scholarly journals Predictive analysis of the number of human brucellosis cases in Xinjiang, China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yanling Zheng ◽  
Liping Zhang ◽  
Chunxia Wang ◽  
Kai Wang ◽  
Gang Guo ◽  
...  
Keyword(s):  
Public Health ◽  
Time Series ◽  
Prevention And Control ◽  
Prediction Models ◽  
Moving Average ◽  
Time Lag ◽  
Health Concern ◽  
Human Brucellosis ◽  
Prediction Analysis ◽  
And Control

AbstractBrucellosis is one of the major public health problems in China, and human brucellosis represents a serious public health concern in Xinjiang and requires a prediction analysis to help making early planning and putting forward science preventive and control countermeasures. According to the characteristics of the time series of monthly reported cases of human brucellosis in Xinjiang from January 2008 to June 2020, we used seasonal autoregressive integrated moving average (SARIMA) method and nonlinear autoregressive regression neural network (NARNN) method, which are widely prevalent and have high prediction accuracy, to construct prediction models and make prediction analysis. Finally, we established the SARIMA((1,4,5,7),0,0)(0,1,2)12 model and the NARNN model with a time lag of 5 and a hidden layer neuron of 10. Both models have high fitting performance. After comparing the accuracies of two established models, we found that the SARIMA((1,4,5,7),0,0)(0,1,2)12 model was better than the NARNN model. We used the SARIMA((1,4,5,7),0,0)(0,1,2)12 model to predict the number of monthly reported cases of human brucellosis in Xinjiang from July 2020 to December 2021, and the results showed that the fluctuation of the time series from July 2020 to December 2021 was similar to that of the last year and a half while maintaining the current prevention and control ability. The methodology applied here and its prediction values of this study could be useful to give a scientific reference for prevention and control human brucellosis.

scholarly journals Predictive study of tuberculosis incidence by time series method and Elman neural network in Kashgar, China

BMJ Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. e041040
Author(s):  
Yanling Zheng ◽  
Xueliang Zhang ◽  
Xijiang Wang ◽  
Kai Wang ◽  
Yan Cui
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Hybrid Model ◽  
Hybrid Method ◽  
Prevention And Control ◽  
Temporal Trends ◽  
Percentage Error ◽  
Elman Neural Network ◽  
Prediction Analysis ◽  
And Control

ObjectivesKashgar, located in Xinjiang, China has a high incidence of tuberculosis (TB) making prevention and control extremely difficult. In addition, there have been very few prediction studies on TB incidence here. We; therefore, considered it a high priority to do prediction analysis of TB incidence in Kashgar, and so provide a scientific reference for eventual prevention and control.DesignTime series study.Setting Kashgar, ChinaKashgar, China.MethodsWe used a single Box-Jenkins method and a Box-Jenkins and Elman neural network (ElmanNN) hybrid method to do prediction analysis of TB incidence in Kashgar. Root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) were used to measure the prediction accuracy.ResultsAfter careful analysis, the single autoregression (AR) (1, 2, 8) model and the AR (1, 2, 8)-ElmanNN (AR-Elman) hybrid model were established, and the optimal neurons value of the AR-Elman hybrid model is 6. In the fitting dataset, the RMSE, MAE and MAPE were 6.15, 4.33 and 0.2858, respectively, for the AR (1, 2, 8) model, and 3.78, 3.38 and 0.1837, respectively, for the AR-Elman hybrid model. In the forecasting dataset, the RMSE, MAE and MAPE were 10.88, 8.75 and 0.2029, respectively, for the AR (1, 2, 8) model, and 8.86, 7.29 and 0.2006, respectively, for the AR-Elman hybrid model.ConclusionsBoth the single AR (1, 2, 8) model and the AR-Elman model could be used to predict the TB incidence in Kashgar, but the modelling and validation scale-dependent measures (RMSE, MAE and MAPE) in the AR (1, 2, 8) model were inferior to those in the AR-Elman hybrid model, which indicated that the AR-Elman hybrid model was better than the AR (1, 2, 8) model. The Box-Jenkins and ElmanNN hybrid method therefore can be highlighted in predicting the temporal trends of TB incidence in Kashgar, which may act as the potential for far-reaching implications for prevention and control of TB.

