Skip to main content Accessibility help

Communicable Disease Surveillance Systems in Disasters: Application of the Input, Process, Product, and Outcome Framework for Performance Assessment

  • Javad Babaie (a1) (a2) (a3), Ali Ardalan (a4) (a5), Hasan Vatandoost (a6), Mohammad Mahdi Goya (a7) and Ali Akbarisari (a8)...



One of the most important measures following disasters is setting up a communicable disease surveillance system (CDSS). This study aimed to develop indicators to assess the performance of CDSSs in disasters.


In this 3-phase study, firstly a qualitative study was conducted through in-depth, semistructured interviews with experts on health in disasters and emergencies, health services managers, and communicable diseases center specialists. The interviews were analyzed, and CDSS performance assessment (PA) indicators were extracted. The appropriateness of these indicators was examined through a questionnaire administered to experts and heads of communicable diseases departments of medical sciences universities. Finally, the designed indicators were weighted using the analytic hierarchy process approach and Expert Choice software.


In this study, 51 indicators were designed, of which 10 were related to the input (19.61%), 17 to the process (33.33%), 13 to the product (25.49%), and 11 to the outcome (21.57%). In weighting, the maximum score was that of input (49.1), and the scores of the process, product, and outcome were 31.4, 12.7, and 6.8, respectively.


Through 3 different phases, PA indicators for 4 phases of a chain of results were developed. The authors believe that these PA indicators can assess the system’s performance and its achievements in response to disasters. (Disaster Med Public Health Preparedness. 2019;13:158–164)


Corresponding author

Correspondence and reprint requests to Javad Babaie, Health services management, School of management and medical informatics, Tabriz University of Medical Sciences, Tabriz, East Azerbaijan, IR (e-mail:


