Techniques and Approaches for Disease Outbreak Prediction

Author(s):  
Asha A. Bharambe ◽  
Dhananjay R. Kalbande
Keyword(s):  
2017 ◽  
Vol 124 (3) ◽  
pp. 215-222 ◽  
Author(s):  
JR López ◽  
L Lorenzo ◽  
R Alcantara ◽  
JI Navas

2016 ◽  
Vol 65 (12) ◽  
Author(s):  
Naomi K. Tepper ◽  
Howard I. Goldberg ◽  
Manuel I. Vargas Bernal ◽  
Brenda Rivera ◽  
Meghan T. Frey ◽  
...  

2017 ◽  
Author(s):  
Lasantha Fernando ◽  
Sriganesh Lokanathan ◽  
Amal Shehan Perera ◽  
Azhar Ghouse ◽  
Hasitha Tissera

1991 ◽  
Vol 24 (2) ◽  
pp. 13-15 ◽  
Author(s):  
Y. Andersson

In Sweden 63 waterborne outbreaks occurred during the last 10 years. Even if these outbreaks include smaller family incidents, at least 10 community outbreaks involved more than 1,000 victims each, the largest being in the city of Boden in 1988. This outbreak hit 41% of the population with gastrointestinal symptoms and was preceded by the distribution of virtually untreated, fecally contaminated river water due to a transitory absence of chlorination.


2020 ◽  
Author(s):  
Andrew Fang ◽  
Jonathan Kia-Sheng Phua ◽  
Terrence Chiew ◽  
Daniel De-Liang Loh ◽  
Lincoln Ming Han Liow ◽  
...  

BACKGROUND During the Coronavirus Disease 2019 (COVID-19) outbreak, community care facilities (CCF) were set up as temporary out-of-hospital isolation facilities to contain the surge of cases in Singapore. Confined living spaces within CCFs posed an increased risk of communicable disease spread among residents. OBJECTIVE This inspired our healthcare team managing a CCF operation to design a low-cost communicable disease outbreak surveillance system (CDOSS). METHODS Our CDOSS was designed with the following considerations: (1) comprehensiveness, (2) efficiency through passive reconnoitering from electronic medical record (EMR) data, (3) ability to provide spatiotemporal insights, (4) low-cost and (5) ease of use. We used Python to develop a lightweight application – Python-based Communicable Disease Outbreak Surveillance System (PyDOSS) – that was able perform syndromic surveillance and fever monitoring. With minimal user actions, its data pipeline would generate daily control charts and geospatial heat maps of cases from raw EMR data and logged vital signs. PyDOSS was successfully implemented as part of our CCF workflow. We also simulated a gastroenteritis (GE) outbreak to test the effectiveness of the system. RESULTS PyDOSS was used throughout the entire duration of operation; the output was reviewed daily by senior management. No disease outbreaks were identified during our medical operation. In the simulated GE outbreak, PyDOSS was able to effectively detect an outbreak within 24 hours and provided information about cluster progression which could aid in contact tracing. The code for a stock version of PyDOSS has been made publicly available. CONCLUSIONS PyDOSS is an effective surveillance system which was successfully implemented in a real-life medical operation. With the system developed using open-source technology and the code made freely available, it significantly reduces the cost of developing and operating CDOSS and may be useful for similar temporary medical operations, or in resource-limited settings.


2019 ◽  
Vol 56 (12) ◽  
pp. 1052-1054 ◽  
Author(s):  
Dhanya Dharmapalan ◽  
Vinay K. Saxena ◽  
Shailesh D. Pawar ◽  
Tarique H. I. H. Qureshi ◽  
Priyanka Surve

Acta Tropica ◽  
2021 ◽  
Vol 215 ◽  
pp. 105803
Author(s):  
Jackeline Monsalve-Lara ◽  
Maurício Lilioso ◽  
Carolina Valença-Barbosa ◽  
Patricia J Thyssen ◽  
Danilo C Miguel ◽  
...  

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 125
Author(s):  
Márcio Moreira ◽  
Denise Schrama ◽  
Ana Paula Farinha ◽  
Marco Cerqueira ◽  
Cláudia Raposo de Magalhães ◽  
...  

One of the main constraints in aquaculture production is farmed fish vulnerability to diseases due to husbandry practices or external factors like pollution, climate changes, or even the alterations in the dynamic of product transactions in this industry. It is though important to better understand and characterize the intervenients in the process of a disease outbreak as these lead to huge economical losses in aquaculture industries. High-throughput technologies like proteomics can be an important characterization tool especially in pathogen identification and the virulence mechanisms related to host-pathogen interactions on disease research and diagnostics that will help to control, prevent, and treat diseases in farmed fish. Proteomics important role is also maximized by its holistic approach to understanding pathogenesis processes and fish responses to external factors like stress or temperature making it one of the most promising tools for fish pathology research.


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