We describe the epidemiological characteristics, pattern of circulation, and geographical distribution of influenza B viruses and its lineages using data from the Global Influenza B Study. We included over 1.8 million influenza cases occurred in thirty-one countries during 2000–2018. We calculated the proportion of cases caused by influenza B and its lineages; determined the timing of influenza A and B epidemics; compared the age distribution of B/Victoria and B/Yamagata cases; and evaluated the frequency of lineage-level mismatch for the trivalent vaccine. The median proportion of influenza cases caused by influenza B virus was 23.4%, with a tendency (borderline statistical significance, p = 0.060) to be higher in tropical vs. temperate countries. Influenza B was the dominant virus type in about one every seven seasons. In temperate countries, influenza B epidemics occurred on average three weeks later than influenza A epidemics; no consistent pattern emerged in the tropics. The two B lineages caused a comparable proportion of influenza B cases globally, however the B/Yamagata was more frequent in temperate countries, and the B/Victoria in the tropics (p = 0.048). B/Yamagata patients were significantly older than B/Victoria patients in almost all countries. A lineage-level vaccine mismatch was observed in over 40% of seasons in temperate countries and in 30% of seasons in the tropics. The type B virus caused a substantial proportion of influenza infections globally in the 21^st century, and its two virus lineages differed in terms of age and geographical distribution of patients. These findings will help inform health policy decisions aiming to reduce disease burden associated with seasonal influenza.

Background: Economic burden estimates are essential to guide policy‐making for influenza vaccination, especially in resource‐limited settings.Methods: We estimated the cost, absenteeism, and years of life lost (YLL) of medically and non‐medically attended influenza‐associated mild and severe respiratory, circulatory and non‐respiratory/non‐circulatory illness in South Africa during 2013‐2015 using a modified version of the World Health Organization (WHO) worksheet based tool for estimating the economic burden of seasonal influenza. Additionally, we restricted the analysis to influenza‐associated severe acute respiratory illness (SARI) and influenza‐like illness (ILI; subsets of all‐respiratory illnesses) as suggested in the WHO manual.Results: The estimated mean annual cost of influenza‐associated illness was $270.5 million, of which $111.3 million (41%) were government‐incurred costs, 40.7 million (15%) were out‐of‐pocket expenses, and $118.4 million (44%) were indirect costs. The cost of influenza‐associated medically attended mild illness ($107.9 million) was 2.3 times higher than that of severe illness ($47.1 million). Influenza‐associated respiratory illness costs ($251.4 million) accounted for 93% of the total cost. Estimated absenteeism and YLL were 13.2 million days and 304 867 years, respectively. Among patients with influenza‐associated WHO‐defined ILI or SARI, the costs ($95.3 million), absenteeism (4.5 million days), and YLL (65 697) were 35%, 34%, and 21% of the total economic and health burden of influenza.Conclusion: The economic burden of influenza‐associated illness was substantial from both a government and a societal perspective. Models that limit estimates to those obtained from patients with WHO‐defined ILI or SARI substantially underestimated the total economic and health burden of influenza‐associated illness.

Studies describing the epidemiology of influenza B lineages in South Africa are lacking. We conducted a prospective study to describe the circulation of influenza B/Victoria and B/Yamagata lineages among patients of all ages enrolled in South Africa through three respiratory illness surveillance systems between 2005 and 2014: (i) the Viral Watch (VW) program enrolled outpatients with influenza-like illness (ILI) from private healthcare facilities during 2005–2014; (ii) the influenza-like illnesses program enrolled outpatients in public healthcare clinics (ILI/PHC) during 2012–2014; and (iii) the severe acute respiratory illnesses (SARI) program enrolled inpatients from public hospitals during 2009–2014. Influenza B viruses were detected by virus isolation during 2005 to 2009 and by real-time reverse transcription polymerase chain reaction from 2009–2014. Clinical and epidemiological characteristics of patients hospitalized with SARI and infected with different influenza B lineages were also compared using unconditional logistic regression. Influenza viruses were detected in 22% (8,706/39,804) of specimens from patients with ILI or SARI during 2005–2014, of which 24% (2,087) were positive for influenza B. Influenza B viruses predominated in all three surveillance systems in 2010. B/Victoria predominated prior to 2011 (except 2008) whereas B/Yamagata predominated thereafter (except 2012). B lineages co-circulated in all seasons, except in 2013 and 2014 for SARI and ILI/PHC surveillance. Among influenza B-positive SARI cases, the detection of influenza B/Yamagata compared to influenza B/Victoria was significantly higher in individuals aged 45–64 years (adjusted odds ratio [aOR]: 4.2; 95% confidence interval [CI]: 1.1–16.5) and ≥65 years (aOR: 12.2; 95% CI: 2.3–64.4) compared to children aged 0–4 years, but was significantly lower in HIV-infected patients (aOR: 0.4; 95% CI: 0.2–0.9). B lineages co-circulated in most seasons except in 2013 and 2014. Hospitalized SARI cases display differential susceptibility for the two influenza B lineages, with B/Victoria being more prevalent among children and HIV-infected persons.

