Heterogeneous and Dynamic Prevalence of Asymptomatic Influenza Virus Infections

The role of asymptomatic infections in influenza transmission: what do we really know

Before the COVID-19 pandemic, the role of asymptomatic influenza virus infections in influenza transmission was uncertain. However, the importance of asymptomatic infection with SARS-CoV-2 for onward transmission of COVID-19 has led experts to question whether the role of asymptomatic influenza virus infections in transmission had been underappreciated. We discuss the existing evidence on the frequency of asymptomatic influenza virus infections, the extent to which they contribute to infection transmission, and remaining knowledge gaps. We propose priority areas for further evaluation, study designs, and case definitions to address existing knowledge gaps.

Avian flu: «for whom the bell tolls»?

The family Orthomyxoviridae consists of 9 genera, including Alphainfluenzavirus, which contains avian influenza viruses. In two subtypes H5 and H7 besides common low-virulent strains, a specific type of highly virulent avian virus have been described to cause more than 60% mortality among domestic birds. These variants of influenza virus are usually referred to as «avian influenza virus». The difference between high (HPAI) and low (LPAI) virulent influenza viruses is due to the structure of the arginine-containing proteolytic activation site in the hemagglutinin (HA) protein. The highly virulent avian influenza virus H5 was identified more than 100 years ago and during this time they cause outbreaks among wild and domestic birds on all continents and only a few local episodes of the disease in humans have been identified in XXI century. Currently, a sharp increase in the incidence of highly virulent virus of the H5N1 subtype (clade h2.3.4.4b) has been registered in birds on all continents, accompanied by the transmission of the virus to various species of mammals. The recorded global mortality rate among wild, domestic and agricultural birds from H5 subtype is approaching to the level of 1 billion cases. A dangerous epidemic factor is becoming more frequent outbreaks of avian influenza with high mortality among mammals, in particular seals and marine lions in North and South America, minks and fur-bearing animals in Spain and Finland, domestic and street cats in Poland. H5N1 avian influenza clade h2.3.4.4b strains isolated from mammals have genetic signatures of partial adaptation to the human body in the PB2, NP, HA, NA genes, which play a major role in regulating the aerosol transmission and the host range of the virus. The current situation poses a real threat of pre-adaptation of the virus in mammals as intermediate hosts, followed by the transition of the pre-adapted virus into the human population with catastrophic consequences.

Epidemiological and health economic implications of symptom propagation in respiratory pathogens: A mathematical modelling investigation

BACKGROUND

Respiratory pathogens inflict a substantial burden on public health and the economy. Although the severity of symptoms caused by these pathogens can vary from asymptomatic to fatal, the factors that determine symptom severity are not fully understood. Correlations in symptoms between infector-infectee pairs, for which evidence is accumulating, can generate large-scale clusters of severe infections that could be devastating to those most at risk, whilst also conceivably leading to chains of mild or asymptomatic infections that generate widespread immunity with minimal cost to public health. Although this effect could be harnessed to amplify the impact of interventions that reduce symptom severity, the mechanistic representation of symptom propagation within mathematical and health economic modelling of respiratory diseases is understudied.

METHODS AND FINDINGS

We propose a novel framework for incorporating different levels of symptom propagation into models of infectious disease transmission via a single parameter, α. Varying α tunes the model from having no symptom propagation (α = 0, as typically assumed) to one where symptoms always propagate (α = 1). For parameters corresponding to three respiratory pathogens-seasonal influenza, pandemic influenza and SARS-CoV-2-we explored how symptom propagation impacted the relative epidemiological and health-economic performance of three interventions, conceptualised as vaccines with different actions: symptom-attenuating (labelled SA), infection-blocking (IB) and infection-blocking admitting only mild breakthrough infections (IB_MB). In the absence of interventions, with fixed underlying epidemiological parameters, stronger symptom propagation increased the proportion of cases that were severe. For SA and IB_MB, interventions were more effective at reducing prevalence (all infections and severe cases) for higher strengths of symptom propagation. For IB, symptom propagation had no impact on effectiveness, and for seasonal influenza this intervention type was more effective than SA at reducing severe infections for all strengths of symptom propagation. For pandemic influenza and SARS-CoV-2, at low intervention uptake, SA was more effective than IB for all levels of symptom propagation; for high uptake, SA only became more effective under strong symptom propagation. Health economic assessments found that, for SA-type interventions, the amount one could spend on control whilst maintaining a cost-effective intervention (termed threshold unit intervention cost) was very sensitive to the strength of symptom propagation.

CONCLUSIONS

Overall, the preferred intervention type depended on the combination of the strength of symptom propagation and uptake. Given the importance of determining robust public health responses, we highlight the need to gather further data on symptom propagation, with our modelling framework acting as a template for future analysis.

Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics

Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empirically validated, and mathematically characterized a quantitative model that simulates disease spread and detection time for any given disease and detection system. We find that hospital monitoring could have detected COVID-19 in Wuhan 0.4 weeks earlier than it was actually discovered, at 2,300 cases (standard error: 76 cases) compared to 3,400 (standard error: 161 cases). Wastewater monitoring would not have accelerated COVID-19 detection in Wuhan, but provides benefit in smaller catchments and for asymptomatic or long-incubation diseases like polio or HIV/AIDS. Monitoring of air travel provides little benefit in most scenarios we evaluated. In sum, early detection systems can substantially mitigate some future pandemics, but would not have changed the course of COVID-19.

