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

Resurgence of seasonal influenza driven by A/H3N2 and B/Victoria in succession during the 2023-2024 season in Beijing showing increased population susceptibility

During the COVID-19 pandemic, non-pharmaceutical interventions were introduced to reduce exposure to respiratory viruses. However, these measures may have led to an "immunity debt" that could make the population more vulnerable. The goal of this study was to examine the transmission dynamics of seasonal influenza in the years 2023-2024. Respiratory samples from patients with influenza-like illness were collected and tested for influenza A and B viruses. The electronic medical records of index cases from October 2023 to March 2024 were analyzed to determine their clinical and epidemiological characteristics. A total of 48984 positive cases were detected, with a pooled prevalence of 46.9% (95% CI 46.3-47.5). This season saw bimodal peaks of influenza activity, with influenza A peaked in week 48, 2023, and influenza B peaked in week 1, 2024. The pooled positive rates were 28.6% (95% CI 55.4-59.6) and 18.3% (95% CI 18.0-18.7) for influenza A and B viruses, respectively. The median values of instantaneous reproduction number were 5.5 (IQR 3.0-6.7) and 4.6 (IQR 2.4-5.5), respectively. The hospitalization rate for influenza A virus (2.2%, 95% CI 2.0-2.5) was significantly higher than that of influenza B virus (1.1%, 95% CI 0.9-1.4). Among the 17 clinical symptoms studied, odds ratios of 15 symptoms were below 1 when comparing influenza A and B positive inpatients, with headache, weakness, and myalgia showing significant differences. This study provides an overview of influenza dynamics and clinical symptoms, highlighting the importance for individuals to receive an annual influenza vaccine.

The Detection of Influenza Virus Before and During the COVID-19 Pandemic in Cameroon

BACKGROUND

Influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are both respiratory viruses with similar clinical manifestations and modes of transmission. This study describes influenza data before and during the coronavirus disease pandemic (COVID-19) in Cameroon and SARS-CoV-2 data during the pandemic period.

METHODS

The study ran from 2017 to 2022, and data were divided into two periods: before (2017-2019) and during (2020-2022) the COVID-19 pandemic. Nasopharyngeal samples collected from persons with respiratory illness were tested for influenza using the Centers for Disease Control and Prevention (CDC) typing and subtyping assays. During the COVID-19 pandemic, the respiratory specimens were simultaneously tested for SARS-CoV-2 using the DaAn gene protocol or the Abbott real-time SARS-CoV-2 assay. The WHO average curve method was used to compare influenza virus seasonality before and during the pandemic.

RESULTS

A total of 6246 samples were tested. Influenza virus detection rates were significantly higher in the pre-pandemic period compared to the pandemic period (30.8% vs. 15.5%; p < 0.001). Meanwhile, the SARS-CoV-2 detection rate was 2.5%. A change in the seasonality of influenza viruses was observed from a bi-annual peak before the pandemic to no clear seasonal pattern during the pandemic. The age groups 2-4 and 5-14 years were significantly associated with higher influenza positivity rates in both pre-pandemic and pandemic periods. For SARS-CoV-2, all age groups above 15 years were the most affected population.

CONCLUSION

The COVID-19 pandemic had a significant impact on the seasonal influenza by changing the seasonality of the virus and reducing its detection rates.

Use of Sentinel Surveillance Platforms for Monitoring SARS-CoV-2 Activity: Evidence From Analysis of Kenya Influenza Sentinel Surveillance Data

BACKGROUND

Little is known about the cocirculation of influenza and SARS-CoV-2 viruses during the COVID-19 pandemic and the use of respiratory disease sentinel surveillance platforms for monitoring SARS-CoV-2 activity in sub-Saharan Africa.

OBJECTIVE

We aimed to describe influenza and SARS-CoV-2 cocirculation in Kenya and how the SARS-CoV-2 data from influenza sentinel surveillance correlated with that of universal national surveillance.

METHODS

From April 2020 to March 2022, we enrolled 7349 patients with severe acute respiratory illness or influenza-like illness at 8 sentinel influenza surveillance sites in Kenya and collected demographic, clinical, underlying medical condition, vaccination, and exposure information, as well as respiratory specimens, from them. Respiratory specimens were tested for influenza and SARS-CoV-2 by real-time reverse transcription polymerase chain reaction. The universal national-level SARS-CoV-2 data were also obtained from the Kenya Ministry of Health. The universal national-level SARS-CoV-2 data were collected from all health facilities nationally, border entry points, and contact tracing in Kenya. Epidemic curves and Pearson r were used to describe the correlation between SARS-CoV-2 positivity in data from the 8 influenza sentinel sites in Kenya and that of the universal national SARS-CoV-2 surveillance data. A logistic regression model was used to assess the association between influenza and SARS-CoV-2 coinfection with severe clinical illness. We defined severe clinical illness as any of oxygen saturation <90%, in-hospital death, admission to intensive care unit or high dependence unit, mechanical ventilation, or a report of any danger sign (ie, inability to drink or eat, severe vomiting, grunting, stridor, or unconsciousness in children younger than 5 years) among patients with severe acute respiratory illness.

