| Literature DB >> 35096227 |
Isah Mohammed Bello1, Maleghemi Sylvester2, Melesachew Ferede2, Godwin Ubong Akpan3, Ademe Tegegne Ayesheshem2, Michael Nzioki Mwanza3, Samuel Okiror3, Atem Anyuon4, Olu Olushayo Oluseun2.
Abstract
INTRODUCTION: the use of digital health technologies and geographical information systems (GIS) in the conduct of immunization campaigns had proven to be a success story, and is gaining acceptance towards improving supervision, accountability, and real-time access to quality information. The demand for real-time information by policymakers and stakeholders in the polio eradication programme is increasing towards ensuring a world free from all polioviruses. This study aims to develop a tool that monitor and evaluate the circulating vaccine-derived poliovirus (cVDPV) campaign processes in real-time using open data kits (ODK) to collect data, analyze and visualize using an interactive dashboard in Power BI, towards improving timeliness and completeness of data reporting and providing real-time quality information to stakeholders.Entities:
Keywords: Geographic information system; Power BI; cVDPV; circulating vaccine derived poliovirus; open data kits; vaccination
Mesh:
Substances:
Year: 2021 PMID: 35096227 PMCID: PMC8760295 DOI: 10.11604/pamj.2021.40.200.31525
Source DB: PubMed Journal: Pan Afr Med J
number of supervisors trained to supervise and monitor the campaign
| States | National sup | State sup | McKings cons | UNICEF sup | Independent mon | WHO field staff * | LQAs surveyors | Total |
|---|---|---|---|---|---|---|---|---|
| National | 2 | 5 | 7 | 14 | ||||
| Lakes | 6 | 8 | 31 | 10 | 4 | 59 | ||
| Northern Bahr El Ghazal | 3 | 5 | 20 | 6 | 4 | 38 | ||
| Unity | 1 | 9 | 4 | 11 | 4 | 29 | ||
| Upper Nile | 1 | 7 | 12 | 10 | 4 | 34 | ||
| Warrap | 6 | 7 | 24 | 9 | 5 | 51 | ||
| Western Bahr El Ghazal | 2 | 3 | 8 | 5 | 2 | 20 | ||
| Western Equatoria | 4 | 6 | 18 | 8 | 4 | 40 | ||
| Total | 25 | 45 | 5 | 7 | 117 | 59 | 27 | 285 |
WHO field staff*: EPI officers, stoppers, and field supervisors; sup: supervisors; mon: monitor; cons: consultant
Figure 1architecture of the system showing the components and connection flow
Figure 2indicators showing pre-campaign indicators (training supervision checklist)
comparison of timeliness of data reporting comparison between paper-based and electronic-based (using ODK) from field to national
| Campaign phase | Data sets | Paper-Based - (avg time in hours) | Electronic-based - (avg time in hours) | Std. deviation | Std. error mean | 95% confidence interval of the difference | P-value | |
|---|---|---|---|---|---|---|---|---|
| Lower | Upper | |||||||
| Pre-campaign | Training checklist | 58 | 5 | 13.322 | 5.035 | 40.536 | 65.178 | 0.001 |
| Preparedness validation | 58 | 5 | 13.322 | 5.035 | 40.536 | 65.178 | 0.001 | |
| Intra-campaign | Team supervision | 178 | 5 | 13.322 | 5.035 | 160.54 | 185.18 | 0.001 |
| In-process monitoring (inside/outside) | 178 | 5 | 13.322 | 5.035 | 160.54 | 185.18 | 0.001 | |
| Post-campaign | LQAs | 86 | 8 | 22.026 | 8.325 | 57.487 | 98.228 | 0.001 |
Figure 3indicators showing team supervision indicators (intra-campaign)
Figure 4lot quality assurance sampling (LQAs) indicators showing indicators for monitoring campaign quality