Dynamics analysis of strangles with asymptomatic infected horses and long-term subclinical carriers

Strangles is one of the most prevalent horse diseases globally. The infected horses may be asymptomatic and can still carry the infectious pathogen after it recovers, which are named asymptomatic infected horses and long-term subclinical carriers, respectively. Based on these horses, this paper establishes a dynamical model to screen, measure, and model the spread of strangles. The basic reproduction number $ \mathcal{R}_0 $ is computed through a next generation matrix method. By constructing Lyapunov functions, we concluded that the disease-free equilibrium is globally asymptotically stable if $ \mathcal{R}_0 < 1 $, and the endemic equilibrium exits uniquely and is globally asymptotically stable if $ \mathcal{R}_0 > 1 $. For example, while studying a strangles outbreak of a horse farm in England in 2012, we computed an $ \mathcal{R}_0 = 0.8416 $ of this outbreak by data fitting. We further conducted a parameter sensitivity analysis of $ \mathcal{R}_0 $ and the final size by numerical simulations. The results show that the asymptomatic horses mainly influence the final size of this outbreak and that long-term carriers are connected to an increased recurrence of strangles. Moreover, in terms of the three control measures implemented to control strangles(i.e., vaccination, implementing screening regularly and isolating symptomatic horses), the result shows that screening is the most effective measurement, followed by vaccination and isolation, which can provide effective guidance for horse management.

Memory Th17 cell-mediated protection against lethal secondary pneumococcal pneumonia following influenza infection

Streptococcus pneumoniae (Sp) frequently causes secondary pneumonia after influenza A virus (IAV) infection, leading to high morbidity and mortality worldwide. Concomitant pneumococcal and influenza vaccination improves protection against coinfection but does not always yield complete protection. Impaired innate and adaptive immune responses have been associated with attenuated bacterial clearance in influenza virus-infected hosts. In this study, we showed that preceding low-dose IAV infection caused persistent Sp infection and suppression of bacteria-specific T-helper type 17 (Th17) responses in mice. Prior Sp infection protected against subsequent IAV/Sp coinfection by improving bacterial clearance and rescuing bacteria-specific Th17 responses in the lungs. Furthermore, blockade of IL-17A by anti-IL-17A antibodies abrogated the protective effect of Sp preinfection. Importantly, memory Th17 responses induced by Sp preinfection overcame viral-driven Th17 inhibition and provided cross-protection against different Sp serotypes following coinfection with IAV. These results indicate that bacteria-specific Th17 memory cells play a key role in providing protection against IAV/Sp coinfection in a serotype-independent manner and suggest that a Th17-based vaccine would have excellent potential to mitigate disease caused by coinfection. IMPORTANCE Streptococcus pneumoniae (Sp) frequently causes secondary bacterial pneumonia after influenza A virus (IAV) infection, leading to increased morbidity and mortality worldwide. Current pneumococcal vaccines induce highly strain-specific antibody responses and provide limited protection against IAV/Sp coinfection. Th17 responses are broadly protective against Sp single infection, but whether the Th17 response, which is dramatically impaired by IAV infection in naïve mice, might be effective in immunization-induced protection against pneumonia caused by coinfection is not known. In this study, we have revealed that Sp-specific memory Th17 cells rescue IAV-driven inhibition and provide cross-protection against subsequent lethal coinfection with IAV and different Sp serotypes. These results indicate that a Th17-based vaccine would have excellent potential to mitigate disease caused by IAV/Sp coinfection.

Border Control for Infectious Respiratory Disease Pandemics: A Modelling Study for H1N1 and Four Strains of SARS-CoV-2

Post-pandemic economic recovery relies on border control for safe cross-border movement. Following the COVID-19 pandemic, we investigate whether effective strategies generalize across diseases and variants. For four SARS-CoV-2 variants and influenza A-H1N1, we simulated 21 strategy families of varying test types and frequencies, quantifying expected transmission risk, relative to no control, by strategy family and quarantine length. We also determined minimum quarantine lengths to suppress relative risk below given thresholds. SARS-CoV-2 variants showed similar relative risk across strategy families and quarantine lengths, with at most 2 days' between-variant difference in minimum quarantine lengths. ART-based and PCR-based strategies showed comparable effectiveness, with regular testing strategies requiring at most 9 days. For influenza A-H1N1, ART-based strategies were ineffective. Daily ART testing reduced relative risk only 9% faster than without regular testing. PCR-based strategies were moderately effective, with daily PCR (0-day delay) testing requiring 16 days for the second-most stringent threshold. Viruses with high typical viral loads and low transmission risk given low viral loads, such as SARS-CoV-2, are effectively controlled with moderate-sensitivity tests (ARTs) and modest quarantine periods. Viruses with low typical viral loads and substantial transmission risk at low viral loads, such as influenza A-H1N1, require high-sensitivity tests (PCR) and longer quarantine periods.

The Spectrum of Influenza in Children

BACKGROUND

Children constitute an important component of the influenza burden and community transmission, but the frequency of asymptomatic infection and post-influenza sequelae at the community level is poorly understood.

METHODS

Two community-based prospective cohort studies (2011-2020, 2017-2020) and 1 case-ascertained study (2012-2017) were conducted in Managua, Nicaragua. Non-immunocompromised children aged 0-14 years with ≥1 influenza infections, determined by polymerase chain reaction and hemagglutination inhibition assay, were included.

RESULTS

A total of 1272 influenza infections occurred in the household-based portion of the study. Influenza infection was asymptomatic in 84 (6.6%) infections, and the asymptomatic fraction increased with age (1.7%, 3.5%, and 9.1% for ages 0-1, 2-4, and 5-14, respectively; P < .001). Of asymptomatic children, 43 (51.2%) shed virus, compared to 1099 (92.5%) symptomatic children (P < .001). Also, 2140 cases of influenza occurred in the primary care portion of the study. Sequelae of influenza were rare, with the most common being pneumonia (52, 2.4%) and acute otitis media (71, 3.3%). A/H1N1 had higher age-adjusted odds of acute otitis media (odds ratio [OR] 1.99, 95% confidence interval [CI]: 1.14-3.48; P = .015) and hospitalization (OR 3.73, 95% CI: 1.68-8.67; P = .002) than A/H3N2. B/Victoria had higher age-adjusted odds of pneumonia (OR 10.99, 95% CI: 1.34-90.28; P = .026) than B/Yamagata.

CONCLUSIONS

Asymptomatic influenza infection is much less common in children than adults, although viral shedding still occurs in asymptomatic children. Post-influenza sequelae are rare in children in the community setting, and virus strain may be important in understanding the risk of sequelae.

