Seasonal Pattern Of Influenza Research Articles

Epidemic trends and prevention and control of seasonal influenza in China after the COVID-19 pandemic

During the COVID-19 pandemic, a series of non-pharmaceutical interventions, which were implemented to curb the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), significantly modified the seasonal pattern of influenza. The intensity of influenza activity markedly decreased and B/Yamagata lineage was no longer detected. As the national influenza sentinel surveillance data shown, clear seasonal patterns were observed for influenza between 2012-2019, annually with an average of 14.57% of specimens tested positive for influenza virus. However, the seasonal pattern of influenza was disrupted after the outbreak of COVID-19. In the 2020-2021 season, influenza demonstrated an extremely low activity (yearly positivity rate<1.0%), followed by a resurgence of winter peak in the 2021-2022 season. Following the downgrade of management of COVID-19 to Class B in China in December 26, 2022, social activities gradually resumed, leading to the rebound of influenza activity with an out-of-season ciculation. After COVID-19 pademic, other respiratory infectious diseases caused by SARS-CoV-2, respiratory syncytial virus, and mycoplasma pneumonia were alternatively or concurrently circulated with influenza. The prevention and control of influenza and other respiratory infectious diseases emphasizes a multi-disease prevention strategy, including long-term and continuous monitoring the epidemic trends in influenza virus and SARS-CoV-2, promoting influenza and COVID-19 vaccination among key populations, and strengthening the knowledge and public awareness of prevention and control for respiratory infectious diseases, etc.

Incidence of COVID-19 among Vaccinated with Sputnik V and CoviVac Vaccines (Results of the Telephone Survey for the Epidemic Season 2021–2022 in St. Petersburg)

Relevance. The emergence of a new SARS-COV-2 coronavirus in early 2020 radically changed the seasonal pattern of influenza and other acute respiratory infections worldwide. Along with a decrease in the frequency of RSV infection, the number of diagnosed cases of influenza virus infection decreased by 99% during the COVID-19 pandemic. Vaccines are known to be the best tool at our disposal for preventing infectious diseases and reducing the risk of serious complications and deaths. The Russian Federation has great experience in developing vaccines against viral and bacterial infections and is constantly improving the technology of their production putting new vaccine preparations into circulation. Domestic vaccines against a new coronavirus infection caused by SARS-CoV-2 virus were developed in the shortest possible time. This work evaluated the efficacy of Gam-Covid-Vac (Sputnik V) and CoviVac vaccines during periods of circulation of different variants of SARS-CoV-2 «Delta» and «Omicron» in St. Petersburg.Aims. To evaluate the prophylactic efficacy of domestic vaccines Gam-Covid-Vac (Sputnik V) and CoviVac in the epidemic season 2021–2022 in the periods of SARS-CoV-2 «Delta» and «Omicron» variants circulation in Saint-Petersburg.Materials and Methods. Vaccination and follow-up of vaccinated subjects was initiated in February 2021, with the arrival of the Gam-Covid-Vac (Sputnik V) and CoviVac vaccines at the specialized clinic of Smorodintsev Research Institute of Influenza. Follow-up of vaccinated subjects for one year after vaccination included 346 men and women aged 19-85 years, who were interviewed in two telephone surveys.Results. Telephone interviews among individuals vaccinated with Gam-Covid-Vaс (Sputnik V) and CoviVac vaccines revealed that during the circulation of «Delta» variant, 2nd half of 2021, COVID-19 disease occurred in 16.3% of people vaccinated with the CoviVac vaccine and in 15.8% of those vaccinated with Sputnik V vaccine – differences between groups were not statistically significant (p &gt; 0.05). COVID-19 disease in both vaccine groups was predominantly mild with 61.95% of observed falling ill in the CoviVac vaccine group and 84.4% (slightly more, 1.4-fold) in Sputnik V vaccine group. At the same time, moderate and severe diseases were slightly more in absolute value among those vaccinated with "CoviVac" vaccine. Cough, lung damage from 30% to 80%, loss of sense of smell and taste dominated among the symptoms in both groups of patients. During the second observation period (January-April 2022), when «Omicron» variant were actively circulating, the number of cases among CoviVac and Sputnik V vaccines was 37.5% and 43.8%, respectively; the differences between the vaccine groups were not statistically significant (p &gt; 0.05). During this period, diseases in CoviVac and Sputnik V vaccine groups were predominantly mild in 84.4% and 90.5%, respectively, with statistically insignificant differences. There were also no significant differences in cases of moderate severity. Among those observed in « CoviVac» group during this period, a greater number of diseases, in absolute value, proceeding in a severe form and requiring hospitalization was noted. Clinically, the diseases caused by «Omicron» variant manifested in symptoms characteristic of flu and common cold: headache and muscle pain, fever, chills, chest pain, nasal congestion, severe fatigue, fatigue, weakness.Conclusions. During periods of active « Delta» variant circulation in the fall of 2021patients vaccinated with SARS-COV-2 coronavirus vaccines were 2.3 to 2.8 times less ill than during circulation periods of «Omicron» variants ВА.1 и ВА.2 in January-April 2022: 16.3% and 15.8%, 37.5% and 43.8%, respectively. Mild COVID-19 disease predominated among patients vaccinated with both vaccines during periods of circulation of «Delta» and «Omicron» variants. Differences in the manifestation of clinical symptoms of the disease in the periods of circulation of different strains were noted. It was shown that the vaccines against SARS-CoV-2 infection Gam-Covid-Vac (Sputnik V) and CoviVac do not protect 100% against the disease, but protect against a severe course of the disease and lethal outcomes.

