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dc.contributor.authorKwiringira, Andrew
dc.date.accessioned2021-05-27T05:48:43Z
dc.date.available2021-05-27T05:48:43Z
dc.date.issued2021-04-09
dc.identifier.citation(Unpublished master’s dissertation). Makerere University, Kampala, Uganda.en_US
dc.identifier.urihttp://hdl.handle.net/10570/8693
dc.descriptionMaster’s Thesisen_US
dc.description.abstractBackground: Every suspected malaria case should be tested for the presence of the malaria parasite, every confirmed case should be treated with antimalarial medicine, and every confirmed case should be tracked through timely and accurate surveillance systems. However, weekly epidemiological reports from health facilities in Gulu district showed that not all suspected malaria cases are tested and when tested, some with negative test results are treated with antimalarials. In some cases, even those not tested receive antimalarials. Objective: To assess the implementation of the malaria Test, Treat and Track policy of testing all suspected malaria cases, treatment of only confirmed malaria cases and tracking malaria cases with a surveillance system in the health facilities in Gulu district. Methods: This was a retrospective analysis and employed a mix of both quantitative and qualitative methods. Quantitative data was collected by retrospective review of OPD register, laboratory register, and DHIS-2 from eight health facilities in Gulu district for a period of one year. Data was summarised monthly for 12 months and was compared monthly, by level of health facility, and by health facility ownership. Categorical data was summarised in frequencies and percentages. Differences between levels of categorical variables were explored using a chi-square test. A p-valve of less 0.05 was considered cut off for statistical significance. The Bland-Altman correlation analysis quantified the numerical consistency between the aggregated malaria cases in OPD registers, laboratory registers, and DHIS2. Factors associated with the proportion of suspected malaria cases tested and confirmed malaria cases treated for each independent variable were assessed using logistic regression models in STATA 14.0. Qualitative data was collected through key informant interviews with the District Health Officer, the health educator, the malaria x focal person, health workers, and health facility in-charges, and malaria focal persons from development partners. Transcripts from the key informant audio files were subjected to schematic analysis. Results: The proportion of suspected malaria cases that were tested for malaria was 99.8% and the proportion of confirmed malaria cases that were treated with antimalarials was 99.9%. The Bland-Altman correlation analysis showed a poor concordance correlation coefficient of 0.558 (95% CI: 0.319- 0.797) when the number of malaria cases recorded in OPD register were compared with the number of malaria cases reported in DHIS2. Logistic regression showed a significant statistical difference in the proportion of suspected malaria cases tested in public and private health facilities (p<0.0001). There was a significant statistical difference in the proportion of confirmed malaria cases treated with antimalarials across different levels of health facilities (p<0.016) and when health facilities were disaggregated by their location (p<0.004). Barriers to implementation of the malaria T3 policy include patient perception, limited malaria support supervision, shortage of health care staff dedicated to data management and declining motivation. Enablers to implementation of T3 policy include availability of antimalarials and diagnostic facilities like RDT and microscopy, and an established surveillance system. Conclusion and Recommendation: Substantial implementation was observed in testing and treatment of malaria cases. However, malaria data used to track malaria cases is of poor quality. To sustain the gains attained in the implementation of T3 policy, the ministry of health and malaria development partners should ensure consistent and sustainable supply and access to all malaria commodities. Regular support supervision visits and data quality audits should be conducted to improve the quality of data for tracking malaria cases.en_US
dc.language.isoenen_US
dc.publisherMakerere Universityen_US
dc.subjectmalaria testen_US
dc.subjecttrack cascadeen_US
dc.subjectTreat and tracken_US
dc.subjectGuluen_US
dc.titleAssessment of implementation of the malaria test, treat and track cascade in eight health facilities in Gulu districten_US
dc.typeThesisen_US


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