RESULTS

Of the 7349 patients from the influenza sentinel surveillance sites, 76.3% (n=5606) were younger than 5 years. We detected any influenza (A or B) in 8.7% (629/7224), SARS-CoV-2 in 10.7% (768/7199), and coinfection in 0.9% (63/7165) of samples tested. Although the number of samples tested for SARS-CoV-2 from the sentinel surveillance was only 0.2% (60 per week vs 36,000 per week) of the number tested in the universal national surveillance, SARS-CoV-2 positivity in the sentinel surveillance data significantly correlated with that of the universal national surveillance (Pearson r=0.58; P<.001). The adjusted odds ratios (aOR) of clinical severe illness among participants with coinfection were similar to those of patients with influenza only (aOR 0.91, 95% CI 0.47-1.79) and SARS-CoV-2 only (aOR 0.92, 95% CI 0.47-1.82).

CONCLUSIONS

Influenza substantially cocirculated with SARS-CoV-2 in Kenya. We found a significant correlation of SARS-CoV-2 positivity in the data from 8 influenza sentinel surveillance sites with that of the universal national SARS-CoV-2 surveillance data. Our findings indicate that the influenza sentinel surveillance system can be used as a sustainable platform for monitoring respiratory pathogens of pandemic potential or public health importance.

United States Influenza 2022-2023 Season Characteristics as Inferred from Wastewater Solids, Influenza Hospitalization, and Syndromic Data

Influenza A virus (IAV) causes significant morbidity and mortality in the United States and has pandemic potential. Identifying IAV epidemic patterns is essential to inform the timing of vaccinations and nonpharmaceutical interventions. In a prospective, longitudinal study design, we measured IAV RNA in wastewater settled solids at 163 wastewater treatment plants across 33 states to characterize the 2022-2023 influenza season at the state, health and human services (HHS) regional, and national scales. Influenza season onset, offset, duration, peak, and intensity using IAV RNA in wastewater were compared with those determined using laboratory-confirmed influenza hospitalization rates and outpatient visits for influenza-like illness (ILI). The onset for HHS regions as determined by IAV RNA in wastewater roughly corresponded with those determined using ILI when the annual geometric mean of IAV RNA concentration was used as a baseline (i.e., the threshold that triggers onset), although offsets between the two differed. IAV RNA in wastewater provided early warning of onset, compared to the ILI estimate, when the baseline was set at twice the limit of IAV RNA detection in wastewater. Peak when determined by IAV RNA in wastewater generally preceded peak determined by IAV hospitalization rate by 2 weeks or less. IAV RNA in wastewater settled solids is an IAV-specific indicator that can be used to augment clinical surveillance for seasonal influenza epidemic timing and intensity.

Etiology of Acute Lower Respiratory Illness Hospitalizations Among Infants in 4 Countries

Background

Recent studies explored which pathogens drive the global burden of pneumonia hospitalizations among young children. However, the etiology of broader acute lower respiratory tract infections (ALRIs) remains unclear.

Methods

Using a multicountry study (Albania, Jordan, Nicaragua, and the Philippines) of hospitalized infants and non-ill community controls between 2015 and 2017, we assessed the prevalence and severity of viral infections and coinfections. We also estimated the proportion of ALRI hospitalizations caused by 21 respiratory pathogens identified via multiplex real-time reverse transcription polymerase chain reaction with bayesian nested partially latent class models.

Results

An overall 3632 hospitalized infants and 1068 non-ill community controls participated in the study and had specimens tested. Among hospitalized infants, 1743 (48.0%) met the ALRI case definition for the etiology analysis. After accounting for the prevalence in non-ill controls, respiratory syncytial virus (RSV) was responsible for the largest proportion of ALRI hospitalizations, although the magnitude varied across sites-ranging from 65.2% (95% credible interval, 46.3%-79.6%) in Albania to 34.9% (95% credible interval, 20.0%-49.0%) in the Philippines. While the fraction of ALRI hospitalizations caused by RSV decreased as age increased, it remained the greatest driver. After RSV, rhinovirus/enterovirus (range, 13.4%-27.1%) and human metapneumovirus (range, 6.3%-12.0%) were the next-highest contributors to ALRI hospitalizations.

Conclusions

We observed substantial numbers of ALRI hospitalizations, with RSV as the largest source, particularly in infants aged <3 months. This underscores the potential for vaccines and long-lasting monoclonal antibodies on the horizon to reduce the burden of ALRI in infants worldwide.