COVID-19 Pandemic Effects on Seasonal Influenza Patterns in West Virginia

Introduction The COVID-19 pandemic began in West Virginia (WV) in March 2020 at the end of the seasonal increase in influenza virus infections. Diagnostic and surveillance testing for influenza continued throughout the pandemic because these viruses cause similar diseases and the effect of SARS-CoV-2 on seasonal influenza patterns were unpredictable. Methods Positivity rates for SARS-CoV-2 and influenza viruses were studied using test results obtained from samples collected across an academic health system from July 2018 through June 2022. Trends in COVID-19 variants were assessed using data obtained from national and local databases. Data were analyzed to detect differences in and correlations between SARS-CoV-2 and influenza positivity rates. Results Test positivity rates were higher for the 602,109 SARS-CoV-2 tests than the 186,563 influenza tests performed during the study period (13.7% vs. 3.5%, p&lt;0.0001). SARS-CoV-2 test positivity rose and fell with the emergence of SARS-CoV-2 variants of differing infectivity, being highest when the omicron variant predominated. Significant negative correlations between the number of SARS-CoV-2 and influenza positive tests were seen throughout stages of the pandemic. The normally expected influenza season did not occur during winter 2020 through spring 2021, and there were essentially no influenza cases during the delta surge. A more typical pattern of seasonal influenza was observed in late 2021 to early 2022 during the omicron surge. Conclusion There was an inverse correlation between SARS-CoV-2 and influenza test positivity rates observed throughout several COVID-19 surges in WV. The reasons for these correlations are unclear.

Regional characteristics of influenza seasonality patterns in mainland China, 2005-2017: a statistical modeling study