Mild and asymptomatic influenza B virus infection among unvaccinated pregnant persons: Implication for effectiveness of non-pharmaceutical intervention and vaccination to prevent influenza

BACKGROUND

We estimated symptomatic and asymptomatic influenza infection frequency in community-dwelling unvaccinated pregnant persons to inform risk communication.

METHODS

We collected residue sera from multiple antenatal-care blood draws during October 2016-April 2017. We determined influenza infection as seroconversion with ≥ 4-fold rise in antibody titers between any two serum samples by improved hemagglutinin-inhibition assay including ether-treated B antigens. The serology data were linked to the results of nuclei acid testing (rRT-PCR) based on acute respiratory illness (ARI) surveillance.

RESULTS

Among all participants, 43 %(602/1384) demonstrated serology and/or rRT-PCR evidenced infection, and 44 %(265/602) of all infections were asymptomatic. ARI-associated rRT-PCR testing identified only 10 %(61/602) of total infections. Only 1 %(5/420) of the B Victoria cases reported ARI and had a rRT-PCR positive result, compared with 33 %(54/165) of the H3N2 cases. Among influenza ARI cases with multiple serum samples, 19 %(11/58) had seroconversion to a different subtype prior to the illness.

CONCLUSIONS

The incidence of influenza B infection in unvaccinated pregnant persons is under-estimated substantially. Non-pharmaceutical intervention may have suboptimal effectiveness in preventing influenza B transmission due to the less clinical manifestation compared to influenza A. The findings support maternal influenza vaccination to protect pregnant persons and reduce consequent household transmission.

SARS-CoV-2 versus other minor viral infection on kidney injury in asymptomatic and mildly symptomatic patients

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has become a global pandemic since December 2019. Most of the patients are mild or asymptomatic and recovered well as those suffered from other respiratory viruses. SARS-CoV-2 infection is supposed to demonstrate more sequelae. Acute kidney injury (AKI) is common among COVID-19 patients and is associated with disease severity and outcomes. Only a few studies focused on a detailed analysis of kidney damage in asymptomatic or mildly symptomatic COVID-19 patients. Whether any minor viral infection is likely to exhibit similar minor effect on renal function as COVID-19 is still unclear, and the definite pathophysiology of viral invasion is not fully understood. Currently, the proposed mechanisms of AKI include direct effects of virus on kidney, dysregulated immune response, or as a result of multi-organs failure have been proposed. This study will discuss the difference between COVID-19 and other viruses, focusing on proposed mechanisms, biomarkers and whether it matters with clinical significance.

Seasonal influenza vaccination of healthcare workers: a narrative review

Influenza is an acute respiratory disease caused by the influenza virus which often occurs in outbreaks and epidemics worldwide. The World Health Organization recommends annual vaccination of healthcare workers (HCWs) against influenza, because most of them are involved in the direct care of patients with a high risk of influenza-related complications. Given the significance of the disease burden, a targeted literature review was conducted to assess issues related to influenza vaccination among HCWs. The primary aim of this review was to assess the incidence of influenza among medical personnel and healthcare-associated influenza, and to outline the benefits of influenza vaccination for patients and HCWs themselves. Vaccination of HCWs seems to be an important strategy for reducing the transmission of influenza from healthcare personnel to their patients and, therefore, for reducing patient morbidity and mortality, increasing patient safety, and reducing work absenteeism among HCWs. The benefits of influenza vaccination for their patients and for HCWs themselves are addressed in literature, but the evidence is mixed and often of low-quality. Int J Occup Med Environ Health. 2022;35(2):127-39.

Epidemiological Consequences of Viral Interference: A Mathematical Modeling Study of Two Interacting Viruses

Some viruses have the ability to block or suppress growth of other viruses when simultaneously present in the same host. This type of viral interference or viral block has been suggested as a potential interaction between some respiratory viruses including SARS-CoV-2 and other co-circulating respiratory viruses. We explore how one virus' ability to block infection with another within a single host affects spread of the viruses within a susceptible population using a compartmental epidemiological model. We find that population-level effect of viral block is a decrease in the number of people infected with the suppressed virus. This effect is most pronounced when the viruses have similar epidemiological parameters. We use the model to simulate co-circulating epidemics of SARS-CoV-2 and influenza, respiratory syncytial virus (RSV), and rhinovirus, finding that co-circulation of SARS-CoV-2 and RSV causes the most suppression of SARS-CoV-2. Paradoxically, co-circulation of SARS-CoV-2 and influenza or rhinovirus results in almost no change in the SARS-CoV-2 epidemic, but causes a shift in the timing of the influenza and rhinovirus epidemics.

Incidence of Influenza Virus Infection among Wroclaw's Healthcare Workers in Pre-COVID-19 2019-2020 Influenza Season Using Novel Flu SensDx Device

Background: Healthcare workers (HCWs) are more exposed to influenza infection, and the influenza vaccination is recommended each year, to reduce the risk of influenza infection and prevent influenza transmission. This study is a cross-sectional study and the objectives were to determine the rate of influenza virus infection among HCWs in the 2019−2020 influenza season. Methods: Between January and March 2020, a survey was carried out in 2 hospitals and 15 primary health-care settings (PHCS) in Wroclaw (Poland). The novel point-of-care testing Flu SensDx device was used, which detects the M1 protein of the influenza virus using electrochemical impedance spectroscopy from biological material (throat/nasal swabs). Results: A total of 150 samples were collected. The majority of participating HCWs by profession were 83 physicians (55.3%) and half (51.3%) of the participating HCWs worked in PHCS. Influenza vaccination coverage was 61.3% in 2019−2020 and 46.0% in the 2018−2019 season for all participants. Of the participating HCWs, 44.0% were positive tested by the Flu SensDx device. There were no statistically significant differences among the positive tested HCWs, their influenza immunization history, and the presence of symptoms of influenza-like illness (p > 0.05). Conclusion: Although the results of the present study suggest that influenza vaccination does not reduce the frequency of influenza virus detection by Flu SensDx testing in the HCWs participants, larger studies are needed to estimate the incidence of influenza virus infection among HCWs to understand the underlying mechanism and fine-tune policies aimed at reducing nosocomial infections.