scholarly journals Forecasting hand-foot-and-mouth disease cases using wavelet-based SARIMA–NNAR hybrid model

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246673
Author(s):  
Gongchao Yu ◽  
Huifen Feng ◽  
Shuang Feng ◽  
Jing Zhao ◽  
Jing Xu
Keyword(s):  
Time Series ◽  
Hybrid Model ◽  
Prevention And Control ◽  
Moving Average ◽  
Foot And Mouth Disease ◽  
Hybrid Models ◽  
High Morbidity ◽  
Foot And Mouth ◽  
And Control ◽  
Nonlinear Autoregressive

Background Hand-foot-and-mouth disease_(HFMD) is one of the most typical diseases in children that is associated with high morbidity. Reliable forecasting is crucial for prevention and control. Recently, hybrid models have become popular, and wavelet analysis has been widely performed. Better prediction accuracy may be achieved using wavelet-based hybrid models. Thus, our aim is to forecast number of HFMD cases with wavelet-based hybrid models. Materials and methods We fitted a wavelet-based seasonal autoregressive integrated moving average (SARIMA)–neural network nonlinear autoregressive (NNAR) hybrid model with HFMD weekly cases from 2009 to 2016 in Zhengzhou, China. Additionally, a single SARIMA model, simplex NNAR model, and pure SARIMA–NNAR hybrid model were established for comparison and estimation. Results The wavelet-based SARIMA–NNAR hybrid model demonstrates excellent performance whether in fitting or forecasting compared with other models. Its fitted and forecasting time series are similar to the actual observed time series. Conclusions The wavelet-based SARIMA–NNAR hybrid model fitted in this study is suitable for forecasting the number of HFMD cases. Hence, it will facilitate the prevention and control of HFMD.

scholarly journals ANTIMICROBIAL RESISTANCE (AMR)-FORECAST FOR 30 COUNTRIES IN EUROPE

2021 ◽  
Vol 5 (2) ◽  
pp. 44-48
Author(s):  
M. Z. A. M. Jaffar ◽  
A. N. Zailan
Keyword(s):  
Public Health ◽  
Time Series ◽  
Antimicrobial Resistance ◽  
Disease Prevention ◽  
Prevention And Control ◽  
Implementation Strategies ◽  
Annual Data ◽  
Health Issues ◽  
Microbial Groups ◽  
And Control

Antimicrobial resistance (AMR) has emerged among the most serious public health issues, prompting the creation of worldwide implementation strategies. In this study, the application of seasonal or time-series approaches was suggested for forecasting the unknown percentages of resistance towards other microbial groups for seven microorganisms. Annual data between 2012 and 2019 were acquired from European Centre for Disease Prevention, and Control (ECDC) reports. Microsoft Excel’s function, ‘FORECAST.ETS’, was used for prediction purposes. Then, a brief analysis was done on the forecasted results. Forecasting AMR’s percentage makes it possible to develop a strategy for dealing with any situation that may emerge.

scholarly journals Global public health significances, health care perception of community, treatments, prevention and control methods of COVID-19

2020 ◽  
pp. 1-9
Author(s):  
Addis Adera Gebru ◽  
Tadesse Birhanu ◽  
Eshetu Wendimu ◽  
Agumas Fentahun Ayalew ◽  
Selamawit Mulat ◽  
...  
Keyword(s):  
Public Health ◽  
Health Care ◽  
Prevention And Control ◽  
Public Health Emergency ◽  
Health Concern ◽  
Control Methods ◽  
Global Public Health ◽  
Novel Coronavirus ◽  
And Control ◽  
Care Perception

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) is one of the most burden respiratory diseases outbreak. Moreover, the public health emergency to fight COVID-19 outbreak was stated by world health organization as global health concern since March, 2020. However, there has been significantly increased morbidity and moratlity of the community in worldwide.The objective of the review was to describe and review the global public health significances and community and health care perception on features, treatments, prevention and control methods of the Outbreak to slow transmission. METHODS: In this review, the literatures were searched by following online databases which include medRxiv, pubmed, medline and Google scholar databases. The ‘COVID-19’, ‘2019 novel coronavirus’, ‘2019-nCoV’, ‘novel coronavirus’and ‘Pneumonia’ key search terms were used to search the literatures. Scientific papers published online by Center for Disease Control (CDC) and WHO from 1 January to 6 May, 2020 in English language were included for analysis. RESULTS: The result of review indicated that COVID-19 is the serious global public health problem. It more affects immune compromised individuals who are living with chronic diseases, aged and pregnant women. The disease spreads rapidly from one country to countries worldwidely. The 212 countries were highlighted the weakened state of essential public health emergency services. The researchers were addressed lack of communities’ perception including health professionals’ against COVID-19. The

scholarly journals Forecasting Hand-Foot-and-Mouth Disease Cases Using a Wavelet-based SARIMA-NNAR Hybrid Model

