Question: How does the coronavirus differ from seasonal flu?

Title: Experience of a screening centre for influenza A/H1N1: the first 50 days. Content: BACKGROUND The authors' emergency department (ED) served as Singapore's screening centre for influenza H1N1 cases. The aims of the study were to describe their screening experience and to compare clinical and laboratory features of H1N1 versus seasonal flu cases. METHODOLOGY The authors conducted a prospective observational study on consecutive patients aged 16 years and above presenting to a busy, urban ED for H1N1 screening over 50 days. Clinical, laboratory, radiological and PCR data were collected from the hospital electronic databases. Primary outcomes were proportions of confirmed H1N1 cases and their distribution of clinical, laboratory and radiological features. Secondary outcomes were comparison of clinical and laboratory features of H1N1 versus seasonal flu cases. Data were analysed using descriptive statistics and univariate analysis was used to compare factors between the two groups. A p value <0.05 was considered statistically significant. RESULTS 1205 patients were screened. 31 (2.6%) and 133 (11%) of them had H1N1 and seasonal flu infections, respectively. The two groups had similar symptoms. There were six clinical and two laboratory features with statistically significant differences between H1N1 and seasonal flu cases. Clinical factors were travel or contact history, median age, respiratory rate, diastolic blood pressure and length of hospital stay. Laboratory factors were median platelet and lymphocyte counts. CONCLUSIONS The authors report their experience as the nation's H1N1 screening centre. They identified factors that were different between H1N1 and seasonal flu cases. Future research is needed to elucidate if and how this information can be used as a screening tool for H1N1.

Title: Understanding Coronavirus Content: Since the identification of the first cases of the coronavirus in December 2019 in Wuhan, China, there has been a significant amount of confusion regarding the origin and spread of the so-called 'coronavirus', officially named SARS-CoV-2, and the cause of the disease COVID-19 Conflicting messages from the media and officials across different countries and organizations, the abundance of disparate sources of information, unfounded conspiracy theories on the origins of the newly emerging virus and the inconsistent public health measures across different countries, have all served to increase the level of anxiety in the population Where did the virus come from? How is it transmitted? How does it cause disease? Is it like flu? What is a pandemic? What can we do to stop its spread? Written by a leading expert, this concise and accessible introduction provides answers to the most common questions surrounding coronavirus for a general audience

Title: Pollen Explains Flu-Like and COVID-19 Seasonality Content: Current models for flu-like epidemics insufficiently explain multi-cycle seasonality. Meteorological factors alone do not predict seasonality, given substantial climate differences between countries that are subject to flu-like epidemics or COVID-19. Pollen is documented to be antiviral and allergenic, play a role in immuno-activation, and seems to create a bio-aerosol lowering the reproduction number of flu-like viruses. Therefore, we hypothesize that pollen may explain the seasonality of flu-like epidemics including COVID-19. We tested the Pollen-Flu Seasonality Theory for 2016-2020 flu-like seasons, including COVID-19, in The Netherlands with its 17 million inhabitants. We combined changes in flu-like incidence per 100K/Dutch citizens (code: ILI) with weekly pollen counts and meteorological data for the same period. Finally, a discrete, predictive model is tested using pollen and meteorological threshold values displaying inhibitory effects on flu-like incidence. We found a highly significant inverse association of r(224)= -.38 between pollen and changes in flu-like incidence corrected for incubation period, confirming our expectations for the 2019/2020 COVID-19 season. We found that our predictive model has the highest inverse correlation with changes in flu-like incidence of r(222) = -.48 (p < .001) when pollen thresholds of 610 total pollen grains/m3 per week, 120 allergenic pollen grains/m3 per week, and a solar radiation threshold of 510 J/cm2 are passed. The passing of at least the pollen thresholds, preludes the beginning and end of flu-like seasons. Solar radiation is a supportive factor, temperature makes no difference, and relative humidity associates even with flu-like incidence increases. We conclude that pollen is a predictor for the inverse seasonality of flu-like epidemics including COVID-19, and solar radiation is a co-inhibitor. The observed seasonality of COVID-19 during Spring, suggests that COVID-19 may revive in The Netherlands after week 33, the start being preceded by the relative absence of pollen, and follows standard pollen-flu seasonality patterns.

Title: Modelling the Extremes of Seasonal Viruses and Hospital Congestion: The Example of Flu in a Swiss Hospital Content: Viruses causing flu or milder coronavirus colds are often referred to as"seasonal viruses"as they tend to subside in warmer months. In other words, meteorological conditions tend to impact the activity of viruses, and this information can be exploited for the operational management of hospitals. In this study, we use three years of daily data from one of the biggest hospitals in Switzerland and focus on modelling the extremes of hospital visits from patients showing flu-like symptoms and the number of positive cases of flu. We propose employing a discrete Generalized Pareto distribution for the number of positive and negative cases, and a Generalized Pareto distribution for the odds of positive cases. Our modelling framework allows for the parameters of these distributions to be linked to covariate effects, and for outlying observations to be dealt with via a robust estimation approach. Because meteorological conditions may vary over time, we use meteorological and not calendar variations to explain hospital charge extremes, and our empirical findings highlight their significance. We propose a measure of hospital congestion and a related tool to estimate the resulting CaRe (Charge-at-Risk-estimation) under different meteorological conditions. The relevant numerical computations can be easily carried out using the freely available GJRM R package. The introduced approach could be applied to several types of seasonal disease data such as those derived from the new virus SARS-CoV-2 and its COVID-19 disease which is at the moment wreaking havoc worldwide. The empirical effectiveness of the proposed method is assessed through a simulation study.

Title: The utility of preemptive mass influenza vaccination in controlling a sars outbreak during flu season. Content: During flu season, respiratory infections can cause non-specific influenza-like-illnesses (ILIs) in up to one-half of the general population. If a future SARS outbreak were to coincide with flu season, it would become exceptionally difficult to distinguish SARS rapidly and accurately from other ILIs, given the non-specific clinical presentation of SARS and the current lack of a widely available, rapid, diagnostic test. We construct a deterministic compartmental model to examine the potential impact of preemptive mass influenza vaccination on SARS containment during a hypothetical SARS outbreak coinciding with a peak flu season. Our model was developed based upon the events of the 2003 SARS outbreak in Toronto, Canada. The relationship of different vaccination rates for influenza and the corresponding required quarantine rates for individuals who are exposed to SARS was analyzed and simulated under different assumptions. The study revealed that a campaign of mass influenza vaccination prior to the onset of flu season could aid the containment of a future SARS outbreak by decreasing the total number of persons with ILIs presenting to the health-care system, and consequently decreasing nosocomial transmission of SARS in persons under investigation for the disease.

Title: Development and verification of real-time PCR assay for identification of viral agents causing acute respiratory infections in human beings Content: A multiplex polymerase chain reaction (PCR) for identification of four viruses causing acute respiratory diseases in human beings was developed. The analytical sensitivity of developed RT-PCR for identification of adenovirus, respiratory-syncytial virus, flu viruses types A and B, and actual subtypes of type A flu virus (seasonal and pandemic variants H1N1, seasonal H3N2, and viruses of bird flu that are pathogenic to human beings H5 and H7) was 1 × 10(3) genome equivalents per milliliter. Diagnostic sensitivity for flu virus type A and B, and also subtypes H1 (seasonal H1N1, pandemic variant of H1N1 of year 2009), H3, H5 was 1 × 10(3)–10(4) viral particles per milliliter. The method developed has high specificity and does not have positive signal in experiments with DNA/cDNA of human beings and viral DNA. We have studied 50 samples using the developed set. Etiology was defined in 33 samples.

Title: Monitoring Influenza Activity in the United States: A Comparison of Traditional Surveillance Systems with Google Flu Trends Content: BACKGROUND: Google Flu Trends was developed to estimate US influenza-like illness (ILI) rates from internet searches; however ILI does not necessarily correlate with actual influenza virus infections. METHODS AND FINDINGS: Influenza activity data from 2003–04 through 2007–08 were obtained from three US surveillance systems: Google Flu Trends, CDC Outpatient ILI Surveillance Network (CDC ILI Surveillance), and US Influenza Virologic Surveillance System (CDC Virus Surveillance). Pearson's correlation coefficients with 95% confidence intervals (95% CI) were calculated to compare surveillance data. An analysis was performed to investigate outlier observations and determine the extent to which they affected the correlations between surveillance data. Pearson's correlation coefficient describing Google Flu Trends and CDC Virus Surveillance over the study period was 0.72 (95% CI: 0.64, 0.79). The correlation between CDC ILI Surveillance and CDC Virus Surveillance over the same period was 0.85 (95% CI: 0.81, 0.89). Most of the outlier observations in both comparisons were from the 2003–04 influenza season. Exclusion of the outlier observations did not substantially improve the correlation between Google Flu Trends and CDC Virus Surveillance (0.82; 95% CI: 0.76, 0.87) or CDC ILI Surveillance and CDC Virus Surveillance (0.86; 95%CI: 0.82, 0.90). CONCLUSIONS: This analysis demonstrates that while Google Flu Trends is highly correlated with rates of ILI, it has a lower correlation with surveillance for laboratory-confirmed influenza. Most of the outlier observations occurred during the 2003–04 influenza season that was characterized by early and intense influenza activity, which potentially altered health care seeking behavior, physician testing practices, and internet search behavior.

Title: Public views of the uk media and government reaction to the 2009 swine flu pandemic Content: BACKGROUND: The first cases of influenza A/H1N1 (swine flu) were confirmed in the UK on 27th April 2009, after a novel virus first identified in Mexico rapidly evolved into a pandemic. The swine flu outbreak was the first pandemic in more than 40 years and for many, their first encounter with a major influenza outbreak. This study examines public understandings of the pandemic, exploring how people deciphered the threat and perceived they could control the risks. METHODS: Purposive sampling was used to recruit seventy three people (61 women and 12 men) to take part in 14 focus group discussions around the time of the second wave in swine flu cases. RESULTS: These discussions showed that there was little evidence of the public over-reacting, that people believed the threat of contracting swine flu was inevitable, and that they assessed their own self-efficacy for protecting against it to be low. Respondents assessed a greater risk to their health from the vaccine than from the disease. Such findings could have led to apathy about following the UK Governments recommended health protective behaviours, and a sub-optimal level of vaccine uptake. More generally, people were confused about the difference between seasonal influenza and swine flu and their vaccines. CONCLUSIONS: This research suggests a gap in public understandings which could hinder attempts to communicate about novel flu viruses in the future. There was general support for the government's handling of the pandemic, although its public awareness campaign was deemed ineffectual as few people changed their current hand hygiene practices. There was less support for the media who were deemed to have over-reported the swine flu pandemic.

Title: Forecasting the 2013–2014 Influenza Season Using Wikipedia Content: Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are applied to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed.

Title: Are dental schools adequately preparing dental students to face outbreaks of infectious diseases such as COVID‐19? Content: The recent 2019‐novel coronavirus (2019‐nCoV, also known as SARS‐CoV‐2) has caused >2,622,571 confirmed cases of coronavirus disease 2019 (COVID‐19) in >185 countries, and >182,359 deaths globally. More than 9000 healthcare workers have also been infected by 2019‐nCoV. Prior to the present pandemic of COVID‐19, there have been multiple large‐scale epidemics and pandemics of other viral respiratory infections, such as seasonal flu, Spanish flu (H1N1), severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and others. Dental professionals are at an increased risk for contracting these viruses from dental patients, as dental practice involves face‐to‐face communication with the patients and frequent exposure to saliva, blood, and other body fluids. Dental education can play an important role in the training of dentists, helping them to adopt adequate knowledge and attitudes related to infection control measures. The current dental curriculum does not cover infection control adequately, especially from airborne pathogens. Infection control education needs to be included in the dental curriculum itself, and students should be trained adequately to protect them and prevent the infection from disseminating even before they see their first patient.

Title: Are dental schools adequately preparing dental students to face outbreaks of infectious diseases such as COVID-19? Content: The recent 2019-novel coronavirus (2019-nCoV, also known as SARS-CoV-2) has caused >2,622,571 confirmed cases of coronavirus disease 2019 (COVID-19) in >185 countries, and >182,359 deaths globally. More than 9000 healthcare workers have also been infected by 2019-nCoV. Prior to the present pandemic of COVID-19, there have been multiple large-scale epidemics and pandemics of other viral respiratory infections, such as seasonal flu, Spanish flu (H1N1), severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and others. Dental professionals are at an increased risk for contracting these viruses from dental patients, as dental practice involves face-to-face communication with the patients and frequent exposure to saliva, blood, and other body fluids. Dental education can play an important role in the training of dentists, helping them to adopt adequate knowledge and attitudes related to infection control measures. The current dental curriculum does not cover infection control adequately, especially from airborne pathogens. Infection control education needs to be included in the dental curriculum itself, and students should be trained adequately to protect them and prevent the infection from disseminating even before they see their first patient.

Title: Environmental factors and seasonal influenza onset in Okayama city, Japan: case-crossover study. Content: Seasonal influenza infection is a major challenge in public health. The term "seasonal influenza" refers to the typical increase in the number of influenza patients in the winter season in temperature zones. However, it is not clear how environmental factors within a single flu season affect influenza infection in a human population. Therefore, we evaluated the effects of temperature and humidity in the 2006-7 flu season on the onset of seasonal influenza using a case-crossover study. We targeted patients who attended one pediatric clinic in Okayama city, Japan and who were diagnosed as being infected with the seasonal influenza virus. Using 2 references (time-stratified and symmetric bidirectional design), we estimated the effects of average temperature and relative humidity from the onset day (lag0) to 10 days before (lag10). The total number of subjects was 419, and their onset days ranged from 26 December 2006 to 30 April 2007. While the onset was significantly associated with lower temperature, relative humidity was not related. In particular, temperatures before the 3-day incubation period had higher-magnitude odds ratios. For example, the odds ratio and 95% confidence interval for average temperature at time lag 8 was 1.12 (1.08-1.17) per 1.0℃ decrease. Low environmental temperature significantly increased the risk of seasonal influenza onset within the 2006-7 winter season.

Title: Subsequent waves of viral pandemics, a hint for the future course of the SARS-CoV-2 pandemic. Content: Background It is unknown if the SARS-CoV-2 pandemic will have a second wave. We analysed published data of five influenza pandemics (such as the Spanish Flu and the Swine Flu) and the SARS-CoV-1 pandemic to describe whether there were subsequent waves and how they differed. Methods We reanalysed literature and WHO reports on SARS-CoV-1 and literature on five influenza pandemics. We report frequencies of second and third waves, wave heights, wavelengths and time between subsequent waves. From this, we estimated peak-to-peak ratios to compare the wave heights, and wave-length-to-wave-length ratios to compare the wavelengths differences in days. Furthermore, we analysed the seasonality of the wave peaks and the time between the peak values of two waves. Results Second waves, the Spanish Flu excluded, were usually about the same height and length as first waves and were observed in 93% of the 57 described epidemic events of influenza pandemics and in 42% of the 19 epidemic events of the SARS-CoV-1 pandemic. Third waves occurred in 54% of the 28 influenza and in 11% of the 19 SARS-CoV-1 epidemic events. Third waves, the Spanish Flu excluded, usually peaked higher than second waves with a peak-to-peak ratio of 0.5. Conclusion While influenza epidemics are usually accompanied by 2nd waves, this is only the case in the minority of SARS-Cov1 epidemics.

Title: Initial psychological responses to Influenza A, H1N1 ("Swine flu") Content: BACKGROUND: The outbreak of the pandemic flu, Influenza A H1N1 (Swine Flu) in early 2009, provided a major challenge to health services around the world. Previous pandemics have led to stockpiling of goods, the victimisation of particular population groups, and the cancellation of travel and the boycotting of particular foods (e.g. pork). We examined initial behavioural and attitudinal responses towards Influenza A, H1N1 ("Swine flu") in the six days following the WHO pandemic alert level 5, and regional differences in these responses. METHODS: 328 respondents completed a cross-sectional Internet or paper-based questionnaire study in Malaysia (N = 180) or Europe (N = 148). Measures assessed changes in transport usage, purchase of preparatory goods for a pandemic, perceived risk groups, indicators of anxiety, assessed estimated mortality rates for seasonal flu, effectiveness of seasonal flu vaccination, and changes in pork consumption RESULTS: 26% of the respondents were 'very concerned' about being a flu victim (42% Malaysians, 5% Europeans, p < .001). 36% reported reduced public transport use (48% Malaysia, 22% Europe, p < .001), 39% flight cancellations (56% Malaysia, 17% Europe, p < .001). 8% had purchased preparatory materials (e.g. face masks: 8% Malaysia, 7% Europe), 41% Malaysia (15% Europe) intended to do so (p < .001). 63% of Europeans, 19% of Malaysians had discussed the pandemic with friends (p < .001). Groups seen as at 'high risk' of infection included the immune compromised (mentioned by 87% respondents), pig farmers (70%), elderly (57%), prostitutes/highly sexually active (53%), and the homeless (53%). In data collected only in Europe, 64% greatly underestimated the mortality rates of seasonal flu, 26% believed seasonal flu vaccination gave protection against swine flu. 7% had reduced/stopped eating pork. 3% had purchased anti-viral drugs for use at home, while 32% intended to do so if the pandemic worsened. CONCLUSION: Initial responses to Influenza A show large regional differences in anxiety, with Malaysians more anxious and more likely to reduce travel and to buy masks and food. Discussions with family and friends may reinforce existing anxiety levels. Particular groups (homosexuals, prostitutes, the homeless) are perceived as at greater risk, potentially leading to increased prejudice during a pandemic. Europeans underestimated mortality of seasonal flu, and require more information about the protection given by seasonal flu inoculation.

