Regional Evaluation of Two SARS-CoV-2 Antigen Rapid Diagnostic Tests in East Africa.

The clinical performance of two rapid antigen tests for the diagnosis of Severe Acute Respiratory Coronavirus (SARS-CoV-2) were regionally evaluated in East African populations. Swabs were collected from 1,432 individuals from five Partner States of the East African Community (Tanzania, Uganda, Burundi, Rwanda and South Sudan). The two rapid antigen tests (Bionote NowCheck COVID-19 Ag and SD Biosensor STANDARD Q COVID-19 Ag) were evaluated against the detection of SARS-CoV-2 RNA by the Reverse Transcription PCR (RT-PCR) gold standard. Of the concordant results with both RT-PCR and rapid antigen test data (862 for Bionote and 852 for SD Biosensor), overall clinical sensitivity was 60% and 50% for the Bionote NowCheck and the SD Biosensor STANDARD Q, respectively. Stratification by viral load, including samples with RT-PCR cycle thresholds (Ct) of <25, improved sensitivity to 90% for both rapid diagnostic tests (RDTs). Overall specificity was good at 99% for both antigen tests. Taken together, the clinical performance of both Ag-RDTs in real world settings within the East African target population was lower than has been reported elsewhere and below the acceptable levels for sensitivity of >80%, as defined by the WHO. Therefore, the rapid antigen test alone should not be used for diagnosis but could be used as part of an algorithm to identify potentially infectious individuals with high viral load. IMPORTANCE Accurate diagnostic tests are essential to both support the management and containment of outbreaks, as well as inform appropriate patient care. In the case of the SARS-CoV-2 pandemic, antigen Rapid Diagnostic Tests (Ag-RDTs) played a major role in this function, enabling widespread testing by untrained individuals, both at home and within health facilities. In East Africa, a number of SARS-CoV-2 Ag-RDTs are available; however, there remains little information on their true test performance within the region, in the hands of the health workers routinely carrying out SARS-CoV-2 diagnostics. This study contributes test performance data for two commonly used SARS-CoV-2 Ag-RDTs in East Africa, which will help inform the use of these RDTs within the region.

Genomic sequencing of SARS-CoV-2 in Rwanda reveals the importance of incoming travelers on lineage diversity.

COVID-19 transmission rates are often linked to locally circulating strains of SARS-CoV-2. Here we describe 203 SARS-CoV-2 whole genome sequences analyzed from strains circulating in Rwanda from May 2020 to February 2021. In particular, we report a shift in variant distribution towards the emerging sub-lineage A.23.1 that is currently dominating. Furthermore, we report the detection of the first Rwandan cases of the B.1.1.7 and B.1.351 variants of concern among incoming travelers tested at Kigali International Airport. To assess the importance of viral introductions from neighboring countries and local transmission, we exploit available individual travel history metadata to inform spatio-temporal phylogeographic inference, enabling us to take into account infections from unsampled locations. We uncover an important role of neighboring countries in seeding introductions into Rwanda, including those from which no genomic sequences were available. Our results highlight the importance of systematic genomic surveillance and regional collaborations for a durable response towards combating COVID-19.

The East African Community (EAC) mobile laboratory networks in Kenya, Burundi, Tanzania, Rwanda, Uganda, and South Sudan-from project implementation to outbreak response against Dengue, Ebola, COVID-19, and epidemic-prone diseases.

