Evaluation of the Measles Case-Based Surveillance System in Kaduna State (2010-2012)

Despite the high investment on Measles surveillance activities, frequent measles outbreaks still occur in Kaduna State. We evaluated the surveillance system to adentify gaps in its operations.We adapted the updated CDC guidelines on surveillance evaluation to assess the systems usefulness, representativeness, simplicity, timeliness, stability and acceptability. Our findings showed that the surveillance system is still useful however there were marked deficiencies in the timeliness and completeness of weekly reporting

Evaluation of the Measles Case-Based Surveillance System in Kaduna State (2010-2012)

Despite the high investment on Measles surveillance activities, frequent measles outbreaks still occur in Kaduna State. We evaluated the surveillance system to adentify gaps in its operations.We adapted the updated CDC guidelines on surveillance evaluation to assess the systems usefulness, representativeness, simplicity, timeliness, stability and acceptability. Our findings showed that the surveillance system is still useful however there were marked deficiencies in the timeliness and completeness of weekly reporting

User Evaluation Indicates High Quality of the Surveillance Outbreak Response Management and Analysis System (SORMAS) After Field Deployment in Nigeria in 2015 and 2018

During the West African Ebola virus disease outbreak in 2014–15, health agencies had severe challenges with case notification and contact tracing. To overcome these, we developed the Surveillance, Outbreak Response Management and Analysis System (SORMAS). The objective of this study was to measure perceived quality of SORMAS and its change over time. We ran a 4-week-pilot and 8-week-implementation of SORMAS among hospital informants in Kano state, Nigeria in 2015 and 2018 respectively. We carried out surveys after the pilot and implementation asking about usefulness and acceptability. We calculated the proportions of users per answer together with their 95% confidence intervals (CI) and compared whether the 2015 response distributions differed from those from 2018. Total of 31 and 74 hospital informants participated in the survey in 2015 and 2018, respectively. In 2018, 94% (CI: 89–100%) of users indicated that the tool was useful, 92% (CI: 86–98%) would recommend SORMAS to colleagues and 18% (CI: 10–28%) had login difficulties. In 2015, the proportions were 74% (CI: 59–90%), 90% (CI: 80–100%), and 87% (CI: 75–99%) respectively. Results indicate high usefulness and acceptability of SORMAS. We recommend mHealth tools to be evaluated to allow repeated measurements and comparisons between different versions and users.Peer Reviewe

User Evaluation Indicates High Quality of the Surveillance Outbreak Response Management and Analysis System (SORMAS) After Field Deployment in Nigeria in 2015 and 2018.

During the West African Ebola virus disease outbreak in 2014-15, health agencies had severe challenges with case notification and contact tracing. To overcome these, we developed the Surveillance, Outbreak Response Management and Analysis System (SORMAS). The objective of this study was to measure perceived quality of SORMAS and its change over time. We ran a 4-week-pilot and 8-week-implementation of SORMAS among hospital informants in Kano state, Nigeria in 2015 and 2018 respectively. We carried out surveys after the pilot and implementation asking about usefulness and acceptability. We calculated the proportions of users per answer together with their 95% confidence intervals (CI) and compared whether the 2015 response distributions differed from those from 2018. Total of 31 and 74 hospital informants participated in the survey in 2015 and 2018, respectively. In 2018, 94% (CI: 89-100%) of users indicated that the tool was useful, 92% (CI: 86-98%) would recommend SORMAS to colleagues and 18% (CI: 10-28%) had login difficulties. In 2015, the proportions were 74% (CI: 59-90%), 90% (CI: 80-100%), and 87% (CI: 75-99%) respectively. Results indicate high usefulness and acceptability of SORMAS. We recommend mHealth tools to be evaluated to allow repeated measurements and comparisons between different versions and users