Participant Centered Active Surveillance for Adverse Event Following Measles Immunization in Gedeo Zone, Ethiopia, 2022. A Multi-center Open-label Randomized Control Trial

Introduction Participant centered active adverse event following immunization (AEFI) surveillance can offer real time vaccine safety data and help in signal detection. Evidence showed that it is still difficult to get AEFI from passive reporting in Ethiopia. Vast novel method of enhanced AEFI surveillance has been practiced globally. However, those methods had serious limitations including the requirement of high resource and expertise. Hence, there is a need to find the most flexible low cost and integrated AEFI surveillance system. To the best of our knowledge, there has no published research in Ethiopia which compare Participant diary, SMS, and telephone interview for the purpose of active AEFI surveillance.

Objective: To assess participant centered active adverse event surveillance following measles immunization at Gedeo Zone health facilities, Ethiopia.

Method: An open randomized trial will be employed from October 1, 2022- December 1, 2023, at Gedio Zone health facilities. All parents, care givers/guardians whose child receive vaccine during the study period in the study site will be included in the study. A total of 391participants will be randomized to SMS, telephone interview or diary card group using random number generator on Excel. Every participant will be contacted on day seven to request them whether they experience any AEFI. Differences in proportions will compared using chi-square tests. A 0.05 level of significance will be used for all analyses. Independent sample t-tests will be used to compare the mean time (in days) required to collect complete AEFI data by SMS, telephone interview and diary card. Multinominal logistic regression analyses will be used assess the factors associated with effective use of tailored SMS, telephone interview and diary card for the AEFI active surveillance. To further investigate the association between the vaccine and the adverse events and factors associated with vaccine binary and multi variable logistic regression will be used.