ObjectivesTo quantify the seasonal and antigenic characteristics of influenza to help understand influenza activity and inform vaccine recommendations. MethodsWe employed a generalized linear model with harmonic terms to quantify the seasonal pattern of influenza in China from 2005-2017, including amplitude (circulatory intensity), semiannual periodicity (given two peaks a year), annual peak time, and epidemic duration. The antigenic differences were distinguished as antigenic similarity between 2009 and 2020. We categorized regions above 33° N, between 27° N and 33° N, and below 27° N as the north, central, and south regions, respectively. ResultsWe estimated that the amplitude in the north region (median: 0.019, 95% CI: 0.018-0.021) was significantly higher than that in the central region (median: 0.011, 95% CI: 0.01-0.012, P <0.001) and south region (median: 0.008, 95% CI: 0.007-0.008, P <0.001) for influenza A virus subtype H3N2 (A/H3N2). The A/H3N2 in the central region had a semiannual periodicity (median: 0.548, 95% CI: 0.517-0.577), while no semiannual pattern was found in other regions or subtypes/lineages. The antigenic similarity was low (below 50% in the 2009-2010, 2014-2015, 2016-2018, and 2019-2020 seasons) for A/H3N2. ConclusionOur study depicted the seasonal pattern differences and antigenic differences of influenza in China, which provides information for vaccination strategies.

Virological surveillance of influenza virus in acute respiratory infection

Introduction: Influenza is viral fever with the main symptom of respiratory tract like cough, fever, breathlessness, nasal discharge, sore throat. The influenza affects a large segment of the world population resulting in significant mortality, morbidity and economic loss. Objective: To monitor the trend of influenza A virus. To know the prevalence of influenza A, H1N1 and seasonal H3 subtypes of influenza virus. To study the seasonal pattern of influenza A virus. Materials and Methods: This prospective study was carried out in the department of Microbiology, B.J. Medical College, Ahmadabad from January 2014 to December 2014. Surveillance samples were taken as per ILI (Influenza like illness) case definition for out Patient department and SARI (sever acute respiratory syndrome) for indoor patients. Total 614 samples are taken and tested with PCR method. Result: Out of 614 samples total 201(32.73%) were positive for influenza. Out of 201 positive samples, 13 (2.11%) were positive for swine H1N1 and 11 (1.79%) for seasonal H3, 177 (28.82%) were positive for influenza A. Conclusion: Prevalence of influenza 201(32.73%). out of this 13 (2.11%) were positive for swine H1N1 and 11 (1.79%) for seasonal H3, 177 (28.82%) were positive for influenza A. swine H1N1 was common in winter and seasonal H3 was common in late monsoon. swine H1N1 and seasonal H3 both are more common in male than female. swine H1N1 is more in >12 age and seasonal H3 is more common in Keywords: Influenza A, Swine H1N1, Seasonal H3, Fever, cough, Breathlessness.

Climate factors influence seasonal influenza activity in Bangkok, Thailand.

Yearly increase in influenza activity is associated with cold and dry winter in the temperate regions, while influenza patterns in tropical countries vary significantly by regional climates and geographic locations. To examine the association between influenza activity in Thailand and local climate factors including temperature, relative humidity, and rainfall, we analyzed the influenza surveillance data from January 2010 to December 2018 obtained from a large private hospital in Bangkok. We found that approximately one in five influenza-like illness samples (21.6% or 6,678/30,852) tested positive for influenza virus. Influenza virus typing showed that 34.2% were influenza A(H1N1)pdm09, 46.0% were influenza A(H3N2), and 19.8% were influenza B virus. There were two seasonal waves of increased influenza activity. Peak influenza A(H1N1)pdm09 activity occurred in February and again in August, while influenza A(H3N2) and influenza B viruses were primarily detected in August and September. Time series analysis suggests that increased relative humidity was significantly associated with increased influenza activity in Bangkok. Months with peak influenza activity generally followed the most humid months of the year. We performed the seasonal autoregressive integrated moving average (SARIMA) multivariate analysis of all influenza activity on the 2011 to 2017 data to predict the influenza activity for 2018. The resulting model closely resembled the actual observed overall influenza detected that year. Consequently, the ability to predict seasonal pattern of influenza in a large tropical city such as Bangkok may enable better public health planning and underscores the importance of annual influenza vaccination prior to the rainy season.

Seasonal pattern of influenza and the association with meteorological factors based on wavelet analysis in Jinan City, Eastern China, 2013-2016.

