Global influenza seasonality: reconciling patterns across temperate and tropical regions

Association between meteorological factors and the epidemics of influenza (sub)types in a subtropical basin of Southwest China

BACKGROUND

The effects of climatic conditions on the prevalence of individual influenza (sub)types are not well understood in the subtropics. This study aims to evaluate the associations between meteorological factors and seasonal epidemics of A(H3N2), A(H1N1)pdm09, and type B influenza viruses, as well as to estimate the interactions between climatic variables in a subtropical basin region.

METHODS

The seasonality of influenza (sub)types during 2010-2019 were characterized in Chengdu Plain Economic Zone, a densely populated and highly humid plain area in Sichuan Basin in subtropical Southwest China. Generalized additive models were adopted to assess the independent exposure-response relationship between meteorological variables and influenza prevalence. The interactions of meteorological variables were further estimated using bivariate response surface models and strata models.

RESULTS

Our analyses indicated that the temperature, relative humidity, and absolute humidity have exhibited a major influence on influenza infection in Chengdu Plain Economic Zone. Low temperature was shown to promote the prevalence of A(H1N1)pdm09 and type B in winter-spring days at all levels of relative humidity. High risk of A(H3N2) infections was observed at low temperature or high temperature, and at higher relative humidity. Moreover, absolute humidity decreased or increased influenza (sub)type infections within different ranges.

CONCLUSIONS

This study found different nonlinear relationships between meteorological factors and the seasonality of influenza (sub)types, as well as significant interactive effects between climatic variables, contributing to the research on the climate drivers of influenza prevalence in warm-humid basin regions in the subtropics.

The Impact of Urbanization and Human Mobility on Seasonal Influenza in Northern China

The intensity of influenza epidemics varies significantly from year to year among regions with similar climatic conditions and populations. However, the underlying mechanisms of the temporal and spatial variations remain unclear. We investigated the impact of urbanization and public transportation size on influenza activity. We used 6-year weekly provincial-level surveillance data of influenza-like disease incidence (ILI) and viral activity in northern China. We derived the transmission potential of influenza for each epidemic season using the susceptible-exposed-infectious-removed-susceptible (SEIRS) model and estimated the transmissibility in the peak period via the instantaneous reproduction number (R_t). Public transport was found to explain approximately 28% of the variance in the seasonal transmission potential. Urbanization and public transportation size explained approximately 10% and 21% of the variance in maximum R_t in the peak period, respectively. For the mean R_t during the peak period, urbanization and public transportation accounted for 9% and 16% of the variance in R_t, respectively. Our results indicated that the differences in the intensity of influenza epidemics among the northern provinces of China were partially driven by urbanization and public transport size. These findings are beneficial for predicting influenza intensity and developing preparedness strategies for the early stages of epidemics.

Circulation and seasonality of influenza viruses in different transmission zones in Africa

Background

Influenza is responsible for more than 5 million severe cases and 290,000 to 650,000 deaths every year worldwide. Developing countries account for 99% of influenza deaths in children under 5 years of age. This paper aimed to determine the dynamics of influenza viruses in African transmission areas to identify regional seasonality for appropriate decision-making and the development of regional preparedness and response strategies.

Methods

We used data from the WHO FluMart website collected by National Influenza Centers for seven transmission periods (2013–2019). We calculated weekly proportions of positive influenza cases and determined transmission trends in African countries to determine the seasonality.

Results

From 2013 to 2019, influenza A(H1N1)pdm2009, A(H3N2), and A(H5N1) viruses, as well as influenza B Victoria and Yamagata lineages, circulated in African regions. Influenza A(H1N1)pdm2009 and A(H3N2) highly circulated in northern and southern Africa regions. Influenza activity followed annual and regional variations. In the tropical zone, from eastern to western via the middle regions, influenza activities were marked by the predominance of influenza A subtypes despite the circulation of B lineages. One season was identified for both the southern and northern regions of Africa. In the eastern zone, four influenza seasons were differentiated, and three were differentiated in the western zone.

Conclusion

Circulation dynamics determined five intense influenza activity zones in Africa. In the tropics, influenza virus circulation waves move from the east to the west, while alternative seasons have been identified in northern and southern temperate zones. Health authorities from countries with the same transmission zone, even in the absence of local data based on an established surveillance system, should implement concerted preparedness and control activities, such as vaccination.

Air Pollution-Related Respiratory Diseases and Associated Environmental Factors in Chiang Mai, Thailand, in 2011–2020

The unfavorable effects of global climate change, which are mostly the result of human activities, have had a particularly negative effect on human health and the planet’s ecosystems. This study attempted to determine the seasonality and association of air pollution, in addition to climate conditions, with two respiratory infections, influenza and pneumonia, in Chiang Mai, Thailand, which has been considered the most polluted city on Earth during the hot season. We used a seasonal-trend decomposition procedure based on loess regression (STL) and a seasonal cycle subseries (SCS) plot to determine the seasonality of the two diseases. In addition, multivariable negative binomial regression (NBR) models were used to assess the association between the diseases and environmental variables (temperature, precipitation, relative humidity, PM2.5, and PM10). The data revealed that influenza had a clear seasonal pattern during the cold months of January and February, whereas the incidence of pneumonia showed a weak seasonal pattern. In terms of forecasting, the preceding month’s PM2.5 and temperature (lag1) had a significant association with influenza incidence, while the previous month’s temperature and relative humidity influenced pneumonia. Using air pollutants as an indication of respiratory disease, our models indicated that PM2.5 lag1 was correlated with the incidence of influenza, but not pneumonia. However, there was a linear association between PM10 and both diseases. This research will help in allocating clinical and public health resources in response to potential environmental changes and forecasting the future dynamics of influenza and pneumonia in the region due to air pollution.

Seasonal variations and risk factors of Streptococcus pyogenes infection: a multicenter research network study

Background:

Streptococcus pyogenes, or Group A Streptococcus (GAS), causes acute pharyngitis and necrotizing fasciitis. Seasonal variations in GAS infections are not robustly characterized. We assessed seasonal variations and risk factors of GAS pharyngitis and ICD-10-diagnosed necrotizing fasciitis.

Methods:

From the period 2010–2019, we conducted a case–control study using laboratory-confirmed cases of GAS pharyngitis and a descriptive observational study of necrotizing fasciitis using ICD-10 codes. Data were collected from TriNetX, a federated research network. We extracted seasonal (quarterly) incidence rates. We used an autoregressive integrated moving average (ARIMA) model to assess seasonal variations. Demographic characteristics and 1-month outcomes were compared among adults with or without GAS pharyngitis.

Results:

We identified 224,471 adults with GAS pharyngitis (test-positive) and 546,142 adults without it (test-negative). GAS pharyngitis adults were younger (25.3 versus 30.2 years of age, p < 0.0001), more likely to be Hispanic individuals (10% versus 8%, p < 0.0001) and slightly more likely to be Black or African American individuals (14% versus 13%, p < 0.0001). Propensity score matching found that adults with test-positive cases of GAS pharyngitis had a higher risk of acute rheumatic fever while having no significant differences in risk of intensive care unit admission and mortality compared with test-negative cases. GAS pharyngitis average incidence peaked in the winter while dipping in the summer (0.32 versus 0.18 and 4.07 versus 1.78 per 1000 adults and pediatric patients, respectively). Necrotizing fasciitis diagnoses were highest during summer (0.032 per 1000 adults). There was a significant ARIMA seasonal variation in the time series analysis for adult and pediatric GAS pharyngitis (p < 0.0001 and p = 0.014, respectively). Necrotizing fasciitis diagnosis was not associated with seasonal variation (p = 0.861).

Conclusion:

Peaks in GAS pharyngitis occur in the winter months. ICD code–based necrotizing fasciitis did not show a quarterly seasonal variation.

