An Epidemiological Analysis of Summer Influenza Epidemics in Okinawa

Clinical profile of influenza virus-related hospitalizations in children aged 1-59 months: A five-year retrospective study from south India

BACKGROUND

Influenza is a seasonal acute respiratory tract infection with different strains in circulation at different time periods with varying spectrum of clinical presentation.

OBJECTIVES

To study the clinical presentation, morbidity, and mortality patterns associated with different strains of influenza virus, to identify the predominant strains related to hospitalization, and to identify the seasonal trend in hospitalization and risk factors for mortality in children aged 1-59 months hospitalized with influenza.

MATERIALS AND METHODS

The records of children hospitalized with influenza were analyzed retrospectively (June 2013 to June 2018). Anonymized data from the Medical Records Department of our Institute, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), were used for the study and waiver of consent was obtained from the Institute Ethics Committee for Human Studies (JIPMER), which also approved the study. The data from the medical records were extracted as per the proforma and entered into Microsoft excel and summary statistics was obtained. Categorical data were expressed as proportion and analyzed using chi square test. Association was tested using odds ratio.

RESULTS

Of the 693 children tested for influenza during the study period, 91 were found to be positive for influenza infection and out of which 68 (74.7%) were hospitalized. Infection was seen during both the summer and winter months. The predominant strain being A (H1N1) pdm09 (63.2%). The other strains found were A (H3N2) and Influenza B. The predominant diagnosis was pneumonia. The need for mechanical ventilation was more common with influenza B infection (p = 0.035). No significant risk factors for mortality could be found in our study.

CONCLUSION

An absence of seasonal predilection for the disease was noted with influenza A (H1N1) pdm09 being the predominant strain with influenza B seen as an emerging strain and an important contributor towards morbidity.

What's Next for Flu? Out-of-Season Circulation of Influenza Viruses in Southern Italy, August 2022

The COVID-19 pandemic has modified the seasonal pattern of respiratory infections. The objective of the present study is to characterize the out-of-season circulation of influenza viruses and an influenza outbreak that occurred in southern Italy in August 2022. Nasopharyngeal swabs collected from patients with influenza-like illnesses (ILI) were tested for the presence of influenza and other respiratory viruses. Epidemiological investigations on 85 patients involved in an influenza outbreak were performed. Sequencing and phylogenetic analysis of hemagglutinin genes was undertaken on samples positive for influenza A. In August 2022, in the Apulia region (Italy), influenza A infection was diagnosed in 19 patients, 18 infected with A/H3N2 and one with A/H1N1pdm09 virus. Seven influenza-positive patients were hospitalized with ILI. A further 17 symptomatic subjects, associated with an influenza outbreak, were also tested; 11 were positive for influenza A/H3N2 virus. Phylogenetic analysis of 12 of the A/H3N2 sequences showed that they all belonged to subclade 3C.2a1b.2a.2. The A/H1N1pdm09 strain belonged to subclade 6B.1A.5a.2. The out-of-season circulation of the influenza virus during the summer months could be linked to changing dynamics in the post-COVID-19 era, as well as to the impact of climate change. Year-round surveillance of respiratory viruses is needed to monitor this phenomenon and to provide effective prevention strategies.

Effectiveness estimates for enhanced trivalent influenza vaccines in an aged care summer outbreak

An influenza outbreak occurred during summer (February 2019) in an aged-care facility in Sydney, Australia. Residents had not received the annual 2019 influenza vaccine while 76.7% had received 2018 influenza vaccines about 9 months prior. Overall, 2018 influenza vaccine effectiveness during this outbreak was high (93.6%). The effectiveness of the high-dose trivalent vaccine (HD-TIV) and adjuvanted trivalent (a-TIV) vaccine were 89.8% (95% confidence interval: 18.8%-98.7%) and 72.5% (95% confidence interval: -106.7%-96.3%) respectively. The differences in effectiveness between HD-TIV, a-TIV and SD-QIV, during the summer outbreak were not significant.