Title: ORBiT: Oak Ridge biosurveillance toolkit for public health dynamics Content: BACKGROUND: The digitization of health-related information through electronic health records (EHR) and electronic healthcare reimbursement claims and the continued growth of self-reported health information through social media provides both tremendous opportunities and challenges in developing effective biosurveillance tools. With novel emerging infectious diseases being reported across different parts of the world, there is a need to build systems that can track, monitor and report such events in a timely manner. Further, it is also important to identify susceptible geographic regions and populations where emerging diseases may have a significant impact. METHODS: In this paper, we present an overview of Oak Ridge Biosurveillance Toolkit (ORBiT), which we have developed specifically to address data analytic challenges in the realm of public health surveillance. In particular, ORBiT provides an extensible environment to pull together diverse, large-scale datasets and analyze them to identify spatial and temporal patterns for various biosurveillance-related tasks. RESULTS: We demonstrate the utility of ORBiT in automatically extracting a small number of spatial and temporal patterns during the 2009-2010 pandemic H1N1 flu season using claims data. These patterns provide quantitative insights into the dynamics of how the pandemic flu spread across different parts of the country. We discovered that the claims data exhibits multi-scale patterns from which we could identify a small number of states in the United States (US) that act as "bridge regions" contributing to one or more specific influenza spread patterns. Similar to previous studies, the patterns show that the south-eastern regions of the US were widely affected by the H1N1 flu pandemic. Several of these south-eastern states act as bridge regions, which connect the north-east and central US in terms of flu occurrences. CONCLUSIONS: These quantitative insights show how the claims data combined with novel analytical techniques can provide important information to decision makers when an epidemic spreads throughout the country. Taken together ORBiT provides a scalable and extensible platform for public health surveillance.

Title: Influenza species and subtypes circulation among hospitalized patients in Laleh hospital during two influenza seasonal (2016-2017 and 2017-2018) using a multiplex Real Time-Polymerase Chain Reaction Content: The introduction of polymerase chain reaction (PCR) techniques has improved the detection of respiratory viruses, particularly with the use of multiplex real-time technique with the capability of simultaneous detection of various pathogens in a single reaction. The aim of this study was to apply the above technology for the diagnosis of influenza infections and at the same time to differentiate between common flu species between hospitalized patients in Laleh hospital (Iran) between two flu seasons (2016-2017 and 2017-2018). Different respiratory specimens were collected from 540 patients from a period of December 2016 to May 2018 and were sent to the laboratory for molecular diagnosis. RNAs were extracted and subsequently, a multiplex real time PCR identifying flu A, flu B and typing flu A (H1N1) was carried out. The mean age of patients was 47.54±23.96. 216 (40%) and 321 (60%) of subjects were male and female, respectively. 219 out of 540 (40.5%) were positive for influenza infection including flu A (n=97, 44.3%), flu A (H1N1) (n=45, 20.7%) and flu B (n=77, 35%). Flu A was the dominant species on 2016-2017 and flu B was the major species on 2017-2018. Flu A (H1N1) was comparable in both time periods. Flu infections were most frequently diagnosed in age groups 21-40. Flu-positive patients suffered more from body pain and sore throat than flunegative patients with significant statistical difference (P values <0.001). The mean duration of hospitalization was shorter for flu-positive patients (P value = 0.016). Application of multiplex real time PCR could facilitate the influenza diagnosis in a short period of time, benefiting patients from exclusion of bacterial infections and avoiding unnecessary antibiotic therapy. Influenza diagnosis was not achieved in up to 60% of flu-like respiratory infections, suggesting the potential benefit of adopting the same methodology for assessing the involvement of other viral or/and bacterial pathogens in those patients.

Title: Pollen likely seasonal factor in inhibiting flu-like epidemics. A Dutch study into the inverse relation between pollen counts, hay fever and flu-like incidence 2016-2019 Content: There is uncertainty if current models for the Covid-19 pandemic should already take into account seasonality. That is because current environmental factors do not provide a powerful explanation of such seasonality, especially given climate differences between countries with moderate climates. It is hypothesized that one major factor is overlooked: pollen count. Pollen are documented to invoke strong immune responses and might create an environmental factor that makes it more difficult for flu-like viruses to survive outside a host. This Dutch study confirms that there is a (highly) significant inverse correlation between pollen count and weekly changes in medical flu consults, and that there is a highly significant inverse correlation between hay fever incidence, as measured by prescribed medication revenues, and weekly flu consults. This supports the idea that pollen are a direct or indirect factor in the seasonality of flu-like epidemics. If seasonality will be observed during the covid-19 spread as well, it is not unlikely that pollen play a role.

Title: Incidence and seasonality of respiratory viruses causing acute respiratory infections in the Northern United Arab Emirates Content: BACKGROUND: The data on the seasonality of respiratory viruses helps to ensure the optimal vaccination period and to monitor the possible outbreaks of variant type. OBJECTIVES: This study was designed to describe the molecular epidemiology and seasonality of acute respiratory infection (ARI)‐related respiratory viruses in the United Arab Emirates (UAE). METHODS: Both upper and lower respiratory specimens were collected for the analysis from all the patients who visited the Sheikh Khalifa Specialty Hospital (SKSH) with ARI for over 2 years. The multiplex real‐time reverse transcription polymerase chain reaction (rRT‐PCR) test was used to detect respiratory viruses, which include human adenovirus, influenza virus (FLU) A and B, respiratory syncytial virus, parainfluenza viruses, human rhinovirus (HRV), human metapneumovirus, human enterovirus, human coronavirus, and human bocavirus. RESULTS: A total of 1,362 respiratory samples were collected from 733 (53.8%) male and 629 (46.2%) female patients with ARI who visited the SKSH between November 2015 and February 2018. The rRT‐PCR test revealed an overall positivity rate of 37.2% (507/1362). The positive rate increased during winter; it was highest in December and lowest in September. FLU was the most frequently detected virus (273/1362 [20.0%]), followed by human rhinovirus (146/1362 [10.7%]). The FLU positivity rate showed two peaks, which occurred in August and December. The peak‐to‐low ratio for FLU was 2.26 (95% confidence interval: 1.52‐3.35). CONCLUSIONS: The pattern of FLU in the UAE parallels to that of temperate countries. The trend of the small peak of FLU in the summer suggests a possibility of semi‐seasonal pattern in the UAE.

Title: Pollen likely seasonal factor in inhibiting flu-like epidemics. A Dutch study into the inverse relation between pollen counts, hay fever and flu-like incidence 2016–2019 Content: Abstract There is uncertainty if current models for the Covid-19 pandemic should already take into account seasonality. That is because current environmental factors do not provide a powerful explanation of such seasonality, especially given climate differences between countries with moderate climates. It is hypothesized that one major factor is overlooked: pollen count. Pollen are documented to invoke strong immune responses and might create an environmental factor that makes it more difficult for flu-like viruses to survive outside a host. This Dutch study confirms that there is a (highly) significant inverse correlation between pollen count and weekly changes in medical flu consults, and that there is a highly significant inverse correlation between hay fever incidence, as measured by prescribed medication revenues, and weekly flu consults. This supports the idea that pollen are a direct or indirect factor in the seasonality of flu-like epidemics. If seasonality will be observed during the covid-19 spread as well, it is not unlikely that pollen play a role.

Title: SARS vs. flu: can you tell serious disease from common malady? Content: Health officials caution that severe acute respiratory syndrome (SARS) may return this fall with the flu season, and the serious disease may be difficult to distinguish from the common malady. Paying attention to public health trends will help you determine how much a diagnosing concern SARS should be in your own ED. More use of rapid diagnostic tests for flu may help, but don't depend too much on them. Confirming a flu diagnosis means you're relatively safe in ruling out SARS. ED physicians may have to be overly cautious this year in identifying cases of potential SARS.

Title: Does this patient have COVID-19? A practical guide for the internist Content: Coronavirus disease 2019 (COVID-19) is currently causing a pandemic and will likely persist in endemic form in the foreseeable future. Physicians need to correctly approach this new disease, often representing a challenge in terms of differential diagnosis. Although COVID-19 lacks specific signs and symptoms, we believe internists should develop specific skills to recognize the disease, learning its 'semeiotic'. In this review article, we summarize the key clinical features that may guide in differentiating a COVID-19 case, requiring specific testing, from upper respiratory and/or influenza-like illnesses of other aetiology. We consider two different clinical settings, where availability of the different diagnostic strategies differs widely: outpatient and inpatient. Our reasoning highlights how challenging a balanced approach to a patient with fever and flu-like symptoms can be. At present, clinical workup of COVID-19 remains a hard task to accomplish. However, knowledge of the natural history of the disease may aid the internist in putting common and unspecific symptoms into the correct clinical context.

Title: Does this patient have COVID-19? A practical guide for the internist Content: Coronavirus disease 2019 (COVID-19) is currently causing a pandemic and will likely persist in endemic form in the foreseeable future. Physicians need to correctly approach this new disease, often representing a challenge in terms of differential diagnosis. Although COVID-19 lacks specific signs and symptoms, we believe internists should develop specific skills to recognize the disease, learning its ‘semeiotic’. In this review article, we summarize the key clinical features that may guide in differentiating a COVID-19 case, requiring specific testing, from upper respiratory and/or influenza-like illnesses of other aetiology. We consider two different clinical settings, where availability of the different diagnostic strategies differs widely: outpatient and inpatient. Our reasoning highlights how challenging a balanced approach to a patient with fever and flu-like symptoms can be. At present, clinical workup of COVID-19 remains a hard task to accomplish. However, knowledge of the natural history of the disease may aid the internist in putting common and unspecific symptoms into the correct clinical context.

Title: Traumatic Times Content: Discusses how businesses are impacted by traumatic events and pandemics such as the current Coronavirus (COVID-19) As I write this in late March, we are early in the coronavirus (COVID-19) pandemic It is like nothing any of us have experienced before, except perhaps the very few who may have lived through the flu pandemic of 1918-1920 The COVID-19 crisis is like a combination of all the worst we've seen There is social trauma as we isolate ourselves, lose some individual liberties, and try to work from home We don't know when society will return to normal and, when it does, how it will have changed

Title: The complex associations of climate variability with seasonal influenza A and B virus transmission in subtropical Shanghai, China Content: Abstract Most previous studies focused on the association between climate variables and seasonal influenza activity in tropical or temperate zones, little is known about the associations in different influenza types in subtropical China. The study aimed to explore the associations of multiple climate variables with influenza A (Flu-A) and B virus (Flu-B) transmissions in Shanghai, China. Weekly influenza virus and climate data (mean temperature (MeanT), diurnal temperature range (DTR), relative humidity (RH) and wind velocity (Wv)) were collected between June 2012 and December 2018. Generalized linear models (GLMs), distributed lag non-linear models (DLNMs) and regression tree models were developed to assess such associations. MeanT exerted the peaking risk of Flu-A at 1.4 °C (2-weeks’ cumulative relative risk (RR): 14.88, 95% confidence interval (CI): 8.67–23.31) and 25.8 °C (RR: 12.21, 95%CI: 6.64–19.83), Flu-B had the peak at 1.4 °C (RR: 26.44, 95%CI: 11.52–51.86). The highest RR of Flu-A was 23.05 (95%CI: 5.12–88.45) at DTR of 15.8 °C, that of Flu-B was 38.25 (95%CI: 15.82–87.61) at 3.2 °C. RH of 51.5% had the highest RR of Flu-A (9.98, 95%CI: 4.03–26.28) and Flu-B (4.63, 95%CI: 1.95–11.27). Wv of 3.5 m/s exerted the peaking RR of Flu-A (7.48, 95%CI: 2.73–30.04) and Flu-B (7.87, 95%CI: 5.53–11.91). DTR ≥ 12 °C and MeanT <22 °C were the key drivers for Flu-A and Flu-B, separately. The study found complex non-linear relationships between climate variability and different influenza types in Shanghai. We suggest the careful use of meteorological variables in influenza prediction in subtropical regions, considering such complex associations, which may facilitate government and health authorities to better minimize the impacts of seasonal influenza.

Title: Analyses of Merging Clinical and Viral Genetic Data for Influenza Surveillance. Content: The annual influenza vaccine is one of the most common public health interventions and is universally recommended for all individuals older than six months. Vaccine composition depends on viruses circulating over the past flu season and are estimated to be the most prevalent and representative strains in the current season. Here, we use clinical data outfitted with viral genetics to characterize confirmed influenza cases from the past two flu seasons and genetically compare them to the strains that they were vaccinated against that year. We show that case similarities to vaccine strains differ by geographic region and that the vaccines appear to have different levels of effectiveness by region. This study demonstrates the value of merging viral genetics with clinical data. Further research is needed to formally evaluate whether this improves biosurveillance efforts and enhances efficacy of influenza vaccines.

Title: Does COVID-19 infection impact on the trend of seasonal influenza infection? 11 countries and regions, from 2014 to 2020 Content: OBJECTIVES: Infection due to the 2019 novel coronavirus disease (COVID-19) is dramatically widespread around the world. The COVID-19 pandemic could increase public concern to prevent infectious disease. The present study aimed to assess the relationship between the COVID-19 epidemic and the potential decrease in seasonal influenza cases. METHODS: This study was performed to show trends in seasonal influenza cases from the 2014-2015 season to the 2019-2020 season in 11 countries and regions, and evaluate whether the trends in the 2019-2020 season were different before and after the COVID-19 pandemic compared to previous seasons using a quasi-experimental difference-in-difference design. RESULTS: In East Asia, the number of seasonal influenza cases in the 2019-20 season was lower after the COVID-19 transmission compared to previous years. However, this was not the case in American countries or in European countries. CONCLUSION: The COVID-19 epidemic might have altered health behaviors, resulting in an unexpected reduction of seasonal influenza cases.

Title: Does COVID-19 infection impact on the trend of seasonal influenza infection? 11 countries and regions, from 2014 to 2020 Content: Abstract Objectives Infection due to the 2019 novel coronavirus disease (COVID-19) is widespread dramatically around the world. This COVID-19 pandemic could increase public concern to prevent infectious disease. The present study aimed to assess the relationship between the COVID-19 epidemic and decreasing another infectious disease. Methods This study was performed to show trends in seasonal influenza cases from the 2014–2015 season to the 2019–2020 season in 11 countries and regions, and evaluate whether the trends in the 2019–2020 season were different before and after the COVID-19 pandemic compared to previous seasons using a quasi-experimental difference-in-difference design. Results In East Asia, the number of seasonal influenza cases in the 2019–20 season was lower after the COVID-19 transmission compared to previous years. However, this was not the case in the American countries or in European countries. Conclusion The COVID-19 epidemic might have altered health behaviors, resulting in an unexpected reduction of seasonal influenza cases.

Title: Difference in immune response in vaccinated and unvaccinated Swedish individuals after the 2009 influenza pandemic Content: BACKGROUND: Previous exposures to flu and subsequent immune responses may impact on 2009/2010 pandemic flu vaccine responses and clinical symptoms upon infection with the 2009 pandemic H1N1 influenza strain. Qualitative and quantitative differences in humoral and cellular immune responses associated with the flu vaccination in 2009/2010 (pandemic H1N1 vaccine) and natural infection have not yet been described in detail. We designed a longitudinal study to examine influenza- (flu-) specific immune responses and the association between pre-existing flu responses, symptoms of influenza-like illness (ILI), impact of pandemic flu infection, and pandemic flu vaccination in a cohort of 2,040 individuals in Sweden in 2009–2010. METHODS: Cellular flu-specific immune responses were assessed by whole-blood antigen stimulation assay, and humoral responses by a single radial hemolysis test. RESULTS: Previous seasonal flu vaccination was associated with significantly lower flu-specific IFN-γ responses (using a whole-blood assay) at study entry. Pandemic flu vaccination induced long-lived T-cell responses (measured by IFN-γ production) to influenza A strains, influenza B strains, and the matrix (M1) antigen. In contrast, individuals with pandemic flu infection (PCR positive) exhibited increased flu-specific T-cell responses shortly after onset of ILI symptoms but the immune response decreased after the flu season (spring 2010). We identified non-pandemic-flu vaccinated participants without ILI symptoms who showed an IFN-γ production profile similar to pandemic-flu infected participants, suggesting exposure without experiencing clinical symptoms. CONCLUSIONS: Strong and long-lived flu-M1 specific immune responses, defined by IFN-γ production, in individuals after vaccination suggest that M1-responses may contribute to protective cellular immune responses. Silent flu infections appeared to be frequent in 2009/2010. The pandemic flu vaccine induced qualitatively and quantitatively different humoral and cellular immune responses as compared to infection with the 2009 H1N1 pandemic H1N1 influenza strain.