The national burden of influenza-like illness and severe respiratory illness overall and associated with nine respiratory viruses in South Africa, 2013-2015

BACKGROUND

Estimates of the disease burden associated with different respiratory viruses are severely limited in low- and middle-income countries, especially in Africa.

METHODS

We estimated age-specific numbers and rates of medically and non-medically attended influenza-like illness (ILI) and severe respiratory illness (SRI) that were associated with influenza, respiratory syncytial virus (RSV), rhinovirus, human metapneumovirus, adenovirus, enterovirus and parainfluenza virus types 1-3 after adjusting for the attributable fraction (AF) of virus detection to illness in South Africa during 2013-2015. The base rates were estimated from five surveillance sites and extrapolated nationally.

RESULTS

The mean annual rates per 100,000 population were 51,383 and 4196 for ILI and SRI, respectively. Of these, 26% (for ILI) and 46% (for SRI) were medically attended. Among outpatients with ILI, rhinovirus had the highest AF-adjusted rate (7221), followed by influenza (6443) and adenovirus (1364); whereas, among inpatients with SRI, rhinovirus had the highest AF-adjusted rate (400), followed by RSV (247) and influenza (130). Rhinovirus (9424) and RSV (2026) had the highest AF-adjusted rates among children aged <5 years with ILI or SRI, respectively, whereas rhinovirus (757) and influenza (306) had the highest AF-adjusted rates among individuals aged ≥65 years with ILI or SRI, respectively.

CONCLUSIONS

There was a substantial burden of ILI and SRI in South Africa during 2013-2015. Rhinovirus and influenza had a prominent disease burden among patients with ILI. RSV and influenza were the most prominent causes of SRI in children and the elderly, respectively.

A modified Susceptible-Infected-Recovered model for observed under-reported incidence data

Fitting Susceptible-Infected-Recovered (SIR) models to incidence data is problematic when not all infected individuals are reported. Assuming an underlying SIR model with general but known distribution for the time to recovery, this paper derives the implied differential-integral equations for observed incidence data when a fixed fraction of newly infected individuals are not observed. The parameters of the resulting system of differential equations are identifiable. Using these differential equations, we develop a stochastic model for the conditional distribution of current disease incidence given the entire past history of reported cases. We estimate the model parameters using Bayesian Markov Chain Monte-Carlo sampling of the posterior distribution. We use our model to estimate the transmission rate and fraction of asymptomatic individuals for the current Coronavirus 2019 outbreak in eight American Countries: the United States of America, Brazil, Mexico, Argentina, Chile, Colombia, Peru, and Panama, from January 2020 to May 2021. Our analysis reveals that the fraction of reported cases varies across all countries. For example, the reported incidence fraction for the United States of America varies from 0.3 to 0.6, while for Brazil it varies from 0.2 to 0.4.

Asymptomatic and pre-symptomatic infection in Coronavirus Disease 2019 pandemic

With the presence of Coronavirus Disease 2019 (COVID-19) asymptomatic infections detected, their proportion, transmission potential, and other aspects such as immunity and related emerging challenges have attracted people's attention. We have found that based on high-quality research, asymptomatic infections account for at least one-third of the total cases, whereas based on systematic review and meta-analysis, the proportion is about one-fifth. Evaluating the true transmission potential of asymptomatic cases is difficult but critical, since it may affect national policies in response to COVID-19. We have summarized the current evidence and found, compared with symptomatic cases, the transmission capacity of asymptomatic individuals is weaker, even though they have similar viral load and relatively short virus shedding duration. As the outbreak progresses, asymptomatic infections have also been found to develop long COVID-19. In addition, the role of asymptomatic infection in COVID-19 remains to be further revealed as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to emerge. Nevertheless, as asymptomatic infections transmit the SARS-CoV-2 virus silently, they still pose a substantial threat to public health. Therefore, it is essential to conduct screening to obtain more knowledge about the asymptomatic infections and to detect them as soon as possible; meanwhile, management of them is also a key point in the fight against COVID-19 community transmission. The different management of asymptomatic infections in various countries are compared and the experience in China is displayed in detail.

A Framework to Identify Antigen-Expanded T Cell Receptor Clusters Within Complex Repertoires

Common approaches for monitoring T cell responses are limited in their multiplexity and sensitivity. In contrast, deep sequencing of the T Cell Receptor (TCR) repertoire provides a global view that is limited only in terms of theoretical sensitivity due to the depth of available sampling; however, the assignment of antigen specificities within TCR repertoires has become a bottleneck. This study combines antigen-driven expansion, deep TCR sequencing, and a novel analysis framework to show that homologous ‘Clusters of Expanded TCRs (CETs)’ can be confidently identified without cell isolation, and assigned to antigen against a background of non-specific clones. We show that clonotypes within each CET respond to the same epitope, and that protein antigens stimulate multiple CETs reactive to constituent peptides. Finally, we demonstrate the personalized assignment of antigen-specificity to rare clones within fully-diverse uncultured repertoires. The method presented here may be used to monitor T cell responses to vaccination and immunotherapy with high fidelity.

Age-seroprevalence curves for the multi-strain structure of influenza A virus

The relationship between age and seroprevalence can be used to estimate the annual attack rate of an infectious disease. For pathogens with multiple serologically distinct strains, there is a need to describe composite exposure to an antigenically variable group of pathogens. In this study, we assay 24,402 general-population serum samples, collected in Vietnam between 2009 to 2015, for antibodies to eleven human influenza A strains. We report that a principal components decomposition of antibody titer data gives the first principal component as an appropriate surrogate for seroprevalence; this results in annual attack rate estimates of 25.6% (95% CI: 24.1% - 27.1%) for subtype H3 and 16.0% (95% CI: 14.7% - 17.3%) for subtype H1. The remaining principal components separate the strains by serological similarity and associate birth cohorts with their particular influenza histories. Our work shows that dimensionality reduction can be used on human antibody profiles to construct an age-seroprevalence relationship for antigenically variable pathogens.

