The Lassa fever surveillance system in Kano state was found to meet some of the key attributes of a good surveillance system. The system was found to be simple, flexible, and acceptable. However, some challenges were identified with the stability, representativeness, timeliness and sensitivity of the system. The state- level stakeholders (WHO National surveillance Officer, WHO surveillance focal persons, UNICEF state team lead, AFENET/CDC Field coordinator, State data manager and state Disease surveillance and notification officer) and LGA level officials (Disease surveillance and notification officers) confirmed that the system was simple, well-structured and flexible. The simplicity of the system stemmed from the ease of operation of the system which is due to availability efficient communication channels as well data tools. This is similar to the findings in studies from Edo, Ondo and Osun states of Nigeria.7–10 However, it is in contrast with the findings from studies conducted in Sierra-Leon, where the system is complex and difficult to operate.11
The surveillance system was acceptable to the respondents as the majority of them (98%) were willing to continue with their work. Equally, tools and case definitions were acceptable to all the stakeholders. Thirty-eight of the respondents (95%) have been completely involved in Lassa fever surveillance activities and expressed that the system appreciates them for doing their work diligently. Similar finding was reported from Sierra Leone, where surveillance activity was accepted by health workers despite lack of inducement. Some of the reasons proposed include sense of service to humanity and opportunities to improve relationship with the communities.12
The surveillance system collated data all year round with active case search during outbreaks. During the study period, all persons were reported from all ages and sexes and from different areas of the state. Similarly, all the stakeholders confirmed that data tools used in the system captured information and distribution of Lassa fever based on age, sex, location, date of diagnosis and disease outcome. However, the surveillance system collated data with little or no representation from the tertiary and private health facilities in the state. Therefore, the surveillance system was not a representation of all the health care facilities in the state. This could be because these facilities may not have a reliable and dedicated focal persons and most of the private facilities may tend to concentrate more on service provision which provides them with more revenue rather than participating in surveillance activities. Similarly, private facilities experience manpower challenges including shortages that make them have inefficient surveillance system in place. Consequently, lack of integration of the tertiary and private facilities within the state in the surveillance system could undermine the validity of the data reported for the state. Similar observations were also reported by a study conducted in the state by Visa et al.13
The system was considered to be sensitive enough to detect some foci of outbreaks in some of the LGAs in the state in 2015 to 2017. However, at the level of case detection, it was not consistently detecting significant number of cases as evident by only three cases in the whole of 2018. Although, this may likely arise from misdiagnosis due to similarities in symptoms with other commonly seen disease conditions in the health facilities like yellow fever and malaria. Many of the respondents (78%) have attested to this possibility of misdiagnosis. This is supported by the findings of Emperador et al., who reported high likelihood of missing or misdiagnosis of suspected Lassa fever cases because it shares similar symptoms with other endemic tropical diseases including malaria, typhoid fever and other viral hemorrhagic fevers.14
Furthermore, the system is fairly stable as significant proportion of the surveillance personnel from the focal persons at the health facility, DSNOs at the LGAs to the officials at the State Ministry of Health, were all under the employment of Kano State government with reliable job security. Similarly, full integration of the system with other diseases under surveillance has contributed to the stability of the system. Data collected were managed either manually (63%) or electronically (37%) at the LGA level. This may pose a serious threat in case of data lost or theft. The state government provided most of the logistics with support from the partner agencies in the state. From the key informant interview (KII), stakeholders revealed that they encounter challenges with transport, logistics and communication occasionally. This is similar to the report of Kaburi et al in Ghana, where the surveillance system was found to be relatively stable despite score of challenges.15
With respect to timeliness, the majority of the respondents (93%) agreed that there was a written policy and agreement on timeliness of data reporting. Substantial proportion of the respondents (98%) succeed in sending their report in good time, usually within two weeks despite some challenges inherent in the system including limited financial resources. The reporting rate at the different health facilities level was equally satisfying. However, it is difficult estimate the reporting rate because of missing and absent data entries in the line-list from different LGAs. The State Epidemiology Unit calculated timeliness and completeness for 2015, 2016, 2017 and 2018 as 81.4%/91.9%, 95.6%/98.8%,98.8%/99.7% and 98.6%/99.7% respectively. The timeliness for the state has been reaching the minimum target set by the WHO of at least 80%. The state has received recognition in the year 2018 because of these achievements. The completeness however has not reached the minimum target of 100% set by the WHO in all the years under study. However, there was continued improvement from 2016 to 2018 with the values almost reaching the desired target of 100%. The implication is the ability to detect and manage outbreak effectively and efficiently with improvement of the system.