Influenza surveillance capacity improvements in Africa during 2011-2017

Clustering and visualisation of the GABRIEL network expertise in the field of infectious diseases

INTRODUCTION

The Global Approach to Biology Research, Infectious diseases and Epidemics in Low-income countries (GABRIEL) network is an international scientific network of 21 centres coordinated by the Merieux Foundation (Lyon, France). Mapping and characterising the similarities and differences in expertise and activities across four major infectious diseases (tuberculosis, antimicrobial-resistant infections, acute respiratory infections and emerging pathogens) among these centres would help to provide a better understanding of the network's capacity. It will also highlight how the applied methodology can enhance information sharing within research networks.

METHODS

Each centre responded to a questionnaire on their core activities and research themes. An advanced multivariate analysis was performed to relate all items together and highlight new synergies among members of the GABRIEL network. Similarities were found using a clustering algorithm and data were visualised using alluvial plots.

RESULTS

This strategy enabled to find new patterns in the GABRIEL network for the implementation of new projects on global health, regardless of geographical proximity or historical connections. Five clusters based on core activities, consisting of 6, 1, 3, 9 and 2 research units, respectively, have been identified, with clusters 1 and 4, including the majority of the units. Four clusters have been defined based on the four major infectious diseases, comprising 7, 3, 5 and 6 research units, respectively.

CONCLUSIONS

The same methodology could also be applied to identify proximities on other networks of experts or between members of different networks for more efficient research or surveillance global programmes.

Microfluidic qPCR for detection of 21 common respiratory viruses in children with influenza-like illness

Multiple respiratory viruses lead to high morbidity and mortality, yet global surveillance platforms focus primarily on seasonal influenza viruses. The COVID-19 pandemic and new RSV vaccines highlight the importance of a broader approach. Upper respiratory tract swabs from children aged 24-59 months presenting with influenza-like illness in The Gambia were collected during follow-up of a live-attenuated influenza vaccine randomised controlled trial in 2017-18. A microfluidic quantitative polymerase chain reaction (qPCR) assay was established and used to detect 21 respiratory viruses. 76.6% of samples had one or more viruses detected (n = 121/158). The viruses detected most frequently were rhinovirus (n = 37/158, 23.4%) and adenovirus (n = 34/158, 21.5%), followed by parainfluenza virus 3, influenza B and human metapneumovirus B. A third of positive samples had multiple viruses detected (two n = 31/121, 25.6%; three n = 9/121, 7.4%). Our data demonstrates how microfluidic qPCR is a useful tool for high-throughput, comprehensive detection of multiple respiratory viruses in surveillance platforms. Rapidly changing epidemiology exemplifies the need for new, broader approaches to virus surveillance in low-resource settings to respond to future epidemics and to guide the need for and use of new prevention and therapeutic measures.

Genetic and antigenic characterization of influenza A(H3N2) virus after 13 consecutive years of influenza surveillance in Senegal, 2010-2022

Despite decades of influenza surveillance in many African countries, little is known about the evolutionary dynamics of seasonal influenza viruses. This study aimed to characterize the epidemiological, genetic and antigenic profiles of A/H3N2 viruses in Senegal from 2010 to 2022. A/H3N2 infection was confirmed using reverse transcription-polymerase chain reaction. Subsequently, a representative of A/H3N2 isolates was selected for genome sequencing. Predicted vaccine efficacy was measured using the Pepitope model. During the study period, 22638 samples were tested and influenza was detected in 31.8%, among which type A was confirmed in 78.1%. Of the Influenza A cases, the H3N2 subtype was detected in 29.8%, peaking at expected times during the rainy season. Genome sequencing of 123A/H3N2 isolates yielded 24 complete and 99 partial genomic sequences. Phylogenetic analysis revealed the circulation of multiple clades of A/H3N2 in Senegal, including 2a.3, 3C.2 and 3C.3a. A/H3N2 isolates were mainly susceptible to the influenza antiviral drugs oseltamivir and zanamivir, but the primary adamantine-resistance marker, S31N was encountered in all isolates. At least nine potential N-linked glycosylation sites were predicted among A/H3N2 strains, six of which (at positions 24, 38, 79, 181, 262 and 301) remains conserved among all isolates. Antigenic distances between circulating strains and vaccine viruses indicated varying vaccine efficacies, from suboptimal to moderate protection. The findings emphasize the need to enhance local genomic and antigenic surveillance and further research on influenza epidemiology and genetic evolution in sub-Saharan Africa.

