method This study examined the associations between the epidemic prevention and control policies adopted in the first 70 days after the outbreak and the number of confirmed cases in China and Singapore using the generalized linear model. Policy comparisons and disparities between the two countries were also discussed. Results The regression models show that factors influencing the cumulative number of confirmed cases in China: Locking down epicenter; activating Level One public health emergency response in all localities; the central government set up a leading group; classified management of “four categories of personnel”; launching makeshift hospitals; digital management for a matrix of urban communities; counterpart assistance. The following four factors were the key influencing factors of the cumulative confirmed cases in Singapore: The National Centre for Infectious Diseases screening center opens; border control measures; surveillance measures; Public Health Preparedness Clinics launched. Conclusions Through analyzing the key epidemic prevention and control policies of the two countries, we found that the following factors are critical to combat COVID-19: active case detection, early detection of patients, timely isolation, and treatment, and increasing of medical capabilities. Countries should choose appropriate response strategies with health equity in mind to ultimately control effectively the spread of COVID-19 worldwide.

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Epidemiological study of scarlet fever in Shenyang, China

BMC Infectious Diseases ◽

10.1186/s12879-019-4705-9 ◽

2019 ◽

Vol 19 (1) ◽

Author(s):

Huijie Chen ◽

Ye Chen ◽

Baijun Sun ◽

Lihai Wen ◽

Xiangdong An

Keyword(s):

Rural Areas ◽

Scarlet Fever ◽

Urban Areas ◽

Primary Schools ◽

Prevention And Control ◽

Hot Spot ◽

Temporal Distribution ◽

Control Measures ◽

And Control ◽

Epidemiological Characteristics

Abstract Background Since 2011, there has been an increase in the incidence of scarlet fever across China. The main objective of this study was to depict the spatiotemporal epidemiological characteristics of the incidence of scarlet fever in Shenyang, China, in 2018 so as to provide the scientific basis for effective strategies of scarlet control and prevention. Methods Excel 2010 was used to demonstrate the temporal distribution at the month level and ArcGIS10.3 was used to demonstrate the spatial distribution at the district/county level. Moran’s autocorrelation coefficient was used to examine the spatial autocorrelation and the Getis-Ord statistic was used to determine the hot-spot areas of scarlet fever. Results A total of 2314 scarlet fever cases were reported in Shenyang in 2018 with an annual incidence of 31.24 per 100,000. The incidence among males was higher than that among females(p<0.001). A vast majority of the cases (96.89%) were among children aged 3 to 11 years. The highest incidence was 625.34/100,000 in children aged 5–9 years. In 2018 there were two seasonal peaks of scarlet fever in June (summer-peak) and December (winter-peak). The incidence of scarlet fever in urban areas was significantly higher than that in rural areas(p<0.001). The incidence of scarlet fever was randomly distributed in Shenyang. There are hotspot areas located in seven districts. Conclusions Urban areas are the hot spots of scarlet fever and joint prevention and control measures between districts should be applied. Children aged 3–11 are the main source of scarlet fever and therefore the introduction of prevention and control into kindergarten and primary schools may be key to the control of scarlet fever epidemics.

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Epidemiological study of scarlet fever in Shenyang , China

10.21203/rs.2.10104/v4 ◽

2019 ◽

Author(s):

Huijie Chen ◽

Ye Chen ◽

Baijun Sun ◽

Lihai Wen ◽

Xiangdong An

Keyword(s):

Rural Areas ◽

Scarlet Fever ◽

Urban Areas ◽

Primary Schools ◽

Prevention And Control ◽

Hot Spot ◽

Temporal Distribution ◽

Control Measures ◽

And Control ◽

Epidemiological Characteristics

Abstract Background: Since 2011, there has been an increase in the incidence of scarlet fever across China. The main objective of this study was to depict the spatiotemporal epidemiological characteristics of the incidence of scarlet fever in Shenyang, China, in 2018 so as to provide the scientific basis for effective strategies of scarlet control and prevention. Methods: Excel 2010 was used to demonstrate the temporal distribution at the month level and ArcGIS10.3 was used to demonstrate the spatial distribution at the district/county level. Moran’s autocorrelation coefficient was used to examine the spatial autocorrelation and the Getis-Ord statistic was used to determine the hot-spot areas of scarlet fever. Results: A total of 2,314 scarlet fever cases were reported in Shenyang in 2018 with an annual incidence of 31.24 per 100,000. The incidence among males was higher than that among females（p＜0.001). A vast majority of the cases (96.89%) were among children aged 3 to 11 years. The highest incidence was 625.34/100,000 in children aged 5-9 years. In 2018 there were two seasonal peaks of scarlet fever in June (summer-peak) and December (winter-peak).The incidence of scarlet fever in urban areas was significantly higher than that in rural areas(p＜0.001).The incidence of scarlet fever was randomly distributed in Shenyang. There are hotspot areas located in seven districts. Conclusions: Urban areas are the hot spots of scarlet fever and joint prevention and control measures between districts should be applied. Children aged 3-11 are the main source of scarlet fever and therefore the introduction of prevention and control into kindergarten and primary schools may be key to the control of scarlet fever epidemics.

