IRD Global, 15 Beach Road #02-01, 189677, Singapore.
IRD Pakistan, 4th Floor, Woodcraft Building, Plot 3 & 3-A, Sector 47, Korangi Creek Road, Karachi, Pakistan.
Int J Med Inform. 2021 May;149:104413. doi: 10.1016/j.ijmedinf.2021.104413. Epub 2021 Feb 8.
BACKGROUND: Despite the proliferation of digital interventions such as Electronic Immunization Registries (EIR), currently, there is little evidence regarding the use of EIR data to improve immunization outcomes in resource-constrained settings. To achieve the Sustainable Development Goal (SDG) of ensuring healthy lives and well-being for all ages, particularly for newborns and children under the age of 5 (goal 3b), it is essential to generate and use quality data for evidence-based decision making to overcome barriers inherent in immunization systems. In Pakistan, only 66 % of children receive all basic vaccinations, and in Sindh province, the number is even lower at 49 %. In 2012, IRD developed and piloted Zindagi Mehfooz (Safe Life; ZM) ElR, an Android-based platform that records and analyses individual-level child data in real-time. In 2017 in collaboration with Expanded Programme for Immunization (EPI) Sindh, ZM was scaled-up across the entire Sindh province and is currently being used by 2521 government vaccinators in 1539 basic health facilities, serving >48 million population. OBJECTIVE: The study aims to demonstrate how big immunization data from the ZM-EIR is being leveraged in Sindh, Pakistan for actionable decision making via three use cases (a) improving performance management of vaccinators to increase geographical coverage, (b) quantifying the impact of provincial accelerated outreach activities, and (c) examining the impact of the COVID-19 pandemic on routine immunization coverage to help devise a tailored approach for future efforts. METHODS: From October 2017 to April 2020, more than 2.9 million children and 0.9 million women have been enrolled, and more than 22 million immunization events have been recorded in the ZM-EIR. We extracted de-identified data from ZM-EIR for January 1, 2019 - April 20, 2020, period. Given the needs of each use case, monthly and daily indicators on vaccinator performance (attendance and compliance), daily immunization visits, and the number of antigens administered were calculated. Geo-coordinate data of antigen administration was extracted and displayed on geographic maps using QGIS. All generated reports were shared at fixed frequency with various stakeholders, such as partners at EPI-Sindh, for utilization in decision making and informing policy. RESULT: Our use-cases demonstrate the use of EIR data for data-driven decision making. From January - December 2019, the monthly monitoring of program indicators helped increase the vaccinator attendance from 44% to 88%, while an 85 % increase in geographical coverage was observed in a polio-endemic super high-risk union council (SHRUC) in Karachi. The analysis of daily average antigens administered during accelerated outreach efforts (AOE) as compared to routine activities showed an increase in average daily Pentavalent-3, Measles-1, and Measles-2 vaccines administered by 103%, 154%, and 180% respectively. These findings helped decide to continue the accelerated effort in high-risk areas (compared to the entire province) rather than discontinuing the activity due to high costs. During COVID-19 lockdown, the daily average number of child immunizations reduced from 16,649 to 4335 per day, a decline of 74% compared to 6 months preceding COVID-19 lockdown. ZM-EIR data is currently helping to shape the planning and implementation of critical strategies to mitigate the impact of the COVID-19 pandemic. CONCLUSION: The big data for vaccines generated through EIRs is a powerful tool to monitor immunization work-force and ensure chronically missed communities are identified and covered through targeted strategies. Geospatial data availability and analysis is changing the way EPI review meetings occur with stakeholders, taking data-driven decisions for better planning and resource allocation. In the fight against COVID-19 pandemic, as governments gradually begin to shift from containing the outbreak to strategizing a plan for sustaining the essential health services, the countries that will emerge most successful are likely the ones who can best use technology and real-time data for targeted efforts.
背景:尽管出现了电子免疫登记系统(EIR)等数字干预措施,但目前关于利用 EIR 数据来改善资源有限环境中的免疫接种结果的证据很少。为了实现确保所有年龄段的健康生活和福祉的可持续发展目标(SDG),特别是针对新生儿和 5 岁以下儿童(目标 3b),必须生成和使用高质量的数据来做出基于证据的决策,以克服免疫接种系统固有的障碍。在巴基斯坦,只有 66%的儿童接受了所有基本疫苗接种,而在信德省,这一数字甚至更低,仅为 49%。2012 年,IRD 开发并试点了 Zindagi Mehfooz(安全生活;ZM)ElR,这是一个基于 Android 的平台,可以实时记录和分析儿童的个人数据。2017 年,在与信德省扩大免疫规划(EPI)合作的基础上,ZM 在整个信德省推广,并由 2521 名政府疫苗接种员在 1539 个基本卫生设施中使用,为>4800 万人口提供服务。
目的:本研究旨在展示巴基斯坦信德省如何利用 ZM-EIR 的大量免疫数据进行决策,提出了三个用例:(a)提高疫苗接种员的绩效管理,以增加地理覆盖范围;(b)量化省级加速外展活动的影响;(c)检查 COVID-19 大流行对常规免疫覆盖率的影响,以帮助制定未来工作的针对性方法。
方法:从 2017 年 10 月到 2020 年 4 月,有超过 290 万名儿童和 90 万名妇女被登记,在 ZM-EIR 中记录了超过 2200 万次免疫接种事件。我们从 ZM-EIR 中提取了 2019 年 1 月 1 日至 2020 年 4 月 20 日期间的匿名数据。鉴于每个用例的需求,计算了疫苗接种员绩效(出勤和合规性)、每日免疫接种访问和接种抗原的每月和每日指标。使用 QGIS 提取抗原接种的地理坐标数据,并在地理地图上显示。所有生成的报告都按固定频率与 EPI-Sindh 等利益相关者共享,用于决策和通知政策。
结果:我们的用例展示了如何利用 EIR 数据进行数据驱动的决策。从 2019 年 1 月至 12 月,通过每月监测项目指标,疫苗接种员的出勤率从 44%提高到 88%,而在卡拉奇的一个脊髓灰质炎高度流行的超级高风险联盟理事会(SHRUC),地理覆盖范围增加了 85%。与常规活动相比,对加速外展活动(AOE)期间平均每天接种的抗原进行分析,显示五价第三针、麻疹第一针和麻疹第二针的平均日接种量分别增加了 103%、154%和 180%。这些发现有助于决定在高风险地区(与整个省份相比)继续进行加速努力,而不是由于成本高而停止活动。在 COVID-19 封锁期间,儿童免疫接种的每日平均数量从每天 16649 人减少到 4335 人,与 COVID-19 封锁前的 6 个月相比下降了 74%。ZM-EIR 数据目前正在帮助制定关键战略的规划和实施,以减轻 COVID-19 大流行的影响。
结论:通过 EIR 生成的疫苗大数据是监测免疫工作队伍的有力工具,可确保确定并覆盖长期未接种疫苗的社区,并通过有针对性的战略加以解决。地理空间数据的可用性和分析正在改变 EPI 审查会议与利益相关者的发生方式,为更好的规划和资源分配做出数据驱动的决策。在与 COVID-19 大流行的斗争中,随着各国政府逐渐从遏制疫情转向制定维持基本卫生服务的计划,最成功的国家可能是那些能够最好地利用技术和实时数据进行有针对性努力的国家。
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