Seasonality of viral infections: mechanisms and unknowns

The role of human rhinovirus in COPD exacerbations in Abu Dhabi: molecular epidemiology and clinical significance

This study aimed to describe the molecular epidemiology and seasonality of human rhinovirus (HRV) in chronic obstructive pulmonary disease (COPD) and its association with COPD exacerbations in Abu Dhabi, the United Arab Emirates (UAE). Sputum specimens were collected for analysis from all COPD patients who visited a medical center from November 2021 to October 2022. The real-time quantitative polymerase chain reaction (qPCR) test was used to detect HRV. Of the 78 COPD patients included in the study, 58 (74%) patients presented with one or more exacerbation episodes. The incidence of COPD exacerbation peaked over the winter and substantially decreased during the summer. HRV positivity in patients during exacerbation (E1) was 11/58 (19%) and 15/58 (26%) two weeks after the exacerbation episode (E2). There was no significant difference in the HRV load in these patients. No statistically significant difference was observed in the detection of HRV during exacerbation compared to patients with stable COPD. This is the first study to assess the association between HRV detection by qPCR and COPD exacerbations in the UAE. The high sensitivity of the detection technology helped collect reliable epidemiologic data. Few studies have provided similar Middle East data. This study's pattern of COPD exacerbations and HRV detection parallels that of temperate countries. This information can help with future, more extensive surveillance of respiratory viruses in the UAE and the Middle East and their association with COPD exacerbations.

Simultaneous detection and characterization of common respiratory pathogens in wastewater through genomic sequencing

Genomic surveillance of SARS-CoV-2 has given insight into the evolution and epidemiology of the virus and its variant lineages during the COVID-19 pandemic. Expanding this approach to include a range of respiratory pathogens can better inform public health preparedness for potential outbreaks and epidemics. Here, we simultaneously sequenced 38 pathogens including influenza viruses, coronaviruses and bocaviruses, to examine the abundance and seasonality of respiratory pathogens in urban wastewater. We deployed a targeted bait capture method and short-read sequencing (Illumina Respiratory Virus Oligos Panel; RVOP) on composite wastewater samples from 8 wastewater treatment plants (WWTPs) and one associated hospital site. By combining seasonal sampling with whole genome sequencing, we were able to concurrently detect and characterise a range of common respiratory pathogens, including SARS-CoV-2, adenovirus and parainfluenza virus. We demonstrated that 38 respiratory pathogens can be detected at low abundances year-round, that hospital pathogen diversity is higher in winter vs. summer sampling events, and that significantly more viruses are detected in raw influent compared to treated effluent samples. Finally, we compared detection sensitivity of RT-qPCR vs. next generation sequencing for SARS-CoV-2, enteroviruses, influenza A/B, and respiratory syncytial viruses. We conclude that both should be used in combination; RT-qPCR allowed accurate quantification, whilst genomic sequencing detected pathogens at lower abundance. We demonstrate the valuable role of wastewater genomic surveillance and its contribution to the field of wastewater-based epidemiology, gaining rapid understanding of the seasonal presence and persistence for common respiratory pathogens. By simultaneously monitoring seasonal trends and early warning signs of many viruses circulating in communities, public health agencies can implement targeted prevention and rapid response plans.

Zoonotic spillover and extreme weather events drive the global outbreaks of airborne viral emerging infectious diseases

Outbreaks of airborne viral emerging infectious diseases (EIDs) cause an increasing burden on global public health, particularly with a backdrop of intensified climate change. However, infection sources and drivers for outbreaks of airborne viral EIDs remain unknown. Here, we aim to explore the driving mechanisms of outbreaks based on the one health perspective. Outbreak information for 20 types of airborne viral EIDs was collected from the Global Infectious Disease and Epidemiology Network database and a systematic literature review. Four statistically significant and high-risk spatiotemporal clusters for airborne viral EID outbreaks were identified globally using multivariate scan statistic tests. There were 112 outbreaks with clear infection sources, and zoonotic spillover was the most common source (95.54%, 107/112). Since 1970, the majority of outbreaks occurred in healthcare facilities (24.82%), followed by schools (17.93%) and animal-related settings (15.93%). Significant associations were detected between the number of earthquakes, storms, duration of floods, and airborne viral EIDs' outbreaks using a case-crossover study design and multivariable conditional logistic regression. These findings implied that zoonotic spillover and extreme weather events are driving global outbreaks of airborne viral EIDs, and targeted prevention and control measures should be made to reduce the airborne viral EIDs burden.

Intravital Imaging of the Human Cornea Reveals the Differential Effects of Season on Innate and Adaptive Immune Cell Morphodynamics

PURPOSE

Defining how the in vivo immune status of peripheral tissues is shaped by the external environment has remained a technical challenge. We recently developed Functional in vivo confocal microscopy (Fun-IVCM) for dynamic, longitudinal imaging of corneal immune cells in living humans. This study investigated the effect of seasonal-driven environmental factors on the morphodynamic features of human corneal immune cell subsets.

DESIGN

Longitudinal, observational clinical study.

PARTICIPANTS

Sixteen healthy participants (aged 18-40 years) attended 2 visits in distinct seasons in Melbourne, Australia (Visit 1, November-December 2021 [spring-summer]; Visit 2, April-June 2022 [autumn-winter]).

METHODS

Environmental data were collected over each period. Participants underwent ocular surface examinations and corneal Fun-IVCM (Heidelberg Engineering). Corneal scans were acquired at 5.5 ± 1.5-minute intervals for up to 5 time points. Time-lapse Fun-IVCM videos were created to analyze corneal immune cells, comprising epithelial T cells and dendritic cells (DCs), and stromal macrophages. Tear cytokines were analyzed using a multiplex bead-based immunoassay.

MAIN OUTCOME MEASURES

Difference in the density, morphology, and dynamic parameters of corneal immune cell subsets over the study periods.

RESULTS

Visit 1 was characterized by higher temperature, lower humidity, and higher air particulate and pollen levels compared with Visit 2. Clinical ocular surface parameters and the density of immune cell subsets were similar across visits. At Visit 1 , corneal epithelial DCs were larger, with a lower dendrite probing speed (0.38 ± 0.21 vs. 0.68 ± 0.33 μm/min; P < 0.001) relative to Visit 2; stromal macrophages were more circular and had less dynamic activity (Visit 1, 7.2 ± 1.9 vs. Visit 2, 10.3 ± 3.7 dancing index; P < 0.001). Corneal T cell morphodynamics were unchanged across periods. Basal tear levels of interleukin 2 and CXCL10 were relatively lower during spring-summer.

CONCLUSIONS

This study identifies that the in vivo morphodynamics of innate corneal immune cells (DCs, macrophages) are modified by environmental factors, but such effects are not evident for adaptive immune cells (T cells). The cornea is a potential in vivo window to investigate season-dependent environmental influences on the human immune system.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

A retrospective longitudinal study of adenovirus group F, norovirus GI and GII, rotavirus, and enterovirus nucleic acids in wastewater solids at two wastewater treatment plants: solid-liquid partitioning and relation to clinical testing data

Enteric infections are important causes of morbidity and mortality, yet clinical surveillance is limited. Wastewater-based epidemiology (WBE) has been used to study community circulation of individual enteric viruses and panels of respiratory diseases, but there is limited work studying the concurrent circulation of a suite of important enteric viruses. A retrospective WBE study was carried out at two wastewater treatment plants located in California, United States. Using digital droplet polymerase chain reaction (PCR), we measured concentrations of human adenovirus group F, enteroviruses, norovirus genogroups I and II, and rotavirus nucleic acids in wastewater solids two times per week for 26 months (n = 459 samples) between February 2021 and mid-April 2023. A novel probe-based PCR assay was developed and validated for adenovirus. We compared viral nucleic acid concentrations to positivity rates for viral infections from clinical specimens submitted to a local clinical laboratory to assess concordance between the data sets. We detected all viral targets in wastewater solids. At both wastewater treatment plants, human adenovirus group F and norovirus GII nucleic acids were detected at the highest concentrations (median concentrations greater than 105 copies/g), while rotavirus RNA was detected at the lowest concentrations (median on the order of 103 copies/g). Rotavirus, adenovirus group F, and norovirus nucleic acid concentrations were positively associated with clinical specimen positivity rates. Concentrations of tested viral nucleic acids exhibited complex associations with SARS-CoV-2 and other respiratory viral nucleic acids in wastewater, suggesting divergent transmission patterns.IMPORTANCEThis study provides evidence for the use of wastewater solids for the sensitive detection of enteric virus targets in wastewater-based epidemiology programs aimed to better understand the spread of enteric disease at a localized, community level without limitations associated with testing many individuals. Wastewater data can inform clinical, public health, and individual decision-making aimed to reduce the transmission of enteric disease.

