INFECTIOUS DISEASES: Rapid Response Could Have Curbed Foot-and-Mouth Epidemic

Science ◽  
2001 ◽  
Vol 294 (5540) ◽  
pp. 26-27
Author(s):  
M. Enserink
Keyword(s):  
Infectious Diseases ◽  
Rapid Response ◽  
Foot And Mouth

scholarly journals Foot and Mouth Disease and Cryptosporidiosis: Possible Interaction between Two Emerging Infectious Diseases

2003 ◽  
Vol 9 (1) ◽  
pp. 109-112 ◽  
Author(s):  
Paul R. Hunter ◽  
Rachel M. Chalmers ◽  
Qutub Syed ◽  
L. Sara Hughes ◽  
Sarah Woodhouse ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Emerging Infectious Diseases ◽  
Foot And Mouth Disease ◽  
Mouth Disease ◽  
Foot And Mouth

scholarly journals Rapid response research to emerging infectious diseases: lessons from SARS

2004 ◽  
Vol 2 (7) ◽  
pp. 602-607 ◽  
Author(s):  
B. Brett Finlay ◽  
Raymond H. See ◽  
Robert C. Brunham
Keyword(s):  
Infectious Diseases ◽  
Emerging Infectious Diseases ◽  
Rapid Response

scholarly journals Rapid, sensitive and effective diagnostic tools for foot-and-mouth disease virus in Africa

2014 ◽  
Vol 81 (2) ◽  
Author(s):  
Christopher J. Kasanga ◽  
Wataru Yamazaki ◽  
Valerie Mioulet ◽  
Donald P. King ◽  
Misheck Mulumba ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Reverse Transcription ◽  
Foot And Mouth Disease ◽  
Mouth Disease ◽  
Diagnostic Tools ◽  
Target Sequence ◽  
Specific Detection ◽  
Fmdv Serotypes ◽  
Mouth Disease Virus ◽  
Foot And Mouth

Speed is paramount in the diagnosis of highly infectious diseases, such as foot-and-mouth disease (FMD), as well as for emerging diseases; however, simplicity is required if a test is to be deployed in the field. Recent developments in molecular biology have enabled the specific detection of FMD virus (FMDV) by reverse-transcription loop-mediated isothermal amplification (RT-LAMP), real-time  reverse-transcription polymerase chain reaction (RT-qPCR) and sequencing. RT-LAMP enables amplification of the FMDV RNA-dependent RNA polymerase 3D(pol) gene at 63 °C (in the presence of a primer mixture and both reverse transcriptase and Bst DNA polymerase) for 1 h, whilst RT-qPCR amplifies the same gene in approximately 2 h 30 min. In this study, we compared the sensitivity and effectiveness of RT-LAMP against RT-qPCR for the detection of the FMDV 3D(pol) gene in 179 oesophageal-pharyngeal scraping samples (collected by probang) obtained from clinically healthy cattle and buffalo in Malawi, Mozambique and Tanzania in 2010. The FMDV detection rate was higher with RT-LAMP (30.2%; n = 54) than with RT-qPCR (17.3%; n = 31). All samples positive by RT-qPCR (Cq ≤ 32.0) were also positive for the RT-LAMP assay; and both assays proved to be highly specific for the FMDV target sequence. In addition, the VP1 sequences of 10 viruses isolated from positive samples corresponded to the respective FMDV serotypes and genotypes. Our findings indicate that the performance of RT-LAMP is superior to RT-qPCR. Accordingly, we consider this test to have great potential with regard to the specific detection and surveillance of infectious diseases of humans and animals in resource-compromised developing countries.

Epidemiology of hand, foot, and mouth disease in children in Shanghai 2007–2010

2011 ◽  
Vol 140 (6) ◽  
pp. 1122-1130 ◽  
Author(s):  
M. ZENG ◽  
Y.-F. LI ◽  
X.-H. WANG ◽  
G.-P. LU ◽  
H.-G. SHEN ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Pulmonary Oedema ◽  
Neurological Disorders ◽  
Foot And Mouth Disease ◽  
Population Group ◽  
Epidemiological Data ◽  
Mouth Disease ◽  
Migrant Children ◽  
Clinical Samples ◽  
Foot And Mouth

SUMMARYWe retrospectively analysed the epidemiological data of all hand, foot, and mouth disease (HFMD) cases from the largest paediatric infectious diseases centre in Shanghai between 2007 and 2010. A total of 28 058 outpatients were diagnosed with HFMD, of which 3948 (14·07%) were hospitalized, 730 (2·60%) had complications with neurological disorders and pulmonary oedema/haemorrhage, and 11 (0·04%) died. The peak season was the summer months. Boys were more affected than girls. Since 2008, the major population group affected has shifted from native Shanghainese children attending preschool to migrant children and younger children cared for at home. Children aged 1–4 years constituted 82·27% of cases. EV-A71 was tested in clinical samples taken from severe cases in 2009 and 2010, and from most inpatients in 2010. EV-A71 was positive in 99·17% and 86·31% of severe cases, respectively in 2009 and 2010. All 12 cases with pulmonary oedema or haemorrhage were infected with EV-A71. Ten (90·90%) of 11 fatal cases were attributable to EV-A71 infection. In 2010, EV-A71-positive cases accounted for 54·12% of inpatients. The dominant circulation of EV-A71 led to the outbreak of HFMD and occurrence of severe and fatal cases.

scholarly journals Optimized Neural Network Based on Genetic Algorithm to Construct Hand-Foot-and-Mouth Disease Prediction and Early-Warning Model

2021 ◽  
Vol 18 (6) ◽  
pp. 2959
Author(s):  
Xialv Lin ◽  
Xiaofeng Wang ◽  
Yuhan Wang ◽  
Xuejie Du ◽  
Lizhu Jin ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Early Warning ◽  
Foot And Mouth Disease ◽  
Mouth Disease ◽  
Prediction Algorithm ◽  
Current Field ◽  
Related Factors ◽  
Foot And Mouth ◽  
Epidemic Prediction ◽  
Warning Model

Accompanied by the rapid economic and social development, there is a phenomenon of the crazy spread of many infectious diseases. It has brought the rapid growth of the number of people infected with hand-foot-and-mouth disease (HFMD), and children, especially infants and young children’s health is at great risk. So it is very important to predict the number of HFMD infections and realize the regional early-warning of HFMD based on big data. However, in the current field of infectious diseases, the research on the prevalence of HFMD mainly predicts the number of future cases based on the number of historical cases in various places, and the influence of many related factors that affect the prevalence of HFMD is ignored. The current early-warning research of HFMD mainly uses direct case report, which uses statistical methods in time and space to have early-warnings of outbreaks separately. It leads to a high error rate and low confidence in the early-warning results. This paper uses machine learning methods to establish a HFMD epidemic prediction model and explore constructing a variety of early-warning models. By comparison of experimental results, we finally verify that the HFMD prediction algorithm proposed in this paper has higher accuracy. At the same time, the early-warning algorithm based on the comparison of threshold has good results.

Sign in / Sign up

Export Citation Format

Share Document