BackgroundInfluenza is a disease under surveillance worldwide with different seasonal patterns in temperate and tropical regions. Previous studies have conducted modeling of influenza seasonality using climate variables. This study aimed to identify potential meteorological factors that are associated with influenza seasonality in Jinan, China.MethodsData from three influenza sentinel hospitals and respective climate factors (average temperature, relatively humidity (RH), absolute humidity (AH), sunshine duration, accumulated rainfall and speed of wind), from 2013 to 2016, were collected. Statistical and wavelet analyses were used to explore the epidemiological characteristics of influenza virus and its potential association with climate factors.ResultsThe dynamic of influenza was characterized by annual cycle, with remarkable winter epidemic peaks from December to February. Spearman’s correlation and wavelet coherence analysis illuminated that temperature, AH and atmospheric pressure were main influencing factors. Multiple wavelet coherence analysis showed that temperature and atmospheric pressure might be the main influencing factors of influenza virus A(H3N2) and influenza virus B, whereas temperature and AH might best shape the seasonality of influenza virus A(H1N1)pdm09. During the epidemic season, the prevalence of influenza virus lagged behind the change of temperature by 1–8 weeks and atmospheric pressure by 0.5–3 weeks for different influenza viruses.ConclusionClimate factors were significantly associated with influenza seasonality in Jinan during the influenza epidemic season and the optional time for influenza vaccination is before November. These finding should be considered in influenza planning of control and prevention.

Forecasting type-specific seasonal influenza after 26 weeks in the United States using influenza activities in other countries.

To identify countries that have seasonal patterns similar to the time series of influenza surveillance data in the United States and other countries, and to forecast the 2018–2019 seasonal influenza outbreak in the U.S., we collected the surveillance data of 164 countries using the FluNet database, search queries from Google Trends, and temperature from 2010 to 2018. Data for influenza-like illness (ILI) in the U.S. were collected from the Fluview database. We identified the time lag between two time-series which were weekly surveillances for ILI, total influenza (Total INF), influenza A (INF A), and influenza B (INF B) viruses between two countries using cross-correlation analysis. In order to forecast ILI, Total INF, INF A, and INF B of next season (after 26 weeks) in the U.S., we developed prediction models using linear regression, auto regressive integrated moving average, and an artificial neural network (ANN). As a result of cross-correlation analysis between the countries located in northern and southern hemisphere, the seasonal influenza patterns in Australia and Chile showed a high correlation with those of the U.S. 22 weeks and 28 weeks earlier, respectively. The R2 score of ANN models for ILI for validation set in 2015–2019 was 0.758 despite how hard it is to forecast 26 weeks ahead. Our prediction models forecast that the ILI for the U.S. in 2018–2019 may be later and less severe than those in 2017–2018, judging from the influenza activity for Australia and Chile in 2018. It allows to estimate peak timing, peak intensity, and type-specific influenza activities for next season at 40th week. The correlation between seasonal influenza patterns in the U.S., Australia, and Chile could be used to forecast the next seasonal influenza pattern, which can help to determine influenza vaccine strategy approximately six months ahead in the U.S.

Influenza hospitalization epidemiology from a severe acute respiratory infection surveillance system in Jordan, January 2008-February 2014.

Acute respiratory infections (ARIs) are a major cause of morbidity and mortality worldwide. Influenza typically contributes substantially to the burden of ARI, but only limited data are available on influenza activity and seasonality in Jordan. Syndromic case definitions were used to identify individuals with severe acute respiratory infections (SARI) admitted to four sentinel hospitals in Jordan. Demographic and clinical data were collected. Nasopharyngeal and oropharyngeal swabs were tested for influenza using real-time reverse transcription polymerase chain reaction and typed as influenza A or B, with influenza A further subtyped. From January 2008-February 2014, 2891 SARI cases were tested for influenza, and 257 (9%) were positive. While 73% of all SARI cases were under 5years of age, only 57% of influenza-positive cases were under 5years of age. Eight (3%) influenza-positive cases died. An annual seasonal pattern of influenza activity was observed. The proportion of influenza-positive cases peaked during November-January (14-42%) in the non-pandemic years. Influenza is associated with substantial morbidity and mortality in Jordan. The seasonal pattern of influenza aligns with known Northern Hemisphere seasonality. Further characterization of the clinical and financial burden of influenza in Jordan will be critical in supporting decisions regarding disease control activities.