Title: Typical epidemiology of respiratory virus infections in a Brazilian slum Content: Host population size, density, immune status, age structure, and contact rates are critical elements of virus epidemiology. Slum populations stand out from other settings and may present differences in the epidemiology of acute viral infections. We collected nasopharyngeal specimens from 282 children aged ≤5 years with acute respiratory tract infection (ARI) during 2005 to 2006 in one of the largest Brazilian slums. We conducted real‐time reverse transcription‐polymerase chain reaction (RT‐PCR) for 16 respiratory viruses, nested RT‐PCR‐based typing of rhinoviruses (HRVs), and collected clinical symptoms. Viruses were common causes of respiratory disease; with ≥1 virus being detected in 65.2% of patients. We detected 15 different viruses during 1 year with a predomidnance of HRV (33.0%) and human respiratory syncytial virus (hRSV, 12.1%) infections, and a high rate of viral coinfections (28.3%). We observed seasonality of hRSV, HRV and human coronavirus infections, more severe symptoms in hRSV and influenza virus (FLU) infections and prolonged circulation of seven HRV clusters likely representing distinct serotypes according to genomic sequence distances. Potentially unusual findings included the absence of human metapneumovirus detections and lack of typical FLU seasonal patterns, which may be linked to the population size and density of the slum. Nonetheless, most epidemiological patterns were similar to other studies globally, suggesting surprising similarities of virus‐associated ARI across highly diverse settings and a complex impact of population characteristics on respiratory virus epidemiology.

Title: An econometric analysis of SARS and Avian Flu on international tourist arrivals to Asia Content: Abstract This paper compares the impacts of SARS and human deaths arising from Avian Flu on international tourist arrivals to Asia. The effects of SARS and human deaths from Avian Flu are compared directly according to the number of human deaths. The nature of the short run and long run relationship is examined empirically by estimating a static line fixed effect model and a difference transformation dynamic model, respectively. Empirical results from the static fixed effect and difference transformation dynamic models are consistent, and indicate that both the short run and long run SARS effect have a more significant impact on international tourist arrivals than does Avian Flu. In addition, the effects of deaths arising from both SARS and Avian Flu suggest that SARS is more important to international tourist arrivals than is Avian Flu. Thus, while Avian Flu is here to stay, its effect is currently not as significant as that of SARS.

Title: News coverage of health-related issues and its impacts on perceptions: Taiwan as an example. Content: This article examines how health news gets framed and the influence of exposure to news framed differently. A content analysis of Taiwanese newspapers indicates that health news in general, and H1N1 flu news in particular, is more likely to use alarm rather than coping frames. According to an experiment, exposure to H1N1 flu news in an alarm frame evokes greater fear and increases perceived severity and vulnerability, though it does not help develop prevention and treatment efficacy. A survey of the general public also shows that attention and exposure to televised news coverage of the H1N1 flu are associated with greater levels of worry and perceptions of the severity of and vulnerability to this health problem, but they are not related to issue knowledge, detection, or prevention efficacy. Thus, it is important for news coverage to provide information that increases the audience's efficacy when alerting it to health threats.

Title: Factors in vaccination intention against the pandemic influenza A/H1N1 Content: Background: Vaccination against pandemic influenza A/H1N1 is an effective strategy to mitigate the spread of the disease. While the vaccine is now available, social acceptance remains relatively uncertain in many societies. The purpose of this study was to examine the beliefs, attitudes and practices associated with the intention to get vaccinated against the A/H1N1 virus among the general population in France. Methods: A representative sample of 1001 individuals (stratified random recruitment procedure, ages 16–90 years) was interviewed by telephone. The questionnaire included a variety of items associated with socio-demographic characteristics, risk perceptions, illness perceptions, political attitudes and worldviews as well as intention to get vaccinated. Results: More than 6 out of 10 of the respondents indicated that they planned to get vaccinated when the vaccine becomes available. The same proportion of parents also reported the intention to vaccinate their children against the disease. In multiple regression analyses, socio-cognitive factors consistently predicting influenza A/H1N1 vaccination were: level of worry, risk perception and previous experience of vaccine against seasonal flu. Conclusions: The factors found to predict vaccination intention and their distribution are assumed to be a consequence of the fact that people perceive the risk of swine flu to be similar to that of seasonal flu. As a result, in the absence of an increase of the risk perception of pandemic influenza A/H1N1, a very low level of actual vaccination is forecasted. Behavioural change would require that the risks and consequences of pandemic influenza A/H1N1 be perceived as highly different from seasonal flu.

Title: Hospital Associated Respiratory Virus Infection in Children and Adults: It Does Not Just Occur During Cold and Flu Season Content: Hospital-associated respiratory virus infections (HARVI) are an underappreciated source of morbidity and mortality. We examined HARVI incidence and clinical respiratory virus testing practices in a cohort of hospitalized patients with acute respiratory illness. HARVI were identified in patients of all ages, both during and outside of the influenza season.

Title: Assessing the interactions between COVID-19 and influenza in the United States Content: The 2019–2020 influenza sentinel surveillance data exhibits unexpected trends. Typical influenza seasons have a small herald wave, followed by a decrease due to school closure during holidays, and then a main post-holiday peak that is significantly larger than the pre-holiday wave. During the 2019–2020 influenza season, influenza-like illness data in the United States appears to have a markedly lower main epidemic peak compared to what would be expected based on the pre-holiday peak. We hypothesize that the 2019–2020 influenza season does have a lower than expected burden and that this deflation is due to a behavioral or ecological interaction with COVID-19. We apply an intervention analysis to assess if this influenza season deviates from expectations, then we compare multiple hypothesized drivers of the decrease in influenza in a spatiotemporal regression model. Lastly, we develop a mechanistic metapopulation model, incorporating transmission reduction that scales with COVID-19 risk perception. We find that the 2019–2020 ILI season is smaller and decreases earlier than expected based on prior influenza seasons, and that the increase in COVID-19 risk perception is associated with this decrease. Additionally, we find that a 5% average reduction in transmission is sufficient to reproduce the observed flu dynamics. We propose that precautionary behaviors driven by COVID-19 risk perception or increased isolation driven by undetected COVID-19 spread dampened the influenza season. We suggest that when surveillance for a novel pathogen is limited, surveillance streams of co-circulating infections may provide a signal.

Title: Relative disease burdens of COVID-19 and seasonal influenza in New York City, February 1 - April 18, 2020. Content: Comparisons between the mortality burdens of COVID-19 and seasonal influenza often fail to account for the fact that the United States Centers for Disease Control and Prevention (CDC) reports annual influenza mortality estimates which are calculated based upon a series of assumptions about the underreporting of flu deaths. COVID-19 deaths, in contrast, are being reported as raw counts. In this report, we compare COVID-19 death counts to seasonal influenza death counts in New York City during the interval from February 1 - April 18, 2020. Using this approach, COVID-19 appears to have caused 21.4 times the number of deaths as seasonal influenza during the same period. We also assessed excess mortality in order to verify this finding. New York City has had approximately 13,032 excess all-cause mortality deaths during this time period. We assume that most of these deaths are COVID-19 related. We therefore calculated the ratio of excess deaths (i.e. assumed COVID-19 deaths) to seasonal influenza deaths during the same time interval and found a similar ratio of 21.1 COVID-19 to seasonal influenza deaths. Our findings are consistent with conditions on the ground today. Comparing COVID-19 deaths with CDC estimates of yearly influenza-related deaths would suggest that, this year, seasonal influenza has killed approximately the same number of Americans as COVID-19 has. This does not comport with the realities of the pandemic we see today.

Title: Ingestion of Exopolymers from Aureobasidium pullulans Reduces the Duration of Cold and Flu Symptoms: A Randomized, Placebo-Controlled Intervention Study Content: AIM: The objective of the study was to assess the efficacy of exopolymers from Aureobasidium pullulans (EAP) on the incidence of colds and flu in healthy adults. METHODS: We conducted a randomized, double-blind, placebo-controlled study at the onset of the influenza season. A total of 76 subjects (30–70 years of age) were recruited from the general population. The subjects were instructed to take one capsule per day of either EAP or a placebo for a period of 8 weeks. The duration of cold and flu symptoms, a primary variable in assessing effectiveness, and serum cytokine levels as well as WBC counts as secondary variables were also evaluated. RESULTS: EAP was associated with a statistically significant decrease in the duration of cold and flu symptoms, a primary variable in assessing effectiveness. Although cold and flu symptom levels were not significantly different at a significance level of 5%, the cold and flu symptom levels of the EAP group were less severe compared to the placebo group. No statistically significant changes of serum cytokine levels as well as WBC counts were observed. CONCLUSION: The results showed that EAP is a useful pharmaceutical and functional food material for preventing and treating colds and flu.

Title: Flu or a Bug? Content: Of late, apart from the four calendar seasons, there is yet another season referred to as the “flu season.” During this time of the year, we routinely hear the phrase “the flu is going around.” I was surprised last week when I heard my 6-year-old son mention to me that there is some bug going around in his class and that his best friend was sick. I asked him to define the bug and he said it causes stuffy nose. The word “bug” is used so callously by adults that it has been registered wrongly in the minds of the little ones.

Title: Does subsidy work? Price elasticity of demand for influenza vaccination among the elderly in Japan Content: Abstract Objectives Subsidy for influenza vaccination is often provided to the elderly in order to encourage them to receive a flu shot in developed countries. However, its effect on uptake rate, i.e., price elasticity of demand, has not been well studied. Methods Japan's decentralised vaccination programme allows observation of various pairs in price and uptake rate of flu shots among the elderly by the municipality from 2001/2002 to 2004/2005 season. We combine our sample survey data (n =281), which monitor price, subsidy and uptake rate, with published data on local characteristics in order to estimate price elasticity of demand with panel model. Results We find price elasticity of demand for influenza vaccine: nearly zero in nationwide, nearly zero in urban area, and −1.07 in rural area. Conclusions The results question the rationale for subsidy, especially in urban area. There are cases where maintaining or increasing the level of subsidy is not an efficient allocation of finite health care resources. When organising a vaccination programme, health manager should be careful about the balance between subsidy and other efforts in order to encourage the elderly to receive shots with price elasticity in mind.

Title: Prior infection by seasonal coronaviruses does not prevent SARS-CoV-2 infection and associated Multisystem Inflammatory Syndrome in children Content: Background: Children have a lower rate of COVID-19, potentially related to cross-protective immunity conferred by seasonal coronaviruses (HCoVs). We tested if prior infections with seasonal coronaviruses impacted SARS-CoV-2 infections and related Multisystem Inflammatory Syndrome (MIS). Methods: This cross-sectional observational study in Paris hospitals enrolled 739 pauci or asymptomatic children (HOS group) plus 36 children with suspected MIS (MIS group). Prevalence, antigen specificity and neutralizing capability of SARS-CoV-2 antibodies were tested. Antibody frequency and titres against Nucleocapsid (N) and Spike (S) of the four seasonal coronaviruses (NL63, HKU1, 229E, OC43) were measured in a subset of seropositive patients (54 SARS-CoV-2 (HOS-P subgroup) and 15 MIS (MIS-P subgroup)), and in 118 matched SARS-CoV-2 seronegative patients (CTL subgroup). Findings: SARS-CoV-2 mean prevalence rate in HOSP children was 11.7% from April 1 to June 1. Neutralizing antibodies were found in 55.6% of seropositive children, and their relative frequency increased with time (up to 100 % by mid-May). A majority of MIS children (25/36) were SARS-CoV-2 seropositive, of which all tested (n=15) had neutralizing antibodies. On average, seropositive MIS children had higher N and S1 SARS-CoV-2 titres as compared to HOS children. Patients from HOS-P, MIS-P, and CTL subgroups had a similar prevalence of antibodies against the four seasonal HCoVs (66.9 -100%). The level of anti-SARS-CoV-2 antibodies was not significantly different in children who had prior seasonal coronavirus infection. Interpretation: Prior infection with HCoVs does not prevent SARS-CoV-2 infection and related MIS in children. Children develop neutralizing antibodies after SARS-CoV-2 infection.

Title: Reproduction of East-African bats may guide risk mitigation for coronavirus spillover Content: BACKGROUND: Bats provide important ecosystem services; however, current evidence supports that they host several zoonotic viruses, including species of the Coronaviridae family. If bats in close interaction with humans host and shed coronaviruses with zoonotic potential, such as the Severe Acute Respiratory Syndrome virus, spillover may occur. Therefore, strategies aiming to mitigate potential spillover and disease emergence, while supporting the conservation of bats and their important ecological roles are needed. Past research suggests that coronavirus shedding in bats varies seasonally following their reproductive cycle; however, shedding dynamics have been assessed in only a few species, which does not allow for generalization of findings across bat taxa and geographic regions. METHODS: To assess the generalizability of coronavirus shedding seasonality, we sampled hundreds of bats belonging to several species with different life history traits across East Africa at different times of the year. We assessed, via Bayesian modeling, the hypothesis that chiropterans, across species and spatial domains, experience seasonal trends in coronavirus shedding as a function of the reproductive cycle. RESULTS: We found that, beyond spatial, taxonomic, and life history differences, coronavirus shedding is more expected when pups are becoming independent from the dam and that juvenile bats are prone to shed these viruses. CONCLUSIONS: These findings could guide policy aimed at the prevention of spillover in limited-resource settings, where longitudinal surveillance is not feasible, by identifying high-risk periods for coronavirus shedding. In these periods, contact with bats should be avoided (for example, by impeding or forbidding people access to caves). Our proposed strategy provides an alternative to culling – an ethically questionable practice that may result in higher pathogen levels – and supports the conservation of bats and the delivery of their key ecosystem services.

Title: Prevalence of respiratory viruses, including newly identified viruses, in hospitalised children in Austria Content: The aim of this epidemiological study was to determine the prevalence of respiratory viruses, including new viruses, in hospitalised children in Austria. Two hundred fourteen nasopharyngeal samples from hospitalised children were tested for the presence of viruses using cell culture and PCR and/or viral antigen assays. The results revealed a parainfluenza virus 1 (PIV1) outbreak that ended right before the onset of the influenza season, with nearly no overlapping, moderate respiratory syncytial virus (RSV) activity, and only a few adenoviruses. Human metapneumovirus (hMPV) was present in 14.5% of the total samples but was detected in combination with other viruses in only five cases: with PIV1 in three cases and with RSV in two cases. There were no cases of dual infection with hMPV and flu or adenovirus. This suggests that hMPV alone is a leading cause of hospitalisation in children under 1 year of age. Interestingly, hMPV, in contrast to RSV, coincided with PIV1 but was absent during the community outbreak of the flu. Samples were also tested for Mimiviridae, a group of newly described DNA viruses that are similar to Legionella spp., replicate in water amoebae, and also have been found in alveolar cells. However, mimivirus was detected neither in respiratory samples nor in amoebae-containing water samples, indicating that this particular type of virus is either not abundant or does not contribute to paediatric respiratory illnesses.

Title: Modeling the impact of mass influenza vaccination and public health interventions on COVID-19 epidemics with limited detection capability Content: The emerging coronavirus SARS-CoV-2 has caused a COVID-19 pandemic. SARS-CoV-2 causes a generally mild, but sometimes severe and even life-threatening infection, known as COVID-19. Currently, there exist no effective vaccines or drugs and, as such, global public authorities have so far relied upon non pharmaceutical interventions (NPIs). Since COVID-19 symptoms are aspecific and may resemble a common cold, if it should come back with a seasonal pattern and coincide with the influenza season, this would be particularly challenging, overwhelming and straining the healthcare systems, particularly in resource-limited contexts, and would increase the likelihood of nosocomial transmission. In the present study, we devised a mathematical model focusing on the treatment of people complaining of influenza-like-illness (ILI) symptoms, potentially at risk of contracting COVID-19 or other emerging/re-emerging respiratory infectious agents during their admission at the health-care setting, who will occupy the detection kits causing a severe shortage of testing resources. The model is used to assess the effect of mass influenza vaccination on the spread of COVID-19 and the other respiratory pathogens in the case of a coincidence of the outbreak with the influenza season. Here, we show that increasing influenza vaccine uptake or enhancing the public health interventions would facilitate the management of respiratory outbreaks coinciding with the peak flu season, especially, compensate the shortage of the detection resources. However, how to increase influenza vaccination coverage rate remains challenging. Public health decision- and policy-makers should adopt evidence-informed strategies to improve influenza vaccine uptake.

