Simulation of Spread of Infectious Diseases and Population Mobility in a Deterministic Epidemic Patch Model

Computer simulation models are widely applied in various areas of the health care sector, including the spread of infectious diseases. Patch models involve explicit movements of people between distinct locations. The aim of the present work has been designed and explored a patch model with population mobility between different patches and between each patch and an external population. The authors considered a SIR （susceptible-infected-recovered） scheme. The model was explored by computer simulations. The results show how endemic levels are reached in all patches of the system. Furthermore, the performed explorations suggest that the people mobility between patches, the immigration from outside the system and the infection rate in each patch, are factors that may influence the dynamics of epidemics and should be considered in health policy planning.

‘Outbreak Gold Standard’Selection to Provide Optimized Threshold for Infectious Diseases Early-alert Based on China Infectious Disease Automated-alert and Response System

The China Infectious Disease Automated-alert and Response System（CIDARS） was successfully implemented and became operational nationwide in 2008. The CIDARS plays an important role in and has been integrated into the routine outbreak monitoring efforts of the Center for Disease Control（CDC） at all levels in China. In the CIDARS, thresholds are determined using the ？Mean＋2SD？ in the early stage which have limitations. This study compared the performance of optimized thresholds defined using the ？Mean ＋2SD？ method to the performance of 5 novel algorithms to select optimal ？Outbreak Gold Standard（OGS）？ and corresponding thresholds for outbreak detection. Data for infectious disease were organized by calendar week and year. The ？Mean＋2 SD？, C1, C2, moving average（MA）, seasonal model（SM）, and cumulative sum（CUSUM） algorithms were applied. Outbreak signals for the predicted value（Px） were calculated using a percentile-based moving window. When the outbreak signals generated by an algorithm were in line with a Px generated outbreak signal for each week, this Px was then defined as the optimized threshold for that algorithm. In this study, six infectious diseases were selected and classified into TYPE A（chickenpox and mumps）, TYPE B（influenza and rubella） and TYPE C [hand foot and mouth disease（HFMD） and scarlet fever]. Optimized thresholds for chickenpox（P_（55））, mumps（P_（50））, influenza（P_（40）, P_（55）, and P_（75））, rubella（P_（45） and P_（75））, HFMD（P_（65） and P_（70））, and scarlet fever（P_（75） and P_（80）） were identified. The C1, C2, CUSUM, SM, and MA algorithms were appropriate for TYPE A. All 6 algorithms were appropriate for TYPE B. C1 and CUSUM algorithms were appropriate for TYPE C. It is critical to incorporate more flexible algorithms as OGS into the CIDRAS and to identify the proper OGS and corresponding recommended optimized threshold by different infectious disease types.

The difficulties of early detection for infectious disease outbreak in China:A qualitative investigation

Objective： To make intensified analysis upon the existing difficulties in early detection for the infectious diseases outbreak in China and put forward some effective measures to improve it. Methods： Field investigation and in-depth interview were applied in 23 interviewees from different-level CDC. Results：The study findings suggest that although the timeliness of outbreak detection has been improved since SARS epidemic in China, some problems still exist, such as： ① lacking syndrome surveillance; ② report quality of infectious disease should be improved; ③ difficulties of identifying the cases at lower social economic status; ④a definite financial compensation mechanism for the operation of web-based report system is absent; ⑤insufficient information exchange among different branches. Conclusion：Some effective measures must be taken including developing syndrome surveillance system; affording more education and txaining for related staff; increasing payout on surveillance and establishing an information exchange platform for early detection of disease outbreak.

Providing Infectious Disease Information to Child-Rearing Families and Its Evaluation

Background: Earlier study without actual trial indicated that caregivers needed delivery of information about outbreak situations independently of their job status. This report describes, for about two months in winter, actual delivery outbreak information to families with preschool children. The study objective was to confirm the usefulness of this information delivery. Method: Participants receiving outbreak information were recruited from the Child Care Support Service in a ward in Tokyo, Japan. Outbreak information was obtained from the Nursery School Absenteeism Surveillance System (NSASSy) covering approximately 40% of all nursery schools in Japan, prescription surveillance and other resources. Delivery of outbreak information started in December 2017 and ceased at the end of February in 2018. After the delivery period, a questionnaire survey was administered to participants. Results: For this area, NSASSy showed the most dominant disease was influenza, with 707 patients, followed by group A streptococcal pharyngitis with 98 patients. The outbreak peak was inferred to be as Monday, 22 January, and it was announced by e-mail on 23 January. Of the 202 persons joined this trial, 60 participants responded to the questionnaire survey after the delivery period. Of those respondents, 98% wanted delivery of that information to continue. Conclusion: We found that almost all respondents confirmed usefulness of the information about infectious diseases which was delivered.

