scholarly journals The impacts of COVID-19 preventive and control interventions on other infectious diseases in China

2021 ◽  
pp. 1-6
Author(s):  
Xiujuan Meng ◽  
Xun Huang ◽  
Feng Zhou ◽  
Yaowang Wang ◽  
Chunhui Li ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
And Control

Communicable and Other Infectious Diseases

2020 ◽  
Author(s):  
Markus Frischhut
Keyword(s):  
Public Health ◽  
European Union ◽  
Infectious Diseases ◽  
Disease Transmission ◽  
Eu Law ◽  
The European Union ◽  
Ethical Perspective ◽  
Health Measures ◽  
Environment Agency ◽  
And Control

This chapter discusses the most important features of EU law on infectious diseases. Communicable diseases not only cross borders, they also often require measures that cross different areas of policy because of different vectors for disease transmission. The relevant EU law cannot be attributed to one sectoral policy only, and thus various EU agencies participate in protecting public health. The key agency is the European Centre for Disease Prevention and Control. Other important agencies include the European Environment Agency; European Food Safety Authority; and the Consumers, Health, Agriculture and Food Executive Agency. However, while integration at the EU level has facilitated protection of the public's health, it also has created potential conflicts among the different objectives of the European Union. The internal market promotes the free movement of products, but public health measures can require restrictions of trade. Other conflicts can arise if protective public health measures conflict with individual human rights. The chapter then considers risk assessment and the different tools of risk management used in dealing with the challenges of infectious diseases. It also turns to the external and ethical perspective and the role the European Union takes in global health.

scholarly journals Cattle trade between and within biomes in the state of Mato Grosso, Brazil

2018 ◽  
Vol 38 (11) ◽  
pp. 2023-2028
Author(s):  
Rísia L. Negreiros ◽  
José H.H. Grisi-Filho ◽  
Ricardo A. Dias ◽  
Fernando Ferreira ◽  
Valéria S.F. Homem ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Animal Movement ◽  
Control Strategies ◽  
The State ◽  
Disease Spread ◽  
Mato Grosso ◽  
Movement Data ◽  
Cattle Movements ◽  
Increased Risk ◽  
And Control

ABSTRACT: The analysis of animal movement patterns may help identify farm premises with a potentially high risk of infectious disease introduction. Farm herd sizes and bovine movement data from 2007 in the state of Mato Grosso, Brazil, were analyzed. There are three different biomes in Mato Grosso: the Amazon, Cerrado, and Pantanal. The analysis of the animal trade between and within biomes would enable characterization of the connections between the biomes and the intensity of the internal trade within each biome. We conducted the following analyses: 1) the concentration of cattle on farm premises in the state and in each biome, 2) the number and relative frequency of cattle moved between biomes, and 3) the most frequent purposes for cattle movements. Twenty percent (20%) of the farm premises had 81.15% of the herd population. Those premises may be important not only for the spread of infectious diseases, but also for the implementation of surveillance and control strategies. Most of the cattle movement was intrastate (97.1%), and internal movements within each biome were predominant (88.6%). A high percentage of movement from the Pantanal was to the Cerrado (48.6%), the biome that received the most cattle for slaughter, fattening and reproduction (62.4%, 56.8%, and 49.1% of all movements for slaughter, fattening, and reproduction, respectively). The primary purposes for cattle trade were fattening (43.5%), slaughter (31.5%), and reproduction (22.7%). Presumably, movements for slaughter has a low risk of disease spread. In contrast, movements for fattening and reproduction purposes (66.2% of all movements) may contribute to an increased risk of the spread of infectious diseases.

scholarly journals Source identification of infectious diseases in networks via label ranking

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245344
Author(s):  
Jianye Zhou ◽  
Yuewen Jiang ◽  
Biqing Huang
Keyword(s):  
Infectious Diseases ◽  
Real World ◽  
Source Identification ◽  
Human Society ◽  
Practical Applications ◽  
Ranking Algorithms ◽  
Label Ranking ◽  
Infection Source ◽  
And Control ◽  
Complete Observation