Neutrophils and Lymphocytes Can Help Distinguish Asymptomatic COVID-19 From Moderate COVID-19

Introduction

Asymptomatic coronavirus disease 2019 (COVID-19) and moderate COVID-19 may be the most common COVID-19 cases. This study was designed to develop a diagnostic model for patients with asymptomatic and moderate COVID-19 based on demographic, clinical, and laboratory variables.

Methods

This retrospective study divided the subjects into 2 groups: asymptomatic COVID-19 (without symptoms, n = 15) and moderate COVID-19 (with symptoms, n = 57). Demographic characteristics, clinical data, routine blood tests, other laboratory tests, and inpatient data were collected and analyzed to compare patients with asymptomatic COVID-19 and moderate COVID-19.

Results

Comparison of the asymptomatic COVID-19 group with the moderate COVID-19 group yielded the following results: the patients were younger (P = 0.045); the cluster of differentiation (CD)8+ (cytotoxic) T cell level was higher (P = 0.017); the C-reactive protein (CRP) level was lower (P = 0.001); the white blood cell (WBC, P < 0.001), neutrophil (NEU, P = 0.036), lymphocyte (LYM, P = 0.009), and eosinophil (EOS, P = 0.036) counts were higher; and the serum iron level (P = 0.049) was higher in the asymptomatic COVID-19 group. The multivariate analysis showed that the NEU count (odds ratio [OR] = 2.007, 95% confidence interval (CI): 1.162 - 3.715, P = 0.014) and LYM count (OR = 9.380, 95% CI: 2.382 - 36.934, P = 0.001) were independent factors for the presence of clinical symptoms after COVID-19 infection. The NEU count and LYM count were diagnostic predictors of asymptomatic COVID-19. This diagnostic prediction model showed high discriminatory power, consistency, and net clinical benefits.

Conclusions

The proposed model can distinguish asymptomatic COVID-19 from moderate COVID-19, thereby helping clinicians identify and distinguish patients with potential asymptomatic COVID-19 from those with moderate COVID-19.

Pharmacometric analysis of seasonal influenza epidemics and the effect of vaccination using sentinel surveillance data

The identification of influenza epidemics and assessment of the efficacy of vaccination against this infection are major challenges for the implementation of effective public health strategies, such as vaccination programs. In this study, we developed a new pharmacometric model to evaluate the efficacy of vaccination based on infection surveillance data from the 2010/2011 to 2018/2019 influenza seasons in Japan. A novel susceptible‐infected‐removed plus vaccination model, based on an indirect response structure with the effect of vaccination, was applied to describe seasonal influenza epidemics using a preseasonal collection of data regarding serological H₁ antibody titer positivity and the fraction of virus strains. Using this model, we evaluated K_in (a parameter describing the transmission rate of symptomatic influenza infection) for different age groups. Furthermore, we defined a new parameter (prevention factor) showing the efficacy of vaccination against each viral strain and in different age groups. We found that the prevention factor of vaccination against influenza varied among age groups. Notably, children aged 5–14 years showed the highest K_in value during the 10 influenza seasons and the greatest preventive effect of vaccination (prevention factor = 70.8%). The propagation of influenza epidemics varies in different age groups. Children aged 5–14 years most likely play a leading role in the transmission of influenza. Prioritized vaccination in this age group may be the most effective strategy for reducing the prevalence of influenza in the community.

Asymptomatic SARS-CoV-2 infection: A systematic review and meta-analysis

Quantification of asymptomatic infections is fundamental for effective public health responses to the COVID-19 pandemic. Discrepancies regarding the extent of asymptomaticity have arisen from inconsistent terminology as well as conflation of index and secondary cases which biases toward lower asymptomaticity. We searched PubMed, Embase, Web of Science, and World Health Organization Global Research Database on COVID-19 between January 1, 2020 and April 2, 2021 to identify studies that reported silent infections at the time of testing, whether presymptomatic or asymptomatic. Index cases were removed to minimize representational bias that would result in overestimation of symptomaticity. By analyzing over 350 studies, we estimate that the percentage of infections that never developed clinical symptoms, and thus were truly asymptomatic, was 35.1% (95% CI: 30.7 to 39.9%). At the time of testing, 42.8% (95% prediction interval: 5.2 to 91.1%) of cases exhibited no symptoms, a group comprising both asymptomatic and presymptomatic infections. Asymptomaticity was significantly lower among the elderly, at 19.7% (95% CI: 12.7 to 29.4%) compared with children at 46.7% (95% CI: 32.0 to 62.0%). We also found that cases with comorbidities had significantly lower asymptomaticity compared to cases with no underlying medical conditions. Without proactive policies to detect asymptomatic infections, such as rapid contact tracing, prolonged efforts for pandemic control may be needed even in the presence of vaccination.

Detection of SARS-CoV-2 infection in asymptomatic populations using the DiaSorin molecular Simplexa and Roche Cobas EUA assays

Identification of asymptomatic patients is necessary to control the COVID-19 pandemic and testing is one of the measures to detect this population. We evaluated the clinical correlation of the DiaSorin Molecular Simplexa COVID-19 Direct (DiaSorin Molecular) and Roche Cobas 6800 SARS-CoV-2 (Roche) assays using 253 oropharyngeal (OP) swab specimens collected from asymptomatic patients. Agreement between DiaSorin Molecular and Roche was 97% (95% CI, 0.94 to 0.99), with a κ statistic of 0.90 (95% CI, 0.83 to 0.97) and a PPA of 89% (95% CI, 0.76 to 0.96) and NPA of 99% (95% CI, 0.97 to 0.99). Simple regression analysis of Ct values revealed a regression line of y = 1.065*X - 5.537 with a Pearson's r of 0.8542, indicating a good correlation between both platforms. The DiaSorin Molecular assay demonstrates clinical performance comparable to that of Roche in this population.