Does Family with Children Need Information about Infectious Disease?

This paper reports a study of the necessity of providing information that is of the most concern of caregivers: health management, responses to sudden onset, and outbreaks of infectious diseases. We asked users and providers of Child Care Support Service in ward A of Tokyo, as respondents, whether they would like to receive information related to infectious diseases. Of questionnaires sent by mail to 383 providers and 3101 users, we received 18 responses from providers and 88 responses from users. All providers and users were required to provide information related to infectious diseases. The most often reported responses were “straight-out hand washing, mask wearing, gargling, and disinfection”, followed by “voluntary restraint of outside activities”, and “measures for illnesses of the family or children.” Results show that caregivers would like to receive information about infectious diseases because they have many health management concerns about their children.

Epidemiological Descriptive Analysis of Disease Outbreaks in 2019 in Sudan

Background: Sudan has often faced outbreaks of malaria, the life-threatening waterborne disease. In 2019, the country experienced an outbreak of six different infectious diseases, i.e., cholera, chikungunya, dengue fever, diphtheria, malaria, and Rift Valley fever. Objectives: The aim of this study was to perform an epidemiological descriptive analysis of data of these disease outbreaks to determine the spatial and temporal patterns of outbreaks and to estimate the magnitude of the diseases. Methods: The data consisted of the number of cases and deaths due to disease outbreaks of cholera, chikungunya, dengue fever, diphtheria, malaria, and Rift Valley fever. We analyzed the reports of an investigation conducted by the World Health Organization and the Federal Ministry of Health, Sudan. Descriptive statistics and case fatality rate (CFR) were used in this study. Results: The frequency of disease occurrence was as follows: cholera (344 cases), chikungunya (308 cases), dengue fever (4236 cases), diphtheria (105 cases), malaria (5,188,135 cases) and River Valley fever (567 cases). The CFRs for cholera, chikungunya, are diphtheria were 4.3%, 2.05%, and 9.5%, respectively. The mortality rate of malaria was 0.0013. The states most affected by outbreaks of these diseases in Sudan were the western states. Women were at a higher risk for all diseases, except River Valley fever. Conclusions: This study highlights the patterns of the outbreak of these diseases in Sudan and provides a basis for future scientific research.

The Cognitive Evolution from“Plague”to“Infectious Disease”

According to the Grand Chinese Dictionary,plague is defined to be an acute infectious disease.The Chinese term“infectious disease”is not what it is commonly thought originated from Japanese.The medical nomenclature shift from the traditional“plague”to the modern“infectious disease”is completed by the medical missionaries,Chinese scholars,and the national authority,each utilising different strategies.It is a history of acceptance concerning the concept of“infectious disease”from academia to national level.The conscious use of infectious disease-related thought and terminology by Chinese officials and doctors when studying infectious disease is a scientific modernization towards the understanding of epidemics.In a sense,this evolution of medical knowledge embodies the modernization of infectious disease in China.

Chinese Medicine,Which Targets Body's Response State,Is An Effective Way to Treat Epidemic Infectious Diseases

In the fight against epidemic infectious diseases in the past 2,000 years,Chinese medicine(CM)has gradually developed a complete response system including diagnosis and treatment.The focal point of CM in the treatment of infectious diseases is the personalized response state to pathogen,which is a treatment method consistent with the personalized concept of precision medicine.Compared with the methods of directly killing or inactivating pathogens,which are used in modern medicine,CM is an effective treatment modality that has a wider range of points of action in the human body.The remarkable effects achieved while treating SARS in 2003 and the current coronavirus disease 2019(COVID-19)pneumonia and the history of the effective responses to epidemics in the past 2,000 years have fully demonstrated the effectiveness of CM in treating infectious diseases.This article discusses the different treatment mechanisms for infectious diseases in CM and modern medicine and the advantages of CM methods,which will reacquaint the world with CM.The improvement of the diagnosis and treatment system of CM based on scientific concepts and methods and the organic combination of both treatment methods of modern medicine and CM will provide the best solution for humans to defeat epidemic infectious diseases.