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Prevention and control measures of the major cold-region diseases (hypertension) in China

Frigid Zone Medicine ◽

10.2478/fzm-2021-0002 ◽

2021 ◽

Vol 1 (1) ◽

pp. 3-8

Author(s):

Zhenwei Pan ◽

Yong Zhang ◽

Tengfei Pan ◽

Haihai Liang ◽

Baofeng Yang

Keyword(s):

Risk Factors ◽

Cardiovascular Events ◽

Prevention And Control ◽

Control Measures ◽

Effective Management ◽

Cold Region ◽

Low Latitude ◽

Prevention And Control Measures ◽

And Control ◽

Epidemiological Characteristics

Abstract Hypertension is the most common cardiovascular condition in clinical practice and a major risk factor for stroke and cardiovascular events. There are more than 270 million hypertension patients in China, and the prevalence of hypertension in the high-latitude cold areas is significantly higher than in the low-latitude warm areas. The unique epidemiological characteristics and risk factors of hypertension in the cold regions of China urge for establishment of the prevention and control system for targeted and more effective management of the condition.

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Epidemiological study of scarlet fever in Shenyang City, China

10.21203/rs.2.10104/v1 ◽

2019 ◽

Author(s):

Huijie Chen ◽

Ye Chen ◽

Baijun Sun ◽

Lihai Wen ◽

Xiangdong An

Keyword(s):

Rural Areas ◽

Hot Spots ◽

Scarlet Fever ◽

Urban Areas ◽

Primary Schools ◽

Prevention And Control ◽

Hot Spot ◽

Control Measures ◽

And Control ◽

Epidemiological Characteristics

Abstract Objectives: To depict the Spatiotemporal epidemiological characteristics of the incidence of scarlet fever in Shenyang, China, in 2018 so as to provide the scientific basis for effective strategies of scarlet control and prevention. Methods: Excel 2010 was used to demonstrate the temporal distribution at the month level and ArcGIS10.3 was used to demonstrate the spatial distribution at the district/county level. Moran’s autocorrelation coefficient was used to examine the spatial autocorrelation and the Getis-Ord statistic was used to determine the hot-spot areas of scarlet fever. Results: A total of 2,314 scarlet fever cases were reported in Shenyang in 2018 with an annual incidence of 31.24 per 100,000. The incidence among males was higher than that among females(X2=95.013, P≤0.001). A vast majority of the cases (96.89%) were among children aged 3 to 11 years. The highest incidence was 625.34/100,000 in children aged 5-9 years. There are two seasonal peaks occurred in June (Summer-peak) and in December (Winter-peak) in 2018. The incidence of scarlet fever in urban areas was significantly higher than that in rural areas(X2=514.115, P≤0.001).The incidence of scarlet fever was randomly distributed in Shenyang. There are hot-spots areas located in seven districts. Conclusions: Urban areas are the hot spots of scarlet fever and joint prevention and control measures between districts should be applied. Children in the kindergartens and the primary school students are the main population of scarlet fever and the time distribution of scarlet fever is highly consistent with their school and vacation time. It is suggested that measure for prevention and control of scarlet fever in kindergartens and primary schools is the key to control the epidemic of scarlet fever.

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Estimating the Transmissibility of Mumps: A Modelling Study in Wuhan City, China

Frontiers in Medicine ◽

10.3389/fmed.2021.683720 ◽

2021 ◽

Vol 8 ◽

Author(s):

Ying Peng ◽

Tianlong Yang ◽

Yuanzhao Zhu ◽

Qingqing Hu ◽

Yao Wang ◽

...

Keyword(s):

Incidence Rate ◽

Transmission Capacity ◽

Control Measures ◽

Peak Time ◽

Peak Incidence ◽

Incidence Data ◽

National Immunization ◽

Prevention And Control Measures ◽

And Control ◽

Epidemiological Characteristics

Despite the adoption of a national immunization program in China, the incidence of mumps remains high. This study aimed to describe the epidemiological characteristics, including the time, region, occupation, and age, of mumps in Wuhan from 2005 to 2018 and to evaluate its transmissibility. In this study, the susceptible–exposed–infectious–asymptomatic–recovered (SEIAR) model fitted the actual incidence data of mumps. The effective reproduction number (Rt) was used to evaluate and compare the transmission capacity in different areas. From 2005 to 2018, there were 36,415 cases. The incidence of mumps was highest among people aged 5–10 years (460.02 per 100,000). The SEIAR model fitted the reported mumps data well (P < 0.01). The median transmissibility (Rt) was 1.04 (range = 0–2.50). There were two peak spreads every year (from March to May and from October to December). The Rt peak always appeared in the first 2 months of the peak incidence rate. The peak time of the epidemic spread of mumps was 1–2 months earlier than the peak incidence rate. The prevention and control measures of vaccination for children aged 5–10 years should be taken before the peak transmission capacity each year, 2 months before the peak of the outbreak, to reduce the spread of mumps.