The influences of the East Asian Monsoon on the spatio-temporal pattern of seasonal influenza activity in China

Previous research has extensively studied the seasonalities of human influenza infections and the effect of specific climatic factors in different regions. However, there is limited understanding of the influences of monsoons. This study applied generalized additive model with monthly surveillance data from mainland China to explore the influences of the East Asian Monsoon on the spatio-temporal pattern of seasonal influenza in China. The results suggested two influenza active periods in northern China and three active periods in southern China. The study found that the northerly advancement of East Asian Summer Monsoon (EASM) influences the summer influenza spatio-temporal patterns in both southern and northern China. At the interannual scale, the north-south converse effect of EASM on influenza activity is mainly due to the converse effect of EASM on humidity and precipitation. Within the annual scale, influenza activity in southern China gradually reaches its maximum during the summer exacerbated by the northerly advancement of EASM. Furthermore, the winter epidemic in China is related to the low temperature and humidity influenced by the East Asian Winter Monsoon (EAWM). Moreover, the active period in transition season is related partially to the large rapid temperature change influenced by the transition of EAWM and EASM. Despite the delayed onset and instability, the climatic condition influenced by the East Asian Monsoon is one of the potential key drivers of influenza activity.

A meta-analysis result: Uneven influences of season, geo-spatial scale and latitude on relationship between meteorological factors and the COVID-19 transmission

Meteorological factors have been confirmed to affect the COVID-19 transmission, but current studied conclusions varied greatly. The underlying causes of the variance remain unclear. Here, we proposed two scientific questions: (1) whether meteorological factors have a consistent influence on virus transmission after combining all the data from the studies; (2) whether the impact of meteorological factors on the COVID-19 transmission can be influenced by season, geospatial scale and latitude. We employed a meta-analysis to address these two questions using results from 2813 published articles. Our results showed that, the influence of meteorological factors on the newly-confirmed COVID-19 cases varied greatly among existing studies, and no consistent conclusion can be drawn. After grouping outbreak time into cold and warm seasons, we found daily maximum and daily minimum temperatures have significant positive influences on the newly-confirmed COVID-19 cases in cold season, while significant negative influences in warm season. After dividing the scope of the outbreak into national and urban scales, relative humidity significantly inhibited the COVID-19 transmission at the national scale, but no effect on the urban scale. The negative impact of relative humidity, and the positive impacts of maximum temperatures and wind speed on the newly-confirmed COVID-19 cases increased with latitude. The relationship of maximum and minimum temperatures with the newly-confirmed COVID-19 cases were more susceptible to season, while relative humidity's relationship was more affected by latitude and geospatial scale. Our results suggested that relationship between meteorological factors and the COVID-19 transmission can be affected by season, geospatial scale and latitude. A rise in temperature would promote virus transmission in cold seasons. We suggested that the formulation and implementation of epidemic prevention and control should mainly refer to studies at the urban scale. The control measures should be developed according to local meteorological properties for individual city.

Inactivation of viruses on surfaces by infrared techniques

Several studies on vaccines and medicines against virus-based illnesses (COVID-19, SARS, MERS) are being conducted worldwide. However, virus mutation is an issue. Therefore, inactivation and disinfection of viruses are crucial. This paper presents a method for virus inactivation by physical techniques. The infrared (IR) technique is preferred over other disinfection techniques such as ultraviolet (UV) and chemical disinfectants (alcohol) due to the associated health and environmental benefits. In this study, IR sources with various wavelengths were characterized and a far infrared (FIR) source was used to inactivate viruses. FIR sources have a therapeutic effect on the human body and have been used in medical centers. Virus spread is highly affected by environmental conditions such as temperature, humidity, and airflow. A setup with IR sources, an IR camera, an automatically controlled humidity chamber, and an airflow unit was constructed to study the viability of viruses in stationary droplets as a function of relative humidity and temperature. Bacteriophage Phi6 was used as a model organism for studying enveloped viruses such as influenza and coronavirus. IR techniques were used for studying virus inactivation. The effect of various physical conditions such as temperature, humidity, and airflows was considered to study the effect of radiation on the stationary droplets of Phi6. All measurements were performed under laboratory conditions with controlled temperature and humidity. The IR camera system was used to measure the surface temperature of Phi6 suspension droplets. The samples subjected to IR radiation were processed for plaque assay preparation and counting. Measurements were carried out to reduce and eliminate droplets, which are one of the transmission pathways of viruses. IR was radiated in closed and open-air conditions with appropriate humidity and temperature. This study reports the effective inactivation of viruses by FIR. The inactivation rate under 50 %rh for IR radiated at 1.4 m height for 3 h in closed environmental chamber was 90%, and that under an airflow rate of 0.20 m/s for 10 min in open-air conditions at a height of 1.0 m was 45.7%.

Prediction of respiratory droplets evolution for safer academic facilities planning amid COVID-19 and future pandemics: A numerical approach

Airborne dispersion of the novel SARS-CoV-2 through the droplets produced during expiratory activities is one of the main transmission mechanisms of this virus from one person to another. Understanding how these droplets spread when infected humans with COVID-19 or other airborne infectious diseases breathe, cough or sneeze is essential for improving prevention strategies in academic facilities. This work aims to assess the transport and fate of droplets in indoor environments using Computational Fluid Dynamics (CFD). This study employs unsteady Reynolds-Averaged Navier-Stokes (URANS) simulations with the Euler-Lagrange approach to visualize the location of thousands of droplets released in a respiratory event and their size evolution. Furthermore, we assess the dispersion of coughing, sneezing, and breathing saliva droplets from an infected source in a classroom with air conditioning and multiple occupants. The results indicate that the suggested social distancing protocol is not enough to avoid the transmission of COVID-19 since small saliva droplets ( ≤ 12 μm) can travel in the streamwise direction up to 4 m when an infected person coughs and more than 7 m when sneezes. These droplets can reach those distances even when there is no airflow from the wind or ventilation systems. The number of airborne droplets in locations close to the respiratory system of a healthy person increases when the relative humidity of the indoor environment is low. This work sets an accurate, rapid, and validated numerical framework reproducible for various indoor environments integrating qualitative and quantitative data analysis of the droplet size evolution of respiratory events for a safer design of physical distancing standards and air cleaning technologies.

Seasonal variation in SARS-CoV-2 transmission in temperate climates: A Bayesian modelling study in 143 European regions

Although seasonal variation has a known influence on the transmission of several respiratory viral infections, its role in SARS-CoV-2 transmission remains unclear. While there is a sizable and growing literature on environmental drivers of COVID-19 transmission, recent reviews have highlighted conflicting and inconclusive findings. This indeterminacy partly owes to the fact that seasonal variation relates to viral transmission by a complicated web of causal pathways, including many interacting biological and behavioural factors. Since analyses of specific factors cannot determine the aggregate strength of seasonal forcing, we sidestep the challenge of disentangling various possible causal paths in favor of a holistic approach. We model seasonality as a sinusoidal variation in transmission and infer a single Bayesian estimate of the overall seasonal effect. By extending two state-of-the-art models of non-pharmaceutical intervention (NPI) effects and their datasets covering 143 regions in temperate Europe, we are able to adjust our estimates for the role of both NPIs and mobility patterns in reducing transmission. We find strong seasonal patterns, consistent with a reduction in the time-varying reproduction number R(t) (the expected number of new infections generated by an infectious individual at time t) of 42.1% (95% CI: 24.7%-53.4%) from the peak of winter to the peak of summer. These results imply that the seasonality of SARS-CoV-2 transmission is comparable in magnitude to the most effective individual NPIs but less than the combined effect of multiple interventions.