Implications of vaccine non-specific effects on licensure of new vaccines

Immune memory was for a long time thought to be an exclusive feature of the adaptive immune system. Emerging evidence has shown that the innate immune system may exhibit memory which has been termed as trained immunity or innate immune memory. Trained immunity following vaccination may produce non-specific effects leading to reduction in morbidity and mortality from heterologous pathogens. This review looked at trained immunity as a mechanism for vaccine induced non-specific effects, mechanisms underlying trained immunity and known vaccine non-specific effects. A discussion is also made on the implications these vaccine non-specific effects may have on overall risk-benefit ratio evaluation by National Medicines Regulatory Authorities (NMRAs) during licensure of new vaccines. Epigenetic remodeling and "rewiring" of cellular metabolism in the innate immune cells especially monocytes, macrophages, and Natural Killer (NK) cells have been suggested to be the mechanisms underlying trained immunity. Trained immunity in other innate cells has largely remained elusive up to date. Non-specific effects have been extensively documented with Bacille Calmette-Guerin (BCG), measles vaccine and oral polio vaccine but it remains unclear if other vaccines may exhibit similar effects. All known vaccine non-specific effects have come from observations in epidemiological studies conducted post-vaccine licensure and roll out in target populations. It remains to be seen if early identification of non-specific effects especially those with protective benefits during the clinical development of new vaccines may contribute to the overall risk-benefit ratio evaluation during licensure by NMRAs.

Descriptive analysis to assess seasonal patterns of COVID-19 and influenza in low-income and middle-income countries in Asia, the Middle East and Latin America

OBJECTIVES

Understanding disease seasonality can help predict the occurrence of outbreaks and inform public health planning. Respiratory diseases typically follow seasonal patterns; however, knowledge regarding the seasonality of COVID-19 and its impact on the seasonality of influenza remains limited. The objective of this study was to provide more evidence to understand the circulation of SARS-CoV-2, the virus responsible for COVID-19, in an endemic scenario to guide potential preventive strategies.

DESIGN

In this study, a descriptive analysis was undertaken to describe seasonality trends and/or overlap between COVID-19 and influenza in 12 low-income and middle-income countries using Our World in Data and FluMart data sources. Plots of COVID-19 and influenza cases were analysed.

SETTING

Singapore, Thailand, Malaysia, the Philippines, Argentina, Brazil, Mexico, South Africa, Morocco, Bahrain, Qatar and Saudi Arabia.

OUTCOME MEASURES

COVID-19 cases and influenza cases.

RESULTS

No seasonal patterns of SARS-CoV-2 or SARS-CoV-2/influenza cocirculation were observed in most countries, even when considering the avian influenza pandemic period.

CONCLUSIONS

These results can inform public health strategies. The lack of observed seasonal behaviour highlights the importance of maintaining year-round vaccination rather than implementing seasonal campaigns. Further research investigating the influence of climate conditions, social behaviour and year-round preventive measures could be fundamental for shaping appropriate policies related to COVID-19 and respiratory viral disease control in low-income and middle-income countries as COVID-19 variant data and epidemiologic patterns accrue over time.

Common and Potential Emerging Foodborne Viruses: A Comprehensive Review

Human viruses and viruses from animals can cause illnesses in humans after the consumption of contaminated food or water. Contamination may occur during preparation by infected food handlers, during food production because of unsuitably controlled working conditions, or following the consumption of animal-based foods contaminated by a zoonotic virus. This review discussed the recent information available on the general and clinical characteristics of viruses, viral foodborne outbreaks and control strategies to prevent the viral contamination of food products and water. Viruses are responsible for the greatest number of illnesses from outbreaks caused by food, and risk assessment experts regard them as a high food safety priority. This concern is well founded, since a significant increase in viral foodborne outbreaks has occurred over the past 20 years. Norovirus, hepatitis A and E viruses, rotavirus, astrovirus, adenovirus, and sapovirus are the major common viruses associated with water or foodborne illness outbreaks. It is also suspected that many human viruses including Aichi virus, Nipah virus, tick-borne encephalitis virus, H5N1 avian influenza viruses, and coronaviruses (SARS-CoV-1, SARS-CoV-2 and MERS-CoV) also have the potential to be transmitted via food products. It is evident that the adoption of strict hygienic food processing measures from farm to table is required to prevent viruses from contaminating our food.

Seasonality and Climatic Factors Associated With Human Rhinovirus/Enterovirus Nasopharyngeal Sample Positivity on Oahu, Hawai'i, 2016-2019

INTRODUCTION

Globally, human rhinoviruses/enteroviruses (HRVs/ENTs), indistinguishable on many widely available molecular platforms, are among the leading causes of the common cold. Geographic and climatic factors impact the peak activity of these viruses. In temperate climates, the peak activity of HRV occurs during autumn and spring whereas that of ENT occurs during autumn and summer. Both viruses are thought to peak during the rainy season in tropical climates like Hawai'i; however, data remain limited. We describe HRV/ENT seasonality and evaluate the climatic factors associated with peak activity among respiratory viral samples processed on Oahu, Hawai'i.

MATERIALS AND METHODS

We conducted a retrospective analysis of all respiratory specimens submitted to Tripler Army Medical Center for multiplex polymerase chain reaction testing between May 2016 and May 2019. Among HRV/ENT-positive samples, we recorded the month and year of positivity. Summative monthly positive detection was calculated with peak months above the mean. Associations between temperature, precipitation levels, relative humidity, and wind speed by week and the number of positive samples for HRV/ENT were evaluated using Poisson regression. This analysis was conducted via IRB exempt protocol number 19R18.

RESULTS

During our study period, there were 7,143 nasopharyngeal respiratory samples sent for multiplex polymerase chain reaction testing, with 1,572 positive for HRV/ENT (22%). Nineteen percent of respiratory samples positive for HRV/ENT were additionally positive for one or more respiratory pathogens. The majority of HRV/ENT-positive samples arose from children < 5 years of age (n = 959, 61%). Peak months were February, March, May, August, November, and December. After controlling for lagged count and year, average wind speed was the only climatic factor significantly associated with HRV/ENT sample positivity.

CONCLUSIONS

The peak monthly activity of HRV/ENT was similar to temperate climates with the exception of peak activity in February. Unlike other tropical climates, lower wind speed was associated with increased weekly HRV/ENT positivity and should be further explored as a transmission factor. Our study contributes to understanding the annual variability of HRV/ENT activity in tropical environments, which can inform clinician expectations regarding respiratory viral symptomatology in this region.

Evaluating the impact of COVID-19 outbreak on hepatitis B and forecasting the epidemiological trend in mainland China: a causal analysis

BACKGROUND

It is uncertain how COVID-19 outbreak influences the hepatitis B epidemics. This study aims to evaluate the effects on hepatitis B owing to the COVID-19 outbreak and forecast the hepatitis B epidemiological trend in mainland China to speed up the course of the "End viral hepatitis Strategy".

METHODS

We estimated the causal impacts and created a forecast through adopting monthly notifications of hepatitis B each year from 2005 to 2020 in mainland China using the Bayesian structural time series (BSTS) method.

RESULTS

The hepatitis B epidemics fluctuates irregularly during the period 2005-2007(APC = 8.7, P = 0.246) and 2015-2020(APC = 1.7, P = 0.290), and there is a downturn (APC=-3.2, 95% CI -5.2 to -1.2, P = 0.006) from 2007 to 2015 in mainland China. The COVID-19 outbreak was found to have a monthly average reduction on the hepatitis B epidemics of 26% (95% CI 18-35%) within the first three months in 2020,17% (95% CI 7.7-26%) within the first six months in 2020, and 10% (95% CI19-22%) all year as a result of the COVID-19 outbreak, (probability of causal effect = 96.591%, P = 0.034) and the forecasts showed an upward trend from 2021 to 2025 (annual percentage change = 4.18, 95% CI 4.0 to 4.3, P < 0.001).