First two months of the 2019 Coronavirus Disease(COVID-19)epidemic in China:realtime surveillance and evaluation with a second derivative model

Background:Similar to outbreaks of many other infectious diseases,success in controlling the novel 2019 coronavirus infection requires a timely and accurate monitoring of the epidemic,particularly during its early period with rather limited data while the need for information increases explosively.Methods:In this study,we used a second derivative model to characterize the coronavirus epidemic in China with cumulatively diagnosed cases during the first 2 months.The analysis was further enhanced by an exponential model with a close-population assumption.This model was built with the data and used to assess the detection rate during the study period,considering the differences between the true infections,detectable and detected cases.Results:Results from the second derivative modeling suggest the coronavirus epidemic as nonlinear and chaotic in nature.Although it emerged gradually,the epidemic was highly responsive to massive interventions initiated on January 21,2020,as indicated by results from both second derivative and exponential modeling analyses.The epidemic started to decelerate immediately after the massive actions.The results derived from our analysis signaled the decline of the epidemic 14 days before it eventually occurred on February 4,2020.Study findings further signaled an accelerated decline in the epidemic starting in 14 days on February 18,2020.Conclusions:The coronavirus epidemic appeared to be nonlinear and chaotic,and was responsive to effective interventions.The methods used in this study can be applied in surveillance to inform and encourage the general public,public health professionals,clinicians and decision-makers to take coordinative and collaborative efforts to control the epidemic.

Influence of population mobility on the novel coronavirus disease(COVID-19)epidemic:based on panel data from Hubei,China

Background:The novel coronavirus disease(COVID-19)was first reported in Wuhan,China.The mass population mobility in China during the Spring Festival has been considered a driver to the transmission of COVID-19,but it still needs more empirical discussion.Methods:Based on the panel data from Hubei,China between January 6th and February 6th,2020,a random effects model was used to estimate the impact of population mobility on the transmission of COVID-19.Stata version 12.0 was used,and p<0.05 was considered statistically significant.Results:The COVID-19 was more likely to be confirmed within 11-12 days after people moved from Wuhan to 16 other prefecture-level cities in Hubei Province,which suggests a period of 11-12 days from contact to being confirmed.The daily confirmed cases and daily increment in incidence in 16 prefecture-level cities show obvious declines 9-12 days post adaptation of city lockdown at the local level.Conclusion:Population mobility is found to be a driver to the rapid transmission of COVID-19,and the lockdown intervention in local prefecture-level cities of Hubei Province has been an effective strategy to block the COVID-19 epidemic.

Need of surveillance response systems to combat Ebola outbreaks and other emerging infectious diseases in African countries

There is growing concern in Sub-Saharan Africa about the spread of the Ebola virus disease(EVD),formerly known as Ebola haemorrhagic fever,and the public health burden that it ensues.Since 1976,there have been 885,343 suspected and laboratory confirmed cases of EVD and the disease has claimed 2,512 cases and 932 fatality in West Africa.There are certain requirements that must be met when responding to EVD outbreaks and this process could incur certain challenges.For the purposes of this paper,five have been identified:(i)the deficiency in the development and implementation of surveillance response systems against Ebola and others infectious disease outbreaks in Africa;(ii)the lack of education and knowledge resulting in an EVD outbreak triggering panic,anxiety,psychosocial trauma,isolation and dignity impounding,stigmatisation,community ostracism and resistance to associated socio-ecological and public health consequences;(iii)limited financial resources,human technical capacity and weak community and national health system operational plans for prevention and control responses,practices and management;(iv)inadequate leadership and coordination;and(v)the lack of development of new strategies,tools and approaches,such as improved diagnostics and novel therapies including vaccines which can assist in preventing,controlling and containing Ebola outbreaks as well as the spread of the disease.Hence,there is an urgent need to develop and implement an active early warning alert and surveillance response system for outbreak response and control of emerging infectious diseases.Understanding the unending risks of transmission dynamics and resurgence is essential in implementing rapid effective response interventions tailored to specific local settings and contexts.Therefore,the following actions are recommended:(i)national and regional inter-sectorial and trans-disciplinary surveillance response systems that include early warnings,as well as critical human resources development,must be quickly adopted by allied ministries and organisations in African countries in epidemic and pandemic responses;(ii)harnessing all stakeholders commitment and advocacy in sustained funding,collaboration,communication and networking including community participation to enhance a coordinated responses,as well as tracking and prompt case management to combat challenges;(iii)more research and development in new drug discovery and vaccines;and(iv)understanding the involvement of global health to promote the establishment of public health surveillance response systems with functions of early warning,as well as monitoring and evaluation in upholding research-action programmes and innovative interventions.

