Agbemafle E, Kubio C, Bandoh D, Odikro M, Azagba C, Issahaku R, Sackey S. Evaluation of the malaria surveillance system - Adaklu District, Volta Region, Ghana, 2019.
Public Health Pract (Oxf) 2023;
6:100414. [PMID:
37564781 PMCID:
PMC10410592 DOI:
10.1016/j.puhip.2023.100414]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 07/24/2023] [Accepted: 07/25/2023] [Indexed: 08/12/2023] Open
Abstract
Objectives
We evaluated the malaria surveillance system in Adaklu District of the Volta Region of Ghana to determine if the system was meeting its objectives and assessed its usefulness and attributes.
Study design
Descriptive cross-sectional design was used in evaluating the surveillance system.
Methods
We interviewed stakeholders using a semi-structured questionnaire on case detection and reporting. We assessed the system attributes using the Centers for Disease Control and Prevention updated guidelines for evaluating public health surveillance systems. We extracted and reviewed malaria surveillance data from the District Health Management Information System 2. Summary statistics and direct content analysis were performed on quantitative and qualitative data respectively.
Results
Of the 80,441 suspected malaria cases recorded in Adaklu District from 2014 to 2018, 47,917 (59.6%) cases were confirmed. The system was meeting its objective of detecting malaria cases and monitoring trends in the population however, the system missed an epidemic in August 2016. Data generated from the surveillance system is used by the NMCP to aid in the distribution of logistics such as LLINs, RDT test kits, and track malaria control progress in the district. Staff at all levels were able to detect, confirm, treat and report malaria. All sub-districts/health facilities reported to the district and reports were all accurate and timely. The predictive value positive was 62.9%.
Conclusions
The malaria surveillance system in Adaklu District was useful and meeting its set objective of monitoring trends of malaria in the population. It was simple, flexible, acceptable and representative; however, the system was not detecting epidemics. The District Health Management Team should set alert and epidemic thresholds to help detect promptly epidemics of malaria in the district.
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