CONCLUSION

The COVID-19 has a positive effect on the decline of hepatitis B cases. And the potential of BSTS model to forecast the epidemiological trend of the hepatitis B can be applied in automatic public health policymaking in mainland China.

Seasonality of COVID-19 incidence in the United States

Background

The surges of Coronavirus Disease 2019 (COVID-19) appeared to follow a repeating pattern of COVID-19 outbreaks regardless of social distancing, mask mandates, and vaccination campaigns.

Objectives

This study aimed to investigate the seasonality of COVID-19 incidence in the United States of America (USA), and to delineate the dominant frequencies of the periodic patterns of the disease.

Methods

We characterized periodicity in COVID-19 incidences over the first three full seasonal years (March 2020 to March 2023) of the COVID-19 pandemic in the USA. We utilized a spectral analysis approach to find the naturally occurring dominant frequencies of oscillation in the incidence data using a Fast Fourier Transform (FFT) algorithm.

Results

Our study revealed four dominant peaks in the periodogram: the two most dominant peaks show a period of oscillation of 366 days and 146.4 days, while two smaller peaks indicate periods of 183 days and 122 days. The period of 366 days indicates that there is a single COVID-19 outbreak that occurs approximately once every year, which correlates with the dominant outbreak in the early/mid-winter months. The period of 146.4 days indicates approximately 3 peaks per year and matches well with each of the 3 annual outbreaks per year.

Conclusion

Our study revealed the predictable seasonality of COVID-19 outbreaks, which will guide public health preventative efforts to control future outbreaks. However, the methods used in this study cannot predict the amplitudes of the incidences in each outbreak: a multifactorial problem that involves complex environmental, social, and viral strain variables.

Rapid detection of gastrointestinal pathogens using a multiplex polymerase chain reaction gastrointestinal panel and its role in antimicrobial stewardship

OBJECTIVES

The FilmArray gastrointestinal panel (FAGIP) is widely used to detect infectious diarrhoea due to its outstanding sensitivity compared to conventional methods, but there is geographic variation, such as in the distribution of pathogens, among populations.

METHODS

This was a retrospective study that analysed patients with acute diarrhoea who underwent FAGIP tests from all age groups during 2022. We compared positive rates of FAGIP between paediatric (n = 245) and adult patients (n = 242) of different origins. The targeted therapy rate and antimicrobial agent use rate were also analysed.

RESULTS

Among the 487 stool samples evaluated, the overall, community-origin (CO), and nosocomial (NC) positivity rates of paediatric patients were significantly higher than those of adults (73.9 % vs. 43.0 %, p = 0.000; 76.2 % vs. 51.7 %, p = 0.000; 50.0 % vs. 19.7 %, p = 0.000). Salmonella was the most frequently detected pathogen (35.9 %) in children, while the predominant pathogen in adult patients was toxin A/B-genic Clostridioides difficile (13.2 %). There was a significantly lower antimicrobial agent use rate after FAGIP results were available (79.1 % vs. 64.5 %, p = 0.000) and a higher rate of targeted therapy towards C. difficile infection in adults than in children (84.4 % vs. 69.0 %, p = 0.011).

CONCLUSION

Paediatric diarrhoea patients showed higher positivity rates than adult patients. Application of FAGIP for acute diarrhoea might lower unnecessary antimicrobial use.

Frequency of respiratory virus-associated infection among children and adolescents from a tertiary-care hospital in Mexico City

Acute respiratory infections (ARIs) are a major cause of morbidity and mortality among children. The causative pathogens show geographic and seasonal variations. We retrospectively evaluated the frequency and seasonality of respiratory pathogens in children and adolescents (age: 0-19 years) with ARIs treated between January 1, 2021, and March 31, 2022, at a single center in Mexico. Out of 2400 patients, 1,603 were diagnosed with SARS-CoV-2 infection and 797 were diagnosed with other common respiratory pathogens (CRPs). Of the 797 patients, 632 were infected with one CRP and 165 with > 2 CRPs. Deaths occurred only in SARS-CoV-2-infected patients. Rhinovirus/Enterovirus, respiratory syncytial virus B, and parainfluenza virus 3 were the most prevalent in cases with single and multiple infections. CRP showed a high frequency between autumn and winter of 2021, with higher incidence of hospitalization compared to COVID-19. The main comorbidities were immunosuppression, cardiovascular disease (CD), and asthma. The frequency of CRPs showed a downward trend throughout the first half of 2021. CRPs increased in single- and co-infection cases between the fourth and fifth waves of COVID-19, probably due to decreased nonpharmaceutical interventions and changes in diagnostic tests. Age, cyanosis (symptom), and immunosuppression (comorbidity) were found to differentiate between SARS-CoV-2 infection and CRP infection.

The Immunoseasonal Theory of Psychiatric Disorders

Although the influence of the weather on the well-being and mental health of psychiatric patients has been widely seen, the relationships between various seasonal weather factors and depressive, manic, anxiety, and psychotic states have not been systematized in the literature. The current article describes the seasonal changes in weather-related immune responses and their impact on the development of episodes of depression, mania, psychosis, and anxiety, highlighting the T-helper 1 (Th1) and Th2 immune balance as their potential trigger. In autumn-winter depression, the hyperactivation of the Th1 system, possibly by microbial/airborne pathogens, may lead to the inflammatory inhibition of prefrontal activity and the subcortical centers responsible for mood, drive, and motivation. Depressive mood periods are present in most people suffering from schizophrenia. In the spring and summertime, when the compensating anti-Th1 property of the Th2 immune system is activated, it decreases the Th1 response. In individuals immunogenetically susceptible to psychosis and mania, the inhibition of Th1 by the Th2 system may be excessive and lead to Th2-related frontal and subcortical hyperactivation and subsequent psychosis. In people suffering from bipolar disorder, hyperintense changes in white matter may be responsible for the partial activation of subcortical areas, preventing full paranoid psychosis. Thus, psychosis may be mood-congruent in affective disorders.

Potential for urban warming to postpone overwintering dormancy of temperate mosquitoes

Cities are generally hotter than surrounding rural areas due to the Urban Heat Island (UHI) effect. These increases in temperature advance plant and animal phenology, development, and reproduction in the spring. However, research determining how increased temperatures affect the seasonal physiology of animals in the fall has been limited. The Northern house mosquito, Culex pipiens, is abundant in cities and transmits several pathogens including West Nile virus. Females of this species enter a state of developmental arrest, or reproductive diapause, in response to short days and low temperatures during autumn. Diapausing females halt reproduction and blood-feeding, and instead accumulate fat and seek sheltered overwintering sites. We found that exposure to increased temperatures in the lab that mimic the UHI effect induced ovarian development and blood-feeding, and that females exposed to these temperatures were as fecund as non-diapausing mosquitoes. We also found that females exposed to higher temperatures had lower survival rates in winter-like conditions, despite having accumulated equivalent lipid reserves relative to their diapausing congeners. These data suggest that urban warming may inhibit diapause initiation in the autumn, thereby extending the active biting season of temperate mosquitoes.

Within-host modeling to measure dynamics of antibody responses after natural infection or vaccination: A systematic review

BACKGROUND

Within-host models describe the dynamics of immune cells when encountering a pathogen, and how these dynamics can lead to an individual-specific immune response. This systematic review aims to summarize which within-host methodology has been used to study and quantify antibody kinetics after infection or vaccination. In particular, we focus on data-driven and theory-driven mechanistic models.

MATERIALS

PubMed and Web of Science databases were used to identify eligible papers published until May 2022. Eligible publications included those studying mathematical models that measure antibody kinetics as the primary outcome (ranging from phenomenological to mechanistic models).

RESULTS

We identified 78 eligible publications, of which 8 relied on an Ordinary Differential Equations (ODEs)-based modelling approach to describe antibody kinetics after vaccination, and 12 studies used such models in the context of humoral immunity induced by natural infection. Mechanistic modeling studies were summarized in terms of type of study, sample size, measurements collected, antibody half-life, compartments and parameters included, inferential or analytical method, and model selection.

