Abstract

Abstract Background Routine childhood immunization coverage in Pakistan remains sub-par, in part, due to the poor quality of service delivery. This study aims to summarize the quality of immunization centers throughout the Sindh province, Pakistan, by assessing all Government vaccination facilities and their associated health workers. Methods A health facility and worker assessment survey adapted from tools developed by BASICS and EPI-Sindh was used to record facility infrastructure, processes, and human resources. Using expert panel ranking, we developed critical criteria to indicate items immunization centers need to be operational (vaccinator, a cold box or refrigerator, and vaccine supplies) as well as high, low, and moderate function requirements and their respective scores. Results Out of 1396 centers assessed, 1236 (88.5%) were operational, while 1209 (86.6%) offered immunization services. Only 793 (66.0%) of the functional immunization facilities met the critical criteria. The average scores for high, moderate, and low function requirements were significantly lower for centers that did not meet the critical criteria. Of 2,153 healthcare workers interviewed, 1874 (87.1%) were vaccinators. 1805 (96.3%), 1655 (88.3%), and 1387 (74.0%) were trained in vaccination, cold chain, and inventory, respectively. Discussion One out of three immunization centers in Sindh lack the critical components essential for quality vaccination services. Health workers have adequate training and experience, suggesting that sub-optimal vaccination center quality is due to inadequate infrastructure and inefficient processes. Our study presents innovative and critical research findings with high-impact policy implications for identifying and addressing gaps to improve vaccination uptake within an LMIC setting. Key messages Every 2 out of 5 facilities in Sindh Province lacked essential equipment for immunizations such as vaccines, vaccinator and cold box for vaccination. In all health facilities, the health workers appear sufficiently trained, indicating that poor quality may be due to missing infrastructure and inefficient processes in resource-constrained settings.

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