Differences in influenza seasonality by latitude, northern India.
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ABSTRACT:
SUBMITTER: Koul PA
PROVIDER: S-EPMC4193176 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Scant data exist about the epidemiology of influenza B in India. We set out to address the epidemiology of influenza B in a temperate region of northern India from 2010 to 2016. Outpatient and inpatient surveillance was conducted in patients presenting with acute respiratory infection in a northern Indian hospital from September 2010 till April 2016. After recording clinical data, combined nasal/throat swabs were collected and tested for influenza viruses by real time RT-PCR. Influenza A viruses were further subtyped into A/H3N2 and A/H1N1 whereas influenza B were differentiated into B/Yamagata and B/Victoria. Virus isolation, haemaggglutination inhibition testing, sequencing and phylogenetic analysis was carried out on representative samples. Of the 6879 recruited cases, influenza B was detected in 299 (4.3%). The patients presented with respiratory symptoms of varying duration; cough, fever and nasal discharge being the most common. The peaking of the activity of the circulation showed a correlation with the onset of the winter with reduced temperatures and high dry humidity. B/Victoria lineage was detected in 35.4% (n = 106/299) whereas 53.8% (n = 161/299) were B/Yamagata. The circulation in each season was dominated by one lineage which correlated with the vaccine strain, but up to 37% consisted of a different lineage. We conclude that Influenza B exhibits a northern hemispherical seasonality in temperate northern India with co-circulation of the 2 lineages of influenza B. These findings have relevance for vaccine effectiveness and argue for vaccination with a quadrivalent influenza vaccine.
| S-EPMC6261902 | biostudies-literature
Project description:BackgroundPakistan ranks amongst the top 20 highest burden tuberculosis (TB) countries in the world. Approximately 369,548 cases of TB (all forms) were notified in 2018, with an estimated incidence of 265 per 100,000 people per year. In other settings, TB has been shown to demonstrate seasonal variation, with higher incidence in the spring/summer months and lower incidence in the autumn/winter; the amplitude of seasonal variation has also been reported to be higher with increasing distance from the equator.MethodsNotifications of newly-diagnosed pulmonary and extrapulmonary TB cases were obtained for 139 districts in Pakistan from 2011 to 2017. Data were provided by the Pakistan National TB Control Programme, Islamabad, Pakistan. Statistical analyses were performed to determine whether there was seasonal variation in TB notifications in Pakistan; whether the amplitude of seasonal variation in TB notifications varied according to latitude; whether the amplitude of seasonal variation of TB in Pakistan differed between extrapulmonary TB vs. pulmonary TB. To assess the quarterly seasonality of TB, we used the X-13-ARIMA-SEATS seasonal adjustment programme from the United States Census Bureau. The mean difference and corresponding 95% confidence intervals of seasonal amplitudes between different latitudes and clinical phenotype of TB were estimated using linear regression.ResultsTB notifications were highest in quarter 2, and lowest in quarter 4. The mean amplitude of seasonal variation was 25.5% (95% CI 25.0 to 25.9%). The mean seasonal amplitude of TB notifications from latitude 24.5°N- < 26.5°N was 29.5% (95% CI 29.3 to 29.7%) whilst the mean seasonal amplitude of TB notifications from latitude 34.5°N - < 36.5°N was 21.7% (95% CI 19.6 to 23.9%). The mean seasonal amplitude of TB notifications across Pakistan between latitudes 24.5°N to 36.5°N reached statistically significant difference (p < 0.001). The amplitude of seasonal variation was greater for extrapulmonary TB (mean seasonal amplitude: 32.6, 95% CI 21.4 to 21.8%) vs. smear positive pulmonary TB mean seasonal amplitude: 21.6, 95% CI 32.1 to 33.1%), p < 0.001.ConclusionTB notifications in Pakistan exhibit seasonal variation with a peak in quarter 2 (April-June) and trough in quarter 4 (October-December). The amplitude of seasonality decreases with increasing latitude, and is more pronounced for extrapulmonary than for pulmonary TB.