Environmental Predictors of Seasonal Influenza Epidemics across Temperate and Tropical Climates

Human influenza infections exhibit a strong seasonal cycle in temperate regions. Recent laboratory and epidemiological evidence suggests that low specific humidity conditions facilitate the airborne survival and transmission of the influenza virus in temperate regions, resulting in annual winter epidemics. However, this relationship is unlikely to account for the epidemiology of influenza in tropical and subtropical regions where epidemics often occur during the rainy season or transmit year-round without a well-defined season. We assessed the role of specific humidity and other local climatic variables on influenza virus seasonality by modeling epidemiological and climatic information from 78 study sites sampled globally. We substantiated that there are two types of environmental conditions associated with seasonal influenza epidemics: “cold-dry” and “humid-rainy”. For sites where monthly average specific humidity or temperature decreases below thresholds of approximately 11–12 g/kg and 18–21°C during the year, influenza activity peaks during the cold-dry season (i.e., winter) when specific humidity and temperature are at minimal levels. For sites where specific humidity and temperature do not decrease below these thresholds, seasonal influenza activity is more likely to peak in months when average precipitation totals are maximal and greater than 150 mm per month. These findings provide a simple climate-based model rooted in empirical data that accounts for the diversity of seasonal influenza patterns observed across temperate, subtropical and tropical climates.

SEASONAL INFLUENZA: LINKS WITH METEOROLOGY AND SOCIAL NETWORK

Background and Aims: Prevention of influenza is a long-standing public health objective. Recent observational studies demonstrate that complex seasonal influenza patterns are sensitive to changes in social networks. The experimental studies suggest potential links with meteorology, when influenza virus infectivity depends on the effect of ambient temperature and humidity. We examined the relationship between influenza, meteorological conditions, and social contacts’ intensity using influenza virus surveillance in Milwaukee, Wisconsin, USA. Methods: Laboratory-confirmed influenza cases were provided by the Milwaukee Health Department Laboratory during 5/22/2004-02/22/2011. Records contain weekly positive test results for the influenza A/H1N1, A/H3N2, 2009-A/H1N1 and Influenza-B strains detected in human subjects from six CDC-WHO-specified age groups (&lt;1,1-4,5-24,25-44,45-64, and ≥65 yrs). Daily meteorological parameters (maximum/mean/minimum for temperature and relative humidity) were aggregated into weekly time series. Public school calendars were used to create the time series to reflect the probability of person-to-person contacts. Poisson harmonic regression models were used to assess seasonal characteristics: peak timing and absolute intensity for each strain and age group. Relative risks of influenza associated with temperature and humidity and their interactions with viral genome were estimated using non-linear regression models. The preliminary results are limited by the first 128 weeks of the study period (prior to the massive testing for 2009-A/H1N1 influenza). Results: Three major influenza strains (A/H1N1, A/H3N2, Influenza-B) have distinct peaks at weeks: 8.6 [95%CI:8.0-9.1], 9.6 [95%CI:8.3-10.3], and 12.9 [95%CI:11.6-15.3] respectively. Influenza-A peaked at colder and less humid weather conditions compared to Influenza-B. The intensity of Influenza-B exhibited the 6-fold increase (p&lt;0.001) over the study period. Intensity of community social network has minimal, impact on the influenza seasonality. Conclusions: The seasonal influenza incidences are likely to be linked with meteorological conditions and school-related activities, however their effects on the circulating viruses and severity at a community level is inconclusive.