2020 ◽  
Author(s):  
Gongchao Yu ◽  
Huifen Feng ◽  
Shuang Feng ◽  
Jing Zhao ◽  
Jing Xu
Keyword(s):  
Time Series ◽  
Hybrid Model ◽  
Prevention And Control ◽  
Moving Average ◽  
Foot And Mouth Disease ◽  
Hybrid Models ◽  
Mouth Disease ◽  
High Morbidity ◽  
Foot And Mouth ◽  
And Control

Abstract Background: Hand-foot-and-mouth disease(HFMD) is one of the most common diseases in children, which has high morbidity. Reliable forecasting is significant for prevention and control. Recently, hybrid models have been becoming popular and wavelet analysis has been widely used. Better prediction accuracy may be achieved with wavelet-based hybrid models. Thus, our aim is to forecast number of HFMD cases with wavelet-based hybrid models.Materials and methods: We fitted a wavelet-based SARIMA(seasonal autoregressive integrated moving average)-NNAR(neural network nonlinear autoregressive) hybrid model with HFMD weekly cases from 2009 to 2016 in Zhengzhou, China. At the same time, single SARIMA model, simplex NNAR model and pure SARIMA-NNAR hybrid model were established as well for comparison and estimation.Results: The wavelet-based SARIMA-NNAR hybrid model had an excellent performance whether in fitting or in forecasting compared to other models. Its fitted and forecasting time series were approximate to the actual observed time series.Conclusions: This wavelet-based SARIMA-NNAR hybrid model that we fitted is suitable for forecasting number of HFMD cases. It will facilitate prevention and control of HFMD.

Strengthening of occupational health promotion by the German Prevention Health Care Act

2019 ◽  
pp. 188-190
Author(s):  
Diana Hart
Keyword(s):  
Public Health ◽  
Health Care ◽  
Health Promotion ◽  
Primary Prevention ◽  
Occupational Health ◽  
Life Expectancy ◽  
Prevention And Control ◽  
Occupational Health Promotion ◽  
And Control

All countries are faced with the problem of the prevention and control of non-communicable diseases (NCD): implement prevention strategies eff ectively, keep up the momentum with long term benefi ts at the individual and the population level, at the same time tackling hea lth inequalities. Th e aff ordability of therapy and care including innovative therapies is going to be one of the key public health priorities in the years to come. Germany has taken in the prevention and control of NCDs. Germany’s health system has a long history of guaranteeing access to high-quality treatment through universal health care coverage. Th r ough their membership people are entitled to prevention and care services maintaining and restoring their health as well as long term follow-up. Like in many other countries general life expectancy has been increasing steadily in Germany. Currently, the average life expectancy is 83 and 79 years in women and men, respectively. Th e other side of the coin is that population aging is strongly associated with a growing burden of disease from NCDs. Already over 70 percent of all deaths in Germany are caused by four disease entities: cardiovascular disease, cancer, chronic respiratory disease and diabetes. Th ese diseases all share four common risk factors: smoking, alcohol abuse, lack of physical activity and overweight. At the same time, more and more people become long term survivors of disease due to improved therapy and care. Th e German Government and public health decision makers are aware of the need for action and have responded by initiating and implementing a wide spectrum of activities. One instrument by strengthening primary prevention is the Prevention Health Care Act. Its overarching aim is to prevent NCDs before they can manifest themselves by strengthening primary prevention and health promotion in diff erent sett ings. One of the main emphasis of the Prevention Health Care Act is the occupational health promotion at the workplace.