BACKGROUND: East Africa is home to 170 million people and prone to frequent outbreaks of viral haemorrhagic fevers and various bacterial diseases. A major challenge is that epidemics mostly happen in remote areas, where infrastructure for Biosecurity Level (BSL) 3/4 laboratory capacity is not available. As samples have to be transported from the outbreak area to the National Public Health Laboratories (NPHL) in the capitals or even flown to international reference centres, diagnosis is significantly delayed and epidemics emerge. MAIN TEXT: The East African Community (EAC), an intergovernmental body of Burundi, Rwanda, Tanzania, Kenya, Uganda, and South Sudan, received 10 million € funding from the German Development Bank (KfW) to establish BSL3/4 capacity in the region. Between 2017 and 2020, the EAC in collaboration with the Bernhard-Nocht-Institute for Tropical Medicine (Germany) and the Partner Countries' Ministries of Health and their respective NPHLs, established a regional network of nine mobile BSL3/4 laboratories. These rapidly deployable laboratories allowed the region to reduce sample turn-around-time (from days to an average of 8h) at the centre of the outbreak and rapidly respond to epidemics. In the present article, the approach for implementing such a regional project is outlined and five major aspects (including recommendations) are described: (i) the overall project coordination activities through the EAC Secretariat and the Partner States, (ii) procurement of equipment, (iii) the established laboratory setup and diagnostic panels, (iv) regional training activities and capacity building of various stakeholders and (v) completed and ongoing field missions. The latter includes an EAC/WHO field simulation exercise that was conducted on the border between Tanzania and Kenya in June 2019, the support in molecular diagnosis during the Tanzanian Dengue outbreak in 2019, the participation in the Ugandan National Ebola response activities in Kisoro district along the Uganda/DRC border in Oct/Nov 2019 and the deployments of the laboratories to assist in SARS-CoV-2 diagnostics throughout the region since early 2020. CONCLUSIONS: The established EAC mobile laboratory network allows accurate and timely diagnosis of BSL3/4 pathogens in all East African countries, important for individual patient management and to effectively contain the spread of epidemic-prone diseases.

Comparative global epidemiology of influenza, respiratory syncytial and parainfluenza viruses, 2010-2015.

OBJECTIVES: To improve our understanding of the global epidemiology of common respiratory viruses by analysing their contemporaneous incidence at multiple sites. METHODS: 2010-2015 incidence data for influenza A (IAV), influenza B (IBV), respiratory syncytial (RSV) and parainfluenza (PIV) virus infections were collected from 18 sites (14 countries), consisting of local (n = 6), regional (n = 9) and national (n = 3) laboratories using molecular diagnostic methods. Each site submitted monthly virus incidence data, together with details of their patient populations tested and diagnostic assays used. RESULTS: For the Northern Hemisphere temperate countries, the IAV, IBV and RSV incidence peaks were 2-6 months out of phase with those in the Southern Hemisphere, with IAV having a sharp out-of-phase difference at 6 months, whereas IBV and RSV showed more variable out-of-phase differences of 2-6 months. The tropical sites Singapore and Kuala Lumpur showed fluctuating incidence of these viruses throughout the year, whereas subtropical sites such as Hong Kong, Brisbane and Sydney showed distinctive biannual peaks for IAV but not for RSV and PIV. CONCLUSIONS: There was a notable pattern of synchrony of IAV, IBV and RSV incidence peaks globally, and within countries with multiple sampling sites (Canada, UK, Australia), despite significant distances between these sites.

The national burden of influenza-associated severe acute respiratory illness hospitalization in Rwanda, 2012-2014.

BACKGROUND: Estimates of influenza-associated hospitalization are severely limited in low- and middle-income countries, especially in Africa. OBJECTIVES: To estimate the national number of influenza-associated severe acute respiratory illness (SARI) hospitalization in Rwanda. METHODS: We multiplied the influenza virus detection rate from influenza surveillance conducted at 6 sentinel hospitals by the national number of respiratory hospitalization obtained from passive surveillance after adjusting for underreporting and reclassification of any respiratory hospitalizations as SARI during 2012-2014. The population at risk was obtained from projections of the 2012 census. Bootstrapping was used for the calculation of confidence intervals (CI) to account for the uncertainty associated with all levels of adjustment. Rates were expressed per 100 000 population. A sensitivity analysis using a different estimation approach was also conducted. RESULTS: SARI cases accounted for 70.6% (9759/13 813) of respiratory admissions at selected hospitals: 77.2% (6783/8786) and 59.2% (2976/5028) among individuals aged <5 and ≥5 years, respectively. Overall, among SARI cases tested, the influenza virus detection rate was 6.3% (190/3022): 5.7% (127/2220) and 7.8% (63/802) among individuals aged <5 and ≥5 years, respectively. The estimated mean annual national number of influenza-associated SARI hospitalizations was 3663 (95% CI: 2930-4395-rate: 34.7; 95% CI: 25.4-47.7): 2637 (95% CI: 2110-3164-rate: 168.7; 95% CI: 135.0-202.4) among children aged <5 years and 1026 (95% CI: 821-1231-rate: 11.3; 95% CI: 9.0-13.6) among individuals aged ≥5 years. The estimates obtained from both approaches were not statistically different (overlapping CIs). CONCLUSIONS: The burden of influenza-associated SARI hospitalizations was substantial and was highest among children aged <5 years.