Title: Modeling the impact of mass influenza vaccination and public health interventions on COVID-19 epidemics with limited detection capability Content: The emerging coronavirus SARS-CoV-2 has caused a COVID-19 pandemic. SARS-CoV-2 causes a generally mild, but sometimes severe and even life-threatening infection, known as COVID-19. Currently, there exist no effective vaccines or drugs and, as such, global public authorities have so far relied upon non pharmaceutical interventions (NPIs). Since COVID-19 symptoms are aspecific and may resemble a common cold, if it should come back with a seasonal pattern and coincide with the influenza season, this would be particularly challenging, overwhelming and straining the healthcare systems, particularly in resource-limited contexts, and would increase the likelihood of nosocomial transmission. In the present study, we devised a mathematical model focusing on the treatment of people complaining of influenza-like-illness (ILI) symptoms, potentially at risk of contracting COVID-19 or other emerging/re-emerging respiratory infectious agents during their admission at the health-care setting, who will occupy the detection kits causing a severe shortage of testing resources. The model is used to assess the effect of mass influenza vaccination on the spread of COVID-19 and other respiratory pathogens in the case of a coincidence of the outbreak with the influenza season. Here, we show that increasing influenza vaccine uptake or enhancing the public health interventions would facilitate the management of respiratory outbreaks coinciding with the peak flu season, especially, compensate the shortage of the detection resources. However, how to increase influenza vaccination coverage rate remains challenging. Public health decision- and policy-makers should adopt evidence-informed strategies to improve influenza vaccine uptake.

Title: Fevers Are Rarest in the Morning: Could We Be Missing Infectious Disease Cases by Screening for Fever Then? Content: Body temperatures are less likely to reach the fever range in the morning, but it is unknown how this affects practice during disease outbreaks. We retrospectively investigated fever-range temperatures ([≥]100.4{degrees}F, [≥]38.0{degrees}C) during seasonal influenza outbreaks and the 2009 H1N1 (swine flu) pandemic, which have recently been used as preparatory models for coronavirus disease 2019 (COVID-19). Our analyses included a nationally representative sample of records from adult visits to US emergency departments (n=202,181) and data from a Boston emergency department (n=93,225). Fever-range temperatures were about half as common in the morning as in the evening, suggesting that morning temperatures can be much less diagnostic, and that revisions may be needed to the practice of once-daily temperature screens at morning arrival to workplaces and schools. Twice-daily screens could be a simple solution, but similar research is still needed on fevers in COVID-19 itself.

Title: Immunohistochemical assessment of respiratory viruses in necropsy samples from lethal non-pandemic seasonal respiratory infections. Content: BACKGROUND/AIM Acute respiratory infections are an important cause of childhood morbidity and mortality throughout the world, and viruses have often been reported to be an aetiological agent. This study aimed to identify respiratory viruses in paraffin-embedded samples of paediatric lung necropsy specimens, using immunohistochemistry on tissue microarray slides. METHODS Retrospective study in 200 lung tissue samples from children who had died from severe respiratory infections during 1985-2005. Immunoperoxidase assay was performed to detect the viruses that were most commonly associated with respiratory tract infections: influenza virus A (FLU A), influenza virus B (FLU B), respiratory syncytial virus (RSV), adenovirus (AdV) and parainfluenza virus (PIV) types 1, 2 and 3. RESULTS Viruses were detected in 71 (35.5%) cases. Most positive cases were observed in children younger than 6 months. In 42.3% of cases, only one virus was detected: 11 (36.7%) RSV; 7 (23.3%) AdV; 4 (13.3%) PIV2; 3 (10%) FLU A; 2 (6.7%) FLU B; 2 (6.7%) PIV3; and 1 (3.3%) PIV1. Co-infection with more than one virus was observed in 41 (57.7%) cases. No positive correlations were observed between the presence of viral antigens and seasonality of the infection, sex, age or histopathological findings. CONCLUSIONS Non-pandemic seasonal respiratory viruses are involved in a significant number of deaths in paediatric patients; these findings highlight the importance of laboratory investigation of these agents in patients hospitalised with severe acute respiratory infections.

Title: Online Social Networks Flu Trend Tracker: A Novel Sensory Approach to Predict Flu Trends Content: Seasonal influenza epidemics cause several million cases of illnesses cases and about 250,000 to 500,000 deaths worldwide each year. Other pandemics like the 1918 “Spanish Flu” may change into devastating event. Reducing the impact of these threats is of paramount importance for health authorities, and studies have shown that effective interventions can be taken to contain the epidemics, if early detection can be made. In this paper, we introduce Social Network Enabled Flu Trends (SNEFT), a continuous data collection framework which monitors flu related messages on online social networks such as Twitter and Facebook and track the emergence and spread of an influenza. We show that text mining significantly enhances the correlation between online social network(OSN) data and the Influenza like Illness (ILI) rates provided by Centers for Disease Control and Prevention (CDC). For accurate prediction, we implemented an auto-regression with exogenous input (ARX) model which uses current OSN data and CDC ILI rates from previous weeks to predict current influenza statistics. Our results show that, while previous ILI data from the CDC offer a true (but delayed) assessment of a flu epidemic, OSN data provides a real-time assessment of the current epidemic condition and can be used to compensate for the lack of current ILI data. We observe that the OSN data is highly correlated with the ILI rates across different regions within USA and can be used to effectively improve the accuracy of our prediction. Therefore, OSN data can act as supplementary indicator to gauge influenza within a population and helps to discover flu trends ahead of CDC.

Title: Multiplex PCR tests sentinel the appearance of pandemic influenza viruses including H1N1 swine influenza Content: BACKGROUND: Since the turn of the century seven new respiratory viruses have infected man and two of these have resulted in worldwide epidemics. Both SARS Coronavirus which quickly spread to 29 countries in February 2003 and H1N1 swine influenza that recently spread from Mexico to 30 countries in three weeks represent major pandemic threats for mankind. Diagnostic assays are required to detect novel influenza strains with pandemic potential. OBJECTIVE: In this report we evaluate the ability of a multiplex PCR test (xTAG(™)RVP) to detect new, “non-seasonal” influenza viruses including the H1N1 swine influenza A/swine/California/04/2009. STUDY DESIGN: Laboratory based study using retrospective and prospective specimens. RESULTS: This multiplex PCR test detected the present of non-seasonal (non-H1, non-H3) influenza in 20 of 20 patients infected with H1N1 swine flu virus. In addition to detecting the current swine flu the xTAG(™) RVP test detected the H5N1 A/Vietnam/1203/2004 high pathogenicity avian influenza virus that circulated in South East Asia in 2003 as well as 17 out of 17 influenza A viruses representing 11 HA subtypes isolated from birds, swine and horses not yet seen in the human population. CONCLUSION: Based on these results we believe that this molecular test can perform an important role as a sentinel test to detect novel non-seasonal influenza A viruses in patients presenting with influenza-like illness (ILI) and therefore act as an early warning system for the detection of future pandemic influenza threats.

Title: Influenza vaccination and respiratory virus interference among Department of Defense personnel during the 2017–2018 influenza season Content: PURPOSE: Receiving influenza vaccination may increase the risk of other respiratory viruses, a phenomenon known as virus interference. Test-negative study designs are often utilized to calculate influenza vaccine effectiveness. The virus interference phenomenon goes against the basic assumption of the test-negative vaccine effectiveness study that vaccination does not change the risk of infection with other respiratory illness, thus potentially biasing vaccine effectiveness results in the positive direction. This study aimed to investigate virus interference by comparing respiratory virus status among Department of Defense personnel based on their influenza vaccination status. Furthermore, individual respiratory viruses and their association with influenza vaccination were examined. RESULTS: We compared vaccination status of 2880 people with non-influenza respiratory viruses to 3240 people with pan-negative results. Comparing vaccinated to non-vaccinated patients, the adjusted odds ratio for non-flu viruses was 0.97 (95% confidence interval (CI): 0.86, 1.09; p = 0.60). Additionally, the vaccination status of 3349 cases of influenza were compared to three different control groups: all controls (N = 6120), non-influenza positive controls (N = 2880), and pan-negative controls (N = 3240). The adjusted ORs for the comparisons among the three control groups did not vary much (range: 0.46–0.51). CONCLUSIONS: Receipt of influenza vaccination was not associated with virus interference among our population. Examining virus interference by specific respiratory viruses showed mixed results. Vaccine derived virus interference was significantly associated with coronavirus and human metapneumovirus; however, significant protection with vaccination was associated not only with most influenza viruses, but also parainfluenza, RSV, and non-influenza virus coinfections.

Title: Swine flu update: bringing home the bacon. Content: In 6 weeks, swine influenza A(H1N1) virus has spread from 10 to 74 countries. Australia has the fifth highest number of cases and the third highest rate of infection among the top five affected nations. People who are hospitalised with or die from this novel virus are more likely to have predisposing risk factors. There is a predilection for younger age groups and sparing of older age groups. This may be a property of influenza A viruses in general rather than being specific to swine influenza A. If unchecked, the sheer number of cases may lead to much higher numbers of deaths and hospitalised patients than would normally be attributed to a standard influenza season. Paradoxically, the low case-fatality rate of the virus raises the question of how best to approach management of this outbreak. It is uncertain how an expected vaccine against the novel virus will be used.

Title: Human temperatures for syndromic surveillance in the emergency department: data from the autumn wave of the 2009 swine flu (H1N1) pandemic and a seasonal influenza outbreak Content: BACKGROUND: The emergency department (ED) increasingly acts as a gateway to the evaluation and treatment of acute illnesses. Consequently, it has also become a key testing ground for systems that monitor and identify outbreaks of disease. Here, we describe a new technology that automatically collects body temperatures during triage. The technology was tested in an ED as an approach to monitoring diseases that cause fever, such as seasonal flu and some pandemics. METHODS: Temporal artery thermometers that log temperature measurements were placed in a Boston ED and used for initial triage vital signs. Time-stamped measurements were collected from the thermometers to investigate the performance a real-time system would offer. The data were summarized in terms of rates of fever (temperatures ≥100.4 °F [≥38.0 °C]) and were qualitatively compared with regional disease surveillance programs in Massachusetts. RESULTS: From September 2009 through August 2011, 71,865 body temperatures were collected and included in our analysis, 2073 (2.6 %) of which were fevers. The period of study included the autumn–winter wave of the 2009–2010 H1N1 (swine flu) pandemic, during which the weekly incidence of fever reached a maximum of 5.6 %, as well as the 2010–2011 seasonal flu outbreak, during which the maximum weekly incidence of fever was 6.6 %. The periods of peak fever rates corresponded with the periods of regionally elevated flu activity. CONCLUSIONS: Temperature measurements were monitored at triage in the ED over a period of 2 years. The resulting data showed promise as a potential surveillance tool for febrile disease that could complement current disease surveillance systems. Because temperature can easily be measured by non-experts, it might also be suitable for monitoring febrile disease activity in schools, workplaces, and transportation hubs, where many traditional syndromic indicators are impractical. However, the system’s validity and generalizability should be evaluated in additional years and settings. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12873-016-0080-7) contains supplementary material, which is available to authorized users.

Title: H1N1 viral proteome peptide microarray predicts individuals at risk for H1N1 infection and segregates infection versus Pandemrix® vaccination Content: A high content peptide microarray containing the entire influenza A virus [A/California/08/2009(H1N1)] proteome and haemagglutinin proteins from 12 other influenza A subtypes, including the haemagglutinin from the [A/South Carolina/1/1918(H1N1)] strain, was used to gauge serum IgG epitope signatures before and after Pandemrix® vaccination or H1N1 infection in a Swedish cohort during the pandemic influenza season 2009. A very narrow pattern of pandemic flu-specific IgG epitope recognition was observed in the serum from individuals who later contracted H1N1 infection. Moreover, the pandemic influenza infection generated IgG reactivity to two adjacent epitopes of the neuraminidase protein. The differential serum IgG recognition was focused on haemagglutinin 1 (H1) and restricted to classical antigenic sites (Cb) in both the vaccinated controls and individuals with flu infections. We further identified a novel epitope VEPGDKITFEATGNL on the Ca antigenic site (251–265) of the pandemic flu haemagglutinin, which was exclusively recognized in serum from individuals with previous vaccinations and never in serum from individuals with H1N1 infection (confirmed by RNA PCR analysis from nasal swabs). This epitope was mapped to the receptor-binding domain of the influenza haemagglutinin and could serve as a correlate of immune protection in the context of pandemic flu. The study shows that unbiased epitope mapping using peptide microarray technology leads to the identification of biologically and clinically relevant target structures. Most significantly an H1N1 infection induced a different footprint of IgG epitope recognition patterns compared with the pandemic H1N1 vaccine.

Title: Detection of Influenza and Other Respiratory Viruses Carried Out in the Influenza Project – Monitoring Vaccine Effectiveness (I-MOVE) Content: The project Influenza Vaccine Effectiveness-Monitoring (I-MOVE) is part of the European research carried out by the ECDC (European Center for Disease Prevention and Control), aimed at monitoring the effectiveness of vaccination in Europe during the growing incidence of flu and influenza-like illnesses in the coming epidemic seasons. Laboratory studies using molecular RT-PCR biology methods for detection of genetic material of influenza virus and other respiratory viruses were performed by Voivodeship Sanitary-Epidemiological Stations in Poland. The validation of the results of swabs taken from the nose and throat were carried out in the Department of Influenza Research, National Influenza Center in Warsaw. The study involved 210 samples from patients across Poland. Positive results were recorded for 72.4 % of the samples; influenza virus type A was detected in 43 and type B in 38 cases, whereas in 71 cases other respiratory viruses were detected, which included Human parainfluenza virus type 1–4; Human respiratory syncytial virus type A and B; Human coronavirus 229E/NL63, OC43; Human rhinovirus type A, B, and C; Human enterovirus; and Human adenovirus. The results show that although influenza viruses predominated in the 2010/2011 season in Poland, other flu-like viruses also abounded.

Title: Talking about colds and flu: The lay diagnosis of two common illnesses among older British people Content: This paper reports on a study of the ways in which 54 older people in South Wales (UK) talk about the symptoms and causes of cold and influenza (flu). The study was designed to understand why older people might reject or accept the offer of seasonal flu vaccine, and in the course of the interviews respondents were also asked to express their views about the nature and causes of the two key illnesses. The latter are among the most common infections in human beings. In terms of the biomedical paradigm the common cold is caused by numerous respiratory viruses, whilst flu is caused by the influenza virus. Medical diagnosis is usually made on clinical grounds without laboratory confirmation. Symptoms of flu include sudden onset of fever and cough, and colds are characterized by sneezing, sore throat, and runny nose, but in practice the symptoms often overlap. In this study we examine the degree by which the views of lay people with respect to both diagnosis and epidemiology diverge with that which is evident in biomedical discourse. Our results indicate that whilst most of the identified symptoms are common to lay and professional people, the former integrate symptoms into a markedly different observational frame from the latter. And as far as causation is concerned it is clear that lay people emphasize the role of ‘resistance’ and ‘immunity’ at least as much as ‘infection’ in accounting for the onset of colds and flu. The data are analyzed using novel methods that focus on the co-occurrence of concepts and are displayed as semantic networks. As well as reporting on its findings the authors draw out some implications of the study for social scientific and policy discussions concerning lay diagnosis, lay expertise and the concept of an expert patient.

Title: Surveillance of community-acquired viral infections due to respiratory viruses in Rhone-Alpes (France) during winter 1994 to 1995. Content: Nasal swab from patients with acute flu-like illness were evaluated for the presence of respiratory viruses in the Rhone-Alpes region of France from 1 October 1994 through 2 May 1995. The relative frequencies and seasonal distributions of the specific viruses were assessed. In addition, virus type was correlated with specific clinical signs and symptoms. During the study, 962 samples were collected by 75 medical practitioners participating in the Groupe Regional d'Observation de la Grippe surveillance network. One or more viruses were detected from 348 samples (36.1%), including 108 respiratory syncytial virus (RSV), 64 influenza virus A type H3N2, 47 influenza virus B, 64 coronavirus, 35 rhinovirus, 22 adenovirus, 5 enterovirus, and 3 parainfluenza-fluenza strains. There were 16 mixed infections. RSV infections peaked in the early winter, and influenza viruses A and B infections peaked during the late winter and early spring. There were two peaks of coronavirus infections (late fall and late winter). Other viruses were detected at lower levels throughout the study period. Patients from whom adenovirus was isolated were significantly more likely to have a fever of > 39.5 degrees C than were patients with other detectable viruses (P < 0.001). Furthermore, there was a significant correlation between influenza and cough (P < 0.01) and RSV and bronchiolitis (P < .001). Thus, the current study defined the overall and relative frequencies of respiratory virus detection from nasal swab specimens in patients with an acute flu-like illness in the Rhone-Alpes region of France during a 7-month period. Correlation with clinical signs and symptoms and provisional conclusions regarding seasonality were also determined.