| S-EPMC7905850 | biostudies-literature
Project description:BackgroundInfluenza surveillance is an important tool to identify emerging/reemerging strains, and defining seasonality. We describe the distinct patterns of circulating strains of the virus in different areas in India from 2009 to 2013.MethodsPatients in ten cities presenting with influenza like illness in out-patient departments of dispensaries/hospitals and hospitalized patients with severe acute respiratory infections were enrolled. Nasopharangeal swabs were tested for influenza viruses by real-time RT-PCR, and subtyping; antigenic and genetic analysis were carried out using standard assays.ResultsOf the 44,127 ILI/SARI cases, 6,193 (14.0%) were positive for influenza virus. Peaks of influenza were observed during July-September coinciding with monsoon in cities Delhi and Lucknow (north), Pune (west), Allaphuza (southwest), Nagpur (central), Kolkata (east) and Dibrugarh (northeast), whereas Chennai and Vellore (southeast) revealed peaks in October-November, coinciding with the monsoon months in these cities. In Srinagar (Northern most city at 34°N latitude) influenza circulation peaked in January-March in winter months. The patterns of circulating strains varied over the years: whereas A/H1N1pdm09 and type B co-circulated in 2009 and 2010, H3N2 was the predominant circulating strain in 2011, followed by circulation of A/H1N1pdm09 and influenza B in 2012 and return of A/H3N2 in 2013. Antigenic analysis revealed that most circulating viruses were close to vaccine selected viral strains.ConclusionsOur data shows that India, though physically located in northern hemisphere, has distinct seasonality that might be related to latitude and environmental factors. While cities with temperate seasonality will benefit from vaccination in September-October, cities with peaks in the monsoon season in July-September will benefit from vaccination in April-May. Continued surveillance is critical to understand regional differences in influenza seasonality at regional and sub-regional level, especially in countries with large latitude span.
| S-EPMC4418715 | biostudies-literature
Project description:ImportanceEvery year, respiratory viruses exact a heavy burden on Canadian hospitals during winter months. Generalizable seasonal patterns of respiratory virus transmission may estimate the evolution of SARS-CoV-2 or other emerging pathogens.ObjectiveTo describe the annual and biennial variation in respiratory virus seasonality in a northern climate.Design, setting, and participantsThis cohort study is an epidemiological assessment using population-based surveillance of patients with medically attended respiratory tract infection from 2005 through 2017 in Alberta, Canada. Incident cases of respiratory virus infection and infant respiratory syncytial virus (RSV) hospitalizations in Alberta were extracted from the Data Integration for Alberta Laboratories platform and Alberta Health Services Discharge Abstract Database, respectively. A deterministic susceptible-infected-recovered-susceptible mathematical model with seasonal forcing function was fitted to the data for each virus. The possible future seasonal course of SARS-CoV-2 in northern latitudes was modeled on the basis of these observations. The analysis was conducted between December 15, 2020, and February 10, 2021.ExposuresSeasonal respiratory pathogens.Main outcomes and measuresIncidence (temporal pattern) of respiratory virus infections and RSV hospitalizations.ResultsA total of 37 719 incident infections with RSV, human metapneumovirus, or human coronaviruses 229E, NL63, OC43, or HKU1 among 35 375 patients (18 069 [51.1%] male; median [interquartile range], 1.29 [0.42-12.2] years) were documented. A susceptible-infected-recovered-susceptible model mirrored the epidemiological data, including a striking biennial variation with alternating severe and mild winter peaks. Qualitative description of the model and numerical simulations showed that strong seasonal contact rate and temporary immunity lasting 6 to 12 months were sufficient to explain biennial seasonality in these various respiratory viruses. The seasonality of 10 212 hospitalizations among children younger than 5 years with RSV was also explored. The median (interquartile range) rate of hospitalizations per 1000 live births was 18.6 (17.6-19.9) and 11.0 (10.4-11.7) in alternating even (severe) and odd (less-severe) seasons, respectively (P = .001). The hazard of admission was higher for children born in severe (even) seasons compared with those born in less-severe (odd) seasons (hazard ratio, 1.68; 95% CI, 1.61-1.75; P < .001).Conclusions and relevanceIn this modeling study of respiratory viruses in Alberta, Canada, the seasonality followed a pattern estimated by simple mathematical models, which may be informative for anticipating future waves of pandemic SARS-CoV-2.
| S-EPMC8446819 | biostudies-literature
Project description:Influenza pandemics can emerge unexpectedly and wreak global devastation. However, each of the six pandemics since 1889 emerged in the Northern Hemisphere just after the flu season, suggesting that pandemic timing may be predictable. Using a stochastic model fit to seasonal flu surveillance data from the United States, we find that seasonal flu leaves a transient wake of heterosubtypic immunity that impedes the emergence of novel flu viruses. This refractory period provides a simple explanation for not only the spring-summer timing of historical pandemics, but also early increases in pandemic severity and multiple waves of transmission. Thus, pandemic risk may be seasonal and predictable, with the accuracy of pre-pandemic and real-time risk assessments hinging on reliable seasonal influenza surveillance and precise estimates of the breadth and duration of heterosubtypic immunity.