CONCLUSIONS

Despite the importance of investigating antibody kinetics and underlying mechanisms of (waning of) the humoral immunity, few publications explicitly account for this in a mathematical model. In particular, most research focuses on phenomenological rather than mechanistic models. The limited information on the age groups or other risk factors that might impact antibody kinetics, as well as a lack of experimental or observational data remain important concerns regarding the interpretation of mathematical modeling results. We reviewed the similarities between the kinetics following vaccination and infection, emphasising that it may be worth translating some features from one setting to another. However, we also stress that some biological mechanisms need to be distinguished. We found that data-driven mechanistic models tend to be more simplistic, and theory-driven approaches lack representative data to validate model results.

Disentangling the rhythms of human activity in the built environment for airborne transmission risk: An analysis of large-scale mobility data

Background

Since the outset of the COVID-19 pandemic, substantial public attention has focused on the role of seasonality in impacting transmission. Misconceptions have relied on seasonal mediation of respiratory diseases driven solely by environmental variables. However, seasonality is expected to be driven by host social behavior, particularly in highly susceptible populations. A key gap in understanding the role of social behavior in respiratory disease seasonality is our incomplete understanding of the seasonality of indoor human activity.

Methods

We leverage a novel data stream on human mobility to characterize activity in indoor versus outdoor environments in the United States. We use an observational mobile app-based location dataset encompassing over 5 million locations nationally. We classify locations as primarily indoor (e.g. stores, offices) or outdoor (e.g. playgrounds, farmers markets), disentangling location-specific visits into indoor and outdoor, to arrive at a fine-scale measure of indoor to outdoor human activity across time and space.

Results

We find the proportion of indoor to outdoor activity during a baseline year is seasonal, peaking in winter months. The measure displays a latitudinal gradient with stronger seasonality at northern latitudes and an additional summer peak in southern latitudes. We statistically fit this baseline indoor-outdoor activity measure to inform the incorporation of this complex empirical pattern into infectious disease dynamic models. However, we find that the disruption of the COVID-19 pandemic caused these patterns to shift significantly from baseline and the empirical patterns are necessary to predict spatiotemporal heterogeneity in disease dynamics.

Conclusions

Our work empirically characterizes, for the first time, the seasonality of human social behavior at a large scale with a high spatiotemporal resolutio and provides a parsimonious parameterization of seasonal behavior that can be included in infectious disease dynamics models. We provide critical evidence and methods necessary to inform the public health of seasonal and pandemic respiratory pathogens and improve our understanding of the relationship between the physical environment and infection risk in the context of global change.

Funding

Research reported in this publication was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R01GM123007.

The interplay between circadian clock and viral infections: A molecular perspective

The circadian clock influences almost every aspect of mammalian behavioral, physiological and metabolic processes. Being a hierarchical network, the circadian clock is driven by the central clock in the brain and is composed of several peripheral tissue-specific clocks. It orchestrates and synchronizes the daily oscillations of biological processes to the environment. Several pathological events are influenced by time and seasonal variations and as such implicate the clock in pathogenesis mechanisms. In context with viral infections, circadian rhythmicity is closely associated with host susceptibility, disease severity, and pharmacokinetics and efficacies of antivirals and vaccines. Leveraging the circadian molecular mechanism insights has increased our understanding of clock infection biology and proposes new avenues for viral diagnostics and therapeutics. In this chapter, we address the molecular interplay between the circadian clock and viral infections and discuss the importance of chronotherapy as a complementary approach to conventional medicines, emphasizing the significance of virus-clock studies.

Multiple waves of COVID-19: a pathway model approach

A generalized pathway model, with time-dependent parameters, is applied to describe the mortality curves of the COVID-19 disease for several countries that exhibit multiple waves of infections. The pathway approach adopted here is formulated explicitly in time, in the sense that the model's growth rate for the number of deaths or infections is written as an explicit function of time, rather than in terms of the cumulative quantity itself. This allows for a direct fit of the model to daily data (new deaths or new cases) without the need of any integration. The model is applied to COVID-19 mortality curves for ten selected countries and found to be in very good agreement with the data for all cases considered. From the fitted theoretical curves for a given location, relevant epidemiological information can be extracted, such as the starting and peak dates for each successive wave. It is argued that obtaining reliable estimates for such characteristic points is important for studying the effectiveness of interventions and the possible negative impact of their relaxation, as it allows for a direct comparison of the time of adoption/relaxation of control measures with the peaks and troughs of the epidemic curve.

Associations between indoor relative humidity and global COVID-19 outcomes

Globally, the spread and severity of COVID-19 have been distinctly non-uniform. Seasonality was suggested as a contributor to regional variability, but the relationship between weather and COVID-19 remains unclear and the focus of attention has been on outdoor conditions. Because humans spend most of their time indoors and because most transmission occurs indoors, we here, instead, investigate the hypothesis that indoor climate-particularly indoor relative humidity (RH)-may be the more relevant modulator of outbreaks. To study this association, we combined population-based COVID-19 statistics and meteorological measurements from 121 countries. We rigorously processed epidemiological data to reduce bias, then developed and experimentally validated a computational workflow to estimate indoor conditions based on outdoor weather data and standard indoor comfort conditions. Our comprehensive analysis shows robust and systematic relationships between regional outbreaks and indoor RH. In particular, we found intermediate RH (40-60%) to be robustly associated with better COVID-19 outbreak outcomes (versus RH < 40% or >60%). Together, these results suggest that indoor conditions, particularly indoor RH, modulate the spread and severity of COVID-19 outbreaks.

Worldwide Evolution of Vaccinable and Nonvaccinable Viral Skin Infections: Google Trends Analysis

BACKGROUND

Most common viral skin infections are not reportable conditions. Studying the population dynamics of these viral epidemics using traditional field methods is costly and time-consuming, especially over wide geographical areas.

OBJECTIVE

This study aimed to explore the evolution, seasonality, and distribution of vaccinable and nonvaccinable viral skin infections through an analysis of Google Trends.

METHODS

Worldwide search trends from January 2004 through May 2021 for viral skin infections were extracted from Google Trends, quantified, and analyzed.

RESULTS

Time series decomposition showed that the total search term volume for warts; zoster; roseola; measles; hand, foot, and mouth disease (HFMD); varicella; and rubella increased worldwide over the study period, whereas the interest for Pityriasis rosea and herpes simplex decreased. Internet searches for HFMD, varicella, and measles exhibited the highest seasonal patterns. The interest for measles and rubella was more pronounced in African countries, whereas the interest for HFMD and roseola was more pronounced in East Asia.

CONCLUSIONS

Harnessing data generated by web searches may increase the efficacy of traditional surveillance systems and strengthens the suspicion that the incidence of some vaccinable viral skin infections such as varicella, measles, and rubella may be globally increasing, whereas the incidence of common nonvaccinable skin infections remains stable.

Natural products as Zika antivirals

Zika virus (ZIKV) is an arbovirus belonging to the flavivirus genus and is transmitted in Aedes mosquito vectors. Since its discovery in humans in 1952 in Uganda, ZIKV has been responsible for many outbreaks in South America, Africa, and Asia. Patients infected with ZIKV are usually asymptomatic; mild symptoms include fever, joint and muscle pain, and fatigue. However, severe infections may have neurological implications, such as Guillain-Barré syndrome and fetal microcephaly. To date, there are no existing approved therapeutic drugs or vaccines against ZIKV infections; treatments mainly target the symptoms of infection. Preventive measures against mosquito breeding are the main strategy for limiting the spread of the virus. Antiviral drug research for the treatment of ZIKV infection has been rapidly developing, with many drug candidates emerging from drug repurposing studies, and compound screening. In particular, several studies have demonstrated the potential of natural products as antivirals for ZIKV infection. Hence, this paper will review recent advances in natural products in ZIKV antiviral drug discovery.

Environmental factors linked to hospital admissions in young children due to acute viral lower respiratory infections: A bidirectional case-crossover study

OBJECTIVE

This study evaluated the association of the short-term exposure to environmental factors (relative humidity, temperature, NO₂, SO₂, O₃, PM₁₀, and CO) with hospital admissions due to acute viral lower respiratory infections (ALRI) in children under two years before the COVID-19 era.

METHODS

We performed a bidirectional case-crossover study in 30,445 children with ALRI under two years of age in the Spanish Minimum Basic Data Set (MBDS) from 2013 to 2015. Environmental data were obtained from Spain's State Meteorological Agency (AEMET). The association was assessed by conditional logistic regression.

