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On April 25, 2017, the Sinoe County Health Team (CHT) notified the Liberia Ministry of Health (MoH) and the National Public Health Institute of Liberia of an unknown illness among 14 persons that resulted in eight deaths in Sinoe County. On April 26, the National Rapid Response Team and epidemiologists from CDC, the World Health Organization (WHO) and the African Field Epidemiology Network (AFENET) in Liberia were deployed to support the county-led response. Measures were immediately implemented to identify all cases, ascertain the cause of illness, and control the outbreak. Illness was associated with attendance at a funeral event, and laboratory testing confirmed Neisseria meningitidis in biologic specimens from cases. The 2014-2015 Ebola virus disease (Ebola) outbreak in West Africa devastated Liberia's already fragile health system, and it took many months for the country to mount an effective response to control the outbreak. Substantial efforts have been made to strengthen Liberia's health system to prevent, detect, and respond to health threats. The rapid and efficient field response to this outbreak of N. meningitidis resulted in implementation of appropriate steps to prevent a widespread outbreak and reflects improved public health and outbreak response capacity in Liberia.

Introduction Measles is an acute viral disease that remains endemic in much of sub-Sahara Africa, including Liberia. The 2014 Ebola epidemic disrupted an already fragile health system contributing to low uptake of immunization services, population immunity remained low thus facilitating recurrent outbreaks of measles in Liberia. We describe lessons learnt from detecting and responding to recurrent outbreaks of measles two years post the 2014 Ebola epidemic in Liberia. Methods We conducted a descriptive study using the findings from Integrated Diseases Surveillance and Response (IDSR) 15 counties, National Public Health Institute of Liberia (NPHIL), National Public Health Reference Laboratory (NPHRL) and District Health Information Software (DIHS2) data conducted from October to December, 2017. We perused the outbreaks line lists and other key documents submitted by the counties to the national level from January 2016 to December 2017. Results From January 2016 to December 2017, 2,954 suspected cases of measles were reported through IDSR. Four hundred sixty-seven (467) were laboratory confirmed (IgM-positive), 776 epidemiologically linked, 574 clinically confirmed, and 1,137 discarded (IgM-negative). Nine deaths out of 1817 cases were reported, a case fatality rate of 0.5%; 49% were children below the age of 5 years. Twenty-two percent (405/1817) of the confirmed cases were vaccinated while the vaccination status of 55% (994/1817) was unknown. Conclusion Revitalization of IDSR contributed to increased detection and reporting of suspected cases of measles thus facilitating early identification and response to outbreaks. Priority needs to be given to increasing the uptake of routine immunization services, introducing a second dose of measles vaccine in the routine immunization program and conducting a high-quality supplementary measles immunization campaign for age group 1 to 10 years to provide protection for a huge cohort of susceptible.

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.

Summary Background On April 25, 2017, a cluster of unexplained illnesses and deaths associated with a funeral was reported in Sinoe County, Liberia. Molecular testing identified Neisseria meningitidis serogroup C (NmC) in specimens from patients. We describe the epidemiological investigation of this cluster and metagenomic characterisation of the outbreak strain. Methods We collected epidemiological data from the field investigation and medical records review. Confirmed, probable, and suspected cases were defined on the basis of molecular testing and signs or symptoms of meningococcal disease. Metagenomic sequences from patient specimens were compared with 141 meningococcal isolate genomes to determine strain lineage. Findings 28 meningococcal disease cases were identified, with dates of symptom onset from April 21 to April 30, 2017: 13 confirmed, three probable, and 12 suspected. 13 patients died. Six (21%) patients reported fever and 23 (82%) reported gastrointestinal symptoms. The attack rate for confirmed and probable cases among funeral attendees was 10%. Metagenomic sequences from six patient specimens were similar to a sequence type (ST) 10217 (clonal complex [CC] 10217) isolate genome from Niger, 2015. Multilocus sequencing identified five of seven alleles from one specimen that matched ST-9367, which is represented in the PubMLST database by one carriage isolate from Burkina Faso, in 2011, and belongs to CC10217. Interpretation This outbreak featured high attack and case fatality rates. Clinical presentation was broadly consistent with previous meningococcal disease outbreaks, but predominance of gastrointestinal symptoms was unusual compared with previous African meningitis epidemics. The outbreak strain was genetically similar to NmC CC10217, which caused meningococcal disease outbreaks in Niger and Nigeria. CC10217 had previously been identified only in the African meningitis belt. Funding US Global Health Security.