Effect of absolute humidity on influenza activity across different climate regions in China

Until now, we have no thorough understanding the role of absolute humidity on influenza activity, especially in tropical and subtropical areas. In this study, we investigated the relationship between absolute humidity and influenza activity in seven municipalities/provinces covering different climatic zones in China. Weekly meteorological data and influenza surveillance data in seven provinces/municipalities in China were collected from January 2012 to December 2019. A distributed lag nonlinear model was adopted to investigate the association between absolute humidity (AH) and influenza activity in each study site. Then, seven study sites were grouped into three regions: northern, intermediate, and southernmost regions. A multivariate meta-analysis was applied to estimate the exposure-lag-response associations in three regions. The province-specific or municipality-specific curves appeared to be nonlinear, and the association between influenza activity and AH varied across regions. In Beijing and Tianjin, located in northern China, the cumulative relative risks (RRs) increased as weekly average AHmean fell below 3.41 g/m³ and 6.62 g/m³. In Guangdong and Hainan, located in southernmost China, the risk of influenza activity increased with rising average AHmean with 16.74 g/m³ and 20.18 g/m³ as the break points. In Shanghai, Zhejiang, and Chongqing, the relationship between weekly average AHmean and influenza could be described as U-shaped curves, with the lowest RRs when weekly average AHmean was 11.95 g/m³, 11.94 g/m³, and 15.96 g/m³, respectively. Meta-analysis results showed the cumulative RRs significantly increased as weekly average AHmean fell below 3.86 g/m³ in the northern region, whereas significantly increased as weekly average AHmean rose above 18.46 g/m³ and 15.22 g/m³ in intermediate and southernmost regions, respectively. Both low and high AH might increase influenza risk in China, and the relationship varies geographically. Our findings suggest that public health policies for climate change adaptation should be tailored to the local climate conditions.

Was the Reduction in Seasonal Influenza Transmission during 2020 Attributable to Non-Pharmaceutical Interventions to Contain Coronavirus Disease 2019 (COVID-19) in Japan?

We quantified the effects of adherence to various non-pharmaceutical interventions (NPIs) on the seasonal influenza epidemic dynamics in Japan during 2020. The total monthly number of seasonal influenza cases per sentinel site (seasonal influenza activity) reported to the National Epidemiological Surveillance of Infectious Diseases and alternative NPI indicators (retail sales of hand hygiene products and number of airline passenger arrivals) from 2014−2020 were collected. The average number of monthly seasonal influenza cases in 2020 had decreased by approximately 66.0% (p < 0.001) compared to those in the preceding six years. An increase in retail sales of hand hygiene products of ¥1 billion over a 3-month period led to a 15.5% (95% confidence interval [CI]: 10.9−20.0%; p < 0.001) reduction in seasonal influenza activity. An increase in the average of one million domestic and international airline passenger arrivals had a significant association with seasonal influenza activity by 11.6% at lag 0−2 months (95% CI: 6.70−16.5%; p < 0.001) and 30.9% at lag 0−2 months (95% CI: 20.9−40.9%; p < 0.001). NPI adherence was associated with decreased seasonal influenza activity during the COVID-19 pandemic in Japan, which has crucial implications for planning public health interventions to minimize the health consequences of adverse seasonal influenza epidemics.

Community-level ambient fine particulate matter and seasonal influenza among children in Guangzhou, China: A Bayesian spatiotemporal analysis

BACKGROUND

Influenza is a major preventable infectious respiratory disease. However, there is little detailed long-term evidence of its associations with PM_2.5 among children. We examined the community-level associations between exposure to ambient PM_2.5 and incident influenza in Guangzhou, China.

METHODS

We used data from the city-wide influenza surveillance system collected by Guangzhou Centre for Disease Control and Prevention (GZCDC) over the period 2013 and 2019. Incident influenza was defined as daily new influenza (both clinically diagnosed and laboratory confirmed) cases as per standard diagnostic criteria. A 200-meter city-wide grid of daily ambient PM_2.5 exposure was generated using a random forest model. We developed spatiotemporal Bayesian hierarchical models to examine the community-level associations between PM_2.5 and the influenza adjusting for meteorological and socioeconomic variables and accounting for spatial autocorrelation. We also calculated community-wide influenza cases attributable to PM_2.5 levels exceeding the China Grade 1 and World Health Organization (WHO) regulatory thresholds.

RESULTS

Our study comprised N = 191,846 children from Guangzhou aged ≤19 years and diagnosed with influenza between January 1, 2013 and December 31, 2019. Each 10 μg/m³ increment in community-level PM_2.5 measured on the day of case confirmation (lag 0) and over a 6-day moving average (lag 0-5 days) was associated with higher risks of influenza (RR = 1.05, 95% CI: 1.05-1.06 for lag 0 and RR = 1.15, 95% CI: 1.14-1.16 for lag 05). We estimated that 8.10% (95%CI: 7.23%-8.57%) and 20.11% (95%CI: 17.64%-21.48%) influenza cases respectively were attributable to daily PM_2.5 exposure exceeding the China Grade I (35 μg/m³) and the WHO limits (25 μg/m³). The risks associated with PM_2.5 exposures were more pronounced among children of the age-group 10-14 compared to other age groups.

CONCLUSIONS

More targeted non-pharmaceutical interventions aimed at reducing PM_2.5 exposures at home, school and during commutes among children may constitute additional influenza prevention and control polices.

Cross-reactive immunity potentially drives global oscillation and opposed alternation patterns of seasonal influenza A viruses

Several human pathogens exhibit distinct patterns of seasonality and circulate as pairs. For instance, influenza A virus subtypes oscillate and peak during winter seasons of the world’s temperate climate zones. Alternation of dominant strains in successive influenza seasons makes epidemic forecasting a major challenge. From the start of the 2009 influenza pandemic we enrolled influenza A virus infected patients (n = 2980) in a global prospective clinical study. Complete hemagglutinin sequences were obtained from 1078 A/H1N1 and 1033 A/H3N2 viruses. We used phylodynamics to construct high resolution spatio-temporal phylogenetic hemagglutinin trees and estimated global influenza A effective reproductive numbers (R) over time (2009–2013). We demonstrate that R oscillates around R = 1 with a clear opposed alternation pattern between phases of the A/H1N1 and A/H3N2 subtypes. Moreover, we find a similar alternation pattern for the number of global viral spread between the sampled geographical locations. Both observations suggest a between-strain competition for susceptible hosts on a global level. Extrinsic factors that affect person-to-person transmission are a major driver of influenza seasonality. The data presented here indicate that cross-reactive host immunity is also a key intrinsic driver of influenza seasonality, which determines the influenza A virus strain at the onset of each epidemic season.

How Drivers of Seasonality in Respiratory Infections May Impact Vaccine Strategy: A Case Study in How Coronavirus Disease 2019 (COVID-19) May Help Us Solve One of Influenza's Biggest Challenges

Vaccines against seasonal infections like influenza offer a recurring testbed, encompassing challenges in design, implementation, and uptake to combat a both familiar and ever-shifting threat. One of the pervading mysteries of influenza epidemiology is what causes the distinctive seasonal outbreak pattern. Proposed theories each suggest different paths forward in being able to tailor precision vaccines and/or deploy them most effectively. One of the greatest challenges in contrasting and supporting these theories is, of course, that there is no means by which to actually test them. In this communication we revisit theories and explore how the ongoing coronavirus disease 2019 (COVID-19) pandemic might provide a unique opportunity to better understand the global circulation of respiratory infections. We discuss how vaccine strategies may be targeted and improved by both isolating drivers and understanding the immunological consequences of seasonality, and how these insights about influenza vaccines may generalize to vaccines for other seasonal respiratory infections.