RESULTS

Lower temperature one week before the day of the event (hospital admission) (q-value = 0.012) and higher relative humidity one week (q-value = 0.003) and two weeks (q-value<0.001) before the day of the event were related to a higher odds of hospital admissions. Higher NO₂ levels two weeks before the event were associated with hospital admissions (q-value<0.001). Moreover, higher concentrations on the day of the event for SO₂ (compared to lag time of 1-week (q-value = 0.026) and 2-weeks (q-value<0.001)), O₃ (compared to lag time of 3-days (q-value<0.001), 1-week (q-value<0.001), and 2-weeks (q-value<0.001)), and PM₁₀ (compared to lag time of 2-weeks (q-value<0.001)) were related to an increased odds of hospital admissions for viral ALRI.

CONCLUSION

Short-term exposure to environmental factors (climatic conditions and ambient air contaminants) was linked to a higher likelihood of hospital admissions due to ALRI. Our findings emphasize the importance of monitoring environmental factors to assess the odds of ALRI hospital admissions and plan public health resources.

Empirical assessment of alternative methods for identifying seasonality in observational healthcare data

Background

Seasonality classification is a well-known and important part of time series analysis. Understanding the seasonality of a biological event can contribute to an improved understanding of its causes and help guide appropriate responses. Observational data, however, are not comprised of biological events, but timestamped diagnosis codes the combination of which (along with additional requirements) are used as proxies for biological events. As there exist different methods for determining the seasonality of a time series, it is necessary to know if these methods exhibit concordance. In this study we seek to determine the concordance of these methods by applying them to time series derived from diagnosis codes in observational data residing in databases that vary in size, type, and provenance.

Methods

We compared 8 methods for determining the seasonality of a time series at three levels of significance (0.01, 0.05, and 0.1), against 10 observational health databases. We evaluated 61,467 time series at each level of significance, totaling 184,401 evaluations.

Results

Across all databases and levels of significance, concordance ranged from 20.2 to 40.2%. Across all databases and levels of significance, the proportion of time series classified seasonal ranged from 4.9 to 88.3%. For each database and level of significance, we computed the difference between the maximum and minimum proportion of time series classified seasonal by all methods. The median within-database difference was 54.8, 34.7, and 39.8%, for p < 0.01, 0.05, and 0.1, respectively.

Conclusion

Methods of binary seasonality classification when applied to time series derived from diagnosis codes in observational health data produce inconsistent results. The methods exhibit considerable discord within all databases, implying that the discord is a result of the difference between the methods themselves and not due to the choice of database. The results indicate that researchers relying on automated methods to assess the seasonality of time series derived from diagnosis codes in observational data should be aware that the methods are not interchangeable and thus the choice of method can affect the generalizability of their work. Seasonality determination is highly dependent on the method chosen.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01652-3.

Seasonal airway microbiome and transcriptome interactions promote childhood asthma exacerbations

BACKGROUND

Seasonal variation in respiratory illnesses and exacerbations in pediatric populations with asthma is well described, though whether upper airway microbes play season-specific roles in these events is unknown.

OBJECTIVE

We hypothesized that nasal microbiota composition is seasonally dynamic and that discrete microbe-host interactions modify risk of asthma exacerbation in a season-specific manner.

METHODS

Repeated nasal samples from children with exacerbation-prone asthma collected during periods of respiratory health (baseline; n = 181 samples) or first captured respiratory illness (n = 97) across all seasons, underwent bacterial (16S ribosomal RNA gene) and fungal (internal transcribed spacer region 2) biomarker sequencing. Virus detection was performed by multiplex PCR. Paired nasal transcriptome data were examined for seasonal dynamics and integrative analyses.

RESULTS

Upper airway bacterial and fungal microbiota and rhinovirus detection exhibited significant seasonal dynamics. In seasonally adjusted analysis, variation in both baseline and respiratory illness microbiota related to subsequent exacerbation. Specifically, in the fall, when respiratory illness and exacerbation events were most frequent, several Moraxella and Haemophilus members were enriched both in virus-positive respiratory illnesses and those that progressed to exacerbations. The abundance of 2 discrete bacterial networks, characteristically comprising either Streptococcus or Staphylococcus, exhibited opposing interactions with an exacerbation-associated SMAD3 nasal epithelial transcriptional module to significantly increase the odds of subsequent exacerbation (odds ratio = 14.7, 95% confidence interval = 1.50-144, P = .02; odds ratio = 39.17, 95% confidence interval = 2.44-626, P = .008, respectively).

CONCLUSIONS

Upper airway microbiomes covary with season and with seasonal trends in respiratory illnesses and asthma exacerbations. Seasonally adjusted analyses reveal specific bacteria-host interactions that significantly increase risk of asthma exacerbation in these children.

COVIDHunter: COVID-19 Pandemic Wave Prediction and Mitigation via Seasonality Aware Modeling

Early detection and isolation of COVID-19 patients are essential for successful implementation of mitigation strategies and eventually curbing the disease spread. With a limited number of daily COVID-19 tests performed in every country, simulating the COVID-19 spread along with the potential effect of each mitigation strategy currently remains one of the most effective ways in managing the healthcare system and guiding policy-makers. We introduce COVIDHunter, a flexible and accurate COVID-19 outbreak simulation model that evaluates the current mitigation measures that are applied to a region, predicts COVID-19 statistics (the daily number of cases, hospitalizations, and deaths), and provides suggestions on what strength the upcoming mitigation measure should be. The key idea of COVIDHunter is to quantify the spread of COVID-19 in a geographical region by simulating the average number of new infections caused by an infected person considering the effect of external factors, such as environmental conditions (e.g., climate, temperature, humidity), different variants of concern, vaccination rate, and mitigation measures. Using Switzerland as a case study, COVIDHunter estimates that we are experiencing a deadly new wave that will peak on 26 January 2022, which is very similar in numbers to the wave we had in February 2020. The policy-makers have only one choice that is to increase the strength of the currently applied mitigation measures for 30 days. Unlike existing models, the COVIDHunter model accurately monitors and predicts the daily number of cases, hospitalizations, and deaths due to COVID-19. Our model is flexible to configure and simple to modify for modeling different scenarios under different environmental conditions and mitigation measures. We release the source code of the COVIDHunter implementation at https://github.com/CMU-SAFARI/COVIDHunter and show how to flexibly configure our model for any scenario and easily extend it for different measures and conditions than we account for.

Survey of Anti-Pathogen Antibody Levels in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Infectious pathogens are implicated in the etiology of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) because of the occurrence of outbreaks of the disease. While a number of different infectious agents have been associated with the onset of ME/CFS, the identity of a specific organism has been difficult to determine in individual cases. The aim of our study is to survey ME/CFS subjects for evidence of an infectious trigger and/or evidence of immune dysregulation via serological testing of plasma samples for antibodies to 122 different pathogen antigens. Immune profiles were compared to age-, sex-, and BMI-matched controls to provide a basis for comparison. Antibody levels to individual antigens surveyed in this study do not implicate any one of the pathogens in ME/CFS, nor do they rule out common pathogens that frequently infect the US population. However, our results revealed sex-based differences in steady-state humoral immunity, both within the ME/CFS cohort and when compared to trends seen in the healthy control cohort.

Respiratory viruses dynamics and interactions: ten years of surveillance in central Europe

Background

Lower respiratory tract infections are among the main causes of death. Although there are many respiratory viruses, diagnostic efforts are focused mainly on influenza. The Respiratory Viruses Network (RespVir) collects infection data, primarily from German university hospitals, for a high diversity of infections by respiratory pathogens. In this study, we computationally analysed a subset of the RespVir database, covering 217,150 samples tested for 17 different viral pathogens in the time span from 2010 to 2019.

Methods

We calculated the prevalence of 17 respiratory viruses, analysed their seasonality patterns using information-theoretic measures and agglomerative clustering, and analysed their propensity for dual infection using a new metric dubbed average coinfection exclusion score (ACES).

Results

After initial data pre-processing, we retained 206,814 samples, corresponding to 1,408,657 performed tests. We found that Influenza viruses were reported for almost the half of all infections and that they exhibited the highest degree of seasonality. Coinfections of viruses are frequent; the most prevalent coinfection was rhinovirus/bocavirus and most of the virus pairs had a positive ACES indicating a tendency to exclude each other regarding infection.