| S-EPMC5654262 | biostudies-literature
Project description:BackgroundInfluenza is a global transmissible disease. Its dynamics is far better understood in temperate climates than in the tropics. We aim to close this knowledge gap between tropical and temperate regions by showing how the influenza seasonality evolves in Brazil, a tropical country that encompasses a wide range of latitudes and six climatic sub-types.MethodsWe analyzed a state-level, weekly Syndrome of Acute Respiratory Disease (SARI) incidence data ranging from 2010 to 2016. We combined two techniques hierarchically: first the wavelet decomposition technique to detect annual periodicity and then circular statistics to describe seasonal measures of the periodic states.ResultsWe found significant annual periodicity in 44% of the states. For these, we calculated several seasonal measures such as the center of gravity or mean timing of activity. The relationship between the seasonal signatures and latitude was clear and statistically significant. States with seasonal signature are clustered along the coast. Most Amazonian and Central West states exhibit no seasonal behavior. Among the seasonal states, influenza starts in Northeast region, spreading southbound.ConclusionsOur study advances the comprehension of influenza seasonality in tropical areas and could be used to design more effective prevention and control strategies.
| S-EPMC6307116 | biostudies-literature
Project description:Microorganisms are essential constituents of ecosystems. To improve our understanding of how various factors shape microbial diversity and composition in nature it is important to study how microorganisms vary in space and time. Factors shaping microbial communities in ground level air have been surveyed in a limited number of studies, indicating that geographic location, season and local climate influence the microbial communities. However, few have surveyed more than one location, at high latitude or continuously over more than a year. We surveyed the airborne microbial communities over two full consecutive years in Kiruna, in the Arctic boreal zone, and Ljungbyhed, in the Southern nemoral zone of Sweden, by using a unique collection of archived air filters. We mapped both geographic and seasonal differences in bacterial and fungal communities and evaluated environmental factors that may contribute to these differences and found that location, season and weather influence the airborne communities. Location had stronger influence on the bacterial community composition compared to season, while location and season had equal influence on the fungal community composition. However, the airborne bacterial and fungal diversity showed overall the same trend over the seasons, regardless of location, with a peak during the warmer parts of the year, except for the fungal seasonal trend in Ljungbyhed, which fluctuated more within season. Interestingly, the diversity and evenness of the airborne communities were generally lower in Ljungbyhed. In addition, both bacterial and fungal communities varied significantly within and between locations, where orders like Rhizobiales, Rhodospirillales and Agaricales dominated in Kiruna, whereas Bacillales, Clostridiales and Sordariales dominated in Ljungbyhed. These differences are a likely reflection of the landscape surrounding the sampling sites where the landscape in Ljungbyhed is more homogenous and predominantly characterized by artificial and agricultural surroundings. Our results further indicate that local landscape, as well as seasonal variation, shapes microbial communities in air.
| S-EPMC6991134 | biostudies-literature
Project description:Background & objectivesMost studies on the clinical presentation with influenza viruses have been conducted in outpatient or inpatient medical facilities with only a few studies in community settings. Clinical differences between influenza A (H1N1) pdm 09 and influenza B virus infections have importance for community-based public health surveillance. An active community surveillance at the time of emergence of pandemic influenza provided us with an opportunity to compare the clinical features among patients infected with influenza A (H1N1) pdm09 virus and those with influenza B virus co-circulating in an active community-based weekly surveillance in three villages in Faridabad, Haryana, north India.MethodsActive surveillance for febrile acute respiratory infection (FARI) was carried out in a rural community (n=16,182) in the context of an inactivated trivalent influenza vaccine trial (among children <11 yr). Individuals with FARI were assessed clinically by nurses and respiratory samples collected and tested for influenza viruses by real time RT-PCR from November 2009 to August 2010. Clinical symptoms of patients with influenza A (H1N1) pdm 09 and influenza B infection were compared.ResultsOf the 4796 samples tested, 822 (17%) were positive for influenza virus. Of these, 443 (54%) were influenza A (H1N1) pdm09, 373 (45%) were influenza B and six were other subtypes/mixed infections. The mean age was lower for patients with influenza B (16.4 yr) than influenza A (H1N1) pdm09 infection (18.7 yr; P=0.04). Among children aged 5-18 yr, chills/rigours (OR 4.0; CI 2.2, 7.4), sore throat (OR 6.8; CI 2.3, 27.3) and headache (OR2.0; CI 1.3, 3.3) were more common in influenza A (H1N1) pdm09 infection than in influenza B cases. Chills/rigours (OR 2.4; CI 1.4, 4.0) and headache (OR 1.7; CI 1.0, 2.7) were associated with influenza A (H1N1) pdm09 infection in those >18 yr. No significant differences were seen in children <5 yr.ConclusionOur findings show that the differences in the clinical presentation of influenza A(H1N1)pdm09 and influenza B infections are not likely to be of clinical or public health significance.