The emergence of SARS-CoV-2 variants of concern in Australia by haplotype coalescence reveals a continental link to COVID-19 seasonality

SARS-CoV-2 continues to evolve, even after implementation of public-wide vaccination, as can be observed by an increasing number of mutations over time. Compared to responses by the United States and European countries, the disease mitigation strategies employed by the Australian government have been swift and effective. This provides a unique opportunity to study the emergence of variants of concern (VOCs) at many latitude levels in a country that has been able to control infection for the majority of the pandemic. In the present study, we explored the occurrence and accumulation of major mutations typical of VOCs in different regions of Australia and the effects that latitude has on the establishment of VOC-induced disease. We also studied the constellation of mutations characteristic of VOCs to determine if the mutation sets acted as haplotypes. Our goal was to explore processes behind the emergence of VOCs as the viral disease progresses towards becoming endemic. Most reported COVID-19 cases were in largest cities located within a -30°S to - 50°S latitude corridor previously identified to be associated with seasonal behavior. Accumulation plots of individual amino acid variants of major VOCs showed that the first major haplotypes reported worldwide were also present in Australia. A classification of accumulation plots revealed the existence of 18 additional haplotypes associated with VOCs alpha, delta and omicron. Core mutant constellations for these VOCs and curve overlaps for variants in each set of haplotypes demonstrated significant decoupling patterns, suggesting processes of emergence. Finally, construction of a "haplotype network" that describes the viral population landscape of Australia throughout the COVID-19 pandemic revealed significant and unanticipated seasonal patterns of emergence and diversification. These results provide a unique window into our evolutionary understanding of a human pathogen of great significance. They may guide future research into mitigation and prediction strategies for future VOCs.

Meteorological factors' effects on COVID-19 show seasonality and spatiality in Brazil

The meteorological conditions may affect COVID-19 transmission. However, the roles of seasonality and macro-climate are still contentious due to the limited time series for early-stage studies. We studied meteorological factors' effects on COVID-19 transmission in Brazil from February 25 to November 15, 2020. We aimed to explore whether this impact showed seasonal characteristics and spatial variations related to the macro-climate. We applied two-way fixed-effect models to identify the effects of meteorological factors on COVID-19 transmission and used spatial analysis to explore their spatial-temporal characteristics with a relatively long-time span. The results showed that cold, dry and windless conditions aggravated COVID-19 transmission. The daily average temperature, humidity, and wind speed negatively affected the daily new cases. Humidity and temperature played a dominant role in this process. For the time series, the influences of meteorological conditions on COVID-19 had a periodic fluctuation of 3-4 months (in line with the seasons in Brazil). The turning points of this fluctuation occurred at the turn of seasons. Spatially, the negative effects of temperature and humidity on COVID-19 transmission clustered in the northeastern and central parts of Brazil. This is consistent with the range of arid climate types. Overall, the seasonality and similar climate types should be considered to estimate the spatial-temporal COVID-19 patterns. Winter is a critical time to be alert for COVID-19, especially in the northern part of Brazil.

Influenza Viruses and Vaccines: The Role of Vaccine Effectiveness Studies for Evaluation of the Benefits of Influenza Vaccines

Influenza is a vaccine preventable disease and vaccination remains the most effective method of controlling the morbidity and mortality of seasonal influenza, especially with respect to risk groups. To date, three types of influenza vaccines have been licensed: inactivated, live-attenuated, and recombinant haemagglutinin vaccines. Effectiveness studies allow an assessment of the positive effects of influenza vaccines in the field. The effectiveness of current influenza is suboptimal, being estimated as 40% to 60% when the vaccines strains are antigenically well-matched with the circulating viruses. This review focuses on influenza viruses and vaccines and the role of vaccine effectiveness studies for evaluating the benefits of influenza vaccines. Overall, influenza vaccines are effective against morbidity and mortality in all age and risk groups, especially in young children and older adults. However, the effectiveness is dependent on several factors such as the age of vaccinees, the match between the strain included in the vaccine composition and the circulating virus, egg-adaptations occurring during the production process, and the subject’s history of previous vaccination.

Effects and Interaction of Meteorological Parameters on Influenza Incidence During 2010-2019 in Lanzhou, China

Background

Influenza is a seasonal infectious disease, and meteorological parameters critically influence the incidence of influenza. However, the meteorological parameters linked to influenza occurrence in semi-arid areas are not studied in detail. This study aimed to clarify the impact of meteorological parameters on influenza incidence during 2010-2019 in Lanzhou. The results are expected to facilitate the optimization of influenza-related public health policies by the local healthcare departments.

Methods

Descriptive data related to influenza incidence and meteorology during 2010-2019 in Lanzhou were analyzed. The exposure-response relationship between the risk of influenza occurrence and meteorological parameters was explored according to the distributed lag no-linear model (DLNM) with Poisson distribution. The response surface model and stratified model were used to estimate the interactive effect between relative humidity (RH) and other meteorological parameters on influenza incidence.

Results

A total of 6701 cases of influenza were reported during 2010-2019. DLNM results showed that the risk of influenza would gradually increase as the weekly mean average ambient temperature (AT), RH, and absolute humidity (AH) decrease at lag 3 weeks when they were lower than 12.16°C, 51.38%, and 5.24 g/m³, respectively. The low Tem (at 5th percentile, P₅) had the greatest effect on influenza incidence; the greatest estimated relative risk (RR) was 4.54 (95%CI: 3.19-6.46) at cumulative lag 2 weeks. The largest estimates of RRs for low RH (P₅) and AH (P₅) were 4.81 (95%CI: 3.82-6.05) and 4.17 (95%CI: 3.30-5.28) at cumulative lag 3 weeks, respectively. An increase in AT by 1°C led to an estimates of percent change (95%CI) of 3.12% (-4.75% to -1.46%) decrease in the weekly influenza case counts in a low RH environment. In addition, RH showed significant interaction with AT and AP on influenza incidence but not with wind speed.

Conclusion

This study indicated that low AT, low humidity (RH and AH), and high air pressure (AP) increased the risk of influenza. Moreover, the interactive effect of low RH with low AT and high AP can aggravate the incidence of influenza.

Influenza seasonality and its environmental driving factors in mainland China and Hong Kong

BACKGROUND

Influenza epidemics occur during winter in temperate zones, but have less regular seasonality in the subtropics and tropics. Here we quantified the role of environmental drivers of influenza seasonality in temperate and subtropical China.

METHODS

We used weekly surveillance data on influenza virus activity in mainland China and Hong Kong from 2005 through 2016. We estimated the transmissibility via the instantaneous reproduction number (R_t), a real-time measure of transmissibility, and examined its relationship with different climactic drivers and allowed for the timing of school holidays and the decline in susceptibility in the population as an epidemic progressed. We developed a multivariable regression model for R_t to quantify the contribution of various potential environmental drivers of transmission.

FINDINGS

We found that absolute humidity is a potential driver of influenza seasonality and had a U-shaped association with transmissibility and hence can predict the pattern of influenza virus transmission across different climate zones. Absolute humidity was able to explain up to 15% of the variance in R_t, and was a stronger predictor of R_t across the latitudes. Other climatic drivers including mean daily temperature explained up to 13% of variance in R_t and limited to the locations where the indoor measures of these factors have better indicators of outdoor measures. The non-climatic driver, holiday-related school closures could explain up to 7% of variance in R_t.

INTERPRETATION

A U-shaped association of absolute humidity with influenza transmissibility was able to predict seasonal patterns of influenza virus epidemics in temperate and subtropical locations.