An Overview of the Ethics of Injury in Public Health

2019 ◽  
pp. 597-603
Author(s):  
Adnan A. Hyder
Keyword(s):  
Public Health ◽  
Injury Prevention ◽  
Prevention And Control ◽  
Public Health Ethics ◽  
Ethical Challenges ◽  
Middle Income ◽  
Middle Income Countries ◽  
Health Ethics ◽  
Prompt Attention ◽  
And Control

This chapter briefly introduces ethics issues in injury prevention and control in low- and middle-income countries (LMICs), using a series of examples that prompt attention to the ethical principles of autonomy and justice. The chapter also introduces the section of The Oxford Handbook of Public Health Ethics dedicated to an examination of injury and public health ethics, with attention given to the complex ethical challenges arising in injury prevention and control in LMICs. The section’s two chapters discuss public health ethics issues arising in the prevention and control of unintentional injuries and intentional injuries, respectively. Those chapters define a set of ethics issues within international injury work and provide an initial analysis of the nature of those ethics issues, their specificity, and potential pathways for addressing them.

scholarly journals COVID-19 Risk Assessment: Contributing to Maintaining Urban Public Health Security and Achieving Sustainable Urban Development

2021 ◽  
Vol 13 (8) ◽  
pp. 4208
Author(s):  
Jun Zhang ◽  
Xiaodie Yuan
Keyword(s):  
Public Health ◽  
Population Density ◽  
Prevention And Control ◽  
Floating Population ◽  
Sustainable Urban Development ◽  
Risk Level ◽  
Health Security ◽  
Main Factors ◽  
And Control ◽  
Epidemic Risk

As the most infectious disease in 2020, COVID-19 is an enormous shock to urban public health security and to urban sustainable development. Although the epidemic in China has been brought into control at present, the prevention and control of it is still the top priority of maintaining public health security. Therefore, the accurate assessment of epidemic risk is of great importance to the prevention and control even to overcoming of COVID-19. Using the fused data obtained from fusing multi-source big data such as POI (Point of Interest) data and Tencent-Yichuxing data, this study assesses and analyzes the epidemic risk and main factors that affect the distribution of COVID-19 on the basis of combining with logistic regression model and geodetector model. What’s more, the following main conclusions are obtained: the high-risk areas of the epidemic are mainly concentrated in the areas with relatively dense permanent population and floating population, which means that the permanent population and floating population are the main factors affecting the risk level of the epidemic. In other words, the reasonable control of population density is greatly conducive to reducing the risk level of the epidemic. Therefore, the control of regional population density remains the key to epidemic prevention and control, and home isolation is also the best means of prevention and control. The precise assessment and analysis of the epidemic conducts by this study is of great significance to maintain urban public health security and achieve the sustainable urban development.

scholarly journals Agro-Environmental Determinants of Leptospirosis: A Retrospective Spatiotemporal Analysis (2004−2014) in Mahasarakham Province (Thailand)

2021 ◽  
Vol 6 (3) ◽  
pp. 115
Author(s):  
Jaruwan Viroj ◽  
Julien Claude ◽  
Claire Lajaunie ◽  
Julien Cappelle ◽  
Anamika Kritiyakan ◽  
...  
Keyword(s):  
Public Health ◽  
Animal Health ◽  
Spatiotemporal Analysis ◽  
Health Concern ◽  
Intersectoral Collaboration ◽  
The Public ◽  
Additive Modeling ◽  
The One ◽  
And Control ◽  
Northeastern Thailand

Leptospirosis has been recognized as a major public health concern in Thailand following dramatic outbreaks. We analyzed human leptospirosis incidence between 2004 and 2014 in Mahasarakham province, Northeastern Thailand, in order to identify the agronomical and environmental factors likely to explain incidence at the level of 133 sub-districts and 1,982 villages of the province. We performed general additive modeling (GAM) in order to take the spatial-temporal epidemiological dynamics into account. The results of GAM analyses showed that the average slope, population size, pig density, cow density and flood cover were significantly associated with leptospirosis occurrence in a district. Our results stress the importance of livestock favoring leptospirosis transmission to humans and suggest that prevention and control of leptospirosis need strong intersectoral collaboration between the public health, the livestock department and local communities. More specifically, such collaboration should integrate leptospirosis surveillance in both public and animal health for a better control of diseases in livestock while promoting public health prevention as encouraged by the One Health approach.

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