Conclusions

The analysis of respiratory viruses dynamics in monoinfection and coinfection contributes to the prevention, diagnostic, treatment, and development of new therapeutics. Data obtained from multiplex testing is fundamental for this analysis and should be prioritized over single pathogen testing.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13555-5.

Association between Meteorological Factors and Mumps and Models for Prediction in Chongqing, China

(1) Background: To explore whether meteorological factors have an impact on the prevalence of mumps, and to make a short−term prediction of the case number of mumps in Chongqing. (2) Methods: K−means clustering algorithm was used to divide the monthly mumps cases of each year into the high and low case number clusters, and Student t−test was applied for difference analysis. The cross−correlation function (CCF) was used to evaluate the correlation between the meteorological factors and mumps, and an ARIMAX model was constructed by additionally incorporating meteorological factors as exogenous variables in the ARIMA model, and a short−term prediction was conducted for mumps in Chongqing, evaluated by MAE, RMSE. (3) Results: All the meteorological factors were significantly different (p < 0.05), except for the relative humidity between the high and low case number clusters. The CCF and ARIMAX model showed that monthly precipitation, temperature, relative humidity and wind velocity were associated with mumps, and there were significant lag effects. The ARIMAX model could accurately predict mumps in the short term, and the prediction errors (MAE, RMSE) were lower than those of the ARIMA model. (4) Conclusions: Meteorological factors can affect the occurrence of mumps, and the ARIMAX model can effectively predict the incidence trend of mumps in Chongqing, which can provide an early warning for relevant departments.

Changes in temporal properties for epidemics of notifiable infectious diseases in China during the COVID-19 epidemic: population-based surveillance study

BACKGROUND

The COVID-19 was first reported in 2019, and the Chinese government immediately carried out stringent and effective control measures in response to the epidemics.

OBJECTIVE

These non-pharmaceutical interventions may have impacted incidences of other infectious diseases as well. Potential explanations underlying this reduction, however, are not clear. Hence, in this study, we aimed to study the influence of the COVID-19 prevention policies on other infectious diseases (mainly class B infectious diseases) in China.

METHODS

The time-series datasets between 2017 and 2021 for 23 notifiable infectious diseases were extracted from public datasets from the National Health Commission of China. Several indices (peak and trough amplitude, infection selectivity, preferred time to outbreak, oscillatory strength) of each infectious disease were calculated before and after the COVID-19 outbreak.

RESULTS

We found that the prevention and control policies for COVID-19 had a strong significant reduction effect on outbreaks of other infectious diseases. A clear event-related trough (ERT) was observed after the outbreak of COVID-19 under the strict control policies, and its decreasing amplitude is related to the infection selectivity and preferred outbreak time of the disease before the COVID-19. We also calculated the oscillatory strength before and after the COVID-19 outbreak and found that it is significantly stronger before the COVID-19 outbreak, and does not correlate with the trough amplitude.

CONCLUSIONS

Our results directly demonstrate that prevention policies for the COVID-19 have immediate additional benefits for controlling most class B infectious diseases, and several factors (infection selectivity, preferred outbreak time) may have contributed to the reduction of outbreaks. This study may guide the implementation of non-pharmaceutical interventions to control a wider range of infectious diseases.

CLINICALTRIAL

Viral transmissibility of SARS-CoV-2 accelerates in the winter, similarly to influenza epidemics

The transmissibility of SARS-CoV-2 is anticipated to increase in the winter because of increased viral survival in cold damp air and thus would exacerbate viral spread in community. Analysis to capture the seasonal trend is needed to be prepared for future epidemics. We compared regression models for the 5-week case prior to each epidemic peak week for both the COVID-19 and influenza epidemics in winter and summer. The weekly case increase ratio was compared, using non-paired t tests between seasons. In order to test the robustness of seasonal transmission patterns, the normalized weekly case numbers of COVID-19 and influenza case rates of all seasons were assessed in a combined quadratic regression analysis. In winter, the weekly case increase ratio accelerated before epidemic peaks, similarly, for both COVID-19 and influenza. The quadratic regression models of weekly cases were observed to be convex curves in the winter and concave curves in the spring/summer for both COVID-19 and influenza. A significant increase of case increase ratio (3.19 [95%CI:0.01-6.37, P = .049]) of the COVID-19 and influenza epidemics was observed in winter as compared to spring/summer before the epidemic peak. The epidemic of COVID-19 was found to mirror that of influenza, suggesting a strong underlying seasonal transmissibility. Influenza epidemics can potentially be a useful reference for the COVID-19 epidemics.

Modeling and Preliminary Analysis of the Impact of Meteorological Conditions on the COVID-19 Epidemic

Since the COVID-19 epidemic outbreak at the end of 2019, many studies regarding the impact of meteorological factors on the attack have been carried out, and inconsistent conclusions have been reached, indicating the issue's complexity. To more accurately identify the effects and patterns of meteorological factors on the epidemic, we used a combination of logistic regression (LgR) and partial least squares regression (PLSR) modeling to investigate the possible effects of common meteorological factors, including air temperature, relative humidity, wind speed, and surface pressure, on the transmission of the COVID-19 epidemic. Our analysis shows that: (1) Different countries and regions show spatial heterogeneity in the number of diagnosed patients of the epidemic, but this can be roughly classified into three types: "continuous growth", "staged shock", and "finished"; (2) Air temperature is the most significant meteorological factor influencing the transmission of the COVID-19 epidemic. Except for a few areas, regional air temperature changes and the transmission of the epidemic show a significant positive correlation, i.e., an increase in air temperature is conducive to the spread of the epidemic; (3) In different countries and regions studied, wind speed, relative humidity, and surface pressure show inconsistent correlation (and significance) with the number of diagnosed cases but show some regularity.

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.

Non-COVID-19 respiratory viral infection

Implemented control measures brought about by the coronavirus disease 2019 (COVID-19) pandemic have changed the prevalence of other respiratory viruses, often relegating them to a secondary plan. However, it must not be forgotten that a diverse group of viruses, including other human coronaviruses, rhinoviruses, respiratory syncytial virus, human metapneumoviruses, parainfluenza and influenza, continue to be responsible for a large burden of disease. In fact, they are among the most common causes of acute upper and lower respiratory tract infections globally. Viral respiratory infections can be categorised in several ways, including by clinical syndrome or aetiological agent. We describe their clinical spectrum. Distinctive imaging features, advances in microbiological diagnosis and treatment of severe forms are also discussed.

Non-COVID-19 respiratory viral infections are a major burden of disease. Emerging molecular-based detection methods and knowledge of viral lower respiratory tract infections’ distinctive features improve diagnosis, treatment and outcome of severe forms.https://bit.ly/3qMqk3T

Clinical spectrum, disease course and management outcome of post-fever retinitis cases: experience from a tertiary eye institute in central India

Purpose

To report a series of five cases with retinitis following episodes of febrile illness, its evaluation, management and outcome.

Method

Retrospective, consecutive case series of five patients presenting with acute retinitis, following a febrile illness.

Results

The retinal lesions had a sudden onset with rapid evolution, preceded by a febrile episode within one month of presentation, in all cases. Extensive serology and PCR testing were non-contributory toward identifying the etiology and guiding therapy. Systemic corticosteroid therapy was effective in hastening the resolution of lesions.

Conclusion

Post-fever retinitis appears to be a distinct clinical form of acute hemorrhagic non-necrotizing retinitis without a uniformly identifiable cause, and some evidence pointing toward a para-infectious etiology secondary to flu-like illnesses. With an unusual morphological presentation and annual seasonal patterns in the endemic areas, it is important to differentiate this entity, from other forms of infectious retinitis, before initiating corticosteroid therapy.