Autopsy results from a COVID-19 patient treated in a tropical area, and a review of the epidemiological history

Since the start of the COVID-19 pandemic, there has been an urgent need to produce accurate and sensitive tests. However, there have been instances where a positive nucleic acid test turns negative after treatment, and then positive again. This case report describes such an instance from the tropical region of Hainan, China. The patient was a 61-year-old female who went to Hainan on vacation from Wuhan during the COVID-19 pandemic in 2020. Symptoms appeared 9 d after arriving in Hainan, and it was confirmed that the nucleic acid test was positive after 4 repeats. Her condition declined rapidly, her heart stopped beating, and she was admitted in a coma to the ICU. After treatment, the SARS-CoV-2 virus nucleic acid test of several nasopharyngeal swabs were negative, and tests on whole blood, anal swabs, and urine were also negative. Later, however, nucleic acid tests on a lower respiratory tract sputum swab and lower respiratory tract lavage fluid were positive. An autopsy examination was carried out 12 h after her death, and multi-organ secretions were extracted for nucleic acid testing. The SARS-CoV-2 virus nucleic acid was only detected in the swabs from the end of the bronchus, which was confirmed by the visualization of the coronavirus by electron microscopy. Autopsy confirmed that the damage was mainly concentrated in the lungs and immune organs and tissues throughout the body. Epidemiology indicated that none of the people she came into contact with after arriving in Hainan, including close contacts, were infected. This is in sharp contrast to the highly contagious virus in Wuhan in the temperate zone during the same period. This case report indicates: (1) The high temperatures in tropical areas may have an impact on the spread and harm of COVID-19, and (2) The reason why nucleic acid testing for COVID-19 was initially negative and then positive after treatment may be related to the survival of the SARS-CoV-2 virus in deep lung tissues.

Global patterns of seasonal influenza activity, duration of activity and virus (sub)type circulation from 2010 to 2020

Background

Seasonal influenza viruses undergo unpredictable changes, which may lead to antigenic mismatch between circulating and vaccine strains and to a reduced vaccine effectiveness. A continuously updated knowledge of influenza strain circulation and seasonality is essential to optimize the effectiveness of influenza vaccination campaigns. We described the global epidemiology of influenza between the 2009 A(H1N1)p and the 2020 COVID‐19 pandemic.

Methods

Influenza virological surveillance data were obtained from the WHO‐FluNet database. We determined the median proportion of influenza cases caused by the different influenza virus types, subtypes, and lineages; the typical timing of the epidemic peak; and the median duration of influenza epidemics (applying the annual average percentage method with a 75% threshold).

Results

We included over 4.6 million influenza cases from 149 countries. The median proportion of influenza cases caused by type A viruses was 75.5%, highest in the Southern hemisphere (81.6%) and lowest in the intertropical belt (73.0%), and ranged across seasons between 60.9% in 2017 and 88.7% in 2018. Epidemic peaks typically occurred during winter months in Northern and Southern hemisphere countries, while much more variability emerged in tropical countries. Influenza epidemics lasted a median of 25 weeks (range 8–42) in countries lying between 30°N and 26°S, and a median of 9 weeks (range 5–25) in countries outside this latitude range.

Conclusions

This work will establish an important baseline to better understand factors that influence seasonal influenza dynamics and how COVID‐19 may have affected seasonal activity and influenza virus types, subtypes, and lineages circulation patterns.

North to south gradient and local waves of influenza in Chile

Influenza seasonality is caused by complex interactions between environmental factors, viral mutations, population crowding, and human travel. To date, no studies have estimated the seasonality and latitudinal patterns of seasonal influenza in Chile. We obtained influenza-like illness (ILI) surveillance data from 29 Chilean public health networks to evaluate seasonality using wavelet analysis. We assessed the relationship between the start, peak, and latitude of the ILI epidemics using linear and piecewise regression. To estimate the presence of incoming and outgoing traveling waves (timing vs distance) between networks and to assess the association with population size, we used linear and logistic regression. We found a north to south gradient of influenza and traveling waves that were present in the central, densely populated region of Chile. Our findings suggest that larger populations in central Chile drive seasonal influenza epidemics.

Sentinel surveillance for influenza A viruses in Lahore District Pakistan in flu season 2015-2016

Background

Influenza A virus (IAV) remains an important global public health threat with limited epidemiological information available from low-and-middle-income countries. The major objective of this study was to describe the proportions, temporal and spatial distribution, and demographic and clinical characteristics of IAV positive patients with influenza like illness (ILI) and severe acute respiratory illness (SARI) in Lahore, Pakistan.

Methods

Prospective surveillance was established in a sentinel hospital from October 2015 to May 2016. All eligible outpatients and inpatients with ILI or SARI were enrolled in the study. Nasal and/or throat swabs were collected along with clinico-epidemiological data. Samples were tested by real-time RT-PCR (rRT-PCR) to identify IAV and subtype. The descriptive analysis of data was done in R software.

Results

Out of 311 enrolled patients, 284 (91.3%) were ILI and 27 (8.7%) were SARI cases. A distinct peak of ILI and SARI activity was observed in February. Fifty individuals (16%) were positive for IAV with peak positivity observed in December. Of 50 IAV, 15 were seasonal H3N2, 14 were H1N1pdm09 and 21 were unable to be typed. The majority of IAV positive cases (98%) presented with current or history of fever, 88% reported cough and 82% reported sore throat. The most common comorbidities in IAV positive cases were hepatitis C (4%), obesity (4%) and tuberculosis (6%). The highest incidence of patients reporting to the hospital was seen three days post symptoms onset (66/311) with 14 of these (14/66) positive for IAV.

Conclusion

Distinct trends of ILI, SARI and IAV positive cases were observed which can be used to inform public health interventions (vaccinations, hand and respiratory hygiene) at appropriate times among high-risk groups. We suggest sampling from both ILI and SARI patients in routine surveillance as recommended by WHO.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-07021-7.

Temperature dependent viral tropism: understanding viral seasonality and pathogenicity as applied to the avoidance and treatment of endemic viral respiratory illnesses

This review seeks to explain three features of viral respiratory illnesses that have perplexed generations of virologists: (1) the seasonal timing of respiratory illness and the rapid response of outbreaks to weather, specifically temperature; (2) the common viruses causing respiratory illness worldwide, including year-round disease in the Tropics; (3) the rapid arrival and termination of epidemics caused by influenza and other viruses. The inadequacy of the popular explanations of seasonality is discussed, and a simple hypothesis is proposed, called temperature dependent viral tropism (TDVT), that is compatible with the above features of respiratory illness. TDVT notes that viruses can spread more effectively if they moderate their pathogenicity (thereby maintaining host mobility) and suggests that endemic respiratory viruses accomplish this by developing thermal sensitivity within a range that supports organ-specific viral tropism within the human body, whereby they replicate most rapidly at temperatures below body temperature. This can confine them to the upper respiratory tract and allow them to avoid infecting the lungs, heart, gut etc. Biochemical and tissue-culture studies show that 'wild' respiratory viruses show such natural thermal sensitivity. The typical early autumn surge of colds and the occurrence of respiratory illness in the Tropics year-round at intermediate levels are explained by the tendency for strains to adapt their thermal sensitivity to their local climate and season. TDVT has important practical implications for preventing and treating respiratory illness including Covid-19. It is testable with many options for experiments to increase our understanding of viral seasonality and pathogenicity.

Sensitivity of airborne transmission of enveloped viruses to seasonal variation in indoor relative humidity

In temperate climates, the peak in infection rates of enveloped viruses during the winter is likely heightened by seasonal variation in relative humidity within indoor spaces. While these seasonal trends are established in influenza and human coronaviruses, the mechanisms driving this seasonality remain poorly understood. Relative humidity impacts the evaporation rate and equilibrium size of airborne particles, which in turn may impact particle removal rates and virion viability. However, the relative importance of these two processes is not known. Here we use the Quadrature-based model of Respiratory Aerosol and Droplets to explore whether the seasonal variation in enveloped viruses is driven by differences in particle removal rates or by differences in virion inactivation rates. Through a large ensemble of simulations, we found that dry indoor conditions typical of winter lead to slower virion inactivation than humid indoor conditions typical of summer; in poorly ventilated spaces, this reduction in inactivation rates increases the airborne concentration of active virions, but this effect was important to virion exposure only when the susceptible person was farther than 2 m downwind of the infectious person. On the other hand, the impact of relative humidity on particle settling velocity did not significantly affect the removal or travel distance of virus-laden particles, suggesting that relative humidity is more likely to affect seasonal transmission via inactivation rates than via particle removal.

