HSP709 - SURVEILLANCE and EARLY WARNING SYSTEM IN COMMUNICA

Course Name Code Semester Theory
(hours/week)		 Application
(hours/week)		 Credit ECTS
SURVEILLANCE and EARLY WARNING SYSTEM IN COMMUNICA HSP709 Any Semester/Year 2 0 2 4
PrequisitesMust have taken HEP 602 ve HEP 603
Course languageTurkish
Course typeElective 
Mode of DeliveryFace-to-Face 
Learning and teaching strategiesLecture
Question and Answer
Preparing and/or Presenting Reports
Other: Group Discussion  
Instructor (s)Prof. Dr. Levent AKIN, MD 
Course objectiveThe aim of the course to develop knowledge of surveillance methods which is used to detect public health challenges, on how to improve, implement and evaluate. 
Learning outcomes
  1. At the end of this course, student will be able to: Describe the surveillance and use of surveillance
  2. Describe type of surveillance
  3. Establish a surveillance system
  4. Describe event-based surveillance
  5. Evaluate a surveillance system
  6. Use mapping in beginner level
  7. Analysis and interprete surveillance data
Course ContentSurveillance of the history and definition; Surveillance types, advantages and disadvantages; An early warning system and event-based surveillance; The surveillance system of the organization of the stages; Surveillance data collection; Surveillance data analysis and interpretation; Mapping and the use of the computer program; General discussion 
References1. Control of Communicable Diseases Manual, 19th Edition. Editor: James Chin, The American Public Health Association, NW, Washington, DC 2008.
2. Public Health and Preventive Medicine, Ed Robert B Wallace, Neal Kohatsu, 15.th ed. Mc Graw Hill Medical Company, Stamford, NY, 2007.
3. Akın L.." Bulaşıcı Hastalıkların Kontrolu " Halk Sağlığı Temel Bilgiler (Editörler: Ç. Güler ve Levent Akın). Hacettepe Üniversitesi yayınları, Ankara, 2006.
 

Course outline weekly

WeeksTopics
Week 1Surveillance of the history and definition
Week 2Surveillance types, advantages and disadvantages
Week 3Early warning system and event-based surveillance
Week 4Surveillance system of the organization of the stages
Week 5Surveillance system of the organization of the stages - case study
Week 6Surveillance data collection
Week 7Surveillance data collection - case study
Week 8Surveillance data analysis and interpretation
Week 9Surveillance data analysis and interpretation
Week 10Homework and presentation: the Surveillance data analysis and interpretation
Week 11Homework and presentation: the Surveillance data analysis and interpretation
Week 12Mapping and the use of the software
Week 13Mapping and the use of the software
Week 14Use of laboratory in surveillance
Week 15General discussion
Week 16Final exam

Assesment methods

Course activitiesNumberPercentage
Attendance00
Laboratory00
Application00
Field activities00
Specific practical training00
Assignments120
Presentation115
Project00
Seminar115
Midterms00
Final exam150
Total100
Percentage of semester activities contributing grade succes350
Percentage of final exam contributing grade succes150
Total100

WORKLOAD AND ECTS CALCULATION

Activities Number Duration (hour) Total Work Load
Course Duration (x14) 14 2 28
Laboratory 0 0 0
Application000
Specific practical training000
Field activities000
Study Hours Out of Class (Preliminary work, reinforcement, ect)6848
Presentation / Seminar Preparation2612
Project000
Homework assignment11616
Midterms (Study duration)000
Final Exam (Study duration) 11616
Total Workload2448120

Matrix Of The Course Learning Outcomes Versus Program Outcomes

D.9. Key Learning OutcomesContrubition level*
12345
1. Has current, advanced knowledge and develops them    X
2. Comprehends interdisciplinary interaction, reaches original results on analysis, synthesis, evaluation of new ideas    X
3. Has advanced knowledge in program development, implementation and evaluation   X 
4. Has knowledge of quantitative and qualitative research and statistical methods   X 
5. Uses the new information in a systematic approach    X
6. Researches, designs, adapts and applies a unique topic   X 

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest