Lessons Learnt From Exercise Celestial Navigation: The Application of a Geographic Information System to Inform Legionnaires’ Disease Control Activity

2018 ◽  
Vol 13 (02) ◽  
pp. 372-374 ◽  
Author(s):  
Emma Quinn ◽  
Kai Hsiao ◽  
George Truman ◽  
Nectarios Rose ◽  
Richard Broome

AbstractGeographic information systems (GIS) have emerged in the past few decades as a technology capable of assisting in the control of infectious disease outbreaks. A Legionnaires’ disease cluster investigation in May 2016 in Sydney, New South Wales (NSW), Australia, demonstrated the importance of using GIS to identify at-risk water sources in real-time for field investigation to help control any immediate environmental health risk, as well as the need for more staff trained in the use of this technology. Sydney Local Health District Public Health Unit (PHU) subsequently ran an exercise (based on this investigation) with 11 staff members from 4 PHUs across Sydney to further test staff capability to use GIS across NSW. At least 80% of exercise participants reported that the scenario progression was realistic, assigned tasks were clear, and sufficient data were provided to complete tasks. The exercise highlighted the multitude of geocoding applications and need for inter-operability of systems, as well as the need for trained staff with specific expertise in spatial analysis to help assist in outbreak control activity across NSW. Evaluation data demonstrated the need for a common GIS, regular education and training, and guidelines to support the collaborative use of GIS for infectious disease epidemiology in NSW. (Disaster Med Public Health Preparedness. 2019;13:372–374)

2017 ◽  
Vol 22 (40) ◽  
Author(s):  
Thomas Harder ◽  
Anja Takla ◽  
Tim Eckmanns ◽  
Simon Ellis ◽  
Frode Forland ◽  
...  

Decisions in public health should be based on the best available evidence, reviewed and appraised using a rigorous and transparent methodology. The Project on a Framework for Rating Evidence in Public Health (PRECEPT) defined a methodology for evaluating and grading evidence in infectious disease epidemiology, prevention and control that takes different domains and question types into consideration. The methodology rates evidence in four domains: disease burden, risk factors, diagnostics and intervention. The framework guiding it has four steps going from overarching questions to an evidence statement. In step 1, approaches for identifying relevant key areas and developing specific questions to guide systematic evidence searches are described. In step 2, methodological guidance for conducting systematic reviews is provided; 15 study quality appraisal tools are proposed and an algorithm is given for matching a given study design with a tool. In step 3, a standardised evidence-grading scheme using the Grading of Recommendations Assessment, Development and Evaluation Working Group (GRADE) methodology is provided, whereby findings are documented in evidence profiles. Step 4 consists of preparing a narrative evidence summary. Users of this framework should be able to evaluate and grade scientific evidence from the four domains in a transparent and reproducible way.


2005 ◽  
Vol 10 (45) ◽  
Author(s):  
E Isakbaeva ◽  
B A Lindstedt ◽  
B Schimmer ◽  
T Vardund ◽  
T L Stavnes ◽  
...  

On 3 November 2005, four cases of multidrug-resistant Salmonella Typhimurium DT 104 infections were notified to the Infectious Disease Epidemiology Department by the Reference Laboratory of the Norwegian Institute of Public Health. The four isolates had identical multilocus VNTR analysis


2019 ◽  
Vol 23 (3) ◽  
pp. 328-334
Author(s):  
E. Ya. Yanchevskaya ◽  
O. A. Mesnyankina

Mathematical modeling of diseases is an urgent problem in the modern world. More and more researchers are turning to mathematical models to predict a particular disease, as they help the most correct and accurate study of changes in certain processes occurring in society. Mathematical modeling is indispensable in certain areas of medicine, where real experiments are impossible or difficult, for example, in epidemiology. The article is devoted to the historical aspects of studying the possibilities of mathematical modeling in medicine. The review demonstrates the main stages of development, achievements and prospects of this direction.


2005 ◽  
pp. 1327-1362
Author(s):  
Susanne Straif-Bourgeois ◽  
Raoult Ratard

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