An evaluation of the Routine Malaria Information System in Guinea in case management and commodity consumption reporting Pubblico

Abstract

Background : The Routine Malaria Information System (RMIS) in Guinea was established in late 2013 to in an effort to capture both epidemiological data and commodity consumption at the health facility level. This study was done to evaluate the current capacity of the RMIS in comparison to the President's Malaria Initiative's (PMI) end-use verification (EUV) surveys in efforts to identify programmatic gaps in routine malaria surveillance systems.

Methods: This was a cross sectional study analyzing four sets of data from July and December 2014, October 2015 and August 2016 in terms of health facility reporting, stock outs, case management indicators, and stock levels. Summaries of data were analyzed using proportions, chi-square test and the Schuirmann's Two One-Sided equivalence test.

Results: RMIS had high reporting rate of health facilities (75%) and demonstrated overall high specificity for stock outs for most commodities except injectable artemether. It showed low sensitivity overall for each commodity and high variability in Kappa values. RMIS is significantly different from the EUV surveys in case management indicator reporting overall. Malaria cases reported in individuals >5 years of age were demonstrated to have consistent correct diagnoses in all the months except for in August 2016 (p value 0.002). Overall, the results show that the RMIS is more likely to overestimate than to underestimate malaria commodity stock levels. In total, all commodities were overestimated except for AS-AQ infant (mean difference: -297 at CI 90%), AL (mean difference: -708 at CI 90%), and quinine tablets (mean difference: -11 at CI 90%).

Conclusions: The RMIS has high variability in data quality and need improvement in case management and commodity consumption reporting. PMI should continue to implement the EUV surveys and implement additional trainings on case management and malaria supply chain management in collaboration with the national program and partners.

Keywords: Routine malaria information system, surveillance, supply chain management, Guinea

Table of Contents

Table of Contents

Chapter 1: Introduction…………………………………………………………………….1

Context…………………………………………………………………………………....1

Problem Statement……………………………………………………………………….2

Purpose of the Project……………………………………………………....……….......3

Chapter 2: Review of the Literature……………………………………………………..4

Background: ……………………………………………………………………………..4

Global burden of malaria………………………………………………………….......4

Malaria transmission, symptoms, and treatment………………………………………4

Malaria in Guinea …………………………………………………………………….5

Malaria control and prevention strategies……………………………………………..8

Malaria surveillance, monitoring and evaluation……………………………………...8

Health system in Guinea……………………………………………………………..13

Impact of Ebola on the health structure……………………………………………...15

The President's Malaria Initiative……………………………………………………17

Routine malaria information system…………………………………………………20

End-use verification surveys…………………………………………………………24

Chapter 3: Manuscript…………………………………………………………………….27

Abstract…………………………………………………………………………………28

Contribution of the Student……………………………………………………………29

Background……………………………………………………………………………..30

Methods………………………………………………………………………………….34

Results…………………………………………………………………………………...37

Discussion……………………………………………………………………………….40

Appendix………………………………………………………………………………...47

Tables and Figures……………………………………………………………………...47

Table 1. Proportions of health facilities reported in both the EUV and the RMIS…..47

Table 2. Accuracy of commodity stock out status reporting of the RMIS compared to the stock out reporting of the EUV…………………………………………………..48

Table 3. A comparison of the difference in ratio of cases by age groups……………………………….………………………………………………..49

Table 4. A comparison of the RMIS and EUV's malaria commodity stock levels reported in mean difference using the Schuirmann's test✢…………………………………………………………………………………50

Figure 1. RMIS Indicators, January-December 2015………………………………..51

Figure 2. EUV Indicators…………………………………………………………….53

Figure 3. Total absolute stock levels between RMIS and EUV reporting…………...59

Figure 4. The total min-mean-max % difference between RMIS and EUV reporting per commodity (except RDT) ……………………………………………………….60

Chapter 4: Conclusions and Implications …………………………………………….61

Reference………………………………….………………………………………………….....64

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School	Rollins School of Public Health
Department	Hubert Department of Global Health
Degree	MPH
Submission	Master's Thesis
Language	English
Research Field	Health Sciences, Public Health
Parola chiave	Guinea Routine malaria information system Surveillance Malaria
Committee Chair / Thesis Advisor	Hussen, Sophia A, Emory University
Committee Members	Plucinski, Mateusz, CDC
Partnering Agencies	International governmental organization (e.g., Agency for International Development, etc.) CDC

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