Effect of the COVID-19 Lockdown on Asthma Biological Rhythms

Asthma has a striking temporal character, in which time-of-day, patient age, and season each influence disease activity. The extent to which rhythms in asthma activity reflect exposure to specific disease triggers remains unclear. In this study, we examined how virus mitigation strategies enacted during the COVID-19 pandemic ("lockdown measures") affected rhythms in asthma clinical activity in children. To this end, we retrospectively analyzed asthma clinical presentations in children aged <18 years to our regional academic medical center, comparing 4 years of medical records prior to COVID-19 lockdown measures with the 12 months immediately after the institution of such measures. We correlated these data to positive viral test results, febrile seizures, and allergic clinical surrogates (allergic reaction visits and Emergency Department [ED] antihistamine prescriptions, respectively) over the same time frame. In the 12 months following the institution of the COVID-19 lockdown, positivity rates for common respiratory viruses dropped by 70.2% and ED visits for asthma among children dropped by 62% compared to pre-COVID years. Lockdown suppressed seasonal variation in positive viral tests and asthma ED visits, while diurnal rhythms in asthma visits were unchanged. Asthma seasonality correlated most strongly with rhinovirus positivity both before and after the institution of COVID lockdown measures. Altogether, our data support a causal role for viruses in driving seasonal variability in asthma exacerbations in children.

Temporal and Gene Reassortment Analysis of Influenza C Virus Outbreaks in Hong Kong, SAR, China

From 2014 to week 07/2020 the Centre for Health Protection in Hong Kong conducted screening for influenza C virus (ICV). A retrospective analysis of ICV detections to week 26/2019 revealed persistent low-level circulation with outbreaks occurring biennially in the winters of 2015 to 2016 and 2017 to 2018 (R. S. Daniels et al., J Virol 94:e01051-20, 2020, https://doi.org/10.1128/JVI.01051-20). Here, we report on an outbreak occurring in 2019 to 2020, reinforcing the observation of biennial seasonality in Hong Kong. All three outbreaks occurred in similar time frames, were subsequently dwarfed by seasonal epidemics of influenza types A and B, and were caused by similar proportions of C/Kanagawa/1/76 (K)-lineage and C/São Paulo/378/82 S1- and S2-sublineage viruses. Ongoing genetic drift was observed in all genes, with some evidence of amino acid substitution in the hemagglutinin-esterase-fusion (HEF) glycoprotein possibly associated with antigenic drift. A total of 61 ICV genomes covering the three outbreaks were analyzed for reassortment, and 9 different reassortant constellations were identified, 1 K-lineage, 4 S1-sublineage, and 4 S2-sublineage, with 6 of these being identified first in the 2019-1920 outbreak (2 S2-lineage and 4 S1-lineage). The roles that virus interference/enhancement, ICV persistent infection, genome evolution, and reassortment might play in the observed seasonality of ICV in Hong Kong are discussed. IMPORTANCE Influenza C virus (ICV) infection of humans is common, with the great majority of people being infected during childhood, though reinfection can occur throughout life. While infection normally results in "cold-like" symptoms, severe disease cases have been reported in recent years. However, knowledge of ICV is limited due to poor systematic surveillance and an inability to propagate the virus in large amounts in the laboratory. Following recent systematic surveillance in Hong Kong SAR, China, and direct ICV gene sequencing from clinical specimens, a 2-year cycle of disease outbreaks (epidemics) has been identified, with gene mixing playing a significant role in ICV evolution. Studies like those reported here are key to developing an understanding of the impact of influenza C virus infection in humans, notably where comorbidities exist and severe respiratory disease can develop.

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.

Phage strategies facilitate bacterial coexistence under environmental variability

Bacterial communities are often exposed to temporal variations in resource availability, which exceed bacterial generation times and thereby affect bacterial coexistence. Bacterial population dynamics are also shaped by bacteriophages, which are a main cause of bacterial mortality. Several strategies are proposed in the literature to describe infections by phages, such as "Killing the Winner", "Piggyback the loser" (PtL) or "Piggyback the Winner" (PtW). The two temperate phage strategies PtL and PtW are defined by a change from lytic to lysogenic infection when the host density changes, from high to low or from low to high, respectively. To date, the occurrence of different phage strategies and their response to environmental variability is poorly understood. In our study, we developed a microbial trophic network model using ordinary differential equations (ODEs) and performed 'in silico' experiments. To model the switch from the lysogenic to the lytic cycle, we modified the lysis rate of infected bacteria and their growth was turned on or off using a density-dependent switching point. We addressed whether and how the different phage strategies facilitate bacteria coexistence competing for limiting resources. We also studied the impact of a fluctuating resource inflow to evaluate the response of the different phage strategies to environmental variability. Our results show that the viral shunt (i.e. nutrient release after bacterial lysis) leads to an enrichment of the system. This enrichment enables bacterial coexistence at lower resource concentrations. We were able to show that an established, purely lytic model leads to stable bacterial coexistence despite fluctuating resources. Both temperate phage models differ in their coexistence patterns. The model of PtW yields stable bacterial coexistence at a limited range of resource supply and is most sensitive to resource fluctuations. Interestingly, the purely lytic phage strategy and PtW both result in stable bacteria coexistence at oligotrophic conditions. The PtL model facilitates stable bacterial coexistence over a large range of stable and fluctuating resource inflow. An increase in bacterial growth rate results in a higher resilience to resource variability for the PtL and the lytic infection model. We propose that both temperate phage strategies represent different mechanisms of phages coping with environmental variability. Our study demonstrates how phage strategies can maintain bacterial coexistence in constant and fluctuating environments.

Seasonal UV exposure and vitamin D: association with the dynamics of COVID-19 transmission in Europe

Several recent studies have demonstrated that low plasma 25(OH) vitamin D levels are associated with the risk of COVID‐19 infection. The primary source of vitamin D production in humans is environmental UV radiation. In many viral respiratory diseases, peak infection rates are observed during winter due to reduced UV exposure and low temperatures. In Europe, the second wave of COVID‐19 began early in the winter of 2020. Investigating the impact of seasonal temperature and UV exposure on COVID‐19 transmission could thus aid in prevention and intervention. As such, we first performed a comprehensive meta‐analysis of all related published literature based on the association between vitamin D and COVID‐19, which supported the hypothesis that the low vitamin D level is a critical risk factor for COVID‐19 infection. Next, to understand the potential impact of seasonal UV and temperature levels on COVID‐19 cases, we analyzed meteorological data and daily COVID‐19 cases per million in the populations of 26 European countries. We observed that low temperature, UV index, and cloud‐free vitamin D UV dose (UVDVF) levels are negatively correlated with COVID‐19 prevalence in Europe. Furthermore, a distributed lag nonlinear model was used to assess the nonlinear delayed effects of individual seasonal factors on COVID‐19 cases. Such analysis highlighted the significantly delayed impact of UVDVF on the cumulative relative risk of COVID‐19 infection. The findings of this study suggest that low UV exposure can affect the required production of vitamin D in the body, which substantially influences the dynamics of COVID‐19 transmission and severity.

The incidence of mumps in Taiwan and its association with the meteorological parameters: An observational study

Mumps is an acute and common childhood disease caused by paramyxovirus. It has been reported that the occurrence of mumps is influenced by seasonality. However, the role of meteorological variables in the incidence of mumps remains unclear. The purpose of this study was to explore the relationship between meteorological factors and the incidence of mumps infection. Poisson regression analysis was used to study the relationship between weather variability and the incidence of mumps in Taiwan. Between 2012 and 2018, 5459 cases of mumps cases were reported to the Centers for Disease Control, Taiwan (Taiwan CDC). The occurrence of mumps virus infections revealed significant seasonality in the spring and summer seasons in Taiwan. The incidence of mumps virus infections began to increase at temperatures of 15°C and started to decline if the temperature was higher than 29°C (r2 = 0.387, P = .008). Similarly, the number of mumps cases began to increase at a relative humidity of 65% to 69% (r2 = 0.838, P < .029). The number of mumps cases was positively associated with temperature and relative humidity during the period preceding the infection. This study showed that the occurrence of mumps is significantly associated with increasing temperature and relative humidity in Taiwan. Therefore, these factors could be regarded as early warning signals and indicate the need to strengthen the intervention and prevention of mumps.

Respiratory Viruses in Acute Exacerbations of Bronchiectasis

BACKGROUND

Bacterial infections are well known factors underlying acute exacerbations in bronchiectasis. However, viral infections may also contribute to acute exacerbations. We aimed to assess the rate of viral detection in acute exacerbations of bronchiectasis, and the associated clinical factors.

METHODS

Diagnostic tests for viral and bacterial etiologies were performed in 792 patients with bronchiectasis who visited the emergency room or the respiratory care inpatient unit in a tertiary referral center in South Korea. All patients were diagnosed with bronchiectasis by chest computerized tomography and were prescribed antibiotics for a minimum of 3 days.