Nanopore sequencing: a rapid solution for infectious disease epidemics

Emerging and re-emerging infectious diseases have given rise to a large number of human infections,morbidity,and heavy economic burden,including the Middle East respiratory syndrome caused by a coronavirus in 2012,global influenza pandemic caused by the H7N9 influenza A virus in2013,Ebola epidemic in West Africa in 2014,and Lassa fever epidemic in Nigeria in 2019.The healthcare war against viruses deserves constant surveillance due to the continuous emergence of new viruses and rapid evolution of existing viruses(Liu and Liu,2017).

Using Interrupted Time Series Design to Analyze Changes in Hand, Foot, and Mouth Disease Incidence during the Declining Incidence Periods of 2008-2010 in China

Objective To identify patterns of hand, foot and mouth disease （HFMD） incidence in China during declining incidence periods of 2008, 2009, and 2010. Methods Reported HFMD cases over a period of 25 months were extracted from the National Disease Reporting System （NDRS） and analyzed. An interrupted time series （ITS） technique was used to detect changes in HFMD incidence rates in terms of level and slope between declining incidence periods of the three years. Results Over 3.58 million HFMD cases younger than 5 years were reported to the NDRS between May 1, 2008, and May 31, 2011. Males comprised 63.4% of the cases. ITS analyses demonstrated a significant increase in incidence rate level （P〈0.0001） when comparing the current period with the previous period. There were significant changes in declining slopes when comparing 2010 to 2009, and 2010 to 2008 （all P〈O.O05）, but not 2009 to 2008. Conclusion Incremental changes in incidence rate level during the declining incidence periods of 2009 and 2010 can potentially be attributed to a few factors. The more steeply declining slope in 2010 compared with previous years could be ascribed to the implementation of more effective interventions and preventive strategies in 2010. Further investigation is required to examine this possibility.

Clostridium difficile infection in the community:Are proton pump inhibitors to blame?

Once a nosocomial disease,Clostridium difficile infection(CDI)now appears frequently in the community in the absence of exposure to antibiotics.Prior studies have shown that patients with community-acquired CDI are younger,more likely to be female,and have fewer comorbidities compared to patients with hospital-associated CDI.Because most studies of CDI are hospitalbased,comparatively little is known about communityacquired CDI.The recent study by Chitnis has received widespread attention because it used active surveillance to capture all cases of community-acquired CDI within a large population and assessed key risk factors.The authors found that low-level healthcare exposure and proton pump inhibitor use were common among those with non-antibiotics associated,community-acquired CDI.In this commentary,we discuss the changing epidemiology of community-acquired CDI and the evidence basis for the controversial association between proton pump inhibitors and community-acquired CDI.

Modelling epidemic growth models for lumpy skin disease cases in Thailand using nationwide outbreak data,2021e2022

Lumpy skin disease(LSD)is a transboundary disease affecting cattle and has a detrimental effect on the cattle industries in numerous countries in Africa,Europe and Asia.In 2021,LSD outbreaks have been reported in almost all of Thailand's provinces.Indeed,fitting LSD occurrences using mathematical models provide important knowledge in the realm of animal disease modeling.Thus,the objective of this study is to fit the pattern of daily new LSD cases and daily cumulative LSD cases in Thailand using mathematical models.The first-and second-order models in the forms of Lorentzian,Gaussian and Pearson-type VII models are used to fit daily new LSD cases whereas Richard's growth,Boltzmann sigmoidal and Power-law growth models are utilized to fit the curve of cumulative LSD cases.Based on the root-mean-squared error(RMSE)and Akaike information criterion(AIC),results showed that both first and second orders of Pearson-type VII models and Richard's growth model(RGM)were fit to the data better than other models used in the present study.The obtained models and their parameters can be utilized to describe the LSD outbreak in Thailand.For disease preparedness purposes,we can use the first order of the Pearson-type VII model to estimate the time of maximum infected cases occurring when the growth rate of infected cases starts to slow down.Furthermore,the period when the growth rate changes at a slower rate,known as the inflection time,obtained from RGM allows us to anticipate when the pandemic has peaked and the situation has stabilized.This is the first study that utilizes mathematical methods to fit the LSD epidemics in Thailand.This study offers decision-makers and authorities with valuable information for establishing an effective disease control strategy.

