Evaluation of the meningitis surveillance system in Luanda Province, Angola, March 2017

Abstract

Introduction: Meningitis due to Neisseria meningitidis is a priority public health disease given its high epidemic potential and associated mortality. Angola is not one of the countries in the African meningitis belt and frequent outbreaks are uncommon. This might affect the preparedness and capacity of the surveillance system to promptly detect and effectively respond, should a meningitis outbreak occur. From 2014 to 2015, there was an increase in the number of meningitis cases identified in Angola, partly due to heightened disease surveillance. We evaluated the meningitis surveillance system to establish if the surveillance system was meeting its set objectives and made recommendations for improvement. Methods: A cross-sectional study was conducted among health workers in Luanda province in March 2017. Using a pretest structured questionnaire, we obtained information on the participants’ demographic characteristics, work experience, training and their knowledge about the meningitis surveillance system. Participants’ knowledge was graded poor (<50%), reasonable (50 – 69%), good (70 – 90%) and excellent (> 90%). We assessed the key system attributes using the updated CDC guidelines for evaluating public health surveillance systems. Results: Of the 52 operators interviewed, 51.9% were (27/52) nurses, 61.5% (32/52) had >5years work experience and 85.6% (45/52) had not been trained in public health surveillance in the last 5 years. Doctors and nurses had knowledge score of <20%, disease specific focal points and the program coordinator scored 85.7% and 100% respectively. Overall scores for the system’s attributes were as follows; simplicity-(33.3%), data quality-69.2 % and timeliness 33.3%. There was no evidence to suggest that data from the surveillance system was analysed at the source. Conclusion: Knowledge of surveillance system among doctors and nurses was very poor. Overall, the system was complex, with poor data quality, not timely and of low utility. We recommend periodic training of health workers, simplifying operation of the system, compliance with reporting timelines and regular data analysis and use for action at the source