Title: Featuring COVID-19 cases via screening symptomatic patients with epidemiologic link during flu season in a medical center of central Taiwan Content: Abstract Background Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CO-V-2), was first reported in Wuhan, Hubei province, China has now rapidly spread over 50 countries. For the prevention and control of infection, Taiwan Centers for Disease Control initiated testing of SARS-CoV-2 on January 24th 2020 for persons suspected with this disease. Until February 28th, 43 flu-like symptomatic patients were screened in China Medical University Hospital. Methods Two patients were confirmed positive for SARS-CoV-2 infection by rRT-PCR as COVID-19 patients A and B. Causative pathogens for included patients were detected using FilmArray™ Respiratory Panel. We retrospectively analyzed the clinical presentations, laboratory data, radiologic findings, and travel and exposure contact histories, of the COVID-19 patients in comparison to those with other respiratory infections. Results Through contact with Taiwan No. 19 case patient on 27th January, COVID-19 patients A and B were infected. Both patients had no identified comorbidities and developed mild illness with temporal fever, persistent cough, and lung interstitial infiltrates. Owing to the persistence of positive SARS-CoV-2 in respiratory specimen, the two COVID-19 patients are still in the isolation rooms despite recovery until 10th of March. The results of FilmArrayTM Respiratory Panel revealed 22 of the 41 non-COVID-19 patients were infected by particular pathogens. In general, seasonal respiratory pathogens are more prevalent than SARS-CoV-2 in symptomatic patients in non- COVID-19 endemic area during the flu season. Since all patients shared similar clinical and laboratory findings, expanded surveillance of detailed exposure history for suspected patients and application of rapid detection tools are highly recommended.

Title: Featuring COVID-19 cases via screening symptomatic patients with epidemiologic link during flu season in a medical center of central Taiwan Content: BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CO-V-2), was first reported in Wuhan, Hubei province, China has now rapidly spread over 50 countries. For the prevention and control of infection, Taiwan Centers for Disease Control initiated testing of SARS-CoV-2 on January 24th 2020 for persons suspected with this disease. Until February 28th, 43 flu-like symptomatic patients were screened in China Medical University Hospital. METHODS: Two patients were confirmed positive for SARS-CoV-2 infection by rRT-PCR as COVID-19 patients A and B. Causative pathogens for included patients were detected using FilmArray™ Respiratory Panel. We retrospectively analyzed the clinical presentations, laboratory data, radiologic findings, and travel and exposure contact histories, of the COVID-19 patients in comparison to those with other respiratory infections. RESULTS: Through contact with Taiwan No. 19 case patient on 27th January, COVID-19 patients A and B were infected. Both patients had no identified comorbidities and developed mild illness with temporal fever, persistent cough, and lung interstitial infiltrates. Owing to the persistence of positive SARS-CoV-2 in respiratory specimen, the two COVID-19 patients are still in the isolation rooms despite recovery until 10th of March. The results of FilmArrayTM Respiratory Panel revealed 22 of the 41 non-COVID-19 patients were infected by particular pathogens. In general, seasonal respiratory pathogens are more prevalent than SARS-CoV-2 in symptomatic patients in non- COVID-19 endemic area during the flu season. Since all patients shared similar clinical and laboratory findings, expanded surveillance of detailed exposure history for suspected patients and application of rapid detection tools are highly recommended.

Title: Measuring COVID-19 and Influenza in the Real World via Person-Generated Health Data Content: Background: Since the beginning of the COVID-19 pandemic data from smartphones and connected sensors has been used to learn about symptoms presentation and management outside the clinic walls. However, reports on the validity of such data are still sparse, especially when it comes to symptom progression and relevance of wearable sensors. Objective: To understand the relevance of Person-GeneratedHealth Data (PGHD) as a means for early detection, monitoring and management of COVID-19 in everyday life. This includes quantifying prevalence and progression of symptoms from self-reports as well as changes in activity and physiological parameters continuously measured from wearable sensors, and contextualizing findings for COVID-19 patients with those from cohorts of flu patients. Design, Setting, and Participants: Retrospective digital cohort study of individuals with a self-reported positive SARS-CoV-2 or influenza test followed over the period 2019-12-02 to2020-04-27. Three cohorts were derived: Patients who self-reported being diagnosed with flu prior to the SARS-CoV-2 pandemic (N=6270, of which 1226 also contributed sensorPGHD); Patients who reported being diagnosed with flu during the SARS-CoV-2 pandemic (N=426, of which 85 also shared sensor PGHD); and patients who reported being diagnosed withCOVID-19 (N=230, of which sensor PGHD was available for 41).The cohorts were derived from a large-scale digital participatory surveillance study designed to track Influenza-like Illness(ILI) incidence and burden over time. Exposures: Self-reported demographic data, comorbidities, and symptoms experienced during a diagnosed ILI episode, including SARS-CoV-2.Physiological and behavioral parameters measured daily from commercial wearable sensors, includingResting Heart Rate (RHR), total step count, and nightly sleep hours. Main Outcomes and Measures: We investigated the percent-age of individuals experiencing symptoms of a given type (e.g.shortness of breath) across demographic groups and over time. We examined illness duration, and care seeking behavior, and how RHR, step count, and nightly sleep hours deviated from expected behavior on healthy days over the course of the infection episode. Results: Self-reported symptoms of COVID-19 present differently from flu. COVID-19 cases tended to last longer than flu(median of 12 vs. 9 days), are uniquely characterized by chest pain/pressure, shortness of breath, and anosmia. The fraction of elevated RHR measurements collected daily from commercial wearable devices rise significantly in the 2 days surrounding ILI symptoms onset, but does not appear to do so in a way specific to COVID-19. Steps lost due to COVID-19 persists for longer. Conclusion and Relevance: PGHD can be a valid source of longitudinal real world data to detect and monitor COVID-19-related symptoms and behaviors at population scale. PGHD may provide continuous, near realtime feedback to intervention effectiveness that otherwise requires waiting for symptoms to develop into contacts with the healthcare system. It has also the potential to increase pre-test probability of other downstream diagnostics. To effectively leverage PGHD for participatory surveillance it is crucial to invest in the creation of trusted, long-term communication channels with individuals through whichdata can be efficiently collected, consented, and contextualized,while protecting the privacy of individuals and ultimately facilitating the transition in and out of care.

Title: Comparative community burden and severity of seasonal and pandemic influenza: results of the Flu Watch cohort study Content: BACKGROUND: Assessment of the effect of influenza on populations, including risk of infection, illness if infected, illness severity, and consultation rates, is essential to inform future control and prevention. We aimed to compare the community burden and severity of seasonal and pandemic influenza across different age groups and study years and gain insight into the extent to which traditional surveillance underestimates this burden. METHODS: Using preseason and postseason serology, weekly illness reporting, and RT-PCR identification of influenza from nasal swabs, we tracked the course of seasonal and pandemic influenza over five successive cohorts (England 2006–11; 5448 person-seasons' follow-up). We compared burden and severity of seasonal and pandemic strains. We weighted analyses to the age and regional structure of England to give nationally representative estimates. We compared symptom profiles over the first week of illness for different strains of PCR-confirmed influenza and non-influenza viruses using ordinal logistic regression with symptom severity grade as the outcome variable. FINDINGS: Based on four-fold titre rises in strain-specific serology, on average influenza infected 18% (95% CI 16–22) of unvaccinated people each winter. Of those infected there were 69 respiratory illnesses per 100 person-influenza-seasons compared with 44 per 100 in those not infected with influenza. The age-adjusted attributable rate of illness if infected was 23 illnesses per 100 person-seasons (13–34), suggesting most influenza infections are asymptomatic. 25% (18–35) of all people with serologically confirmed infections had PCR-confirmed disease. 17% (10–26) of people with PCR-confirmed influenza had medically attended illness. These figures did not differ significantly when comparing pandemic with seasonal influenza. Of PCR-confirmed cases, people infected with the 2009 pandemic strain had markedly less severe symptoms than those infected with seasonal H3N2. INTERPRETATION: Seasonal influenza and the 2009 pandemic strain were characterised by similar high rates of mainly asymptomatic infection with most symptomatic cases self-managing without medical consultation. In the community the 2009 pandemic strain caused milder symptoms than seasonal H3N2. FUNDING: Medical Research Council and the Wellcome Trust.

Title: Outcomes of Influenza A(H1N1)pdm09 Virus Infection: Results from Two International Cohort Studies Content: BACKGROUND: Data from prospectively planned cohort studies on risk of major clinical outcomes and prognostic factors for patients with influenza A(H1N1)pdm09 virus are limited. In 2009, in order to assess outcomes and evaluate risk factors for progression of illness, two cohort studies were initiated: FLU 002 in outpatients and FLU 003 in hospitalized patients. METHODS AND FINDINGS: Between October 2009 and December 2012, adults with influenza-like illness (ILI) were enrolled; outpatients were followed for 14 days and inpatients for 60 days. Disease progression was defined as hospitalization and/or death for outpatients, and hospitalization for >28 days, transfer to intensive care unit (ICU) if enrolled from general ward, and/or death for inpatients. Infection was confirmed by RT-PCR. 590 FLU 002 and 392 FLU 003 patients with influenza A (H1N1)pdm09 were enrolled from 81 sites in 17 countries at 2 days (IQR 1–3) and 6 days (IQR 4–10) following ILI onset, respectively. Disease progression was experienced by 29 (1 death) outpatients (5.1%; 95% CI: 3.4–7.2%) and 80 inpatients [death (32), hospitalization >28 days (43) or ICU transfer (20)] (21.6%; 95% CI: 17.5–26.2%). Disease progression (death) for hospitalized patients was 53.1% (26.6%) and 12.8% (3.8%), respectively, for those enrolled in the ICU and general ward. In pooled analyses for both studies, predictors of disease progression were age, longer duration of symptoms at enrollment and immunosuppression. Patients hospitalized during the pandemic period had a poorer prognosis than in subsequent seasons. CONCLUSIONS: Patients with influenza A(H1N1)pdm09, particularly when requiring hospital admission, are at high risk for disease progression, especially if they are older, immunodeficient, or admitted late in infection. These data reinforce the need for international trials of novel treatment strategies for influenza infection and serve as a reminder of the need to monitor the severity of seasonal and pandemic influenza epidemics globally. TRIAL REGISTRATION: ClinicalTrials.gov Identifiers: FLU 002- NCT01056354, FLU 003- NCT01056185.

Title: A close look at the biology of SARS-CoV-2, and the potential influence of weather conditions and seasons on COVID-19 case spread Content: BACKGROUND: There is sufficient epidemiological and biological evidence of increased human susceptibility to viral pathogens such as Middle East respiratory syndrome coronavirus, respiratory syncytial virus, human metapneumovirus and influenza virus, in cold weather. The pattern of outbreak of the coronavirus disease 2019 (COVID-19) in China during the flu season is further proof that meteorological conditions may potentially influence the susceptibility of human populations to coronaviruses, a situation that may become increasingly evident as the current global pandemic of COVID-19 unfolds. MAIN BODY: A very rapid spread and high mortality rates have characterized the COVID-19 pandemic in countries north of the equator where air temperatures have been seasonally low. It is unclear if the currently high rates of COVID-19 infections in countries of the northern hemisphere will wane during the summer months, or if fewer people overall will become infected with COVID-19 in countries south of the equator where warmer weather conditions prevail through most of the year. However, apart from the influence of seasons, evidence based on the structural biology and biochemical properties of many enveloped viruses similar to the novel severe acute respiratory syndrome coronavirus 2 or SARS-CoV-2 (aetiology of COVID-19), support the higher likelihood of the latter of the two outcomes. Other factors that may potentially impact the rate of virus spread include the effectiveness of infection control practices, individual and herd immunity, and emergency preparedness levels of countries. CONCLUSION: This report highlights the potential influence of weather conditions, seasons and non-climatological factors on the geographical spread of cases of COVID-19 across the globe.

Title: A Model for Characterizing Annual Flu Cases Content: Influenza outbreaks occur seasonally and peak during winter season in temperate zones of the Northern and Southern hemisphere. The occurrence and recurrence of flu epidemics has been alluded to variability in mechanisms such temperature, climate, host contact and traveling patterns [4]. This work promotes a Gaussian–type regression model to study flu outbreak trends and predict new cases based on influenza–like–illness data for France (1985–2005). We show that the proposed models are appropriate descriptors of these outbreaks and can improve the surveillance of diseases such as flu. Our results show that limited data reduces our ability to predict unobserved cases. Based on laboratory surveillance data, we prototype each season according to the dominating virus (H3N2, H1N1, B) and show that high intensity outbreaks are correlated with early peak times. These findings are in accordance with the dynamics observed for influenza outbreaks in the US.

Title: Evaluating the diagnostic accuracy of the WHO Severe Acute Respiratory Infection (SARI) criteria in Middle Eastern children under two years over three respiratory seasons Content: OBJECTIVE: The World Health Organization created the Severe Acute Respiratory Infection (SARI) criteria in 2011 to monitor influenza (flu)-related hospitalization. Many studies have since used the SARI case definition as inclusion criteria for surveillance studies. We sought to determine the sensitivity, specificity, positive predictive value, and negative predictive value of the SARI criteria for detecting ten different respiratory viruses in a Middle Eastern pediatric cohort. MATERIALS AND METHODS: The data for this study comes from a prospective acute respiratory surveillance study of hospitalized children <2 years in Amman, Jordan from March 16, 2010 to March 31, 2013. Participants were recruited if they had a fever and/or respiratory symptoms. Nasal and throat swabs were obtained and tested by real-time RT-PCR for eleven viruses. Subjects meeting SARI criteria were determined post-hoc. Sensitivity, specificity, positive predictive value, and negative predictive value of the SARI case definition for detecting ten different viruses were calculated and results were stratified by age. RESULTS: Of the 3,175 patients enrolled, 3,164 were eligible for this study, with a median age of 3.5 months, 60.4% male, and 82% virus-positive (44% RSV and 3.8% flu). The sensitivity and specificity of the SARI criteria for detecting virus-positive patients were 44% and 77.9%, respectively. Sensitivity of SARI criteria for any virus was lowest in children <3 months at 22.4%. Removing fever as a criterion improved the sensitivity by 65.3% for detecting RSV in children <3 months; whereas when cough was removed, the sensitivity improved by 45.5% for detecting flu in same age group. CONCLUSIONS: The SARI criteria have poor sensitivity for detecting RSV, flu, and other respiratory viruses—particularly in children <3 months. Researchers and policy makers should use caution if using the criteria to estimate burden of disease in children.

Title: Comparison of the fecal microbiota of domestic commercial meat, laboratory, companion, and shelter rabbits (Oryctolagus cuniculi) Content: BACKGROUND: Rabbits are cecotrophic, hindgut-fermenters that rely heavily on their gastrointestinal microbiota for optimal digestion of plant-based diets. Dysbiosis, caused by disruption of the gastrointestinal microbiota, is known to predispose rabbits to rabbit enteritis complex (REC), a major cause of morbidity and mortality. The objectives of this study were to describe the fecal microbiota of domestic rabbits from a variety of settings (commercial meat, companion, laboratory, and shelter) and to identify how factors such as age, season, and routine antimicrobial use affect the fecal microbiota composition. RESULTS: A total of 86 pooled commercial meat, 54 companion, 14 pooled laboratory, and 14 shelter rabbit fecal samples were evaluated using 16S rRNA gene sequencing of the V4 region. In all sample types, the predominant bacterial phylum was Firmicutes. Other commonly identified phyla (composing ≥ 1% of the total microbiota composition) were Verrucomicrobia, Proteobacteria, and Bacteroidetes. Significant differences in composition were noted between commercial, companion, laboratory, and shelter rabbit samples for proportions of Verrucomicrobia (P < 0.01), Proteobacteria (P < 0.01), and Lentisphaerae (P = 0.01) within the total microbiota. Within the commercial meat rabbit samples, significant differences between the microbiota composition of growers (n = 42) and does (n = 44) were limited to one unclassified Firmicutes (P = 0.03) and no differences were identified at the phylum level. Significant differences were present between fecal samples taken from rabbits during the summer (n = 44) compared to the winter (n = 42), with Firmicutes (P = 0.04), Verrucomicrobia (P = 0.03), Proteobacteria (P = 0.02), Deinococcus-Thermus (P = 0.04), Armatimonadates (P = 0.003), and Actinobacteria (P = 0.03) forming significantly different proportions of the microbiota. The only significant difference in composition between those farms that routinely reported antimicrobial use and those that did not was in one unclassified Bacteroidetes (P < 0.05) and no differences were identified at the phylum level. CONCLUSIONS: Rabbit husbandry and diet, in addition to season, significantly influence the fecal microbiota composition of domestic rabbits, while age of the rabbit post-weaning has minimal impact. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12917-018-1464-6) contains supplementary material, which is available to authorized users.