Asymptomatic transmission and high community burden of seasonal influenza in an urban and a rural community in South Africa, 2017-18 (PHIRST): a population cohort study

BACKGROUND

Data on influenza community burden and transmission are important to plan interventions especially in resource-limited settings. However, data are limited, particularly from low-income and middle-income countries. We aimed to evaluate the community burden and transmission of influenza in a rural and an urban setting in South Africa.

METHODS

In this prospective cohort study approximately 50 households were selected sequentially from both a rural setting (Agincourt, Mpumalanga Province, South Africa; with a health and sociodemographic surveillance system) and an urban setting (Klerksdorp, Northwest Province, South Africa; using global positioning system data), enrolled, and followed up for 10 months in 2017 and 2018. Different households were enrolled in each year. Households of more than two individuals in which 80% or more of the occupants agreed to participate were included in the study. Nasopharyngeal swabs were collected twice per week from participating household members irrespective of symptoms and tested for influenza using real-time RT-PCR. The primary outcome was the incidence of influenza infection, defined as the number of real-time RT-PCR-positive episodes divided by the person-time under observation. Household cumulative infection risk (HCIR) was defined as the number of subsequent infections within a household following influenza introduction.

FINDINGS

81 430 nasopharyngeal samples were collected from 1116 participants in 225 households (follow-up rate 88%). 917 (1%) tested positive for influenza; 178 (79%) of 225 households had one or more influenza-positive individual. The incidence of influenza infection was 43·6 (95% CI 39·8-47·7) per 100 person-seasons. 69 (17%) of 408 individuals who had one influenza infection had a repeat influenza infection during the same season. The incidence (67·4 per 100 person-seasons) and proportion with repeat infections (22 [23%] of 97 children) were highest in children younger than 5 years and decreased with increasing age (p<0·0001). Overall, 268 (56%) of 478 infections were symptomatic and 66 (14%) of 478 infections were medically attended. The overall HCIR was 10% (109 of 1088 exposed household members infected [95% CI 9-13%). Transmission (HCIR) from index cases was highest in participants aged 1-4 years (16%; 40 of 252 exposed household members) and individuals with two or more symptoms (17%; 68 of 396 exposed household members). Individuals with asymptomatic influenza transmitted infection to 29 (6%) of 509 household contacts. HIV infection, affecting 167 (16%) of 1075 individuals, was not associated with increased incidence or HCIR.

INTERPRETATION

Approximately half of influenza infections were symptomatic, with asymptomatic individuals transmitting influenza to 6% of household contacts. This suggests that strategies, such as quarantine and isolation, might be ineffective to control influenza. Vaccination of children, with the aim of reducing influenza transmission might be effective in African settings given the young population and high influenza burden.

FUNDING

US Centers for Disease Control and Prevention.

Optimizing antiviral treatment for seasonal influenza in the USA: a mathematical modeling analysis

BACKGROUND

Seasonal influenza remains a major cause of morbidity and mortality in the USA. Despite the US Centers for Disease Control and Prevention recommendation promoting the early antiviral treatment of high-risk patients, treatment coverage remains low.

METHODS

To evaluate the population-level impact of increasing antiviral treatment timeliness and coverage among high-risk patients in the USA, we developed an influenza transmission model that incorporates data on infectious viral load, social contact, and healthcare-seeking behavior. We modeled the reduction in transmissibility in treated individuals based on their reduced daily viral load. The reduction in hospitalizations following treatment was based on estimates from clinical trials. We calibrated the model to weekly influenza data from Texas, California, Connecticut, and Virginia between 2014 and 2019. We considered in the baseline scenario that 2.7-4.8% are treated within 48 h of symptom onset while an additional 7.3-12.8% are treated after 48 h of symptom onset. We evaluated the impact of improving the timeliness and uptake of antiviral treatment on influenza cases and hospitalizations.

RESULTS

Model projections suggest that treating high-risk individuals as early as 48 h after symptom onset while maintaining the current treatment coverage level would avert 2.9-4.5% of all symptomatic cases and 5.5-7.1% of all hospitalizations. Geographic variability in the effectiveness of earlier treatment arises primarily from variabilities in vaccination coverage and population demographics. Regardless of these variabilities, we found that when 20% of the high-risk individuals were treated within 48 h, the reduction in hospitalizations doubled. We found that treatment of the elderly population (> 65 years old) had the highest impact on reducing hospitalizations, whereas treating high-risk individuals aged 5-19 years old had the highest impact on reducing transmission. Furthermore, the population-level benefit per treated individual is enhanced under conditions of high vaccination coverage and a low attack rate during an influenza season.

CONCLUSIONS

Increased timeliness and coverage of antiviral treatment among high-risk patients have the potential to substantially reduce the burden of seasonal influenza in the USA, regardless of influenza vaccination coverage and the severity of the influenza season.

COVID-19: Rethinking the Lockdown Groupthink

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused the Coronavirus Disease 2019 (COVID-19) worldwide pandemic in 2020. In response, most countries in the world implemented lockdowns, restricting their population's movements, work, education, gatherings, and general activities in attempt to "flatten the curve" of COVID-19 cases. The public health goal of lockdowns was to save the population from COVID-19 cases and deaths, and to prevent overwhelming health care systems with COVID-19 patients. In this narrative review I explain why I changed my mind about supporting lockdowns. The initial modeling predictions induced fear and crowd-effects (i.e., groupthink). Over time, important information emerged relevant to the modeling, including the lower infection fatality rate (median 0.23%), clarification of high-risk groups (specifically, those 70 years of age and older), lower herd immunity thresholds (likely 20-40% population immunity), and the difficult exit strategies. In addition, information emerged on significant collateral damage due to the response to the pandemic, adversely affecting many millions of people with poverty, food insecurity, loneliness, unemployment, school closures, and interrupted healthcare. Raw numbers of COVID-19 cases and deaths were difficult to interpret, and may be tempered by information placing the number of COVID-19 deaths in proper context and perspective relative to background rates. Considering this information, a cost-benefit analysis of the response to COVID-19 finds that lockdowns are far more harmful to public health (at least 5-10 times so in terms of wellbeing years) than COVID-19 can be. Controversies and objections about the main points made are considered and addressed. Progress in the response to COVID-19 depends on considering the trade-offs discussed here that determine the wellbeing of populations. I close with some suggestions for moving forward, including focused protection of those truly at high risk, opening of schools, and building back better with a economy.