Estimating household contact matrices structure from easily collectable metadata

Contact matrices are a commonly adopted data representation, used to develop compartmental models for epidemic spreading, accounting for the contact heterogeneities across age groups. Their estimation, however, is generally time and effort consuming and model-driven strategies to quantify the contacts are often needed. In this article we focus on household contact matrices, describing the contacts among the members of a family and develop a parametric model to describe them. This model combines demographic and easily quantifiable survey-based data and is tested on high resolution proximity data collected in two sites in South Africa. Given its simplicity and interpretability, we expect our method to be easily applied to other contexts as well and we identify relevant questions that need to be addressed during the data collection procedure.

Timing of seasonal influenza epidemics for 25 countries in Africa during 2010-19: a retrospective analysis

BACKGROUND

Using country-specific surveillance data to describe influenza epidemic activity could inform decisions on the timing of influenza vaccination. We analysed surveillance data from African countries to characterise the timing of seasonal influenza epidemics to inform national vaccination strategies.

METHODS

We used publicly available sentinel data from African countries reporting to the WHO Global Influenza Surveillance and Response FluNet platform that had 3-10 years of data collected during 2010-19. We calculated a 3-week moving proportion of samples positive for influenza virus and assessed epidemic timing using an aggregate average method. The start and end of each epidemic were defined as the first week when the proportion of positive samples exceeded or went below the annual mean, respectively, for at least 3 consecutive weeks. We categorised countries into five epidemic patterns: northern hemisphere-dominant, with epidemics occurring in October-March; southern hemisphere-dominant, with epidemics occurring in April-September; primarily northern hemisphere with some epidemic activity in southern hemisphere months; primarily southern hemisphere with some epidemic activity in northern hemisphere months; and year-round influenza transmission without a discernible northern hemisphere or southern hemisphere predominance (no clear pattern).

FINDINGS

Of the 34 countries reporting data to FluNet, 25 had at least 3 years of data, representing 46% of the countries in Africa and 89% of Africa's population. Study countries reported RT-PCR respiratory virus results for a total of 503 609 specimens (median 12 971 [IQR 9607-20 960] per country-year), of which 74 001 (15%; median 2078 [IQR 1087-3008] per country-year) were positive for influenza viruses. 248 epidemics occurred across 236 country-years of data (median 10 [range 7-10] per country). Six (24%) countries had a northern hemisphere pattern (Algeria, Burkina Faso, Egypt, Morocco, Niger, and Tunisia). Eight (32%) had a primarily northern hemisphere pattern with some southern hemisphere epidemics (Cameroon, Ethiopia, Mali, Mozambique, Nigeria, Senegal, Tanzania, and Togo). Three (12%) had a primarily southern hemisphere pattern with some northern hemisphere epidemics (Ghana, Kenya, and Uganda). Three (12%) had a southern hemisphere pattern (Central African Republic, South Africa, and Zambia). Five (20%) had no clear pattern (Côte d'Ivoire, DR Congo, Madagascar, Mauritius, and Rwanda).

INTERPRETATION

Most countries had identifiable influenza epidemic periods that could be used to inform authorities of non-seasonal and seasonal influenza activity, guide vaccine timing, and promote timely interventions.

FUNDING

None.

TRANSLATIONS

For the Berber, Luganda, Xhosa, Chewa, Yoruba, Igbo, Hausa and Afan Oromo translations of the abstract see Supplementary Materials section.

Phylogenomic analysis uncovers a 9-year variation of Uganda influenza type-A strains from the WHO-recommended vaccines and other Africa strains

Genetic characterisation of circulating influenza viruses directs annual vaccine strain selection and mitigation of infection spread. We used next-generation sequencing to locally generate whole genomes from 116 A(H1N1)pdm09 and 118 A(H3N2) positive patient swabs collected across Uganda between 2010 and 2018. We recovered sequences from 92% (215/234) of the swabs, 90% (193/215) of which were whole genomes. The newly-generated sequences were genetically and phylogenetically compared to the WHO-recommended vaccines and other Africa strains sampled since 1994. Uganda strain hemagglutinin (n = 206), neuraminidase (n = 207), and matrix protein (MP, n = 213) sequences had 95.23-99.65%, 95.31-99.79%, and 95.46-100% amino acid similarity to the 2010-2020 season vaccines, respectively, with several mutated hemagglutinin antigenic, receptor binding, and N-linked glycosylation sites. Uganda influenza type-A virus strains sequenced before 2016 clustered uniquely while later strains mixed with other Africa and global strains. We are the first to report novel A(H1N1)pdm09 subclades 6B.1A.3, 6B.1A.5(a,b), and 6B.1A.6 (± T120A) that circulated in Eastern, Western, and Southern Africa in 2017-2019. Africa forms part of the global influenza ecology with high viral genetic diversity, progressive antigenic drift, and local transmissions. For a continent with inadequate health resources and where social distancing is unsustainable, vaccination is the best option. Hence, African stakeholders should prioritise routine genome sequencing and analysis to direct vaccine selection and virus control.