Title: Impacts of rapid flu clinic services at an emergency department during the pandemic flu season Content: BACKGROUND: We performed an assessment of an independent rapid flu clinic service (RFCS) unit, which was set up outside the emergency department (ED) during the 2009 H1N1 pandemic season. The unit was able to relieve the crowding of regular ambulatory and emergency services. METHODS: Between August and December 2009, a total of 6,152 patients with influenza-like illness were enrolled in this observational retrospective study. Patients with positive influenza tests were interviewed to evaluate the efficiency of RFCS. RESULTS: The mean length of stay (LOS) for the RFCS was 50 minutes, which was shorter than the LOS for ambulatory services (1 hour) and regular ED services (3.5 hours). Overall, 88% of patients were satisfied with the RFCS. Of 6,152 patients receiving flu tests, 1,235 (20%) had a positive result. Fever (odds ratio [OR], 4.28, 95% confidence interval [CI]: 3.11-5.89), fever combined with cough and sore throat (OR, 2.52; 95% CI: 2.18-2.92), fever combined with sore throat (OR, 2.42; 95% CI: 2.13-2.75), history of contacting confirmed flu patients within 7 days (OR, 2.40; 95% CI: 2.07-2.78), fever combined with cough (OR, 2.19; 95% CI: 1.92-2.47), sore throat (OR, 2.03, 95% CI: 1.79-2.30); and cough (OR, 1.91, 95% CI: 1.69-2.17) were significantly associated with positive influenza tests. CONCLUSION: Setting up the RFSC was beneficial to health care facilities during a pandemic flu season.

Title: Evaluation of the Xpert Flu A Panel nucleic acid amplification-based point-of-care test for influenza A virus detection and pandemic H1 subtyping Content: Abstract Background Influenza antigenic point-of-care (POC) tests are too insensitive for individual reliable diagnosis of influenza virus infections without additional laboratory confirmation. Molecular POC tests could be a valuable alternative. Objectives To evaluate the first influenza molecular POC test commercially available, the Cepheid Xpert Flu A Panel designed to simultaneously detect influenza A virus and subtype A(H1N1) 2009 pandemic virus, and compare it with in-house real-time RT-PCR (qRT-PCR). Study design Clinical specimens positive for influenza virus and influenza virus isolates with different viral loads and of different type and subtype were used to determine the analytical reactivity and sensitivity. A panel of pathogen negative specimens and isolates of 19 different respiratory pathogens were used to determine the analytical specificity. Results Except A(H9N2) virus the Xpert Flu A Panel detected A(H1N1) seasonal and 2009 pandemic, A(H3N2), A(H5N2), A(H5N1) and A(H7N7) viruses and correctly subtyped A(H1N1) 2009 virus. Analytical sensitivity was similar to qRT-PCR in the range of 400–5000 viral particles per ml. However, of most subtypes some specimens with cycle threshold values greater than 30 in qRT-PCR and A(H1N1) 2009 specimens with inconsistent results in the qRT-PCR due to primer or probe mismatches were not detected in the Xpert Flu A Panel. Analytical specificity was 100%. Conclusions The Xpert Flu A Panel is the first commercially available POC molecular test for detection of influenza A virus and determination of the H1 2009 subtype and is analytically reasonable sensitive compared with qRT-PCR and highly specific and therefore a welcome alternative to antigenic POC tests.

Title: Tuberculosis and COVID-19 in 2020: lessons from the past viral outbreaks and possible future outcomes Content: Background. The threat of contagious infectious diseases is constantly evolving, as demographic explosion, travel globalization and changes in human lifestyle increase the risk of spreading pathogens, leading to accelerated changes in disease landscape. Of particular interest is the aftermath of superimposing viral epidemics (especially SARS-CoV-2) over long-standing diseases, such as tuberculosis (TB), which remains a significant disease for public health worldwide and especially in emerging economies. Methods and Results. PubMed electronic database was requested for relevant articles linking TB, influenza and SARS-CoV viruses and subsequently assessed eligibility according to inclusion criteria. Using a data mining approach, we also queried the COVID-19 Open Research Dataset (CORD-19). We aimed to answer the following questions: What can be learned from other coronavirus outbreaks (with a focus on TB patients)? Is coinfection (TB and SARS-CoV-2) more severe? Is there a vaccine for SARS-CoV-2? How does the TB vaccine affect COVID-19? How does one diagnosis affect the other? Discussions. Few essential elements about TB and SARS-CoV coinfections were discussed. First, lessons from the past outbreaks (other coronaviruses), as well as influenza pandemic / seasonal outbreaks have taught the importance of infection control to avoid the severe impact on TB patients. Second, although challenging due to data scarcity, investigating the pathological pathways linking TB and SARS-CoV-2 leads to the idea that their coexistence might yield a more severe clinical evolution. Finally, we addressed the issues of vaccination and diagnostic reliability in the context of coinfection. Conclusions. Because viral respiratory infections and TB impede the host's immune responses, it can be assumed that their harmful synergism may contribute to more severe clinical evolution. Despite the rapidly growing number of cases, the data needed to predict the impact of the COVID-19 pandemic on patients with latent TB and TB sequelae still lies ahead.

Title: Hajj-associated infections Content: Abstract Background The Hajj is the largest annual mass gathering event in the world, thus favoring the transmission of various infections: 183 different nationalities, high temperatures, coincidence with the start of the flu season in the Northern hemisphere, a long barefoot walk, tent-type accommodation, communal toilet facilities, absence of food control, and sharing of razors. Infections are the first cause of hospital admission, which often occurs in the home country of pilgrims. Methods Literature review on PubMed from 1952 to November 2015 on the epidemiology and prevention of infections contracted during the Hajj, using the keywords “Hajj” and “infections”. Results Respiratory tract infections, ENT infections, influenza, pyogenic pneumonia, whooping cough, and tuberculosis are most frequently observed during the Hajj. Outbreaks of meningococcal meningitis have been reported in pilgrims and their contacts. Waterborne infections such as gastroenteritis and hepatitis A are common, despite the improvement of health conditions. Pyoderma and furuncles are also frequently observed. Recently, dengue fever, Alkhumra hemorrhagic fever, and Rift Valley fever have emerged but no case of MERS-coronavirus, appeared in Saudi Arabia in 2012, have yet been observed during the 2012–2014 Hajj. Conclusion Prevention is based on compulsory meningococcal vaccination, vaccination against seasonal influenza and pneumococcal infections for pilgrims at high risk of contracting the infection, and on vaccination against hepatitis A. Updating immunization for diphtheria/tetanus/poliomyelitis/pertussis and measles/mumps is also crucial and pilgrims must comply with hygiene precautions.

Title: Social Distancing and Personal Protective Measures Decrease Influenza Morbidity and Mortality Content: Seasonal influenza (flu) is an underappreciated source of disease morbidity and mortality worldwide. While vaccination remains the cornerstone of influenza prevention, common measures practiced during the COVID-19 pandemic such as social distancing, the use of protective face masks, and frequent hand washing are rarely utilized during flu season. In this investigation, we examined the effect of these preventative measures in decreasing influenza burden this year. We examined three countries with major COVID-19 outbreaks i.e. China, Italy and the United States, and compared the flu activity this year to the average of the last 4 years (2015-2019). We found that this year in China and Italy, there was a significantly steeper decline of flu cases than average, which correlated with an increase in positive COVID-19 case reports in those countries. These "averted" cases can be translated into a substantial decrease in morbidity and mortality. As such, we conclude that the current COVID-19 pandemic is a reminder that behavioral measures can decrease the burden of communicable respiratory infections, and these measures should be adopted to an extent during normal influenza season.

Title: High Level Antibody Response to Pandemic Influenza H1N1/09 Virus Is Associated With Interferon-Induced Transmembrane Protein-3 rs12252-CC in Young Adults Content: Background: The C allele of the interferon-induced transmembrane protein-3 (IFITM3) SNP rs12252, a common allele in South East Asia and China, is strongly associated with severe influenza infection. However, despite the high occurrence of rs12252-CC genotype in Chinese population (~25%), severe influenza infection is rare. The aim of study is to determine whether rs12252-CC individuals have pre-existing antibody responses to previous seasonal influenza infections. Cohort and Method: A total 99 young healthy volunteers (18–20 years) were recruited and received an influenza seasonal Vaccination [A/Switzerland/9715293/2013(H3N2), A/California/7/2009 (pdm09H1N1) and B/Jeep/3073/2013-like virus (Flu-B)]. Plasma and gDNA was isolated from each volunteer before, and 14, 28, 180, 360, and 540 days after vaccination. Additionally, 68 elderlies (>65 years) were also recruited as a control group to compare the levels of antibodies at baseline between the young adults and the elderly. For each sample IFITM3 rs12252 genotype was determined and antibody levels in response to pdmH1N1, H3N2 and Influenza B infection were measured for each time point. Results: We found a significantly higher level of pre-existing antibodies to pandemic influenza H1N1/09 virus (pdm09H1N1) but not to H3N2 or FluB in CC donors in comparison with CT/TT donors prior to vaccination. No impact of IFITM3 genotype in boosting influenza specific antibodies in young adults within 1 year after receiving seasonal influenza vaccination was observed. In addition, there was no difference in pdm09H1N1 specific antibody levels observed in the elderly cohort between volunteers carrying different IFITM3 genotypes. Higher levels of antibodies to pdmH1N1 were observed in elderly CC carriers when compared to the young CC carriers, but this trend was not replicated in TT carriers. Conclusion: IFITM3-rs12252 CC carriers exhibit a high level of pre-existing immunity to pdm09H1N1 compared to TT carriers in the young cohort. This suggests that compensatory mechanisms exist which might contribute to viral control in patients carrying the rs12252-CC genotype who do not become sick after flu infection. However, such a potential compensatory effect appears to be lost overtime, as evidenced in the elderly cohort. If this compensatory mechanism is lost, it may make the CC carrying elderly more susceptible to severe influenza infection.

Title: Influenza A non-H1N1 associated with acute respiratory failure and acute renal failure in a previously vaccinated cystic fibrosis patient Content: In the 2014 - 2015 season, most influenza infections were due to A (H3N2) viruses. More than two-thirds of circulating A (H3N2) viruses are antigenically and genetically different (drifted) from the A (H3N2) vaccine component of 2014 - 2015 northern and southern Hemisphere seasonal influenza vaccines. The purpose of this paper is to report a case of seasonal influenza A non-H1N1 infection that occurred in June 2015 in an adult cystic fibrosis patient with severe lung disease previously vaccinated with the anti-flu trivalent vaccine. The patient evolved to respiratory and renal failure (without rhabdomyolysis) and was placed under mechanical ventilation and hemodialysis. The clinical outcome was positive after 39 days of hospital stay. In addition, the patient was clinically stable after 18 months of follow-up. With the recent advances in critical care medicine and in cystic fibrosis treatment, survival with advanced pulmonary disease in cystic fibrosis presents new questions and potential problems, which are still being formulated.

Title: Characterising the epidemic spread of Influenza A/H3N2 within a city through phylogenetics Content: Infecting large portions of the global population, seasonal influenza is a major burden on societies around the globe. While the global source sink dynamics of the different seasonal influenza viruses have been studied intensively, it’s local spread remains less clear. In order to improve our understanding of how influenza is transmitted on a city scale, we collected an extremely densely sampled set of influenza sequences alongside patient metadata. To do so, we sequenced influenza viruses isolated from patients of two different hospitals, as well as private practitioners in Basel, Switzerland during the 2016/2017 influenza season. The genetic sequences reveal that repeated introductions into the city drove the influenza season. We then reconstruct how the effective reproduction number changed over the course of the season. We find trends in transmission dynamics correlated positively with trends in temperature, but not relative humidity nor school holidays. Alongside the genetic sequence data that allows us to see how individual cases are connected, we gathered patient information, such as the age or household status. Zooming into the local transmission outbreaks suggests that the elderly were to a large extent infected within their own transmission network, while school children likely drove the spread within the remaining transmission network. These patterns will be valuable to plan interventions combating the spread of respiratory diseases within cities given that similar patterns are observed for other influenza seasons and cities. Author summary As shown with the current SARS-CoV-2 pandemic, respiratory diseases can quickly spread around the globe. While it can be hugely important to understand how diseases spread around the globe, local spread is most often the main driver of novel infections of respiratory diseases such as SARS-CoV-2 or influenza. We here use genetic sequence data alongside patient information to better understand what the drives the local spread of influenza by looking at the 2016/2017 influenza season in Basel, Switzerland as an example. The genetic sequence data allows us to reconstruct the how the transmission dynamics changed over the course of the season, which we correlate to changes, but not humidity or school holidays. Additionally, the genetic sequence data allows us to see how individual cases are connected. Using patient information, such as age and household status our analyses suggest that the elderly mainly transmit within their own transmission network. Additionally, they suggest that school aged children, but not pre-school aged children are important drivers of the local spread of influenza.

Title: The impact of media coverage on the transmission dynamics of human influenza Content: BACKGROUND: There is an urgent need to understand how the provision of information influences individual risk perception and how this in turn shapes the evolution of epidemics. Individuals are influenced by information in complex and unpredictable ways. Emerging infectious diseases, such as the recent swine flu epidemic, may be particular hotspots for a media-fueled rush to vaccination; conversely, seasonal diseases may receive little media attention, despite their high mortality rate, due to their perceived lack of newness. METHODS: We formulate a deterministic transmission and vaccination model to investigate the effects of media coverage on the transmission dynamics of influenza. The population is subdivided into different classes according to their disease status. The compartmental model includes the effect of media coverage on reporting the number of infections as well as the number of individuals successfully vaccinated. RESULTS: A threshold parameter (the basic reproductive ratio) is analytically derived and used to discuss the local stability of the disease-free steady state. The impact of costs that can be incurred, which include vaccination, education, implementation and campaigns on media coverage, are also investigated using optimal control theory. A simplified version of the model with pulse vaccination shows that the media can trigger a vaccinating panic if the vaccine is imperfect and simplified messages result in the vaccinated mixing with the infectives without regard to disease risk. CONCLUSIONS: The effects of media on an outbreak are complex. Simplified understandings of disease epidemiology, propogated through media soundbites, may make the disease significantly worse.

Title: Viral Etiology of Acute Respiratory Infection in Gansu Province, China, 2011 Content: BACKGROUND: Acute respiratory infections (ARIs) are the leading cause of children and their leading killer. ARIs are responsible for at least six percent of the world's disability and death. Viruses are one of the most common agents causing ARIs. Few studies on the viral etiology and clinical characteristics of ARIs have been performed in the northwest region of China, including Gansu Province. METHODS: Clinical and demographic information and throat swabs were collected from 279 patients from January 1st to December 30st, 2011. Multiplex RT-PCR was performed to detect 16 respiratory viral pathogens. RESULTS: 279 patients were admitted for ARIs. The patients aged from 1 month to 12 years, with the median age of 2 years. Of which, 105 (37.6%) were positive for at least one pathogen. A total of 136 respiratory viral pathogens were identified from the 105 patients. Respiratory syncytial virus (RSV) was the most frequently detected pathogen (26.5%, 36/136), followed by parainfluenza virus (PIV) 1–3 (22.1%, 30/136), human rhinovirus (HRV) (21.3%, 29/136), human coronavirus (CoV) (10.3%, 14/136) and human adenovirus (HAdV) (9.6%, 13/136). Influenza A (Flu A), human metapneumovirus (hMPV) and human bocavirus (BoCA) were found 4.4%, 3.7% and 2.2%, respectively. Influenza B (Flu B) and seasonal influenza A H1N1(sH1N1) were not detected. Single-infections were detected in 30.5% (85/279) of cases. RSV was the most common pathogens in patients under 1 year and showed seasonal variation with peaks during winter and spring. CONCLUSIONS: This paper presents data on the epidemiology of viral pathogens associated with ARIs among children in Gansu Province, China. RSV is most frequently detected in our study. The findings could serve as a reference for local CDC in drawing up further plans to prevent and control ARIs.

Title: Potential impact of seasonal forcing on a SARS-CoV-2 pandemic. Content: A novel coronavirus (SARS-CoV-2) first detected in Wuhan, China, has spread rapidly since December 2019, causing more than 100,000 confirmed infections and 4000 fatalities (as of 10 March 2020). The outbreak has been declared a pandemic by the WHO on Mar 11, 2020. Here, we explore how seasonal variation in transmissibility could modulate a SARS-CoV-2 pandemic. Data from routine diagnostics show a strong and consistent seasonal variation of the four endemic coronaviruses (229E, HKU1, NL63, OC43) and we parameterise our model for SARS-CoV-2 using these data. The model allows for many subpopulations of different size with variable parameters. Simulations of different scenarios show that plausible parameters result in a small peak in early 2020 in temperate regions of the Northern Hemisphere and a larger peak in winter 2020/2021. Variation in transmission and migration rates can result in substantial variation in prevalence between regions. While the uncertainty in parameters is large, the scenarios we explore show that transient reductions in the incidence rate might be due to a combination of seasonal variation and infection control efforts but do not necessarily mean the epidemic is contained. Seasonal forcing on SARS-CoV-2 should thus be taken into account in the further monitoring of the global transmission. The likely aggregated effect of seasonal variation, infection control measures, and transmission rate variation is a prolonged pandemic wave with lower prevalence at any given time, thereby providing a window of opportunity for better preparation of health care systems.