Effectiveness of the Brazilian influenza vaccination policy, a systematic review

Since 1999, Brazil has undertaken annual influenza vaccine campaigns, free of charge, targeting the elderly population, health professionals, and immune-deficient patients. We conducted a systematic review of literature in order to evaluate the effectiveness of the initiative. We used the keywords influenza, vaccine, Brazil and effectiveness to search the main databases. Thirty-one studies matched our inclusion and exclusion criteria. Influenza vaccine coverage among the elderly is high, though not as high as suggested by the official figures. Estimates on effectiveness are scarce. The majority come from ecological studies that show a modest reduction in mortality and hospital admissions due to influenza-related causes. Such reduction is not evident in the North and Northeastern states of Brazil, a finding that is probably related to the different seasonal pattern of influenza in equatorial and tropical regions. Brazilian epidemiologists still owe society better-designed studies addressing the effectiveness of influenza vaccine campaigns.

Dual Seasonal Patterns for Influenza, China

Dual Seasonal Patterns for Influenza, China

Clinical features of Malaysian children hospitalized with community-acquired seasonal influenza

The clinical impact of seasonal influenza is understudied in tropical countries. The aim of this study was to describe the clinical features and seasonal pattern of influenza in children hospitalized in Malaysia, and to identify predictors of severe disease. Children hospitalized with community-acquired, laboratory-confirmed influenza at a teaching hospital in Kuala Lumpur, Malaysia during 2002-2007 were identified retrospectively. Clinical data were collected, and predictors of severe disease were identified by multivariate logistic regression. All influenza cases from 1982 to 2007 were also analyzed for seasonal patterns. A total of 132 children were included in the study, 48 (36.4%) of whom had underlying medical conditions. The mean age was 2.5 years and 116 (87.9%) were <5 years old. The most common presenting features were fever or history of fever, cough, rhinitis, vomiting, and pharyngitis. Severe influenza was seen in 16 patients (12.1%; nine previously healthy), including 12 (9.1%; eight previously healthy) requiring intensive care. There were three (2.3%) deaths. Severe disease was associated with age <12 months, female sex, and absence of rhinitis on admission. Influenza was seen year-round, with peaks in November-January and May-July. Seasonal influenza has a considerable impact on children hospitalized in Malaysia, in both the healthy and those with underlying medical conditions.

Epidemiologic Study of Influenza Infection in Okinawa, Japan, from 2001 to 2007: Changing Patterns of Seasonality and Prevalence of Amantadine-Resistant Influenza A Virus

To clarify seasonal influenza patterns and the prevalence of amantadine-resistant influenza A viruses in Okinawa, located at the southern extremity of Japan in a subtropical climate, we conducted a laboratory-based study of influenza virus infections from 2001 to 2007. The annual outbreaks tended to show two peaks in Okinawa, in summer and winter, although the main islands of Japan, located in a temperate climate area, showed only winter influenza activity. Epidemic types and subtypes in Okinawa mostly matched those on the main islands of Japan in winter and those in Taiwan in summer. Rates of amantadine resistance dramatically increased, from 7.3% in the November 2002-to-March 2003 season to 90.0% in summer 2005, and a similarly high rate of resistance continued for the rest of the study period. Phylogenetic analysis of the hemagglutinin gene of A/H3N2 isolates collected from 2002 to 2007 revealed a monophyletic lineage that was divided into four period groups. Each group included amantadine-sensitive and -resistant viruses within independent clusters. In the November 2005-to-March 2006 season, all of the amantadine-resistant viruses were clustered in clade N, with dual (position 193 and 225) amino acid mutations in their HA1 subunits. In 2005, clade N amantadine-resistant viruses existed in Okinawa several months before the circulation of this clade on the main islands of Japan. In conclusion, surveillance in Okinawa to monitor influenza virus circulation is important for elucidating the dynamics of virus transmission in a border area between temperate and subtropical areas, as Okinawa is one of the best sentinel points in Japan.