Background Outbreaks of infectious diseases would cause great losses to the human society. Source identification in networks has drawn considerable interest in order to understand and control the infectious disease propagation processes. Unsatisfactory accuracy and high time complexity are major obstacles to practical applications under various real-world situations for existing source identification algorithms. Methods This study attempts to measure the possibility for nodes to become the infection source through label ranking. A unified Label Ranking framework for source identification with complete observation and snapshot is proposed. Firstly, a basic label ranking algorithm with complete observation of the network considering both infected and uninfected nodes is designed. Our inferred infection source node with the highest label ranking tends to have more infected nodes surrounding it, which makes it likely to be in the center of infection subgraph and far from the uninfected frontier. A two-stage algorithm for source identification via semi-supervised learning and label ranking is further proposed to address the source identification issue with snapshot. Results Extensive experiments are conducted on both synthetic and real-world network datasets. It turns out that the proposed label ranking algorithms are capable of identifying the propagation source under different situations fairly accurately with acceptable computational complexity without knowing the underlying model of infection propagation. Conclusions The effectiveness and efficiency of the label ranking algorithms proposed in this study make them be of practical value for infection source identification.

scholarly journals Estimating the distribution of time to extinction of infectious diseases in mean-field approaches

2020 ◽  
Author(s):  
Maryam Aliee ◽  
Kat S. Rock ◽  
Matt J. Keeling
Keyword(s):  
Infectious Diseases ◽  
Stochastic Models ◽  
Mean Field ◽  
Practical Method ◽  
Deterministic Models ◽  
Recovery Processes ◽  
Time To Extinction ◽  
And Control ◽  
Field Approaches ◽  
Birth Death

AbstractA key challenge for many infectious diseases is to predict the time to extinction under specific interventions. In general this question requires the use of stochastic models which recognise the inherent individual-based, chance-driven nature of the dynamics; yet stochastic models are inherently computationally expensive, especially when parameter uncertainty also needs to be incorporated. Deterministic models are often used for prediction as they are more tractable, however their inability to precisely reach zero infections makes forecasting extinction times problematic. Here, we study the extinction problem in deterministic models with the help of an effective “birth-death” description of infection and recovery processes. We present a practical method to estimate the distribution, and therefore robust means and prediction intervals, of extinction times by calculating their different moments within the birth-death framework. We show these predictions agree very well with the results of stochastic models by analysing the simplified SIS dynamics as well as studying an example of more complex and realistic dynamics accounting for the infection and control of African sleeping sickness (Trypanosoma brucei gambiense).

scholarly journals Underreporting of communicable diseases in the prefecture of Achaia, western Greece, 1999-2004 – missed opportunities for early intervention

2010 ◽  
Vol 15 (21) ◽  
Author(s):  
E Jelastopulu ◽  
G Merekoulias ◽  
E C Alexopoulos
Keyword(s):  
Infectious Diseases ◽  
Control Strategies ◽  
Health Centre ◽  
Health Resources ◽  
Health Department ◽  
Public Health Department ◽  
Missed Opportunities ◽  
Notification System ◽  
And Control ◽  
Western Greece

This study investigates the completeness of the reporting of infectious diseases in the prefecture of Achaia, western Greece in the period of 1999-2004. We collected hospital records relating to infectious diseases retrospectively from three major hospitals in the region and compared the records to corresponding records at the prefectural public health department (PHD). After record-linkage and cross-validation a total of 1,143 notifiable cases were identified in the three hospitals, of which 707 were reported to the PHD of Achaia, resulting in an observed underreporting of infectious diseases of 38% during the study period. At prefecture level, a further 259 cases were notified by other sources, mainly by the fourth hospital of the region not included in our study, resulting in a total of 966 cases reported to the PHD; 73% of these were reported from the three hospitals included in our study, 27% were notified by the fourth hospital not included in our study and less then 0,3% by physicians working in a private practice or health centre. Meningitis (51%), tuberculosis (12%) and salmonellosis (8%) were the most frequently reported diseases followed by hospitalised cases of varicella (7%), brucellosis (6%) and hepatitis (6%). During the study period, clustering of specific diseases like brucellosis, meningitis, mumps, and salmonellosis was observed, indicating possible outbreaks. Our results show that notification system needs to be improved, in order to ensure proper health resources allocation and implementation of focused prevention and control strategies.

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