Lessons learned from early implementation of the Growing Expertise in E-health Knowledge and Skills (GEEKS) program in Nigeria, 2019 - 2021.

Introduction: the Growing Expertise in E-health Knowledge and Skills (GEEKS) program is an applied apprenticeship program that aims to improve informatics capacity at various levels of the national health system and create a sustainable informatics workforce. Nigeria adapted the GEEKS model in 2019 as a mechanism to strengthen data quality and use of routine immunization (RI) and vaccine-preventable disease (VPD) surveillance data among Expanded Programme on Immunization (EPI) staff. Since the start of the GEEKS-EPI program, there has not been a formal assessment conducted to measure the extent to which GEEKS-EPI has been able to build local informatics workforce capacity and strengthen RI and VPD surveillance (VPDS) data quality and use in Nigeria. Methods: we conducted a qualitative assessment to inform the extent to which GEEKS-EPI has been able to build informatics skillsets to enhance local workforce capacity, foster collaboration across government agencies, and create a sustainable informatics workforce in Nigeria. In-Depth Interviews (IDIs) and Focus Group Discussions (FGDs) were held with GEEKS-EPI supervisors, mentors, and mentees from previous GEEKS-EPI cohorts. Results: while there were challenges reported during early implementation of the GEEKS-EPI program in Nigeria, particularly early on in the COVID-19 pandemic, participants and supervisors reported that the fellowship provided a framework for building a sustainable RI and VPDS informatics workforce through regular mentorship, peer-to-peer exchanges and Subject Matter Expert (SME)-led trainings. Conclusion: lessons learned from early implementation of GEEKS-EPI in Nigeria will help to inform its implementation in other countries, where strengthened national RI and VPDS informatics capacity is the primary objective.

Patterns of diarrhoeal disease among under-five children in Plateau State, Nigeria, 2013-2017.

BACKGROUND: Diarrhoea is the second commonest cause of under-five mortality accounting for over half a million deaths annually. Although the prevalence of diarrhoea in Plateau State is lower than the national figure, the level remains high despite remarkable progress in the reduction of under-five mortality. This study seeks to determine the pattern of diarrhoea disease among under-fives in Plateau State. METHODS: We extracted data from the Integrated Disease Surveillance and Response platform between January 2013 and December 2017 and analysed the trends of diarrhoea, age-specific case fatality rate (ASCFR), and seasonal patterns. We modelled the quarterly pattern of diarrhoea cases using additive time series and predicted the expected cases for 2018-2020. RESULTS: We documented 60,935 cases of diarrhoea with age group 12-59 months having the highest number of cases (49.3%). The age group < 1 month had the highest ASCFR of 0.53%. Seasonal variation showed cases peaked in the first and third quarters of each year, except for the year 2016. The time series projection estimated 16,256, 17,645 and 19,034 cases in the year 2018, 2019 and 2020 respectively. CONCLUSION: Seasonal variation exists, and trends show an increased pattern of diarrhoeal disease among under-fives. There is a need to strengthen the implementation of diarrhoeal preventive and control strategy in the state and to improve the quality of data reporting.

Implementing the routine immunisation data module and dashboard of DHIS2 in Nigeria, 2014-2019.

In 2010, Nigeria adopted the use of web-based software District Health Information System, V.2 (DHIS2) as the platform for the National Health Management Information System. The platform supports real-time data reporting and promotes government ownership and accountability. To strengthen its routine immunisation (RI) component, the US Centers for Disease Control and Prevention (CDC) through its implementing partner, the African Field Epidemiology Network-National Stop Transmission of Polio, in collaboration with the Government of Nigeria, developed the RI module and dashboard and piloted it in Kano state in 2014. The module was scaled up nationally over the next 4 years with funding from the Bill & Melinda Gates Foundation and CDC. One implementation officer was deployed per state for 2 years to support operations. Over 60 000 RI healthcare workers were trained on data collection, entry and interpretation and each local immunisation officer in the 774 local government areas (LGAs) received a laptop and stock of RI paper data tools. Templates for national-level and state-level RI bulletins and LGA quarterly performance tools were developed to promote real-time data use for feedback and decision making, and enhance the performance of RI services. By December 2017, the DHIS2 RI module had been rolled out in all 36 states and the Federal Capital Territory, and all states now report their RI data through the RI Module. All states identified at least one government DHIS2 focal person for oversight of the system's reporting and management operations. Government officials routinely collect RI data and use them to improve RI vaccination coverage. This article describes the implementation process-including planning and implementation activities, achievements, lessons learnt, challenges and innovative solutions-and reports the achievements in improving timeliness and completeness rates.

Comparison of Micro-Census Results for Magarya Ward, Wurno Local Government Area of Sokoto State, Nigeria, with Other Sources of Denominator Data.

Routine immunization coverage in Nigeria is suboptimal. In the northwestern state of Sokoto, an independent population-based survey for 2016 found immunization coverage with the third dose of Pentavalent vaccine to be 3%, whereas administrative coverage in 2016 was reported to be 69%. One possibility driving this large discrepancy is that administrative coverage is calculated using an under-estimated target population. Official population projections from the 2006 Census are based on state-specific standard population growth rates. Immunization target population estimates from other sources have not been independently validated. We conducted a micro-census in Magarya ward, Wurno Local Government Area of Sokoto state to obtain an accurate count of the total population living in the ward, and to compare these results with other sources of denominator data. We developed a precise micro-plan using satellite imagery, and used the navigation tool EpiSample v1 in the field to guide teams to each building, without duplications or omissions. The particular characteristics of the selected ward underscore the importance of using standardized shape files to draw precise boundaries for enumeration micro-plans. While the use of this methodology did not resolve the discrepancy between independent and administrative vaccination coverage rates, a simplified application can better define the target population for routine immunization services and estimate the number of children still unprotected from vaccine-preventable diseases.