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Epidemiological study of scarlet fever in Shenyang , China

10.21203/rs.2.10104/v2 ◽

2019 ◽

Author(s):

Huijie Chen ◽

Ye Chen ◽

Baijun Sun ◽

Lihai Wen ◽

Xiangdong An

Keyword(s):

Rural Areas ◽

Scarlet Fever ◽

Urban Areas ◽

Primary Schools ◽

Prevention And Control ◽

Hot Spot ◽

Temporal Distribution ◽

Control Measures ◽

And Control ◽

Epidemiological Characteristics

Abstract Background : Since 2011, the rising incidence of scarlet fever has exerted a marked influence on people. The main objective of this study was to depict the Spatiotemporal epidemiological characteristics of the incidence of scarlet fever in Shenyang, China, in 2018 so as to provide the scientific basis for effective strategies of scarlet control and prevention. Methods: Excel 2010 was used to demonstrate the temporal distribution at the month level and ArcGIS10.3 was used to demonstrate the spatial distribution at the district/county level. Moran’s autocorrelation coefficient was used to examine the spatial autocorrelation and the Getis-Ord statistic was used to determine the hot-spot areas of scarlet fever. Results: A total of 2,314 scarlet fever cases were reported in Shenyang in 2018 with an annual incidence of 31.24 per 100,000. The incidence among males was higher than that among females（ p ＜0.001). A vast majority of the cases (96.89%) were among children aged 3 to 11 years. The highest incidence was 625.34/100,000 in children aged 5-9 years. There are two seasonal peaks occurred in June (Summer-peak) and in December (Winter-peak) in 2018. The incidence of scarlet fever in urban areas was significantly higher than that in rural areas( p ＜0.001).The incidence of scarlet fever was randomly distributed in Shenyang. There are hotspot areas located in seven districts. Conclusions: Urban areas are the hot spots of scarlet fever and joint prevention and control measures between districts should be applied. Children in the kindergartens and the primary schools are the main population of scarlet fever and measures for prevention and control in kindergartens and primary schools may be the key to control the epidemic of scarlet fever.

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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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Assessment and forecasting the spread of SARS-CoV-2 outbreak in Changsha, China: Based on a SEIAR Dynamic Model

10.21203/rs.3.rs-16659/v1 ◽

2020 ◽

Author(s):

Wenting Zha ◽

Nan Zhou ◽

Guoqun Li ◽

Weitong Li ◽

Heng Zhang ◽

...

Keyword(s):

Prevention And Control ◽

Model Simulation ◽

Control Measures ◽

Capital City ◽

Time To Peak ◽

First Case ◽

Number Of Patients ◽

Prevention And Control Measures ◽

Fourth Order Method ◽

And Control

Abstract Background: A new human coronavirus named SARS-CoV-2 emerged during December 2019 in Wuhan, China. Cases have been exported to other Chinese cities and abroad, which may cause the global outbreak. Chang Sha is the nearest provincial capital city to Wuhan, the first case of COVID-19 in Changsha was diagnosed on January 21, 2020. Estimating the transmissibility and forecasting the trend of the outbreak of SARS-CoV-2 under the prevention and control measures in Changsha could inform evidence based decisions to policy makers. Methods: Data were collected from the Health Commission of Changsha and Hunan Center for Disease Control and Prevention. A Susceptible-exposed-infections/ asymptomatic- removed (SEIAR) model was established to simulate the transmission of SARS-CoV-2 in Changsha. Berkeley Madonna 8.3.18 were employed for the model simulation and prediction, while the curve fitting problem was solved by the Runge-Kutta fourth-order method, with a tolerance of 0.001. Results: In this study, we found that Rt was 2.05 from January 21 to 27 and reduced to 0.2 after January 27, 2020 in Changsha. The prediction results showed that when no obvious prevention and control measures were applied, the total number of patients in Changsha would reach the maximum (2.27 million) on the 79th day after the outbreak, and end in about 240 days; When measures have not been fully launched, the total number of patients would reach the maximum (1.60 million) on the 28th day after the outbreak, and end in about 110 days; When measures have been fully launched, the total number of patients would reach the maximum (234) on the 23rd day after the outbreak, and end in about 60 days. Conclusions: Outbreak of SARS-CoV-2 in Changsha is in a controllable stage under current prevention and control measures, it is predicted that the cumulative patients would reach the maximum of 234 on February 12, and the outbreak would be over on 20 March in Changsha. With the fully implementation of prevention and control measures, it could effectively reduce the peak value, short the time to peak and duration of the outbreak.

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