Extreme Precipitation Events and Infectious Disease Risk: A Scoping Review and Framework for Infectious Respiratory Viruses

Extreme precipitation events (EPE) change the natural and built environments and alter human behavior in ways that facilitate infectious disease transmission. EPEs are expected with high confidence to increase in frequency and are thus of great public health importance. This scoping review seeks to summarize the mechanisms and severity of impacts of EPEs on infectious diseases, to provide a conceptual framework for the influence of EPEs on infectious respiratory diseases, and to define areas of future study currently lacking in this field. The effects of EPEs are well-studied with respect to enteric, vector-borne, and allergic illness where they are shown to moderately increase risk of illness, but not well-understood in relation to infectious respiratory illness. We propose a framework for a similar influence of EPEs on infectious respiratory viruses through several plausible pathways: decreased UV radiation, increased ambient relative humidity, and changes to human behavior (increased time indoors and use of heating and cooling systems). However, limited work has evaluated meteorologic risk factors for infectious respiratory diseases. Future research is needed to evaluate the effects of EPEs on infectious respiratory diseases using individual-level case surveillance, fine spatial scales, and lag periods suited to the incubation periods of the disease under study, as well as a full characterization of susceptible, vulnerable, and sensitive population characteristics.

Attitudes, practices, and obstacles towards influenza vaccination for international travelers among travel health advisors in Germany: A questionnaire-based survey

BACKGROUND

Influenza is the most frequent vaccine-preventable infection in travelers, and both national and international guidelines recommend considering seasonal influenza vaccination (SIV) not only for those with risk factors for complications but for all travelers. However, vaccination coverage may be hampered by a lack of awareness among travelers and health care providers and limited vaccine availability outside the local influenza season.

METHODS

We identified travel health advisors in databases of German medical professional societies and invited them to complete an online questionnaire between April and May 2021.

RESULTS

Among 1085 travel health advisors contacted by email, 253 (23.3%) completed the online questionnaire. Most of them recommend SIV for travelers older than 60 years or those with comorbidities regardless of the travel destination or the influenza season in Germany. However, only very few respondents stated that they had regular access to SIV in June (n = 16, 6.5%), July (n = 10, 4.0%), and August (n = 17, 6.9%), respectively. While most participants (n = 197, 79.4%) stated that they would vaccinate more travelers if they had SIV regularly available outside the German influenza season, only eleven respondents (4.4%) have previously ordered SIV produced for the southern hemisphere, which was attributed mainly to logistic barriers.

CONCLUSIONS

Travel health advisors in Germany recommend SIV for a considerable proportion of travelers. While most of them see a necessity to vaccinate throughout the year, availability of SIV outside the German season is very limited. Current organizational barriers must be overcome to increase vaccination coverage among international travelers.

The Effects of Climate and Bioclimate on COVID-19 Cases in Poland

The correlations between air temperatures, relative and absolute humidity, wind, cloudiness, precipitation and number of influenza cases have been extensively studied in the past. Because, initially, COVID-19 cases were similar to influenza cases, researchers were prompted to look for similar relationships. The aim of the study is to identify the effects of changes in air temperature on the number of COVID-19 infections in Poland. The hypothesis under consideration concerns an increase in the number of COVID-19 cases as temperature decreases. The spatial heterogeneity of the relationship under study during the first year and a half of the COVID-19 pandemic in Polish counties is thus revealed.

Comparable seasonal pattern for COVID-19 and flu-like illnesses

BACKGROUND

During the first wave of COVID-19 it was hypothesized that COVID-19 is subject to multi-wave seasonality, similar to Influenza-Like Illnesses since time immemorial. One year into the pandemic, we aimed to test the seasonality hypothesis for COVID-19.

METHODS

We calculated the average annual time-series for Influenza-Like Illnesses based on incidence data from 2016 till 2019 in the Netherlands, and compared these with two COVID-19 time-series during 2020/2021 for the Netherlands. We plotted the time-series on a standardized logarithmic infection scale. Finally, we calculated correlation coefficients and used univariate regression analysis to estimate the strength of the association between the time-series of COVID-19 and Influenza-Like Illnesses.

RESULTS

The time-series for COVID-19 and Influenza-Like Illnesses were strongly and highly significantly correlated. The COVID-19 peaks were all during flu season, and lows were all in the opposing period. Finally, COVID-19 meets the multi-wave characteristics of earlier flu-like pandemics, namely a short first wave at the tail-end of a flu season, and a longer and more intense second wave during the subsequent flu season.

CONCLUSIONS

We conclude that seasonal patterns of COVID-19 incidence and Influenza-Like Illnesses incidence are highly similar, in a country in the temperate climate zone, such as the Netherlands. Further, the COVID-19 pandemic satisfies the criteria of earlier respiratory pandemics, namely a first wave that is short-lived at the tail-end of flu season, and a second wave that is longer and more severe.This seems to imply that the same factors that are driving the seasonality of Influenza-Like Illnesses are causing COVID-19 seasonality as well, such as solar radiation (UV), temperature, relative humidity, and subsequently seasonal allergens and allergies.

Influences of climatic and non-climatic factors on COVID-19 outbreak: A review of existing literature

Coronavirus disease 2019 (COVID-19) has become a significant global public health issue resulting from SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2). COVID-19 outbreak approaches an unprecedented challenge for human health, the economy, and societies. The transmission of the COVID-19 is influenced by many factors, including climatic, environmental, socioeconomic, and demographic. This study aimed to investigate the influences of climatic and sociodemographic determinants on COVID-19 transmission. The climatic variables considered herein were air temperature, relative humidity, wind speed, air pollution, and cumulative precipitation. Sociodemographic variables included population density, socioeconomic conditions, misinformation, and personal hygiene practices towards the pandemic. Review results indicated that lower temperatures and greater incidence of COVID-19 are reported in a more significant number of studies. Another factor linked to COVID-19 occurrence was the humidity. However, the results were varied; some research reported positive, and others reported negative relationships. In addition, poor air quality, along with strong winds, makes the virus more vulnerable to spreading, leading to a spike in COVID-19 cases. PM2.5, O3, and NO2 also showed a strong correlation with the recent epidemic. The findings on rainfall were inconsistent between studies. Among the non-climatic factors, population density, education, and income were credited as potential determinants for the coronavirus outbreak. Climatic and sociodemographic factors showed a significant correlation on the COVID-19 outbreak. Thus, our review emphasizes the critical importance of considering climatic and non-climatic factors while developing intervention measures. This study's core findings will support the decision-makers in identifying climatic and socioeconomic elements that influence the risks of future pandemics.

SARS-CoV-2 and influenza virus coinfection among patients with severe acute respiratory infection during the first wave of COVID-19 pandemic in Bangladesh: a hospital-based descriptive study

OBJECTIVE

To estimate the proportion of SARS-CoV-2 and influenza virus coinfection among severe acute respiratory infection (SARI) cases-patients during the first wave of COVID-19 pandemic in Bangladesh.

DESIGN

Descriptive study.

SETTING

Nine tertiary level hospitals across Bangladesh.

PARTICIPANTS

Patients admitted as SARI (defined as cases with subjective or measured fever of ≥38 C° and cough with onset within the last 10 days and requiring hospital admission) case-patients.

PRIMARY AND SECONDARY OUTCOMES

Proportion of SARS-CoV-2 and influenza virus coinfection and proportion of mortality among SARI case-patients.