Title: Potential impact of seasonal forcing on a SARS-CoV-2 pandemic Content: A novel coronavirus (SARS-CoV-2) first detected in Wuhan, China, has spread rapidly since December 2019, causing more than 80,000 confirmed infections and 2,700 fatalities (as of Feb 27, 2020). Imported cases and transmission clusters of various sizes have been reported globally suggesting a pandemic is likely. Here, we explore how seasonal variation in transmissibility could modulate a SARS-CoV-2 pandemic. Data from routine diagnostics show a strong and consistent seasonal variation of the four endemic coronaviruses (229E, HKU1, NL63, OC43) and we parameterize our model for SARS-CoV-2 using these data. The model allows for many subpopulations of different size with variable parameters. Simulations of different scenarios show that plausible parameters result in a small peak in early 2020 in temperate regions of the Northern Hemisphere and a larger peak in winter 2020/2021. Variation in transmission and migration rates can result in substantial variation in prevalence between regions. While the uncertainty in parameters is large, the scenarios we explore show that transient reductions in the incidence rate might be due to a combination of seasonal variation and infection control efforts but do not necessarily mean the epidemic is contained. Seasonal forcing on SARS-CoV-2 should thus be taken into account in the further monitoring of the global transmission. The likely aggregated effect of seasonal variation, infection control measures and transmission rate variation is a prolonged pandemic wave with lower prevalence at any given time, thereby providing a window of opportunity for better preparation of health care systems.

Title: Potential impact of seasonal forcing on a SARS-CoV-2 pandemic Content: A novel coronavirus (SARS-CoV-2) first detected in Wuhan, China, has spread rapidly since December 2019, causing more than 100,000 confirmed infections and 4000 fatalities (as of 10 March 2020). The outbreak has been declared a pandemic by the WHO on Mar 11, 2020. Here, we explore how seasonal variation in transmissibility could modulate a SARS-CoV-2 pandemic. Data from routine diagnostics show a strong and consistent seasonal variation of the four endemic coronaviruses (229E, HKU1, NL63, OC43) and we parameterise our model for SARS-CoV-2 using these data. The model allows for many subpopulations of different size with variable parameters. Simulations of different scenarios show that plausible parameters result in a small peak in early 2020 in temperate regions of the Northern Hemisphere and a larger peak in winter 2020/2021. Variation in transmission and migration rates can result in substantial variation in prevalence between regions. While the uncertainty in parameters is large, the scenarios we explore show that transient reductions in the incidence rate might be due to a combination of seasonal variation and infection control efforts but do not necessarily mean the epidemic is contained. Seasonal forcing on SARS-CoV-2 should thus be taken into account in the further monitoring of the global transmission. The likely aggregated effect of seasonal variation, infection control measures, and transmission rate variation is a prolonged pandemic wave with lower prevalence at any given time, thereby providing a window of opportunity for better preparation of health care systems.

Title: How diseases rise and fall with the seasons—and what it could mean for coronavirus Content: Scientists and doctors have observed for thousands of years that some diseases, such as polio and influenza, rise and fall with the seasons But why? Ongoing research in animals and humans suggests a variety of causes, including changes in the environment (like pH, temperature, and humidity) and even seasonal and daily changes to our own immune systems Figuring out those answers could one day make all the difference in minimizing the impact of infectious disease outbreaks—such as coronavirus disease 2019

Title: Estimating the Early Outbreak Cumulative Incidence of COVID-19 in the United States: Three Complementary Approaches Content: Effectively designing and evaluating public health responses to the ongoing COVID-19 pandemic requires accurate estimation of the weekly incidence of COVID-19. Unfortunately, a lack of systematic testing across the United States (US) due to equipment shortages and varying testing strategies has hindered the usefulness of the reported positive COVID-19 case counts. We introduce three complementary approaches to estimate the cumulative incidence of symptomatic COVID-19 during the early outbreak in each state in the US as well as in New York City, using a combination of excess influenza-like illness reports, COVID-19 test statistics, and COVID-19 mortality reports. Instead of relying on an estimate from a single data source or method that may be biased, we provide multiple estimates, each relying on different assumptions and data sources. Across our three approaches, there is a consistent conclusion that estimated state-level COVID-19 symptomatic case counts from March 1 to April 4, 2020 varied from 5 to 50 times greater than the official positive test counts. Nationally, our estimates of COVID-19 symptomatic cases in the US as of April 4 have a likely range of 2.2 to 5.1 million cases, with possibly as high as 8.1 million cases, up to 26 times greater than the cumulative confirmed cases of about 311,000. Extending our method to May 16, 2020, we estimate that cumulative symptomatic incidence ranges from 6.0 to 12.2 million, which compares with 1.5 million positive test counts. Our approaches demonstrate the value of leveraging existing influenza-like-illness surveillance systems during the flu season for measuring the burden of new diseases that share symptoms with influenza-like-illnesses. Our methods may prove useful in assessing the burden of COVID-19 during upcoming flu seasons in the US and other countries with comparable influenza surveillance systems.

Title: Health Information–Seeking Patterns of the General Public and Indications for Disease Surveillance: Register-Based Study Using Lyme Disease Content: BACKGROUND: People using the Internet to find information on health issues, such as specific diseases, usually start their search from a general search engine, for example, Google. Internet searches such as these may yield results and data of questionable quality and reliability. Health Library is a free-of-charge medical portal on the Internet providing medical information for the general public. Physician’s Databases, an Internet evidence-based medicine source, provides medical information for health care professionals (HCPs) to support their clinical practice. Both databases are available throughout Finland, but the latter is used only by health professionals and pharmacies. Little is known about how the general public seeks medical information from medical sources on the Internet, how this behavior differs from HCPs’ queries, and what causes possible differences in behavior. OBJECTIVE: The aim of our study was to evaluate how the general public’s and HCPs’ information-seeking trends from Internet medical databases differ seasonally and temporally. In addition, we aimed to evaluate whether the general public’s information-seeking trends could be utilized for disease surveillance and whether media coverage could affect these seeking trends. METHODS: Lyme disease, serving as a well-defined disease model with distinct seasonal variation, was chosen as a case study. Two Internet medical databases, Health Library and Physician’s Databases, were used. We compared the general public’s article openings on Lyme disease from Health Library to HCPs’ article openings on Lyme disease from Physician’s Databases seasonally across Finland from 2011 to 2015. Additionally, media publications related to Lyme disease were searched from the largest and most popular media websites in Finland. RESULTS: Both databases, Health Library and Physician’s Databases, show visually similar patterns in temporal variations of article openings on Lyme disease in Finland from 2011 to 2015. However, Health Library openings show not only an increasing trend over time but also greater fluctuations, especially during peak opening seasons. Outside these seasons, publications in the media coincide with Health Library article openings only occasionally. CONCLUSIONS: Lyme disease–related information-seeking behaviors between the general public and HCPs from Internet medical portals share similar temporal variations, which is consistent with the trend seen in epidemiological data. Therefore, the general public’s article openings could be used as a supplementary source of information for disease surveillance. The fluctuations in article openings appeared stronger among the general public, thus, suggesting that different factors such as media coverage, affect the information-seeking behaviors of the public versus professionals. However, media coverage may also have an influence on HCPs. Not every publication was associated with an increase in openings, but the higher the media coverage by some publications, the higher the general public’s access to Health Library.

Title: The Pace and Pulse of the Fight against Coronavirus across the US, A Google Trends Approach Content: The coronavirus pandemic is impacting our lives at unprecedented speed and scale - including how we eat and work, what we worry about, how much we move, and our ability to earn. Google Trends can be used as a proxy for what people are thinking, needing, and planning. We use it to provide both insights into, and potential indicators of, important changes in information-seeking patterns during pandemics like COVID-19. Key questions we address are: (1) What is the relationship between the coronavirus outbreak and internet searches related to healthcare seeking, government support programs, media sources of different ideologies, planning around social activities, travel, and food, and new coronavirus-specific behaviors and concerns?; (2) How does the popularity of search terms differ across states and regions and can we explain these differences?; (3) Can we find distinct, tangible search patterns across states suggestive of policy gaps to inform pandemic response? (4) Does Google Trends data correlate with and potentially precede real-life events? We suggest strategic shifts for policy makers to improve the precision and effectiveness of non-pharmaceutical interventions (NPIs) and recommend the development of a real-time dashboard as a decision-making tool. Methods used include trend analysis of US search data; geographic analyses of the differences in search popularity across US states during March 1st to April 15th, 2020; and Principal Component Analyses (PCA) to extract search patterns across states.

Title: Influenza as a model system for studying the cross-species transfer and evolution of the SARS coronavirus. Content: Severe acute respiratory syndrome coronavirus (SARS-CoV) moved into humans from a reservoir species and subsequently caused an epidemic in its new host. We know little about the processes that allowed the cross-species transfer of this previously unknown virus. I discuss what we have learned about the movement of viruses into humans from studies of influenza A, both how it crossed from birds to humans and how it subsequently evolved within the human population. Starting with a brief review of severe acute respiratory syndrome to highlight the kinds of problems we face in learning about this viral disease, I then turn to influenza A, focusing on three topics. First, I present a reanalysis of data used to test the hypothesis that swine served as a "mixing vessel" or intermediate host in the transmission of avian influenza to humans during the 1918 "Spanish flu" pandemic. Second, I review studies of archived viruses from the three recent influenza pandemics. Third, I discuss current limitations in using molecular data to study the evolution of infectious disease. Although influenza A and SARS-CoV differ in many ways, our knowledge of influenza A may provide important clues about what limits or favours cross-species transfers and subsequent epidemics of newly emerging pathogens.

Title: Using web search queries to monitor influenza-like illness: an exploratory retrospective analysis, Netherlands, 2017/18 influenza season Content: BACKGROUND: Despite the early development of Google Flu Trends in 2009, standards for digital epidemiology methods have not been established and research from European countries is scarce. AIM: In this article, we study the use of web search queries to monitor influenza-like illness (ILI) rates in the Netherlands in real time. METHODS: In this retrospective analysis, we simulated the weekly use of a prediction model for estimating the then-current ILI incidence across the 2017/18 influenza season solely based on Google search query data. We used weekly ILI data as reported to The European Surveillance System (TESSY) each week, and we removed the then-last 4 weeks from our dataset. We then fitted a prediction model based on the then-most-recent search query data from Google Trends to fill the 4-week gap (‘Nowcasting’). Lasso regression, in combination with cross-validation, was applied to select predictors and to fit the 52 models, one for each week of the season. RESULTS: The models provided accurate predictions with a mean and maximum absolute error of 1.40 (95% confidence interval: 1.09–1.75) and 6.36 per 10,000 population. The onset, peak and end of the epidemic were predicted with an error of 1, 3 and 2 weeks, respectively. The number of search terms retained as predictors ranged from three to five, with one keyword, ‘griep’ (‘flu’), having the most weight in all models. DISCUSSION: This study demonstrates the feasibility of accurate, real-time ILI incidence predictions in the Netherlands using Google search query data.

Title: How Should the Rehabilitation Community Prepare for 2019-nCoV? Content: With the novel coronavirus 2019 (2019-nCoV) pandemic spreading quickly in the United States and the world, it is urgent that the rehabilitation community quickly understands the epidemiology of the virus and what we can and must do to face this microbial adversary at the early stages of this likely long global pandemic. The 2019-nCoV is a novel virus so most of the world's population does not have prior immunity to it. It is more infectious and fatal than seasonal influenza, and definitive treatment and a vaccine are months away. Our arsenal against it is currently mainly social distancing and infection control measures.

Title: How necessary is a fast testkit for mitigation of pandemic flu? Content: It is widely feared that a novel, highly pathogenic, human transmissible influenza virus may evolve that could cause the next global pandemic. Mitigating the spread of such an influenza pandemic would require not only the timely administration of antiviral drugs to those infected, but also the implementation of suitable intervention policies for stunting the spread of the virus. Towards this end, mathematical modelling and simulation studies are crucial as they allow us to evaluate the predicted effectiveness of the various intervention policies before enforcing them. Diagnosis plays a vital role in the overall pandemic management framework by detecting and distinguishing the pathogenic strain from the less threatening seasonal strains and other influenza-like illnesses. This allows treatment and intervention to be deployed effectively, given limited antiviral supplies and other resources. However, the time required to design a fast and accurate testkit for novel strains may limit the role of diagnosis. Herein, we aim to investigate the cost and effectiveness of different diagnostic methods using a stochastic agent-based city-scale model, and then address the issue of whether conventional testing approaches, when used with appropriate intervention policies, can be as effective as fast testkits in containing a pandemic outbreak. We found that for mitigation purposes, fast and accurate testkits are not necessary as long as sufficient medication is given, and are generally recommended only when used with extensive contact tracing and prophylaxis. Additionally, in the event of insufficient medication and fast testkits, the use of slower, conventional testkits together with proper isolation policies while waiting for the diagnostic results can be an equally effective substitute.

Title: Implications of COVID-19 Outbreak on Immune Therapies in Multiple Sclerosis Patients-Lessons Learned From SARS and MERS Content: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic keeps the world in suspense. In addition to the fundamental challenges for the health care system, the individual departments must decide how to deal with patients at risk. Neurologists are confronted with the question, how they should advise their patients regarding immunosuppressive treatment. In particular, the large number of different disease-modifying therapies (DMTs) in the treatment of neuroimmunological diseases such as multiple sclerosis poses a challenge. To a limited extent, it might be useful to transfer knowledge from previous SARS- and Middle East respiratory syndrome (MERS) coronavirus outbreaks in 2002/2003 and 2012 to the current situation. Overall, immunosuppressive therapy does neither seem to have a major impact on infection with SARS- and MERS-CoV nor does it seem to lead to a severe disease course in many cases. Considering the immunological responses against infections with novel coronaviruses in humans, interferons, glatiramer acetate, and teriflunomide appear to be safe. As lymphopenia seems to be associated with a more severe disease course, all DMTs causing lymphopenia, such as cladribine, alemtuzumab, and dimethyl fumarate, need to be reviewed more thoroughly. As they are, in general, associated with a higher risk of infection, depleting anti-CD20 antibodies may be problematic drugs. However, it has to be differentiated between the depletion phase and the phase of immune reconstitution. In summary, previous coronavirus outbreaks have not shown an increased risk for immunocompromised patients. Patients with severe neuroimmunological diseases should be kept from hasty discontinuation of immunotherapy.

Title: Implications of COVID-19 Outbreak on Immune Therapies in Multiple Sclerosis Patients—Lessons Learned From SARS and MERS Content: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic keeps the world in suspense. In addition to the fundamental challenges for the health care system, the individual departments must decide how to deal with patients at risk. Neurologists are confronted with the question, how they should advise their patients regarding immunosuppressive treatment. In particular, the large number of different disease-modifying therapies (DMTs) in the treatment of neuroimmunological diseases such as multiple sclerosis poses a challenge. To a limited extent, it might be useful to transfer knowledge from previous SARS- and Middle East respiratory syndrome (MERS) coronavirus outbreaks in 2002/2003 and 2012 to the current situation. Overall, immunosuppressive therapy does neither seem to have a major impact on infection with SARS- and MERS-CoV nor does it seem to lead to a severe disease course in many cases. Considering the immunological responses against infections with novel coronaviruses in humans, interferons, glatiramer acetate, and teriflunomide appear to be safe. As lymphopenia seems to be associated with a more severe disease course, all DMTs causing lymphopenia, such as cladribine, alemtuzumab, and dimethyl fumarate, need to be reviewed more thoroughly. As they are, in general, associated with a higher risk of infection, depleting anti-CD20 antibodies may be problematic drugs. However, it has to be differentiated between the depletion phase and the phase of immune reconstitution. In summary, previous coronavirus outbreaks have not shown an increased risk for immunocompromised patients. Patients with severe neuroimmunological diseases should be kept from hasty discontinuation of immunotherapy.

Title: Prevalence of Flu-like Symptoms and COVID-19 in Healthcare Workers from India Content: Background: The current COVID-19 pandemic is unprecedented. As the numbers expand exponentially, a paucity of data regarding health care workers (HCWs), who are at the forefront of this disaster, exists. Hence we decided to conduct a study amongst the HCWs to determine the prevalence and risk factor stratification. Methods: This was an online questionnaire-based survey of healthcare workers conducted at Max Super Speciality Hospital, Saket, New Delhi, India from 23rd March to 30th April 2020. Data on flu-like symptoms, travel history, posting in high-risk or low risk zones, and prophylactic drugs was collected. Results: Out of the 18000 HCWs who were approached 4403 responded and adequate data of 3667 was available for analysis. 14.7% had flu-like symptoms. 1.8% (20/1113) of the participants tested were positive for the virus. HCWs posted in the high-risk zones had more symptoms than those working in low-risk zones (169/539, 31.4% vs 679/3128, 21.7%), p<0.001; but no difference in COVID-19 positivity rates (p=0.849). Symptomatic HCWs had higher positivity (10/193, 5.2%) than the asymptomatic ones (10/920, 1.1%), p=0.001. HCQ was taken by 755/1113 (67.8%) people and 14 (1.9%) of these reported positive for the virus. Conclusion: This is the first study on healthcare workers from India to the best of our knowledge. Our findings suggest that posting in a high-risk zone with adequate PPE does not pose higher risk to the HCWs. Moreover, HCQ as a prophylactic has no use. ClinicalTrials.gov Identifier: NCT04339608.