United States Centers for Disease Control and Prevention support for influenza surveillance, 2013-2021

Objective

To assess the stability of improvements in global respiratory virus surveillance in countries supported by the United States Centers for Disease Control and Prevention (CDC) after reductions in CDC funding and with the stress of the coronavirus disease 2019 (COVID-19) pandemic.

Methods

We assessed whether national influenza surveillance systems of CDC-funded countries: (i) continued to analyse as many specimens between 2013 and 2021; (ii) participated in activities of the World Health Organization's (WHO) Global Influenza Surveillance and Response System; (iii) tested enough specimens to detect rare events or signals of unusual activity; and (iv) demonstrated stability before and during the COVID-19 pandemic. We used CDC budget records and data from the WHO Global Influenza Surveillance and Response System.

Findings

While CDC reduced per-country influenza funding by about 75% over 10 years, the number of specimens tested annually remained stable (mean 2261). Reporting varied substantially by country and transmission zone. Countries funded by CDC accounted for 71% (range 61-75%) of specimens included in WHO consultations on the composition of influenza virus vaccines. In 2019, only eight of the 17 transmission zones sent enough specimens to WHO collaborating centres before the vaccine composition meeting to reliably identify antigenic variants.

Conclusion

Great progress has been made in the global understanding of influenza trends and seasonality. To optimize surveillance to identify atypical influenza viruses, and to integrate molecular testing, sequencing and reporting of severe acute respiratory syndrome coronavirus 2 into existing systems, funding must continue to support these efforts.

Molecular Epidemiology and Evolutionary Dynamics of Human Influenza Type-A Viruses in Africa: A Systematic Review

Genomic characterization of circulating influenza type-A viruses (IAVs) directs the selection of appropriate vaccine formulations and early detection of potentially pandemic virus strains. However, longitudinal data on the genomic evolution and transmission of IAVs in Africa are scarce, limiting Africa's benefits from potential influenza control strategies. We searched seven databases: African Journals Online, Embase, Global Health, Google Scholar, PubMed, Scopus, and Web of Science according to the PRISMA guidelines for studies that sequenced and/or genomically characterized Africa IAVs. Our review highlights the emergence and diversification of IAVs in Africa since 1993. Circulating strains continuously acquired new amino acid substitutions at the major antigenic and potential N-linked glycosylation sites in their hemagglutinin proteins, which dramatically affected vaccine protectiveness. Africa IAVs phylogenetically mixed with global strains forming strong temporal and geographical evolution structures. Phylogeographic analyses confirmed that viral migration into Africa from abroad, especially South Asia, Europe, and North America, and extensive local viral mixing sustained the genomic diversity, antigenic drift, and persistence of IAVs in Africa. However, the role of reassortment and zoonosis remains unknown. Interestingly, we observed substitutions and clades and persistent viral lineages unique to Africa. Therefore, Africa's contribution to the global influenza ecology may be understated. Our results were geographically biased, with data from 63% (34/54) of African countries. Thus, there is a need to expand influenza surveillance across Africa and prioritize routine whole-genome sequencing and genomic analysis to detect new strains early for effective viral control.

Influenza surveillance capacity improvements in Africa during 2011-2017

Background

Influenza surveillance helps time prevention and control interventions especially where complex seasonal patterns exist. We assessed influenza surveillance sustainability in Africa where influenza activity varies and external funds for surveillance have decreased.

Methods

We surveyed African Network for Influenza Surveillance and Epidemiology (ANISE) countries about 2011‐2017 surveillance system characteristics. Data were summarized with descriptive statistics and analyzed with univariate and multivariable analyses to quantify sustained or expanded influenza surveillance capacity in Africa.

Results

Eighteen (75%) of 24 ANISE members participated in the survey; their cumulative population of 710 751 471 represent 56% of Africa's total population. All 18 countries scored a mean 95% on WHO laboratory quality assurance panels. The number of samples collected from severe acute respiratory infection case‐patients remained consistent between 2011 and 2017 (13 823 vs 13 674 respectively) but decreased by 12% for influenza‐like illness case‐patients (16 210 vs 14 477). Nine (50%) gained capacity to lineage‐type influenza B. The number of countries reporting each week to WHO FluNet increased from 15 (83%) in 2011 to 17 (94%) in 2017.

Conclusions

Despite declines in external surveillance funding, ANISE countries gained additional laboratory testing capacity and continued influenza testing and reporting to WHO. These gains represent important achievements toward sustainable surveillance and epidemic/pandemic preparedness.