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Introduction: in spite of the efforts and resources committed by the division of infectious disease and epidemiology (DIDE) of the national public health institute of Liberia (NPHIL)/Ministry of health to strengthening integrated disease surveillance and response (IDSR) across the country, quality data management system remains a challenge to the Liberia NPHIL/MoH (Ministry of health), with incomplete and inconsistent data constantly being reported at different levels of the surveillance system. As part of the monitoring and evaluation strategy for IDSR continuous improvement, data quality assessment (DQA) of the IDSR system to identify successes and gaps in the disease surveillance information system (DSIS) with the aim of ensuring data accuracy, reliability and credibility of generated data at all levels of the health system; and to inform an operational plan to address data quality needs for IDSR activities is required., Methods: multi-stage cluster sampling that included stage 1: simple random sample (SRS) of five counties, stage 2: simple random sample of two districts and stage 3: simple random sample of three health facilities was employed during the study pilot assessment done in Montserrado County with Liberia institute of bio medical research (LIBR) inclusive. A total of thirty (30) facilities was targeted, twenty nine (29) of the facilities were successfully audited: one hospital, two health centers, twenty clinics and respondents included: health facility surveillance focal persons (HFSFP), zonal surveillance officers (ZSOs), district surveillance officers (DSOs) and County surveillance officers (CSOs)., Results: the assessment revealed that data use is limited to risk communication and sensitization, no examples of use of data for prioritization or decision making at the subnational level. The findings indicated the following: 23% (7/29) of health facilities having dedicated phone for reporting, 20% (6/29) reported no cell phone network, 17% (5/29) reported daily access to internet, 56.6% (17/29) reported a consistent supply of electricity, and no facility reported access to functional laptop. It was also established that 40% of health facilities have experienced a stock out of laboratory specimens packaging supplies in the past year. About half of the surveyed health facilities delivered specimens through riders and were assisted by the DSOs. There was a large variety in the reported packaging process, with many staff unable to give clear processes. The findings during the exercise also indicated that 91% of health facility staff were mentored on data quality check and data management including the importance of the timeliness and completeness of reporting through supportive supervision and mentorship; 65% of the health facility assessed received supervision on IDSR core performance indicator; and 58% of the health facility officer in charge gave feedback to the community level., Conclusion: public health is a data-intensive field which needs high-quality data and authoritative information to support public health assessment, decision-making and to assure the health of communities. Data quality assessment is important for public health. In this review completeness, accuracy, and timeliness were the three most-assessed attributes. Quantitative data quality assessment primarily used descriptive surveys and data audits, while qualitative data quality assessment methods include primarily interviews, questionnaires administration, documentation reviews and field observations. We found that data-use and data-process have not been given adequate attention, although they were equally important factors which determine the quality of data. Other limitations of the previous studies were inconsistency in the definition of the attributes of data quality, failure to address data users' concerns and a lack of triangulation of mixed methods for data quality assessment. The reliability and validity of the data quality assessment were rarely reported. These gaps suggest that in the future, data quality assessment for public health needs to consider equally the three dimensions of data quality, data use and data process. Measuring the perceptions of end users or consumers towards data quality will enrich our understanding of data quality issues. Data use is limited to risk communication and sensitization, no examples of use of data for prioritization or decision making at the sub national level., Competing Interests: The authors declare no competing interest.

Introduction: Although Liberia adapted the integrated diseases surveillance and response (IDSR) in 2004 as a platform for implementation of International Health Regulation (IHR (2005)), IDSR was not actively implemented until 2015. Some innovations and best practices were observed during the implementation of IDSR in Liberia after Ebola virus disease outbreak. This paper describes the different approaches used for implementation of IDSR in Liberia from 2015 to 2017., Methods: We conducted a cross-sectional study using the findings from IDSR supervisions conducted from September to November 2017 and perused the outbreaks linelists submitted by the counties to the national level from January to December 2017 and key documents available at the national level., Results: In 2017, the country piloted the use of mobile phones application to store and send data from the health facilities to the national level. In addition, an electronic platform for acute flaccid paralysis (AFP) surveillance called Auto-Visual AFP Detection and Reporting (AVADAR) was piloted in Montserrado County during the first semester of 2017. The timeliness and completeness of reports submitted from the counties to national level were above the target of 80% stable despite the challenges like insufficient resources, including skilled staff., Conclusion: IDSR is being actively implemented in Liberia since 2015. Although the country is facing the same challenges as other countries during the early stages of implementation of IDSR, the several innovations were implemented in a short time. The surveillance system reveled to be resilient, despite the challenges., Competing Interests: The authors declare no competing interest.