Statistical Techniques and Stochastic Modeling in Public Health Surveillance Systems Engineering

Author(s):  
Emmanouil-Nektarios Kalligeris ◽  
Alex Karagrigoriou ◽  
Christina Parpoula ◽  
Angeliki Lambrou
2020 ◽  
Author(s):  
Falaho Sani ◽  
Mohammed Hasen ◽  
Mohammed Seid ◽  
Nuriya Umer

Abstract Background: Public health surveillance systems should be evaluated periodically to ensure that the problems of public health importance are being monitored efficiently and effectively. Despite the widespread measles outbreak in Ginnir district of Bale zone in 2019, evaluation of measles surveillance system has not been conducted. Therefore, we evaluated the performance of measles surveillance system and its key attributes in Ginnir district, Southeast Ethiopia.Methods: We conducted a concurrent embedded mixed quantitative/qualitative study in August 2019 among 15 health facilities/study units in Ginnir district. Health facilities are selected using lottery method. The qualitative study involved purposively selected 15 key informants. Data were collected using semi-structured questionnaire adapted from Centers for Disease Control and Prevention guidelines for evaluating public health surveillance systems through face-to-face interview and record review. The quantitative findings were analyzed using Microsoft Excel 2016 and summarized by frequency and proportion. The qualitative findings were narrated and summarized based on thematic areas to supplement the quantitative findings.Results: The structure of surveillance data flow was from the community to the respective upper level. Emergency preparedness and response plan was available only at the district level. Completeness of weekly report was 95%, while timeliness was 87%. No regular analysis and interpretations of surveillance data, and the supportive supervision and feedback system was weak. The participation and willingness of surveillance stakeholders in implementation of the system was good. The surveillance system was found to be useful, easy to implement, representative and can accommodate and adapt to changing conditions. Report documentation and quality of data was poor at lower level health facilities. Stability of the system has been challenged by shortage of budget and logistics, staff turnover and lack of update trainings.Conclusions: The surveillance system was acceptable, useful, simple, flexible and representative. Data quality, timeliness and stability of the system were attributes that require improvement. The overall performance of measles surveillance system in the district was poor. Hence, regular analysis of data, preparation and dissemination of epidemiological bulletin, capacity building and regular supervision and feedback are recommended to enhance performance of the system.


2014 ◽  
Vol 6 (1) ◽  
Author(s):  
Rhonda A. Lizewski ◽  
Howard Burkom ◽  
Joseph Lombardo ◽  
Christopher Cuellar ◽  
Yevgeniy Elbert ◽  
...  

While other surveillance systems may only use death and admissions as severity indicators, these serious events may overshadow the more subtle severity signals based on appointment type, disposition from an outpatient setting, and whether that patient had to return for care if they their condition has not improved.  This abstract discusses how these additional data fields were utilized in a fusion model to improve the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE).


2018 ◽  
Vol 32 (4) ◽  
pp. 401-410 ◽  
Author(s):  
Charitha Gowda ◽  
Samuel Kennedy ◽  
Catherine Glover ◽  
Mona R. Prasad ◽  
Ling Wang ◽  
...  

2011 ◽  
Vol 139 (12) ◽  
pp. 1827-1834 ◽  
Author(s):  
A. J. IDROVO ◽  
J. A. FERNÁNDEZ-NIÑO ◽  
I. BOJÓRQUEZ-CHAPELA ◽  
J. MORENO-MONTOYA

SUMMARYThe A(H1N1) influenza pandemic has been a challenge for public health surveillance systems in all countries. An objective evaluation has not been conducted, as yet, of the performance of those systems during the pandemic. This paper presents an algorithm based on Benford's Law and the mortality ratio in order to evaluate the quality of the data and the sensitivity of surveillance systems. It analyses records of confirmed cases reported to the Pan American Health Organization by its 35 member countries between epidemiological weeks 13 and 47 in 2009. Seventeen countries did not fulfil Benford's Law, and mortality exceeded the regional average in 40% of the countries. The results suggest uneven performance by surveillance systems in the different countries, with the most frequent problem being low diagnostic coverage. Benford's Law proved to be a useful tool for the evaluation of a public health surveillance system's performance.


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