Nucleic acid detection and quantitative analysis of influenza virus using exhaled breath condensate

Exhaled breath condensate (EBC) is increasingly being used as a non-invasive method for disease diagnosis and environmental exposure assessment. We previously detected the nucleic acids of bacterial pathogens in EBC. Influenza viruses can be transmitted through aerosols during coughing and exhaling. Existing detection methods for influenza have various limitations. The EBC collection method is convenient, non-invasive, and reduces the risk of exposure. We investigated the detection of influenza virus in EBC using a sensitive nucleic acid testing method and performed quantitative analysis to evaluate the present and content of influenza virus in the breath. We evaluated 30 patients with respiratory tract infection during the 2019 influenza season. The clinical data and samples of nasal swabs were collected for rapid influenza diagnostic (antigen) tests. Pharyngeal swab and EBC samples were used for influenza virus nucleic acid detection. Each EBC sample was assessed twice as well as at one-month follow-up of the patients. The nucleic acid test in the EBC of 30 cases revealed 20 and two cases of influenza A and B, respectively, giving a detection rate of 73.3%. The rapid influenza diagnostic (antigen) tests revealed four and 12 cases of influenza A and B, respectively, with a detection rate of 53.3%. All pharyngeal swab samples evaluated by the nucleic acid test were influenza-positive; 12 cases were positive for both influenza A and B and 18 cases were positive for influenza B alone. The influenza viral load in the EBC was 10³-10⁷ copies ml^-1. Among the 16 patients followed-up after 1 month, 4 were positive (25%) in EBC samples and 10 were positive (62.5%) in pharyngeal swab samples. It was preliminary exploration that influenza virus could be detected in EBC. EBC is one of the sample types that would be used for molecular diagnosis of influenza.

Modelling the impact of universal influenza vaccines on seasonal influenza with different subtypes

Several candidates of universal influenza vaccine (UIV) have entered phase III clinical trials, which are expected to improve the willingness and coverage of the population substantially. The impact of UIV on the seasonal influenza epidemic in low influenza vaccination coverage regions like China remains unclear. We proposed a new compartmental model involving the transmission of different influenza subtypes to evaluate the effects of UIV. We calibrated the model by weekly surveillance data of influenza in Xi'an City, Shaanxi Province, China, during 2010/11–2018/19 influenza seasons. We calculated the percentage of averted infections under 2-month (September to October) and 6-month (September to the next February) vaccination patterns with varied UIV effectiveness and coverage in each influenza season, compared with no UIV scenario. A total of 195 766 influenza-like illness (ILI) cases were reported during the nine influenza seasons (2010/11–2018/19), of which the highest ILI cases were among age group 0–4 (59.60%) years old, followed by 5–14 (25.22%), 25–59 (8.19%), 15–24 (3.75%) and ⩾60 (3.37%) years old. The influenza-positive rate for all age groups among ILI cases was 17.51%, which is highest among 5–14 (23.75%) age group and followed by 25–59 (16.44%), 15–24 (16.42%), 0–4 (14.66%) and ⩾60 (13.98%) age groups, respectively. Our model showed that UIV might greatly avert influenza infections irrespective of subtypes in each influenza season. For example, in the 2018/19 influenza season, 2-month vaccination pattern with low UIV effectiveness (50%) and coverage (10%), and high UIV effectiveness (75%) and coverage (30%) could avert 41.6% (95% CI 27.8–55.4%) and 83.4% (80.9–85.9%) of influenza infections, respectively; 6-month vaccination pattern with low and high UIV effectiveness and coverage could avert 32.0% (15.9–48.2%) and 74.2% (69.7–78.7%) of influenza infections, respectively. It would need 11.4% (7.9–15.0%) of coverage to reduce half of the influenza infections for 2-month vaccination pattern with low UIV effectiveness and 8.5% (5.0–11.2%) of coverage with high UIV effectiveness, while it would need 15.5% (8.9–20.7%) of coverage for 6-month vaccination pattern with low UIV effectiveness and 11.2% (6.5–15.0%) of coverage with high UIV effectiveness. We conclude that UIV could significantly reduce the influenza infections even for low UIV effectiveness and coverage. The 2-month vaccination pattern could avert more influenza infections than the 6-month vaccination pattern irrespective of influenza subtype and UIV effectiveness and coverage.

Potential sources, modes of transmission and effectiveness of prevention measures against SARS-CoV-2

During the current SARS-CoV-2 pandemic new studies are emerging daily providing novel information about sources, transmission risks and possible prevention measures. In this review, we aimed to comprehensively summarize the current evidence on possible sources for SARS-CoV-2, including evaluation of transmission risks and effectiveness of applied prevention measures. Next to symptomatic patients, asymptomatic or pre-symptomatic carriers are a possible source with respiratory secretions as the most likely cause for viral transmission. Air and inanimate surfaces may be sources; however, viral RNA has been inconsistently detected. Similarly, even though SARS-CoV-2 RNA has been detected on or in personal protective equipment (PPE), blood, urine, eyes, the gastrointestinal tract and pets, these sources are currently thought to play a negligible role for transmission. Finally, various prevention measures such as handwashing, hand disinfection, face masks, gloves, surface disinfection or physical distancing for the healthcare setting and in public are analysed for their expected protective effect.