RESULTS

Viral pathogens were detected in 202 of the 792 enrolled patients (25.5%). The most common viral pathogen isolated was influenza A virus (24.8%), followed by rhinovirus (22.4%), influenza B virus (9.8%), respiratory syncytial virus B (8.9%), and human metapneumovirus (6.1%). In 145 patients, a viral, but not bacterial, pathogen was detected, whereas no pathogens were found in 443 patients with exacerbations. Multivariable analysis revealed that female sex and chronic heart disease as a comorbidity were positively associated with viral detection in acute exacerbations of patients with bronchiectasis, whereas the presence of radiographic infiltration was negatively associated.

CONCLUSION

Respiratory viruses were identified in approximately 25% of the acute exacerbations observed among patients with bronchiectasis. Of the viruses detected, influenza viruses and rhinovirus made up over 50%. More attention to viruses as possible causative pathogens for acute deteriorating symptoms in patients with bronchiectasis is warranted.

The Impact of Weather and Air Pollution on Viral Infection and Disease Outcome Among Pediatric Pneumonia Patients in Chongqing, China, from 2009 to 2018: A Prospective Observational Study

BACKGROUND

For pediatric pneumonia, the meteorological and air pollution indicators have been frequently investigated for their association with viral circulation but not for their impact on disease severity.

METHODS

We performed a 10-year prospective, observational study in 1 hospital in Chongqing, China, to recruit children with pneumonia. Eight commonly seen respiratory viruses were tested. Autoregressive distributed lag (ADL) and random forest (RF) models were used to fit monthly detection rates of each virus at the population level and to predict the possibility of severe pneumonia at the individual level, respectively.

RESULTS

Between 2009 and 2018, 6611 pediatric pneumonia patients were included, and 4846 (73.3%) tested positive for at least 1 respiratory virus. The patient median age was 9 months (interquartile range, 4‒20). ADL models demonstrated a decent fitting of detection rates of R2 > 0.7 for respiratory syncytial virus, human rhinovirus, parainfluenza virus, and human metapneumovirus. Based on the RF models, the area under the curve for host-related factors alone was 0.88 (95% confidence interval [CI], .87‒.89) and 0.86 (95% CI, .85‒.88) for meteorological and air pollution indicators alone and 0.62 (95% CI, .60‒.63) for viral infections alone. The final model indicated that 9 weather and air pollution indicators were important determinants of severe pneumonia, with a relative contribution of 62.53%, which is significantly higher than respiratory viral infections (7.36%).

CONCLUSIONS

Meteorological and air pollution predictors contributed more to severe pneumonia in children than did respiratory viruses. These meteorological data could help predict times when children would be at increased risk for severe pneumonia and when interventions, such as reducing outdoor activities, may be warranted.

Changes in Seasonal Respiratory Illnesses in the United States During the Coronavirus Disease 2019 (COVID-19) Pandemic

Background

Respiratory tract infections are common, often seasonal, and caused by multiple pathogens. We assessed whether seasonal respiratory illness patterns changed during the COVID-19 pandemic.

Methods

We categorized emergency department (ED) visits reported to the National Syndromic Surveillance Program according to chief complaints and diagnosis codes, excluding visits with diagnosed SARS-CoV-2 infections. For each week during March 1, 2020 through December 26, 2020 (“pandemic period”), we compared the proportion of ED visits in each respiratory category with the proportion of visits in that category during the corresponding weeks of 2017–2019 (“pre-pandemic period”). We analyzed positivity of respiratory viral tests from two independent clinical laboratories.

Results

During March 2020, cough, shortness of breath, and influenza-like illness accounted for twice as many ED visits compared with the pre-pandemic period. During the last four months of 2020, all respiratory conditions, except shortness of breath, accounted for a smaller proportion of ED visits than during the pre-pandemic period. Percent positivity for influenza virus, respiratory syncytial virus, human parainfluenza virus, adenoviruses, and human metapneumovirus were lower in 2020 than 2019. Although test volume decreased, percent positivity was higher for rhinovirus/enterovirus during the final weeks of 2020 compared with 2019; with ED visits similar to the pre-pandemic period.

Discussion

Broad reductions in respiratory test positivity and respiratory emergency department visits (excluding COVID-19) occurred during 2020. Interventions for mitigating spread of SARS-CoV-2 likely also reduced transmission of other pathogens. Timely surveillance is needed to understand community health threats, particularly when current trends deviate from seasonal norms.

A novel geo-hierarchical population mobility model for spatial spreading of resurgent epidemics

Computational models for large, resurgent epidemics are recognized as a crucial tool for predicting the spread of infectious diseases. It is widely agreed, that such models can be augmented with realistic multiscale population models and by incorporating human mobility patterns. Nevertheless, a large proportion of recent studies, aimed at better understanding global epidemics, like influenza, measles, H1N1, SARS, and COVID-19, underestimate the role of heterogeneous mixing in populations, characterized by strong social structures and geography. Motivated by the reduced tractability of studies employing homogeneous mixing, which make conclusions hard to deduce, we propose a new, very fine-grained model incorporating the spatial distribution of population into geographical settlements, with a hierarchical organization down to the level of households (inside which we assume homogeneous mixing). In addition, population is organized heterogeneously outside households, and we model the movement of individuals using travel distance and frequency parameters for inter- and intra-settlement movement. Discrete event simulation, employing an adapted SIR model with relapse, reproduces important qualitative characteristics of real epidemics, like high variation in size and temporal heterogeneity (e.g., waves), that are challenging to reproduce and to quantify with existing measures. Our results pinpoint an important aspect, that epidemic size is more sensitive to the increase in distance of travel, rather that the frequency of travel. Finally, we discuss implications for the control of epidemics by integrating human mobility restrictions, as well as progressive vaccination of individuals.

Respiratory virus surveillance in Canada during the COVID-19 pandemic: An epidemiological analysis of the effectiveness of pandemic-related public health measures in reducing seasonal respiratory viruses test positivity

Background

Various public health measures have been implemented globally to counter the coronavirus disease 2019 (COVID-19) pandemic. The purpose of this study was to evaluate respiratory virus surveillance data to determine the effectiveness of such interventions in reducing transmission of seasonal respiratory viruses.

Method

We retrospectively analysed data from the Respiratory Virus Detection Surveillance System in Canada, before and during the COVID-19 pandemic, by interrupted time series regression.

Results

The national level of infection with seasonal respiratory viruses, which generally does not necessitate quarantine or contact screening, was greatly reduced after Canada imposed physical distancing and other quarantine measures. The 2019–2020 influenza season ended earlier than it did in the previous year. The influenza virus was replaced by rhinovirus/enterovirus or parainfluenza virus in the previous year, with the overall test positivity remaining at approximately 35%. However, during the 2019–2020 post-influenza period, the overall test positivity of respiratory viruses during the COVID-19 was still low (7.2%). Moreover, the 2020–2021 influenza season had not occurred by the end of February 2021.

Conclusion

Respiratory virus surveillance data may provide real-world evidence of the effectiveness of implemented public health interventions during the current and future pandemics.

The Enterovirus Theory of Disease Etiology in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Critical Review

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex, multi-system disease whose etiological basis has not been established. Enteroviruses (EVs) as a cause of ME/CFS have sometimes been proposed, as they are known agents of acute respiratory and gastrointestinal infections that may persist in secondary infection sites, including the central nervous system, muscle, and heart. To date, the body of research that has investigated enterovirus infections in relation to ME/CFS supports an increased prevalence of chronic or persistent enteroviral infections in ME/CFS patient cohorts than in healthy individuals. Nevertheless, inconsistent results have fueled a decline in related studies over the past two decades. This review covers the aspects of ME/CFS pathophysiology that are consistent with a chronic enterovirus infection and critically reviews methodologies and approaches used in past EV-related ME/CFS studies. We describe the prior sample types that were interrogated, the methods used and the limitations to the approaches that were chosen. We conclude that there is considerable evidence that prior outbreaks of ME/CFS were caused by one or more enterovirus groups. Furthermore, we find that the methods used in prior studies were inadequate to rule out the presence of chronic enteroviral infections in individuals with ME/CFS. Given the possibility that such infections could be contributing to morbidity and preventing recovery, further studies of appropriate biological samples with the latest molecular methods are urgently needed.