This paper is in the following e-collection/theme issue:

EMPHNET 7th Regional Conference 2021: “Towards Public Health Resilience in the EMR: Breaking Barriers” (62)

Published on in Vol 8, No 1 (2022): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36635, first published .
Surveillance System Evaluation for COVID-19 Vaccine–Associated Adverse Events Following Immunization (AEFI), Sindh Pakistan (2021)

Surveillance System Evaluation for COVID-19 Vaccine–Associated Adverse Events Following Immunization (AEFI), Sindh Pakistan (2021)

Surveillance System Evaluation for COVID-19 Vaccine–Associated Adverse Events Following Immunization (AEFI), Sindh Pakistan (2021)

Authors of this article:

Samreen Ashraf Qureshi1 ;   Naveed Masood2 ;   Asif Syed3 ;   Mudassar Hussain4 ;   Kashif Hussain4 ;   Saeed Ahmed Bhurt5 ;   Muhammad Ali Gadehi5 ;   Fahad Memon5 ;   Muhammad Juman Bahoto4
Article Authors Cited by Tweetations Metrics

    Abstract

    1Department of Health Government of Sindh, Hyderabad, Pakistan

    2Department of Health, Government of Sindh, Hyderabad, Pakistan

    3Department of Health, Government of Pakistan, Karachi, Pakistan

    4Department of Health, Government of Pakistan, Hyderabad, Pakistan

    5Health Department, Government of Pakistan, Hyderabad, Pakistan

    Corresponding Author:

    Samreen Ashraf Qureshi, MBBS, Diploma Family Health

    Department of Health Government of Sindh

    Provincial Disease Surveillance and Response Unit at Directorate General Health Services Sindh

    Hyderabad

    Pakistan

    Phone: 92 3213021631

    Email: qsamreen@yahoo.com


    Background: In February 2021, a mass vaccination campaign commenced in Sindh Province in response to the COVID-19 epidemic. An adverse-events-following-immunization surveillance system (AEFI-SS) was established to monitor the adverse events following vaccination.

    Objective: We evaluated the AEFI-SS with the aim to identify its strengths and weaknesses and suggest recommendations.

    Methods: In May-June 2021, a descriptive evaluation study was conducted in Sindh Province, Pakistan. The Centers for Disease Control and Prevention’s (CDC) updated guidelines for evaluation of SS-2001 were followed to measure the qualitative, quantitative, and utility attributes of the AEFI-SS. Key stakeholders were identified based on their involvement in the AEFI-SS and were interviewed. Case investigation proformas for the AEFI were randomly reviewed for data quality, timeliness, and completeness. Sensitivity was calculated. Each attribute was rated as good, fair, or poor based on a scoring legend.

    Results: The SS was useful in effectively identifying 7147 cases of AEFIs. Timeliness of all AEFI cases was good and was found to be 100%, as all cases were reported within 24 hours. The World Health Organization (WHO)-approved case definition was used for the identification of AEFI cases and had a simple flow of information. The AEFI-SS was good in data quality and completeness (100%), and data collection tools were filled by trained medical officers. Sensitivity was 100%, and the predictive value positive (PVP) was not calculated due to the absence of a laboratory component. Good representativeness (>80%) of the population was covered by 1004 vaccination centers. The system was found to be stable as resources of the health department government of Sindh were being used. The AEFI-SS was paper based and deficient in a feedback mechanism.

    Conclusions: Sindh Province has an appropriate surveillance mechanism for AEFI detection and management for the ongoing COVID-19 vaccination SS. The representativeness can be increased by involvement of the private health sector. Establishment of a feedback mechanism and digital data transformation and integration of the AEFI system with the Expanded Program on Immunization (EPI) are recommended.

    iproc 2022;8(1):e36635

    doi:10.2196/36635

    Keywords

    surveillance system evaluation; COVID-19 vaccine–associated AEFI 

    Edited by Y Khader; This is a non–peer-reviewed article. submitted 19.01.22; accepted 19.01.22; published 18.02.22

    Copyright

    ©Samreen Ashraf Qureshi, Naveed Masood, Asif Syed, Mudassar Hussain, Kashif Hussain, Saeed Ahmed Bhurt, Muhammad Ali Gadehi, Fahad Memon, Muhammad Juman Bahoto. Originally published in Iproceedings (https://www.iproc.org), 18.02.2022.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in Iproceedings, is properly cited. The complete bibliographic information, a link to the original publication on https://www.iproc.org/, as well as this copyright and license information must be included.