BackgroundAn outbreak of pneumococcal meningitis among non-infant children and adults occurred in the Brong-Ahafo region of Ghana between December 2015 and April 2016 despite the recent nationwide implementation of a vaccination programme for infants with the 13-valent pneumococcal conjugate vaccine (PCV13).MethodsCerebrospinal fluid (CSF) specimens were collected from patients with suspected meningitis in the Brong-Ahafo region. CSF specimens were subjected to Gram staining, culture and rapid antigen testing. Quantitative PCR was performed to identify pneumococcus, meningococcus and Haemophilus influenzae. Latex agglutination and molecular serotyping were performed on samples. Antibiogram and whole genome sequencing were performed on pneumococcal isolates.ResultsEight hundred eighty six patients were reported with suspected meningitis in the Brong-Ahafo region during the period of the outbreak. In the epicenter district, the prevalence was as high as 363 suspected cases per 100,000 people. Over 95 % of suspected cases occurred in non-infant children and adults, with a median age of 20 years. Bacterial meningitis was confirmed in just under a quarter of CSF specimens tested. Pneumococcus, meningococcus and Group B Streptococcus accounted for 77 %, 22 % and 1 % of confirmed cases respectively. The vast majority of serotyped pneumococci (80 %) belonged to serotype 1. Most of the pneumococcal isolates tested were susceptible to a broad range of antibiotics, with the exception of two pneumococcal serotype 1 strains that were resistant to both penicillin and trimethoprim-sulfamethoxazole. All sequenced pneumococcal serotype 1 strains belong to Sequence Type (ST) 303 in the hypervirulent ST217 clonal complex.ConclusionThe occurrence of a pneumococcal serotype 1 meningitis outbreak three years after the introduction of PCV13 is alarming and calls for strengthening of meningitis surveillance and a re-evaluation of the current vaccination programme in high risk countries.Electronic supplementary materialThe online version of this article (doi:10.1186/s12879-016-1914-3) contains supplementary material, which is available to authorized users.

BackgroundInfluenza-like Illness (ILI) is a medical diagnosis of possible influenza or another respiratory illness with a common set of symptoms. The deaths of four schoolchildren, during a pandemic influenza outbreak in December 2017 in Ghana, raised doubts about the ILI surveillance system’s performance. We evaluated the ILI surveillance system in the Greater Accra region, Ghana, to assess the system’s attributes and its performance on set objectives.MethodsCDC guidelines were used to evaluate the data of the ILI surveillance system between 2013 and 2017. We interviewed the surveillance personnel on the system’s description and operation. Additionally, routinely entered ILI data from the National Influenza Center provided by the six sentinel sites in Accra was extracted. We sampled and reviewed 120 ILI case-investigation forms from these sites. Surveillance activities were examined on system’s performance indicators, each being scored on a scale of 1 to 3 (poorest to best performance).ResultsAll population and age groups were under ILI surveillance over the period evaluated. Overall, 2948 suspected case-patients, including 392 (13.3%) children under-five were reported, with 219 being positive for influenza virus (Predictive value positive = 7.4%). The predominant influenza subtype was H3N2, recorded in 90 (41.1%) of positive case-patients. The system only met two out of its four objectives. None of the six sentinel sites consistently met their annual 260 suspected case-detection quota. Samples reached the laboratory on average 48 hours after collection and results were disseminated within 7 days. Of 120 case-investigation forms sampled, 91 (76.3%) were completely filled in.ConclusionsThe ILI surveillance system in the Greater Accra region is only partially meeting its objectives. While it is found to be sensitive, representative and timely, the data quality was sub-optimal. We recommend the determination of thresholds for alert and outbreak detection and ensuring that sentinel sites meet their weekly case-detection targets.

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