RESULTS

We enrolled 1986 SARI case-patients with a median age: 28 years (IQR: 1.2-53 years), and 67.6% were male. Among them, 285 (14.3%) were infected with SARS-CoV-2; 175 (8.8%) were infected with the influenza virus, and five (0.3%) were coinfected with both viruses. There was a non-appearance of influenza during the usual peak season (May to July) in Bangladesh. SARS-CoV-2 infection was significantly more associated with diabetes (14.0% vs 5.9%, p<0.001) and hypertension (26.7% vs 11.5%, p<0.001). But influenza among SARI case-patients was significantly less associated with diabetes (4.0% vs 7.4%, p=0.047) and hypertension (5.7% vs 14.4%, p=0.001). The proportion of in-hospital deaths among SARS-CoV-2 infected SARI case-patients were higher (10.9% (n=31) vs 4.4% (n=75), p<0.001) than those without SARS-CoV-2 infection; the proportion of postdischarge deaths within 30 days was also higher (9.1% (n=25) vs 4.6% (n=74), p=0.001) among SARS-CoV-2 infected SARI case-patients than those without infection. No in-hospital mortality or postdischarge mortality was registered among the five coinfected SARI case-patients.

CONCLUSIONS

Our findings suggest that coinfection with SARS-CoV-2 and influenza virus was not very common and had less disease severity considering mortality in Bangladesh. There was no circulating influenza virus during the influenza peak season during the COVID-19 pandemic in 2020. Future studies are warranted for further exploration.

The seasonal behaviour of COVID-19 and its galectin-like culprit of the viral spike

Seasonal behaviour is an attribute of many viral diseases. Like other 'winter' RNA viruses, infections caused by the causative agent of COVID-19, SARS-CoV-2, appear to exhibit significant seasonal changes. Here we discuss the seasonal behaviour of COVID-19, emerging viral phenotypes, viral evolution, and how the mutational landscape of the virus affects the seasonal attributes of the disease. We propose that the multiple seasonal drivers behind infectious disease spread (and the spread of COVID-19 specifically) are in 'trade-off' relationships and can be better described within a framework of a 'triangle of viral persistence' modulated by the environment, physiology, and behaviour. This 'trade-off' exists as one trait cannot increase without a decrease in another. We also propose that molecular components of the virus can act as sensors of environment and physiology, and could represent molecular culprits of seasonality. We searched for flexible protein structures capable of being modulated by the environment and identified a galectin-like fold within the N-terminal domain of the spike protein of SARS-CoV-2 as a potential candidate. Tracking the prevalence of mutations in this structure resulted in the identification of a hemisphere-dependent seasonal pattern driven by mutational bursts. We propose that the galectin-like structure is a frequent target of mutations because it helps the virus evade or modulate the physiological responses of the host to further its spread and survival. The flexible regions of the N-terminal domain should now become a focus for mitigation through vaccines and therapeutics and for prediction and informed public health decision making.

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.

Correlating indoor and outdoor temperature and humidity in a sample of buildings in tropical climates

The incidence of several respiratory viral infections has been shown to be related to climate. Because humans spend most of their time indoors, measures of indoor climate, rather than outdoor climate, may be better predictors of disease incidence and transmission. Therefore, understanding the relationship between indoor and outdoor climate will help illuminate their influence on the seasonality of diseases caused by respiratory viruses. Indoor-outdoor relationships between temperature and humidity have been documented in temperate regions, but little information is available for tropical regions, where seasonal patterns of respiratory viral diseases differ. We have examined indoor-outdoor correlations of temperature, relative humidity (RH), and absolute humidity (AH) over a 1-year period in each of seven tropical cities. Across all cities, the average monthly indoor temperature was 25 ± 3°C (mean ± standard deviation) with a range of 20-30°C. The average monthly indoor RH was 66 ± 9% with a range of 50-78%, and the average monthly indoor AH was 15 ± 3 g/m³ with a range of 10-23 g/m³ . Indoor AH and RH were linearly correlated with outdoor AH when the air conditioning (AC) was off, suggesting that outdoor AH may be a good proxy of indoor humidity in the absence of AC. All indoor measurements were more strongly correlated with outdoor measurements as distance from the equator increased. Such correlations were weaker during the wet season, especially when AC was in operation. These correlations will provide insight for assessing the seasonality of respiratory viral infections using outdoor climate data, which is more widely available than indoor data, even though transmission of these diseases mainly occurs indoors.

Associations between Temperature and Influenza Activity: A National Time Series Study in China

Previous studies have reported that temperature is the main meteorological factor associated with influenza activity. This study used generalized additive models (GAMs) to explore the relationship between temperature and influenza activity in China. From the national perspective, the average temperature (AT) had an approximately negative linear correlation with the incidence of influenza, as well as a positive rate of influenza H1N1 virus (A/H1N1). Every degree that the monthly AT rose, the influenza cases decreased by 2.49% (95%CI: 1.24%–3.72%). The risk of influenza cases reached a peak at −5.35 °C with RRs of 2.14 (95%CI: 1.38–3.33) and the monthly AT in the range of −5.35 °C to 18.31 °C had significant effects on the incidence of influenza. Every degree that the weekly AT rose, the positive rate of A/H1N1 decreased by 5.28% (95%CI: 0.35%–9.96%). The risk of A/H1N1 reached a peak at −3.14 °C with RRs of 4.88 (95%CI: 1.01–23.75) and the weekly AT in the range of −3.14 °C to 17.25 °C had significant effects on the incidence of influenza. Our study found that AT is negatively associated with influenza activity, especially for A/H1N1. These findings indicate that temperature could be integrated into the current influenza surveillance system to develop early warning systems to better predict and prepare for the risks of influenza.

A cross-sectional analysis of meteorological factors and SARS-CoV-2 transmission in 409 cities across 26 countries

There is conflicting evidence on the influence of weather on COVID-19 transmission. Our aim is to estimate weather-dependent signatures in the early phase of the pandemic, while controlling for socio-economic factors and non-pharmaceutical interventions. We identify a modest non-linear association between mean temperature and the effective reproduction number (Re) in 409 cities in 26 countries, with a decrease of 0.087 (95% CI: 0.025; 0.148) for a 10 °C increase. Early interventions have a greater effect on Re with a decrease of 0.285 (95% CI 0.223; 0.347) for a 5th - 95th percentile increase in the government response index. The variation in the effective reproduction number explained by government interventions is 6 times greater than for mean temperature. We find little evidence of meteorological conditions having influenced the early stages of local epidemics and conclude that population behaviour and government interventions are more important drivers of transmission.

Seasonality of Respiratory Viruses at Northern Latitudes

IMPORTANCE

Every 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.

OBJECTIVE

To describe the annual and biennial variation in respiratory virus seasonality in a northern climate.

DESIGN, SETTING, AND PARTICIPANTS

This 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.

EXPOSURES

Seasonal respiratory pathogens.

MAIN OUTCOMES AND MEASURES

Incidence (temporal pattern) of respiratory virus infections and RSV hospitalizations.

RESULTS

A 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 RELEVANCE

In 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.

Pollen antigens and atmospheric circulation driven seasonal respiratory viral outbreak and its implication to the Covid-19 pandemic

The patterns of respiratory virus illness are expressed differently between temperate and tropical climates. Tropical outbreaks often peak in wet seasons. Temperate outbreaks typically peak during the winter. The prevailing causal hypotheses focus on sunlight, temperature and humidity variations. Yet no consistent factors have been identified to sufficiently explain seasonal virus emergence and decline at any latitude. Here we demonstrate close connections among global-scale atmospheric circulations, IgE antibody enhancement through seasonal pollen inhalation, and respiratory virus patterns at any populated latitude, with a focus on the US. Pollens emerge each Spring, and the renewed IgE titers in the population are argued to terminate each winter peak of respiratory illness. Globally circulated airborne viruses are postulated to subsequently deposit across the Southern US during lower zonal geostrophic winds each late Summer. This seasonally refreshed viral load is postulated to trigger a new influenza outbreak, once the existing IgE antibodies diminish to a critical value each Fall. Our study offers a new and consistent explanation for the seasonal diminishment of respiratory viral illnesses in temperate climates, the subdued seasonal signature in the tropics, the annually circulated virus phenotypes, and the northerly migration of influenza across the US every year. Our integrated geospatial and IgE hypothesis provides a new perspective for prediction, mitigation and prevention of the outbreak and spread of seasonal respiratory viruses including Covid-19 pandemic.

