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.
Introduction
Following a declaration by the World Health Organization that Liberia had successfully interrupted Ebola virus transmission on May 9th, 2015; the country entered a period of enhanced surveillance. The number of cases had significantly reduced prior to the declaration, leading to closure of eight out of eleven Ebola testing laboratories. Enhanced surveillance led to an abrupt increase in demand for laboratory services. We report interventions, achievements, lessons learned and recommendations drawn from enhancing laboratory capacity.
Methods
Using archived data, we reported before and after interventions that aimed at increasing laboratory capacity. Laboratory capacity was defined by number of laboratories with Ebola Virus Disease (EVD) testing capacity, number of competent staff, number of specimens tested, specimen backlog, daily and surge testing capacity, and turnaround time. Using Stata 14 (Stata Corporation, College Station, TX, USA), medians and trends were reported for all continuous variables.
Results
Between May and December 2015, interventions including recruitment and training of eight staff, establishment of one EVD laboratory facility, implementation of ten Ebola GeneXpert diagnostic platforms, and establishment of working shifts yielded an 8-fold increase in number of specimens tested, a reduction in specimens backlog to zero, and restoration of turn-around time to 24 hours. This enabled a more efficient surveillance system that facilitated timely detection and containment of two EVD clusters observed thereafter.
Conclusion
Effective enhancement of laboratory services during high demand periods requires a combination of context-specific interventions. Building and ensuring sustainability of local capacity is an integral part of effective surveillance and disease outbreak response efforts.
Background: Rubella is an RNA virus in the genus Rubivirus within the Matonaviridae family. Rubella remains a leading vaccine-preventable cause of birth defects. Most African countries including Liberia do not currently provide rubella-containing vaccine (RCV) in their immunization program. We analyzed the existing surveillance data to describe rubella cases and identify the at-risk population. Methods: We conducted a retrospective descriptive statistics on the suspected-measles case-based surveillance data that obtained from the national database. Suspected-measles cases who were negative and indeterminate for measles IgM and tested for rubella IgM were extracted from the database. We used only rubella IgM positive cases to calculate trends and percentages by person, place and time. The cumulative-percent curve was used to visually describe the age distribution of rubella cases. Results: During 2017-2018, a total of 2027 suspected-measles cases with known laboratory results were reported; of which, 1307 were tested for rubella IgM. Among tested cases, 472 (36%) were positive, 769 (59%) were negative and 66 (5%) were indeterminate for rubella IgM. Female contributed 269 (57%) of the confirmed rubella cases respectively. The median age was 7 years with an interquartile range of 5-10 years. From the total rubella cases, 6 (1%) were under 1 year, 109 (23%) were 1-4 years, 207 (44%) were 5-9 years, 87 (18%) were 10-14 years and 56 (12%) were more than or equal to 15 years. Women in their reproductive-age contributed 23 (5%) of rubella cases with 17% positivity rate. Two-thirds or 307 (65%) of the cases were reported from February to May which is dry season in Liberia.
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