Title: Prevalence of Flu-like Symptoms and COVID-19 in Healthcare Workers from India. Content: Background The current COVID-19 pandemic is unprecedented. As the numbers expand exponentially, a paucity of data regarding health care workers (HCWs), who are at the forefront of this disaster, exists. Hence we decided to conduct a study amongst the HCWs to determine the prevalence and risk factor stratification. Methods This was an online questionnaire-based survey of healthcare workers conducted at Max Super Speciality Hospital, Saket, New Delhi, India from 23rd March to 30th April 2020. Data on flu-like symptoms, travel history, posting in high-risk or low risk zones, and prophylactic drugs was collected. Results Out of the 18000 HCWs who were approached 4403 responded and adequate data of 3667 was available for analysis. 14.7% had flu-like symptoms. 1.8% (20/1113) of the participants tested were positive for the virus. HCWs posted in the high-risk zones had more symptoms than those working in low-risk zones (169/539, 31.4% vs 679/3128, 21.7%), p<0.001; but no difference in COVID-19 positivity rates (p=0.849). Symptomatic HCWs had higher positivity (10/193, 5.2%) than the asymptomatic ones (10/920, 1.1%), p=0.001. HCQ was taken by 755/1113 (67.8%) people and 14 (1.9%) of these reported positive for the virus. Conclusion This is the first study on healthcare workers from India to the best of our knowledge. Our findings suggest that posting in a high-risk zone with adequate PPE does not pose higher risk to the HCWs. Moreover, HCQ as a prophylactic has no use. ClinicalTrials.gov Identifier NCT04339608.

Title: Risk stratification of hospitalized COVID-19 patients through comparative studies of laboratory results with influenza Content: Background The outbreak of coronavirus disease 2019 (COVID-19) in December 2019 overlaps with the flu season. Methods We compared clinical and laboratory results from 719 influenza and 973 COVID-19 patients from January to April 2020. We compiled laboratory results from the first 14 days of the hospitalized patients using parameters that are most significantly different between COVID-19 and influenza and hierarchically clustered COVID-19 patients based on these data. The clinical outcomes were compared among different clusters. Results Temporal analyses of laboratory results revealed that compared to influenza, patients with COVID-19 exhibited a continued increase in the white blood cell count, rapid decline of hemoglobin, more rapid increase in blood urea nitrogen (BUN) and D-dimer, and higher level of alanine transaminase, C-reactive protein, ferritin, and fibrinogen. Using these results, we sub-classified the COVID-19 patients into 5 clusters through a hierarchical clustering analysis. We then reviewed the medical record of these patients and risk stratified them based on the clinical outcomes. The cluster with the highest risk showed 27.8% fatality, 94% ICU admission, 94% intubation, and 28% discharge rates compared to 0%, 38%, 22%, and 88% in the lowest risk cluster, respectively. Patients in the highest risk cluster had leukocytosis including neutrophilia and monocytosis, severe anemia, higher BUN, creatinine, D-dimer, alkaline phosphatase, bilirubin, and troponin. Conclusions There are significant differences in the clinical and laboratory courses between COVID-19 and influenza. Risk stratification in hospitalized COVID-19 patients using laboratory data could be useful to predict clinical outcomes and pathophysiology of these patients.

Title: Self-Swabbing for Virological Confirmation of Influenza-Like Illness Among an Internet-Based Cohort in the UK During the 2014-2015 Flu Season: Pilot Study Content: BACKGROUND: Routine influenza surveillance, based on laboratory confirmation of viral infection, often fails to estimate the true burden of influenza-like illness (ILI) in the community because those with ILI often manage their own symptoms without visiting a health professional. Internet-based surveillance can complement this traditional surveillance by measuring symptoms and health behavior of a population with minimal time delay. Flusurvey, the UK’s largest crowd-sourced platform for surveillance of influenza, collects routine data on more than 6000 voluntary participants and offers real-time estimates of ILI circulation. However, one criticism of this method of surveillance is that it is only able to assess ILI, rather than virologically confirmed influenza. OBJECTIVE: We designed a pilot study to see if it was feasible to ask individuals from the Flusurvey platform to perform a self-swabbing task and to assess whether they were able to collect samples with a suitable viral content to detect an influenza virus in the laboratory. METHODS: Virological swabbing kits were sent to pilot study participants, who then monitored their ILI symptoms over the influenza season (2014-2015) through the Flusurvey platform. If they reported ILI, they were asked to undertake self-swabbing and return the swabs to a Public Health England laboratory for multiplex respiratory virus polymerase chain reaction testing. RESULTS: A total of 700 swab kits were distributed at the start of the study; from these, 66 participants met the definition for ILI and were asked to return samples. In all, 51 samples were received in the laboratory, 18 of which tested positive for a viral cause of ILI (35%). CONCLUSIONS: This demonstrated proof of concept that it is possible to apply self-swabbing for virological laboratory testing to an online cohort study. This pilot does not have significant numbers to validate whether Flusurvey surveillance accurately reflects influenza infection in the community, but highlights that the methodology is feasible. Self-swabbing could be expanded to larger online surveillance activities, such as during the initial stages of a pandemic, to understand community transmission or to better assess interseasonal activity.

Title: Viral pathogens of acute lower respiratory tract infection in China. Content: OBJECTIVES To document the viral etiology of acute lower respiratory tract infection (ALRIs) in Chinese children. SETTING Children Hospital, Zhejiang University, China. STUDY DESIGN Cross-sectional. PARTICIPANTS 34885 children with ALRI between January 2001 to December 2006. METHODS Nasopharyngeal aspirates were collected from all subjects. Respiratory syncytial virus (RSV), adenovirus (ADV), type 1 to 3 parainfluenza viruses (PIV), and type A and B influenza virus (Flu) were detected by direct immunofluorescence. RESULTS Viruses were identified in 32.3% cases, including RSV (23.6%), PIV 3 (4.3%), Flu A (2.0%), ADV (1.7%), PIV I (0.6%), Flu B (0.2%) and PIV 2 (0.1%). RSV and PIV 3 predominated in younger children while Flu A and Flu B predominated in older children (P<0.001, respectively). PIV 1 was more prevalent in children aged 1 to 3 years. The peak frequency of RSV, PIV 3 and Flu A were in early spring, June to August, and August and September, respectively. Flu B had a peak in the winter and spring. Adenovirus infections occurred in all seasons with a relatively constant frequency. CONCLUSIONS Viruses are an important cause of ALRIs in Chinese children constituting 1/3 of total cases. RSV is the most common pathogen.

Title: Are coinfections with COVID-19 and influenza low or underreported? An observational study examining current published literature including three new unpublished cases Content: As the coronavirus disease-2019 (COVID-19) pandemic continues, one major point of uncertainty is the impact this novel pathogen will have during the upcoming 2020 to 2021 flu season. While the influenza virus is a known contributor to human morbidity and mortality, the question of how a coinfection between COVID-19 and influenza might manifest is of utmost concern. The aim of this study was to review the limited cases of COVID-19/influenza coinfection currently available in the literature, along with cases in the community of El Paso, TX, to determine whether any patterns of clinical presentation and morbidity emerged. An international review of the literature was conducted. Six published articles describing COVID-19/influenza coinfection were identified, with a total of 13 patients described therein. Three additional patients were identified from the El Paso, TX data. The most common presenting symptoms were fever and cough. The most common laboratory findings were elevated C-reactive protein and lymphocytopenia. Thirteen patients presented with viral pneumonia findings on CT, and nine had findings of ground-glass opacity. Finally, complications were reported in six patients, with most common complication being acute respiratory distress syndrome. The results of the review indicate that, due to the similarity in presentation between COVID-19 and influenza, further analysis will be required to understand the effects of coinfection on morbidity and mortality. However, the limited number of coinfection cases in the literature indicates that the implementation of COVID-19 control measures may continue to play a role in limiting the spread of these human respiratory pathogens.

Title: From “A”IV to “Z”IKV: Attacks from Emerging and Re-emerging Pathogens Content: 100 years after the infamous “Spanish flu” pandemic, the 2017–2018 flu season has been severe, with numerous infections worldwide. In between, there have been continuous, relentless attacks from (re-)emerging viruses. To fully understand viral pathogenesis and develop effective medical countermeasures, we must strengthen current surveillance and basic research efforts.

Title: Human coronaviruses: what do they cause? Content: SARS-CoV, human coronavirus NL63 (HCoV-NL63) and HCoV-HKU1 were first described in 2003, 2004 and 2005 respectively. Nevertheless, discovery of three new human coronaviruses does not necessary represent a sudden increase in emerging infections by new coronaviruses. Only SARS-CoV has recently been introduced to the human population; the other two have been circulating in humans for a long time. HCoV-HKU1 and HCoV-NL63 are respiratory coronaviruses, are frequently found during lower and upper respiratory tract infections, have spread worldwide, and prefer the winter season. These characteristics do not differ greatly from the symptoms described for the 'old' viruses HCoV-229E and HCoV-OC43. This report presents an overview of the current knowledge of the four human coronavirus that are now circulating in the human population.

Title: The contribution of respiratory pathogens to the seasonality of NHS Direct calls Content: Summary Objectives Primary care is thought to bear half the cost of treating infections in the UK. We describe the seasonal variation in NHS Direct respiratory calls (a new source of primary care data) and estimate the contribution of specific respiratory pathogens to this variation. Methods Linear regression models were used to estimate the weekly contribution of specific respiratory pathogens to the volume of NHS Direct respiratory calls (England and Wales, 2002–2004, all ages and 0–4years). Results Annual peaks in NHS Direct cough and difficulty breathing calls occurred in late December, with peaks in ‘cold/flu’ and fever calls occurring between November and April. The main explanatory variables were influenza (estimated to account for 72.5 calls per 100,000/year; 22% of ‘cold/flu’ calls; 15% of cough; and 13% of fever) and Streptococcus pneumoniae (55.5 per 100,000; 33% of ‘cold/flu’ calls; 20% of cough; and 15% of fever (0–4years)). Conclusions It is estimated that respiratory viruses, notably influenza and RSV, are responsible for at least 50% of the seasonal variation in NHS Direct respiratory calls. These results provide estimates of the burden of specific respiratory diseases reported to NHS Direct, and will help interpret syndromic surveillance data used to provide early warning of rises in community morbidity.

Title: Creating a comprehensive multi-tiered influenza management plan for a large healthcare system Content: ISSUE: Influenza infections affect 20% of the U.S. population, with an average of 110,000 hospitalizations and 36,000 deaths annually. The shortage of influenza vaccine for the 2004–2005 season brought with it the potential for an even higher rate of morbidity and mortality due to influenza. The Infection Control and Healthcare Epidemiology Consortium of a 12-hospital healthcare system located in St. Louis, Missouri, determined that a comprehensive multi-tiered influenza management plan was needed. PROJECT: A team of four infection control practitioners (ICPs) was established from three of the system's hospitals, including a large, metropolitan teaching hospital, a comprehensive pediatric hospital, and a small community hospital, along with three system-level consultants, under the advisement of their medical directors. The team developed a resource packet containing a comprehensive multi-tiered influenza management plan. The packet included a core policy, to be customized by each entity, a checklist of recommended materials to have on hand, and algorithms for influenza testing, patient placement, and healthcare worker immunization. The packet also included an admission screening tool, examples of local health department' line list reports, and educational posters to be used throughout the healthcare facilities to heighten influenza infection prevention awareness. Many of the tools have specific recommendations for different stages of the influenza season; for example, extensive use of rapid diagnostic tests is appropriate early on, but unnecessary during peak flu season when diagnosis can reliably be made based on symptoms. The packet was developed as a guide to assist ICPs in preparing for an influenza season. RESULTS: A resource packet with a comprehensive multi-tiered influenza management plan was developed for all of the system's hospitals. The packet contains information addressing the action to be taken prior to and at the early onset of the influenza season, when there is an increased level of influenza activity, and during a pandemic event. LESSONS LEARNED: Annual influenza outbreaks are a serious threat to U.S. patients. To reduce that threat, it is necessary to carefully plan and prepare for each influenza season. A resource packet with a comprehensive multi-tiered influenza management plan is a useful tool in making the necessary plans and preparations.

Title: Animals and coronavirus, help for African labs and a short flu season Content:

Title: Reassuring and managing patients with concerns about swine flu: Qualitative interviews with callers to NHS Direct Content: BACKGROUND: During the early stages of the 2009 swine flu (influenza H1N1) outbreak, the large majority of patients who contacted the health services about the illness did not have it. In the UK, the NHS Direct telephone service was used by many of these patients. We used qualitative interviews to identify the main reasons why people approached NHS Direct with concerns about swine flu and to identify aspects of their contact which were reassuring, using a framework approach. METHODS: 33 patients participated in semi-structured interviews. All patients had telephoned NHS Direct between 11 and 14 May with concerns about swine flu and had been assessed as being unlikely to have the illness. RESULTS: Reasons for seeking advice about swine flu included: the presence of unexpectedly severe flu-like symptoms; uncertainties about how one can catch swine flu; concern about giving it to others; pressure from friends or employers; and seeking 'peace of mind.' Most participants found speaking to NHS Direct reassuring or useful. Helpful aspects included: having swine flu ruled out; receiving an alternative explanation for symptoms; clarification on how swine flu is transmitted; and the perceived credibility of NHS Direct. No-one reported anything that had increased their anxiety and only one participant subsequently sought additional advice about swine flu from elsewhere. CONCLUSIONS: Future major incidents involving other forms of chemical, biological or radiological hazards may also cause large numbers of unexposed people to seek health advice. Our data suggest that providing telephone triage and information is helpful in such instances, particularly where advice can be given via a trusted, pre-existing service.

Title: Patterns of mortality during pandemic: An example of Spanish flu pandemic of 1918 Content: Now the attention of the whole world is focused on the developing pandemic of the coronavirus infection COVID-19. This article discusses mortality patterns of the deadliest epidemic in the last 120 years – the Spanish flu pandemic of 1918. Statistical sources from Italy and the USA, published shortly after the pandemic, were analyzed. The analysis was carried out for mortality from all causes, since in this case inaccuracies associated with establishing the causes of death are minimized. Despite the fact that the first cases of the Spanish flu appeared in the United States as early as March 1918, this first wave of epidemic practically did not affect the total mortality rate. The main peak of mortality in 1918 occurred in October 1918 both in the USA and Italy, with a gradual decrease in mortality over several months. Analysis of age-specific mortality demonstrates a significant increase in mortality at middle ages (20–50 years) in 1918 compared with 1917. Analysis of mortality trends using the method of latent variables shows a significant increase in the background mortality factor in 1918, which turned out to be higher for Italy than the mortality losses during the Second World War. The Spanish flu pandemic differs from the current coronavirus pandemic, because of significant increase in mortality of middle-aged people, while the COVID-19 pandemic causes a more marked increase in mortality among the elderly. With this, the COVID-19 pandemic is more like the recent flu epidemics than the earlier Spanish flu pandemic.

Title: Towards a data-driven characterization of behavioral changes induced by the seasonal flu Content: In this work, we aim to determine the main factors driving self-initiated behavioral changes during the seasonal flu. To this end, we designed and deployed a questionnaire via Influweb, a Web platform for participatory surveillance in Italy, during the 2017 − 18 and 2018 − 19 seasons. We collected 599 surveys completed by 434 users. The data provide socio-demographic information, level of concerns about the flu, past experience with illnesses, and the type of behavioral changes voluntarily implemented by each participant. We describe each response with a set of features and divide them in three target categories. These describe those that report i) no (26%), ii) only moderately (36%), iii) significant (38%) changes in behaviors. In these settings, we adopt machine learning algorithms to investigate the extent to which target variables can be predicted by looking only at the set of features. Notably, 66% of the samples in the category describing more significant changes in behaviors are correctly classified through Gradient Boosted Trees. Furthermore, we investigate the importance of each feature in the classification task and uncover complex relationships between individuals’ characteristics and their attitude towards behavioral change. We find that intensity, recency of past illnesses, perceived susceptibility to and perceived severity of an infection are the most significant features in the classification task and are associated to significant changes in behaviors. Overall, the research contributes to the small set of empirical studies devoted to the data-driven characterization of behavioral changes induced by infectious diseases.