Local spread of influenza A (H1N1) viruses without a mutation for the maximum duration of an epidemic season in Japan

Close observation of the local transmission of influenza A(H1N1) viruses enabled an estimate of the length of time the virus was transmitted without a mutation. Of 4,448 isolates from 11 consecutive years, 237 isolates could be categorized into 57 strain groups with identical hemagglutinin genes, which were monitored for the entire duration of an epidemic season. In addition, 35 isolates with identical sequences were identified at the study site and in other countries within 147 days. Consequently, it can be postulated that once an influenza virus enters a temperate region, the strain rarely mutates before the end of the season.

Evidence for an increase in the intensity of inter-seasonal influenza, Queensland, Australia, 2009-2019

BACKGROUND

Inter-seasonal influenza cases have been increasing in Australia. Studies of influenza seasonality typically focus on seasonal transmission in temperate regions, leaving our understanding of inter-seasonal epidemiology limited. We aimed to improve understanding of influenza epidemiology during inter-seasonal periods across climate zones, and explored influenza intensity and strain dominance patterns over time.

METHODS

Queensland state-wide laboratory-confirmed influenza notifications and public laboratory influenza test data from 2009-2019 were described by demographics, time period, region and strain type. We compared influenza intensity over time using the WHO Average Curve method to provide thresholds for seasonal and inter-seasonal periods.

RESULTS

Among the 243 830 influenza notifications and 490 772 laboratory tests reported in Queensland between 2009 and 2019, 15% of notifications and 40% of tests occurred during inter-seasonal periods, with 6.3% of inter-seasonal tests positive. Inter-seasonal notifications and tests substantially increased over time and increases in weekly proportions positive and intensity classifications suggested gradual increases in virus activity. Tropical inter-seasonal activity was higher with periods of marked increase. Influenza A was dominant, although influenza B represented up to 72% and 42% of notifications during some seasonal and inter-seasonal periods, respectively.

CONCLUSIONS

Using notification and testing data, we have demonstrated a gradual increase in inter-seasonal influenza over time. Our findings suggest this increase results from an interplay between testing, activity and intensity, and strain circulation. Seasonal intensity and strain circulation appeared to modify subsequent period intensity. Routine year-round surveillance data would provide a better understanding of influenza epidemiology during this infrequently studied inter-seasonal time period.

Disappearance of summer influenza in the Okinawa prefecture during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic

Since the Okinawan islands are located in the southernmost part of Japan, where the climate is subtropical, several episodes of influenza epidemics occur during the summer season. More recently, we have demonstrated that summer influenza epidemics occur every year. After the outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began in January 2020, measures to avoid disease transmission have been widely promoted in Japan, such as the use of masks, handwashing, remote work, and cancellation of large events. These measures might also have reduced the spread of other infectious diseases, such as the seasonal influenza. Based on this background, we evaluated weekly influenza activity in the 2019/2020 season. After the SARS-CoV-2 pandemic, the summer influenza in the Okinawa prefecture disappeared in 2020. The reasons for the disappearance of summer influenza in Okinawa are discussed herein.

Intense interseasonal influenza outbreaks, Australia, 2018/19

BackgroundInterseasonal influenza outbreaks are not unusual in countries with temperate climates and well-defined influenza seasons. Usually, these are small and diminish before the main influenza season begins. However, the 2018/19 summer-autumn interseasonal influenza period in Australia saw unprecedented large and widespread influenza outbreaks.AimOur objective was to determine the extent of the intense 2018/19 interseasonal influenza outbreaks in Australia epidemiologically and examine the genetic, antigenic and structural properties of the viruses responsible for these outbreaks.MethodsThis observational study combined the epidemiological and virological surveillance data obtained from the Australian Government Department of Health, the New South Wales Ministry of Health, sentinel outpatient surveillance, public health laboratories and data generated by the World Health Organization Collaborating Centre for Reference and Research on Influenza in Melbourne and the Singapore Agency for Science, Technology and Research.ResultsThere was a record number of laboratory-confirmed influenza cases during the interseasonal period November 2018 to May 2019 (n= 85,286; 5 times the previous 3-year average) and also more institutional outbreaks, hospitalisations and deaths, than what is normally seen.ConclusionsThe unusually large interseasonal influenza outbreaks in 2018/19 followed a mild 2018 influenza season and resulted in a very early start to the 2019 influenza season across Australia. The reasons for this unusual event have yet to be fully elucidated but are likely to be a complex mix of climatic, virological and host immunity-related factors. These outbreaks reinforce the need for year-round surveillance of influenza, even in temperate climates with strong seasonality patterns.