Hide All
1. The United Nations Office for Disaster Risk Reduction (UNISDR). 2009; UNISDR terminology on disaster risk reduction. UNISDR website. Accessed October 18, 2014.
2. Ardalan, A, Mowafi, H, Khoshgsabeghe, HY. Impacts of natural hazards on primary health care facilities of Iran: a 10-year retrospective survey. PLoS Curr. 2013:5. doi: pii: ecurrents.dis.ccdbd870f5d1697e4edee5.
3. International Strategy for Disaster Reduction (ISDR). Hospitals safe from disasters. ISDR website. Accessed December 21, 2014.
4. Djalali, A, Hosseinijenab, V, Hasani, A, et al. A fundamental, national, disaster management plan: an education based model. Prehosp Disaster Med. 2009;24(6):565-569.
5. Thomas, TL, Hsu, EB, Kim, HK, et al. The incident command system in disasters: evaluation methods for a hospital-based exercise. Prehosp Disaster Med. 2005;20(1):14-23.
6. Myint, NW, Kaewkungwal, J, Singhasivanon, P, et al. Are there any changes in burden and management of communicable diseases in areas affected by Cyclone Nargis? Confl Health. 2011;5(1):9.
7. Tohma, K, Suzuki, A, Otani, K, et al. Monitoring of influenza virus in the aftermath of Great East Japan earthquake. Jpn J Infect Dis. 2012;65:542-544.
8. Yan, G, Mei, X. Mobile device-based reporting system for Sichuan earthquake-affected areas infectious diseases reporting in China. Biomed Environ Sci. 2012;25(6):724-729.
9. Schneider, MC, Tirado, Mc, Rereddy, S, et al. Natural disasters and communicable diseases in the Americas: contribution of veterinary public health. Veterinaria Italiana. 2012;48(2):193-218.
10. Brazilay, EJ, Schaad, N, Magloire, R, et al. Cholera surveillance during the Haiti epidemic- the first two years. N Engl J Med. 2013;368(7):599-609.
11. Nelli, G, Kakar, SR, Rahim Khan, M, et al. Early warning disease surveillance after a flood emergency — Pakistan, 2010. MMWR Morb Mortal Wkly Rep. 2012;61(49):1002-1007.
12. Topran, A, Ratard, R, Bourgeois, SS, et al. Surveillance in hurricane evacuation centers-louisiana, September-October 2005. MMWR Morb Mortal Wkly Rep. 2006;55(02):32-35.
13. Williams, W, Guariso, J, Guillot, K, et al. Surveillance for illness and injury after hurricane Katrina. New Orleans, Louisiana, September 8-25, 2005. MMWR Morb Mortal Wkly Rep. 2005;54(40):1018-1020.
14. Polonsky, J, Luquero, F, Francois, G, et al. Public health surveillance after the 2010 Haiti earthquake: the experience of Médecins Sans Frontières. PLoS Curr. 2013;7:5.
15. Centers for Diseases Control and Prevention. Updated guidelines for evaluating public health surveillance systems. MMWR Morb Mortal Wkly Rep. 2001;50(RR-13):1-51.
16. Scnall, AH, Wolkin, AF, Noe, R, et al. Evaluation of a standardized morbidity surveillance form for use during disasters caused by natural hazards. Prehosp Disaster Med. 2011;26(2):90-98.
17. Choudhary, E, Zane, DF, Beasley, C, et al. Evaluation of active mortality surveillance system data for monitoring hurricane-related deaths-Texas, 2008. Prehosp Disaster Med. 2012;27(4):392.
18. Smith, PC, Mossialos, E, Papanicolas, I. Performance measurement for health system improvement: experiences, challenges and prospects. World Health Organization Regional Office for Europe website. Accessed April 11, 2014.
19. Tashobya, CK, Da Silveira, VC, Ssengooba, F, et al. Health systems performance assessment in low-income countries: learning from international experiences. Global Health. February 13 2014:10 5. doi: 10.1186/1744-8603-10-5.
20. Magloire, R, Mung, K, Harris, S, et al. Launching a national surveillance system after an earthquake — Haiti, 2010. MMWR Morb Mortal Wkly Rep. August. 6 2010;59(30):933-935.
21. Sabatinalli, G, Kakar, SR, Rahim Khan, M, et al. Early warning disease surveillance after a flood emergency – Pakistan 2010. MMWR Morb Mortal Wkly Rep. 2012;61(49):1002-1007.
22. Babaie, J, Ardalan, A, Vatandoost, H, et al. Performance assessment of communicable disease surveillance in disasters: a systematic review. PLoS Curr. February 24 2015; doi: 10.1371/currents.dis.c 72864d9c7ee99ffbe9ea707fe4465.
23. Strauss, AL, Corbin, JM. Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory, 2nd ed. Sage Publication Inc. 1998.
24. Giri, S, Nejadhashem, AP. Application of analytical hierarchy process for effective selection of agricultural best management practices. J Environ Manag. 2014;132:165-177. doi: 10.1016/j.jenvman.2013.10.021. Epub 2013 Dec 3.
25. Kouadio, IK, Koffi, AK, Attoh-Toure, H, et al. Outbreak of measles and rubella in refugee transit camps. Epidemiol Infect. 2009;137(11):1593-1601.
26. Altevogt, BM, Pope, AM, Hill, MN, et al, Research priorities in emergency preparedness and response for public health systems. The National Academies Press website. Accessed April 05, 2013.
27. Osman, IH, Berbary, LN, Sidani, Y, et al. Data envelop analysis model for the appraisal and relative performance evaluation of nurses at an intensive care unit. J Med Syst. 2011;35:1039-1062.
28. Communicable Diseases Surveillance and Response Systems: A Guide to Monitoring and Evaluating. World Health Organization; 2006.
29. Connolly MA, ed. Communicable Diseases Control in Emergencies: A Field Manual. World Health Organization; 2005.
30. Veillard, J, Champagne, F, Klazinga, N, et al. A performance assessment framework for hospitals: the WHO regional office for Europe PATH project. Int J Qual Health Care. 2005;17(6):487-499.
31. Murray, CJ, Frenk, J. A framework for assessing the performance of health systems. Bull World Health Organ. 2000;78(6):717-731.
32. Ghana Ministry of Health. Holistic assessment of the health sector, program of woke 2012. Ghana Ministry of Health website. Accessed July 14, 2013.


Communicable Disease Surveillance Systems in Disasters: Application of the Input, Process, Product, and Outcome Framework for Performance Assessment

  • Javad Babaie (a1) (a2) (a3), Ali Ardalan (a4) (a5), Hasan Vatandoost (a6), Mohammad Mahdi Goya (a7) and Ali Akbarisari (a8)...


Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed