ABSTRACT
BACKGROUND: Influenza surveillance data from tropical, sub-Saharan African countries are limited. To better understand the epidemiology of influenza, Nigeria initiated influenza surveillance in 2008. METHODS: Outpatients with influenza-like illness (ILI) and inpatients with severe acute respiratory illness (SARI) were enrolled at 4 sentinel facilities. Epidemiologic data were obtained, and respiratory specimens were tested for influenza viruses, using real-time reverse-transcription polymerase chain reaction assays. RESULTS: During April 2009-August 2010, 2841 patients were enrolled. Of 2803 specimens tested, 217 (7.7%) were positive for influenza viruses (167 [8%] were from subjects with ILI, 17 [5%] were from subjects with SARI, and 33 were from subjects with an unclassified condition). During the prepandemic period, subtype H3N2 (A[H3N2]) was the dominant circulating influenza A virus subtype; 2009 pandemic influenza A virus subtype H1N1 (A[H1N1]pdm09) replaced A(H3N2) as the dominant circulating virus during November 2009. Among persons with ILI, A(H1N1)pdm09 was most frequently found in children aged 5-17 years, whereas among subjects with SARI, it was most frequently found in persons aged ≥ 65 years. The percentage of specimens that tested positive for influenza viruses peaked at 18.9% in February 2010, and the majority were A(H1N1)pdm09. CONCLUSIONS: Influenza viruses cause ILI and SARI in Nigeria. Data from additional years are needed to better understand the epidemiology and seasonality of influenza viruses in Nigeria.
Subject(s)
Influenza A virus/classification , Influenza A virus/isolation & purification , Influenza, Human/epidemiology , Influenza, Human/virology , Adolescent , Adult , Aged , Aged, 80 and over , Body Fluids/virology , Child , Child, Preschool , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Nigeria/epidemiology , Prevalence , Real-Time Polymerase Chain Reaction , Sentinel Surveillance , Young AdultABSTRACT
BACKGROUND: In response to the potential threat of an influenza pandemic, several international institutions and governments, in partnership with African countries, invested in the development of epidemiologic and laboratory influenza surveillance capacity in Africa and the African Network of Influenza Surveillance and Epidemiology (ANISE) was formed. METHODS: We used a standardized form to collect information on influenza surveillance system characteristics, the number and percent of influenza-positive patients with influenza-like illness (ILI), or severe acute respiratory infection (SARI) and virologic data from countries participating in ANISE. RESULTS: Between 2006 and 2010, the number of ILI and SARI sites in 15 African countries increased from 21 to 127 and from 2 to 98, respectively. Children 0-4 years accounted for 48% of all ILI and SARI cases of which 22% and 10%, respectively, were positive for influenza. Influenza peaks were generally discernible in North and South Africa. Substantial cocirculation of influenza A and B occurred most years. CONCLUSIONS: Influenza is a major cause of respiratory illness in Africa, especially in children. Further strengthening influenza surveillance, along with conducting special studies on influenza burden, cost of illness, and role of other respiratory pathogens will help detect novel influenza viruses and inform and develop targeted influenza prevention policy decisions in the region.
Subject(s)
Influenza, Human/diagnosis , Influenza, Human/epidemiology , Sentinel Surveillance , Adolescent , Adult , Africa/epidemiology , Aged , Aged, 80 and over , Child , Child, Preschool , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Prevalence , Young AdultABSTRACT
BACKGROUND: The Nigeria AIDS Indicator and Impact Survey (NAIIS), a cross-sectional household survey, was conducted in 2018 with primary objectives to estimate HIV prevalence, HIV-1 incidence, and status of UNAIDS 90-90-90 cascade. We conducted retrospective analysis of the performance of HIV rapid tests and the national HIV testing algorithm used in Nigeria. METHODS: The national algorithm included Determine HIV-1/2 as test 1 (T1), Unigold HIV-1/2 as test 2 (T2), and StatPak HIV-1/2 as the tie-breaker test (T3). Individuals reactive with T1 and either T2 or T3 were considered HIV-positive. HIV-positive specimens from the algorithm were further confirmed for the survey using supplemental test Geenius HIV-1/2. If Geenius did not confirm HIV-positive status, HIV-1 Western blot was performed. We calculated the concordance between tests and positive predictive value (PPV) of the algorithm on unweighted data. RESULTS: Of 204,930 participants (ages ≥18 months) 5,103 (2.5%) were reactive on T1. Serial testing of T1 reactive specimens with T2 or if needed by tiebreaker T3 identified 2958 (1.44%) persons as HIV-positive. Supplemental testing confirmed 2,800 (95%) as HIV-positive (HIV-1 = 2,767 [98.8%]; HIV-2 = 5 [0.2%]; dual infections = 22 [0.8%]). Concordance between T1 and T2 was 56.6% while PPV of the national algorithm was 94.5%. CONCLUSIONS: Our results show high discordant rates and poor PPV of the national algorithm with a false-positive rate of about 5.5% in the NAIIS survey. Considering our findings have major implications for HIV diagnosis in routine HIV testing services, additional evaluation of testing algorithm is warranted in Nigeria.