Marginal warming associated with a COVID-19 quarantine and the implications for disease transmission

During January-February 2020, parts of China faced restricted mobility under COVID-19 quarantines, which have been associated with improved air quality. Because particulate pollutants scatter, diffuse, and absorb incoming solar radiation, a net negative radiative forcing, decreased air pollution can yield surface warming. As such, this study (1) documents the evolution of China's January-February 2020 air temperature and concurrent particulate changes; (2) determines the temperature response related to reduced particulates during the COVID-19 quarantine (C19Q); and (3) discusses the conceptual implications for temperature-dependent disease transmission. C19Q particulate evolution is monitored using satellite analyses, and concurrent temperature anomalies are diagnosed using surface stations and Aqua AIRS imagery. Meanwhile, two WRF-Chem simulations are forced by normal emissions and the satellite-based urban aerosol changes, respectively. Urban aerosols decreased from 27.1% of pre-C19Q aerosols to only 17.5% during C19Q. WRF-Chem resolved ~0.2 °C warming across east-central China, that represented a minor, though statistically significant contribution to C19Q temperature anomalies. The largest area of warming is concentrated south of Chengdu and Wuhan where temperatures increased between +0.2-0.3 °C. The results of this study are important for understanding the anthropogenic forcing on regional meteorology. Epidemiologically, the marginal, yet persistent, warming during C19Q may retard temperature-dependent disease transmission, possibly including SARS-CoV-2.

Low levels of respiratory syncytial virus activity in Europe during the 2020/21 season: what can we expect in the coming summer and autumn/winter?

Since the introduction of non-pharmacological interventions to control COVID-19, respiratory syncytial virus (RSV) activity in Europe has been limited. Surveillance data for 17 countries showed delayed RSV epidemics in France (≥ 12 w) and Iceland (≥ 4 w) during the 2020/21 season. RSV cases (predominantly small children) in France and Iceland were older compared with previous seasons. We hypothesise that future RSV epidemic(s) could start outside the usual autumn/winter season and be larger than expected. Year-round surveillance of RSV is of critical importance.

Association of temperature and relative humidity with the growth rate of the coronavirus disease 2019 epidemic

The effects of temperature and relative humidity on the growth of coronavirus disease 2019 (COVID-19) remain unclear. Data on the COVID-19 epidemic that were analyzed in this study were obtained from the official websites of the National Health Commission of China and the Health Commissions of 31 provinces in China. From January 26 to February 25, 2020, the cumulative number of confirmed COVID-19 cases in each region was counted daily using data from our database. Curve fitting of daily scatter plots of the relationship between epidemic growth rate (GR) with average temperature (AT) and average relative humidity (ARH) was conducted using the loess method. The heterogeneity across days and provinces was calculated to assess the necessity of using a longitudinal model. Fixed-effect models with polynomial terms were developed to quantify the relationship between variations in the GR and AT or ARH. An increased AT markedly reduced the GR when the AT was lower than -5°C, the GR was moderately reduced when the AT ranged from -5°C to 15°C, and the GR increased when the AT exceeded 15°C. ARH increased the GR when it was less than 72% and reduced the GR when it exceeded 72%. The temperature and relative humidity curves were not linearly associated with the GR of COVID-19. The GR was moderately reduced when the AT ranged from -5°C to 15°C. When the AT was lower or higher than -5°C to 15°C, the GR of COVID-19 increased. An increased ARH increased the GR when the ARH was lower than 72% and reduced the GR when the ARH exceeded 72%.

On the Environmental Determinants of COVID-19 Seasonality

Viral respiratory diseases (VRDs), such as influenza and COVID-19, are thought to spread faster during winter than during summer. It has been previously argued that cold and dry conditions are more conducive to the transmission of VRDs than warm and humid climates, although this relationship appears restricted to temperate regions and the causal relationship is not well understood. The severe acute respiratory syndrome coronavirus 2 causing COVID-19 has emerged as a serious global public health problem after the first COVID-19 reports in Wuhan, China, in late 2019. It is still unclear whether this novel respiratory disease will ultimately prove to be a seasonal endemic disease. Here, we suggest that air drying capacity (ADC; an atmospheric state variable that controls the fate/evolution of the virus-laden droplets) and ultraviolet radiation (UV) are probable environmental determinants in shaping the transmission of COVID-19 at the seasonal time scale. These variables, unlike temperature and humidity, provide a physically based framework consistent with the apparent seasonal variability in COVID-19 and prevalent across a broad range of climates (e.g., Germany and India). Since this disease is known to be influenced by the compounding effect of social, biological, and environmental determinants, this study does not claim that these environmental determinants exclusively shape the seasonality of COVID-19. However, we argue that ADC and UV play a significant role in COVID-19 dynamics at the seasonal scale. These findings could help guide the development of a sound adaptation strategy against the pandemic over the coming seasons.

Associations between meteorology and COVID-19 in early studies: Inconsistencies, uncertainties, and recommendations

Meteorological variables, such as the ambient temperature and humidity, play a well-established role in the seasonal transmission of respiratory viruses and influenza in temperate climates. Since the onset of the novel coronavirus disease 2019 (COVID-19) pandemic, a growing body of literature has attempted to characterize the sensitivity of COVID-19 to meteorological factors and thus understand how changes in the weather and seasonality may impede COVID-19 transmission. Here we select a subset of this literature, summarize the diversity in these studies' scopes and methodologies, and show the lack of consensus in their conclusions on the roles of temperature, humidity, and other meteorological factors on COVID-19 transmission dynamics. We discuss how several aspects of studies' methodologies may challenge direct comparisons across studies and inflate the importance of meteorological factors on COVID-19 transmission. We further comment on outstanding challenges for this area of research and how future studies might overcome them by carefully considering robust modeling approaches, adjusting for mediating and covariate effects, and choosing appropriate scales of analysis.

Modeling influenza seasonality in the tropics and subtropics

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.

Impact of biometeorological conditions and air pollution on influenza-like illnesses incidence in Warsaw

In order to assess the influence of atmospheric conditions and particulate matter (PM) on the seasonally varying incidence of influenza-like illnesses (ILI) in the capital of Poland-Warsaw, we analysed time series of ILI reported for the about 1.75 million residents in total and for different age groups in 288 approximately weekly periods, covering 6 years 2013-2018. Using Poisson regression, we predicted ILI by the Universal Thermal Climate Index (UTCI) as biometeorological indicator, and by PM2.5 and PM10, respectively, as air quality measures accounting for lagged effects spanning up to 3 weeks. Excess ILI incidence after adjusting for seasonal and annual trends was calculated by fitting generalized additive models. ILI morbidity increased with rising PM concentrations, for both PM2.5 and PM10, and with cooler atmospheric conditions as indicated by decreasing UTCI. While the PM effect focused on the actual reporting period, the atmospheric influence exhibited a more evenly distributed lagged effect pattern over the considered 3-week period. Though ILI incidence adjusted for population size significantly declined with age, age did not significantly modify the effect sizes of both PM and UTCI. These findings contribute to better understanding environmental conditionings of influenza seasonality in a temperate climate. This will be beneficial to forecasting future dynamics of ILI and to planning clinical and public health resources under climate change scenarios.