| S-EPMC3978989 | biostudies-literature
Project description:Climate drivers such as humidity and temperature may play a key role in influenza seasonal transmission dynamics. Such a relationship has been well defined for temperate regions. However, to date no models capable of capturing the diverse seasonal pattern in tropical and subtropical climates exist. In addition, multiple influenza viruses could cocirculate and shape epidemic dynamics. Here we construct seven mechanistic epidemic models to test the effect of two major climate drivers (humidity and temperature) and multi-strain co-circulation on influenza transmission in Hong Kong, an influenza epidemic center located in the subtropics. Based on model fit to long-term influenza surveillance data from 1998 to 2018, we found that a simple model incorporating the effect of both humidity and temperature best recreated the influenza epidemic patterns observed in Hong Kong. The model quantifies a bimodal effect of absolute humidity on influenza transmission where both low and very high humidity levels facilitate transmission quadratically; the model also quantifies the monotonic but nonlinear relationship with temperature. In addition, model results suggest that, at the population level, a shorter immunity period can approximate the co-circulation of influenza virus (sub)types. The basic reproductive number R0 estimated by the best-fit model is also consistent with laboratory influenza survival and transmission studies under various combinations of humidity and temperature levels. Overall, our study has developed a simple mechanistic model capable of quantifying the impact of climate drivers on influenza transmission in (sub)tropical regions. This model can be applied to improve influenza forecasting in the (sub)tropics in the future.
| S-EPMC8216520 | biostudies-literature
Project description:Importance:Coronavirus disease 2019 (COVID-19) infection has resulted in a global crisis. Investigating the potential association of climate and seasonality with the spread of this infection could aid in preventive and surveillance strategies. Objective:To examine the association of climate with the spread of COVID-19 infection. Design, Setting, and Participants:This cohort study examined climate data from 50 cities worldwide with and without substantial community spread of COVID-19. Eight cities with substantial spread of COVID-19 (Wuhan, China; Tokyo, Japan; Daegu, South Korea; Qom, Iran; Milan, Italy; Paris, France; Seattle, US; and Madrid, Spain) were compared with 42 cities that have not been affected or did not have substantial community spread. Data were collected from January to March 10, 2020. Main Outcomes and Measures:Substantial community transmission was defined as at least 10 reported deaths in a country as of March 10, 2020. Climate data (latitude, mean 2-m temperature, mean specific humidity, and mean relative humidity) were obtained from ERA-5 reanalysis. Results:The 8 cities with substantial community spread as of March 10, 2020, were located on a narrow band, roughly on the 30° N to 50° N corridor. They had consistently similar weather patterns, consisting of mean temperatures of between 5 and 11 °C, combined with low specific humidity (3-6 g/kg) and low absolute humidity (4-7 g/m3). There was a lack of substantial community establishment in expected locations based on proximity. For example, while Wuhan, China (30.8° N) had 3136 deaths and 80?757 cases, Moscow, Russia (56.0° N), had 0 deaths and 10 cases and Hanoi, Vietnam (21.2° N), had 0 deaths and 31 cases. Conclusions and Relevance:In this study, the distribution of substantial community outbreaks of COVID-19 along restricted latitude, temperature, and humidity measurements was consistent with the behavior of a seasonal respiratory virus. Using weather modeling, it may be possible to estimate the regions most likely to be at a higher risk of substantial community spread of COVID-19 in the upcoming weeks, allowing for concentration of public health efforts on surveillance and containment.
| S-EPMC7290414 | biostudies-literature