Current Status and Stategies of Infectious Diseases among Migratory Population in Wenzhou

Along with increase of the migratory population as the development of economy, the morbidities of some infec- tious diseases increases among mingratory population in some areas in the current years. The epidemiological characteris tics of infectious diseases among migratory, population differ from them of local residents. In this article we described the current status and its reasons of occurrences and outbreaks of some infectious diseases among the migratory population in Wenzhou city, and provided the strategies on control and Prevention for infectious diseases accordingly.

重大传染病疫情下应急医疗物资需求预测和配置研究

为了科学合理地进行应急医疗物资配置,提高重大传染病疫情防控效率,根据疫情演化不同阶段的特点开展应急医疗物资需求预测和配置研究。首先,根据疫情数据特征,提出传染病模型SEIR(Susceptible Exposed Infectious Recovered)和长短期记忆(Long Short-Term Memory,LSTM)网络相结合的模型(SEIR-LSTM)预测各需求点的应急医疗物资需求量,该方法利用LSTM对时间序列数据良好的学习能力预测感染率,输入SEIR模型提高预测准确率。然后,根据传染病疫情演化关键阶段的特点,考虑物资配送成本、需求紧迫度和分配公平性等因素构建分阶段多目标物资配置模型。最后,以上海新冠肺炎疫情进行实例分析,结果表明,基于SEIR-LSTM的应急物资需求量预测方法准确率较高,根据分阶段配置模型求出的方案能够满足各个阶段物资分配的要求,验证了提出的模型和算法的有效性。

2013—2022年桐乡市法定传染病流行特征分析

目的分析桐乡市法定传染病流行特征,为制定有效的防控措施提供科学依据。方法对2013—2022年桐乡市法定传染病报告的发病情况数据,采用描述性流行病学方法进行分析。结果全市无甲类传染病报告,共报告法定传染病29种47944例,年均发病率546.69/10万,报告死亡病例43例,年均死亡率0.49/10万;发病数居前5位的病种依次为其他感染性腹泻病、手足口病、淋病、梅毒、肺结核,占传染病发病报告总数的86.64%;三间分布疫情特征符合传染病发病特点;传播途径构成比从高到低依次为肠道传染病61.03%、血源及性传播传染病23.11%、呼吸道传染病15.41%、自然疫源及虫媒传染病0.39%、其他途径0.06%;低年龄组(0~<15岁)发病以其他感染性腹泻和手足口病为主。结论托幼机构、学校等人员密集单位需要重点关注以其他感染性腹泻病、手足口病、流行性感冒等肠道和呼吸道传染病的防控;成人需要关注淋病、梅毒等性传播疾病和其他感染性腹泻等肠道传染病,加强健康教育宣传,提高防病意识,降低传染病发病率。

基于风险评估模型的传染病预警体系的建立

目的建立一套基于风险评估模型的传染病预警体系,推动传染病管理水平的提升。方法通过搜集、整理最新的研究成果,参考相关的传染病预警评价指标体系的理论框架,构建基于风险评估模型的传染病预警体系。结果本次研究共纳入了12名专家,筛选出了三个一级指标,涉及流行前期指标、典型症状期指标、非典型症状期指标等,同时涉及7个二级指标。体系的必要性平均得分为8.27±0.24分,可获得性平均得分为7.74±0.34分。结论基于风险评估模型的传染病预警体系的建立有利于当地及时掌握传染病流行趋势,并进行调查指标分布趋势分析,然后提出相应的预警方案,可为有效预防传染病提供相关的依据。

公众感知下重大传染病疫情冲击对社区韧性驱动因子独立、耦合作用及区域异质性分析

目的:探究公众感知下重大传染病疫情冲击对社区韧性驱动因子独立、耦合作用及区域特征,为后续精准施策提供理论依据。方法:采用网络调查法在我国东、中、西部各选一个省会城市展开调查,运用地理探测器和ESDA对社区韧性驱动因子进行探测并比较区域异质性特征。结果:政府公信力(0.322)、应急物品准备情况(0.297)是社区韧性的主导因子;任意两因子耦合对社区韧性的解释力均显著增强;各驱动因子对社区韧性的影响在空间上存在差异性,且“风险意识”“政府公信力”“家庭应急计划”是造成区域异质性的关键因子。结论:重大传染病疫情冲击下的社区韧性是多因子耦合作用的结果,多因子耦合对社区韧性的复杂影响需要多部门、多阶段、多机制因地制宜采取差异化的举措,全方位提升社区韧性。