No abstract

BackgroundOver the last decade, capacity for influenza surveillance and research in West Africa has strengthened. Data from these surveillance systems showed influenza A(H1N1)pdm09 circulated in West Africa later than in other regions of the continent.MethodsWe contacted 11 West African countries to collect information about their influenza surveillance systems (number of sites, type of surveillance, sampling strategy, populations sampled, case definitions used, number of specimens collected and number of specimens positive for influenza viruses) for the time period January 2010 through December 2012.ResultsOf the 11 countries contacted, 8 responded: Burkina Faso, Cote d’Ivoire, Mali, Mauritania, Niger, Nigeria, Sierra Leone and Togo. Countries used standard World Health Organization (WHO) case definitions for influenza-like illness (ILI) and severe acute respiratory illness (SARI) or slight variations thereof. There were 70 surveillance sites: 26 SARI and 44 ILI. Seven countries conducted SARI surveillance and collected 3114 specimens of which 209 (7%) were positive for influenza viruses. Among influenza-positive SARI patients, 132 (63%) were influenza A [68 influenza A(H1N1)pdm09, 64 influenza A(H3N2)] and 77 (37%) were influenza B. All eight countries conducted ILI surveillance and collected 20,375 specimens, of which 2278 (11%) were positive for influenza viruses. Among influenza-positive ILI patients, 1431 (63%) were influenza A [820 influenza A(H1N1)pdm09, 611 influenza A(H3N2)] and 847 (37%) were influenza B. A majority of SARI and ILI case-patients who tested positive for influenza (72% SARI and 59% ILI) were children aged 0–4 years, as were a majority of those enrolled in surveillance. The seasonality of influenza and the predominant influenza type or subtype varied by country and year.ConclusionsInfluenza A(H1N1)pdm09 continued to circulate in West Africa along with influenza A(H3N2) and influenza B during 2010–2012. Although ILI surveillance systems produced a robust number of samples during the study period, more could be done to strengthen surveillance among hospitalized SARI case-patients. Surveillance systems captured young children but lacked data on adults and the elderly. More data on risk groups for severe influenza in West Africa are needed to help shape influenza prevention and clinical management policies and guidelines.Electronic supplementary materialThe online version of this article (10.1186/s12879-017-2839-1) contains supplementary material, which is available to authorized users.

After the successful roll out of MenAfriVac, Nigeria has experienced sequential meningitis outbreaks attributed to meningococcus serogroup C (NmC). Zamfara State in North-western Nigeria recently was at the epicentre of the largest NmC outbreak in the 21st Century with 7,140 suspected meningitis cases and 553 deaths reported between December 2016 and May 2017. The overall attack rate was 155 per 100,000 population and children 5–14 years accounted for 47% (3,369/7,140) of suspected cases. The case fatality rate (CFR) among children 5–9 years was 10%, double that reported among adults ≥ 30 years (5%). NmC and pneumococcus accounted for 94% (172/184) and 5% (9/184) of the laboratory-confirmed cases, respectively. The sequenced NmC belonged to the ST-10217 clonal complex (CC). All serotyped pneumococci were PCV10 serotypes. The emergence of NmC ST-10217 CC outbreaks threatens the public health gains made by MenAfriVac, which calls for an urgent strategic action against meningitis outbreaks.

Background: Non-cold chain-dependent HIV rapid testing has been adopted in many resource-constrained nations as a strategy for reaching out to populations. HIV rapid test kits (RTKs) have the advantage of ease of use, low operational cost and short turnaround times. Before 2005, different RTKs had been used in Nigeria without formal evaluation. Between 2005 and 2007, a study was conducted to formally evaluate a number of RTKs and construct HIV testing algorithms. Objectives: The objectives of this study were to assess and select HIV RTKs and develop national testing algorithms. Method: Nine RTKs were evaluated using 528 well-characterised plasma samples. These comprised 198 HIV-positive specimens (37.5%) and 330 HIV-negative specimens (62.5%), collected nationally. Sensitivity and specificity were calculated with 95% confidence intervals for all nine RTKs singly and for serial and parallel combinations of six RTKs; and relative costs were estimated. Results: Six of the nine RTKs met the selection criteria, including minimum sensitivity and specificity (both ≥ 99.0%) requirements. There were no significant differences in sensitivities or specificities of RTKs in the serial and parallel algorithms, but the cost of RTKs in parallel algorithms was twice that in serial algorithms. Consequently, three serial algorithms, comprising four test kits (BundiTM, DetermineTM, Stat-Pak® and Uni-GoldTM) with 100.0% sensitivity and 99.1% – 100.0% specificity, were recommended and adopted as national interim testing algorithms in 2007. Conclusion: This evaluation provides the first evidence for reliable combinations of RTKs for HIV testing in Nigeria. However, these RTKs need further evaluation in the field (Phase II) to re-validate their performance.

ObjectiveTo assess the performance of the surveillance system and identify factors affecting the performance.