Inter-seasonality of influenza in Australia

BACKGROUND

It appears inter-seasonal influenza notifications have been increasing in summer months in Australia. This study aims to determine changes in inter-seasonal influenza activity in Australia over time.

METHODS

Routine influenza surveillance data and hospitalisations data were analysed to study the epidemiology of inter-seasonal influenza and to examine the impact of inter-seasonal influenza on morbidity in Australia at a national level. To adjust for changes in testing over time, we calculated a ratio of summer-to-winter notifications for each year in the study. A P-value of <0.05 was used for statistical significance.

RESULTS

Nationally, 18 933 notifications were reported during summer months from December to February 2005-2016. There have been increasing summer notifications over time, which corresponded to similarly increased notifications in winter. A significant upward trend was observed for rate of notification during summer period over these years, P < 0.01. However, the ratio of summer-to-winter notifications demonstrated that while notifications have increased, the ratio has not increased markedly over the years and did not show a significant trend. No seasonal trend in rates of hospitalisation for influenza and pneumonia, respiratory and circulatory diagnosis was observed over the studied years.

CONCLUSION

This study provides a clearer understanding of the epidemiology and burden of inter-seasonal influenza and trends over time in Australia. The ratio of summer-to-winter notifications remains relatively constant and is supported by reasonably constant hospitalisation rates over the years.

Inferring the global phylodynamics of influenza A/H3N2 viruses in Taiwan

BACKGROUND/PURPOSE

Influenza A/H3N2 viruses are characterized by highly mutated RNA genomes. In this study, we focused on tracing the phylodynamics of Taiwanese strains over the past four decades.

METHODS

All Taiwanese H3N2 HA1 sequences and references were downloaded from public database. A Bayesian skyline plot (BSP) and phylogenetic tree were used to analyze the evolutionary history, and Bayesian phylogeographic analysis was applied to predict the spatiotemporal migrations of influenza outbreaks.

RESULTS

Genetic diversity was found to have peaked near the summer of 2009 in BSP, in addition to the two earlier reported ones in summer of 2005 and 2007. We predicted their spatiotemporal migrations and found the summer epidemic of 2005 from Korea, and 2007 and 2009 from the Western United States. BSP also predicted an elevated genetic diversity in 2015-2017. Quasispecies were found over approximately 20% of the strains included in this time span. In addition, a first-time seen N31S mutation was noted in Taiwan in 2016-2017.

CONCLUSION

We comprehensively investigated the evolutionary history of Taiwanese strains in 1979-2017. An epidemic caution could thus be raised if genetic diversity was found to have peaked. An example showed a newly-discovered cluster in 2016-2017 strains featuring a mutation N31S together with HA-160 quasispecies. Phylogeographic analysis, moreover, provided useful insights in tracing the possible source and migrations of these epidemics around the world. We demonstrated that Asian destinations including Taiwan were the immediate followers, while U.S. continent was predicted the origin of two summer epidemics in 2007 and 2009.

Centennial review of influenza in Taiwan

The history of influenza in Taiwan can be traced up to the 1918 H1N1 Spanish flu pandemic, followed by several others including the 1957 H2N2, 1968 H3N2, and the 2009 new H1N1. A couple of avian influenza viruses of H5N1 and H7N9 also posed threats to the general public in Taiwan in the two recent decades. Nevertheless, two seasonal influenza A viruses and two lineages of influenza B viruses continue causing annual endemics one after the other, or appearing simultaneously. Their interplay provided interesting evolutionary trajectories for these viruses, allowing us to computationally model their global migrations together with the data collected elsewhere from different geographical locations. An island-wide laboratory-based surveillance network was also established since 2000 for systematically collecting and managing the disease and molecular epidemiology. Experiences learned from this network helped in encountering and managing newly emerging infectious diseases, including the 2003 SARS and 2009 H1N1 outbreaks.