Influenza surveillance in 15 countries in Africa, 2006-2010.

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.

Influenza sentinel surveillance in Rwanda, 2008-2010.

BACKGROUND: In 2008, Rwanda established an influenza sentinel surveillance (ISS) system to describe the epidemiology of influenza and monitor for the emergence of novel influenza A viruses. We report surveillance results from August 2008 to July 2010. METHODS: We conducted ISS by monitoring patients with influenza-like illness (ILI) and severe acute respiratory infection (SARI) at 6 hospitals. For each case, demographic and clinical data, 1 nasopharyngeal specimen, and 1 oropharyngeal specimen were collected. Specimens were tested by real-time reverse-transcription polymerase chain reaction for influenza A and B viruses at the National Reference Laboratory in Rwanda. RESULTS: A total of 1916 cases (945 ILI and 971 SARI) were identified. Of these, 29.2% (n = 276) of ILI and 10.4% (n = 101) of SARI cases tested positive for influenza. Of the total influenza-positive cases (n = 377), 71.8% (n = 271) were A(H1N1) pdm09, 5.6% (n = 21) influenza A(H1), 7.7% (n = 29) influenza A(H3), 1.6% (n = 6) influenza A (unsubtyped), and 13.3% (n = 50) influenza B. The percentage of positivity for influenza viruses was highest in October-November and February-March, during peaks in rainfall. CONCLUSIONS: The implementation of ISS enabled characterization of the epidemiology and seasonality of influenza in Rwanda for the first time. Future efforts should determine the population-based influenza burden to inform interventions such as targeted vaccination.

2009 pandemic influenza A (H1N1) virus outbreak and response--Rwanda, October, 2009-May, 2010.

BACKGROUND: In October 2009, the first case of pandemic influenza A(H1N1)pdm09 (pH1N1) was confirmed in Kigali, Rwanda and countrywide dissemination occurred within several weeks. We describe clinical and epidemiological characteristics of this epidemic. METHODS: From October 2009 through May 2010, we undertook epidemiologic investigations and response to pH1N1. Respiratory specimens were collected from all patients meeting the WHO case definition for pH1N1, which were tested using CDC's real time RT-PCR protocol at the Rwandan National Reference Laboratory (NRL). Following documented viral transmission in the community, testing focused on clinically severe and high-risk group suspect cases. RESULTS: From October 9, 2009 through May 31, 2010, NRL tested 2,045 specimens. In total, 26% (n = 532) of specimens tested influenza positive; of these 96% (n = 510) were influenza A and 4% (n = 22) were influenza B. Of cases testing influenza A positive, 96.8% (n = 494), 3% (n = 15), and 0.2% (n = 1) were A(H1N1)pdm09, Seasonal A(H3) and Seasonal A(non-subtyped), respectively. Among laboratory-confirmed cases, 263 (53.2%) were children <15 years and 275 (52%) were female. In total, 58 (12%) cases were hospitalized with mean duration of hospitalization of 5 days (Range: 2-15 days). All cases recovered and there were no deaths. Overall, 339 (68%) confirmed cases received oseltamivir in any setting. Among all positive cases, 26.9% (143/532) were among groups known to be at high risk of influenza-associated complications, including age <5 years 23% (122/532), asthma 0.8% (4/532), cardiac disease 1.5% (8/532), pregnancy 0.6% (3/532), diabetes mellitus 0.4% (2/532), and chronic malnutrition 0.8% (4/532). CONCLUSIONS: Rwanda experienced a PH1N1 outbreak which was epidemiologically similar to PH1N1 outbreaks in the region. Unlike seasonal influenza, children <15 years were the most affected by pH1N1. Lessons learned from the outbreak response included the need to strengthen integrated disease surveillance, develop laboratory contingency plans, and evaluate the influenza sentinel surveillance system.