The circulation of Omicron BA.1 led to the rapid increase in severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) cases in South Africa in November 2021, which warranted the use of more rapid detection methods. We, therefore, assessed the ability to detect Omicron BA.1 using genotyping assays to identify specific mutations in SARS‐CoV‐2 positive samples, Gauteng province, South Africa. The TaqPath™ COVID‐19 real‐time polymerase chain reaction assay was performed on all samples selected to identify spike gene target failure (SGTF). SARS‐CoV‐2 genotyping assays were used for the detection of del69/70 and K417N mutation. Whole‐genome sequencing was performed on a subset of genotyped samples to confirm these findings. Of the positive samples received, 11.0% (175/1589) were randomly selected to assess if SGTF and genotyping assays, that detect del69/70 and K417N mutations, could identify Omicron BA.1. We identified SGTF in 98.9% (173/175) of samples, of which 88.0% (154/175) had both the del69/70 and K417N mutation. The genotyped samples (45.7%; 80/175) that were sequenced confirmed Omicron BA.1 (97.5%; 78/80). Our data show that genotyping for the detection of the del69/70 and K417N coupled with SGTF is efficient to exclude Alpha and Beta variants and rapidly detect Omicron BA.1. However, we still require assays for the detection of unique mutations that will allow for the differentiation between other Omicron sublineages. Therefore, the use of genotyping assays to detect new dominant or emerging lineages of SARS‐CoV‐2 will be beneficial in limited‐resource settings.

Aim: To investigate the prevalence of human bocavirus (hBoV), human coronaviruses (hCoV), and human polyomaviruses (hPyV) among patients with severe acute respiratory illness (SARI), in South Africa.Methods: The study included 680 South African patients randomly selected in age‐defined categories from hospitalised patients enrolled through SARI surveillance during 2012 to 2013. A multiplex reverse transcription real‐time polymerase chain reaction assay was used to detect hBoV; hCoV‐OC43, hCoV‐229E, hCoV‐NL63, and hCoV‐HKU1; and Washington University hPyV (hPyV‐WU) and Karolinska Insitute hPyV (hPyV‐KI), in respiratory tract specimens collected from patients with SARI. All respiratory specimens from patients enrolled through SARI surveillance were also routinely tested by multiplex reverse transcription real‐time polymerase chain reaction for adenovirus; enterovirus; human metapneumovirus; parainfluenza virus types 1, 2, and 3; respiratory syncytial virus; rhinovirus; influenza A, and influenza B.Results: Human bocavirus, hCoV‐229E, and hPyV‐WU were detected in 3.7% (25/680), 4.1% (28/680), and 4.1% (28/680) of respiratory specimens, respectively. All other viruses were detected in <2% of specimens. Rhinovirus was the most common coinfecting virus (21.4%‐60.7%), followed by adenovirus (21.4%‐39.3%), and respiratory syncytial virus (10.7%‐24.0%). Testing for the additional viruses (hBoV, hCoV, and hPyV) decreased the number of specimens that initially tested negative by 2.9% (20/680).Conclusion: Inclusion of laboratory tests for hBoV, hCoV‐229E, and hPyV‐WU in differential testing algorithms for surveillance and diagnostics for suspected cases of respiratory illness of unknown cause may improve our understanding of the etiology of SARI, especially in a country like South Africa with a high number of immune compromised persons.

The use of molecular diagnostic techniques for the evaluation of the impact of pneumococcal conjugate vaccines (PCVs) has not been documented. We aimed to evaluate the impact of PCVs on invasive pneumococcal disease (IPD) using polymerase chain reaction (PCR)-based techniques and compare with results obtained from culture-based methods. We implemented two independent surveillance programs for IPD among individuals hospitalized at one large surveillance site in Soweto, South Africa during 2009–2012: (i) PCR-based (targeting the lytA gene) syndromic pneumonia surveillance; and (ii) culture-based laboratory surveillance. Positive samples were serotyped. The molecular serotyping assay included targets for 42 serotypes including all serotypes/serogroups included in the 7-valent (PCV-7) and 13-valent (PCV-13) PCV. The Quellung reaction was used for serotyping of culture-positive cases. We calculated the change in rates of IPD (lytA- or culture-positive) among HIV-uninfected children aged <2 years from the year of PCV-7 introduction (2009) to the post-vaccine years (2011 or 2012). During the study period there were 607 lytA-positive and 1,197 culture-positive cases that were serotyped. Samples with lytA cycle threshold (Ct)-values ≥35 (30.2 %; 123/407) were significantly less likely to have a serotype/serogroup detected for serotypes included in the molecular serotyping assay than those with Ct-values <35 (78.0 %; 156/200) (p < 0.001). From 2009 to 2012 rates of PCV-7 serotypes/serogroups decreased −63.8 % (95 % CI: −79.3 % to −39.1 %) among lytA-positive cases and −91.7 % (95 % CI: −98.8 % to −73.6 %) among culture-positive cases. Rates of lytA-positive non-vaccine serotypes/serogroups also significantly decreased (−71.7 %; 95 % CI: −81.1 % to −58.5 %) over the same period. Such decline was not observed among the culture-positive non-vaccine serotypes (1.2 %; 95 % CI: −96.7 % to 58.4 %). Significant downward trends in IPD PCV-7 serotype-associated rates were observed among patients tested by PCR or culture methods; however trends of non-vaccine serotypes/serogroups differed between the two groups. Misclassifications of serotypes/serogroups, affecting the use of non-vaccine serotypes as a control group, may have occurred due to the low performance of the serotyping assay among lytA-positive cases with high Ct-values. Until PCR methods improve further, culture methods should continue to be used to monitor the effects of PCV vaccination programs on IPD incidence.