Proportion of asymptomatic coronavirus disease 2019: A systematic review and meta-analysis

We aim to systematically review the characteristics of asymptomatic infection in the coronavirus disease 2019 (COVID‐19). PubMed and EMBASE were electronically searched to identify original studies containing the rate of asymptomatic infection in COVID‐19 patients before 20 May 2020. Then mate‐analysis was conducted using R version 3.6.2. A total of 50 155 patients from 41 studies with confirmed COVID‐19 were included. The pooled percentage of asymptomatic infection is 15.6% (95% CI, 10.1%‐23.0%). Ten included studies contain the number of presymptomatic patients, who were asymptomatic at screening point and developed symptoms during follow‐up. The pooled percentage of presymptomatic infection among 180 initially asymptomatic patients is 48.9% (95% CI, 31.6%‐66.2%). The pooled proportion of asymptomatic infection among 1152 COVID‐19 children from 11 studies is 27.7% (95% CI, 16.4%‐42.7%), which is much higher than patients from all aged groups. Abnormal CT features are common in asymptomatic COVID‐19 infection. For 36 patients from 4 studies that CT results were available, 15 (41.7%) patients had bilateral involvement and 14 (38.9%) had unilateral involvement in CT results. Reduced white blood cell count, increased lactate dehydrogenase, and increased C‐reactive protein were also recorded. About 15.6% of confirmed COVID‐19 patients are asymptomatic. Nearly half of the patients with no symptoms at detection time will develop symptoms later. Children are likely to have a higher proportion of asymptomatic infection than adults. Asymptomatic COVID‐19 patients could have abnormal laboratory and radiational manifestations, which can be used as screening strategies to identify asymptomatic infection.

By systematically reviewing the proportion and clinical features of asymptomatic infection in COVID‐19, our study provides a useful quantity to understand the true burden of this disease.

Respiratory viruses in individuals with a high frequency of animal exposure in southern and highland Vietnam

Active surveillance for zoonotic respiratory viruses is essential to inform the development of appropriate interventions and outbreak responses. Here we target individuals with a high frequency of animal exposure in Vietnam. Three-year community-based surveillance was conducted in Vietnam during 2013-2016. We enrolled a total of 581 individuals (animal-raising farmers, slaughterers, animal-health workers, and rat traders), and utilized reverse transcription-polymerase chain reaction to detect 15 common respiratory viruses in pooled nasal-throat swabs collected at baseline or acute respiratory disease episodes. A respiratory virus was detected in 7.9% (58 of 732) of baseline samples, and 17.7% (136 of 770) of disease episode samples (P < .001), with enteroviruses (EVs), rhinoviruses and influenza A virus being the predominant viruses detected. There were temporal and spatial fluctuations in the frequencies of the detected viruses over the study period, for example, EVs and influenza A viruses were more often detected during rainy seasons. We reported the detection of common respiratory viruses in individuals with a high frequency of animal exposure in Vietnam, an emerging infectious disease hotspot. The results show the value of baseline/control sampling in delineating the causative relationships and have revealed important insights into the ecological aspects of EVs, rhinoviruses and influenza A and their contributions to the burden posed by respiratory infections in Vietnam.

One hundred years of (influenza) immunopathology

It has been over 100 years since the 1918 influenza pandemic, one of the most infamous examples of viral immunopathology. Since that time, there has been an inevitable repetition of influenza pandemics every few decades and yearly influenza seasons, which have a significant impact on human health. Recently, noteworthy progress has been made in defining the cellular and molecular mechanisms underlying pathology induced by an exuberant host response to influenza virus infection. Infection with influenza viruses is associated with a wide spectrum of disease, from mild symptoms to severe complications including respiratory failure, and the severity of influenza disease is driven by a complex interplay of viral and host factors. This chapter will discuss mechanisms of infection severity using concepts of disease resistance and tolerance as a framework for understanding the balance between viral clearance and immunopathology. We review mechanistic studies in animal models of infection and correlational studies in humans that have begun to define these factors and discuss promising host therapeutic targets to improve outcomes from severe influenza disease.

Interventions to mitigate early spread of SARS-CoV-2 in Singapore: a modelling study

BACKGROUND

Since the coronavirus disease 2019 outbreak began in the Chinese city of Wuhan on Dec 31, 2019, 68 imported cases and 175 locally acquired infections have been reported in Singapore. We aimed to investigate options for early intervention in Singapore should local containment (eg, preventing disease spread through contact tracing efforts) be unsuccessful.

METHODS

We adapted an influenza epidemic simulation model to estimate the likelihood of human-to-human transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a simulated Singaporean population. Using this model, we estimated the cumulative number of SARS-CoV-2 infections at 80 days, after detection of 100 cases of community transmission, under three infectivity scenarios (basic reproduction number [R₀] of 1·5, 2·0, or 2·5) and assuming 7·5% of infections are asymptomatic. We first ran the model assuming no intervention was in place (baseline scenario), and then assessed the effect of four intervention scenarios compared with a baseline scenario on the size and progression of the outbreak for each R₀ value. These scenarios included isolation measures for infected individuals and quarantining of family members (hereafter referred to as quarantine); quarantine plus school closure; quarantine plus workplace distancing; and quarantine, school closure, and workplace distancing (hereafter referred to as the combined intervention). We also did sensitivity analyses by altering the asymptomatic fraction of infections (22·7%, 30·0%, 40·0%, and 50·0%) to compare outbreak sizes under the same control measures.

FINDINGS

For the baseline scenario, when R₀ was 1·5, the median cumulative number of infections at day 80 was 279 000 (IQR 245 000-320 000), corresponding to 7·4% (IQR 6·5-8·5) of the resident population of Singapore. The median number of infections increased with higher infectivity: 727 000 cases (670 000-776 000) when R₀ was 2·0, corresponding to 19·3% (17·8-20·6) of the Singaporean population, and 1 207 000 cases (1 164 000-1 249 000) when R₀ was 2·5, corresponding to 32% (30·9-33·1) of the Singaporean population. Compared with the baseline scenario, the combined intervention was the most effective, reducing the estimated median number of infections by 99·3% (IQR 92·6-99·9) when R₀ was 1·5, by 93·0% (81·5-99·7) when R₀ was 2·0, and by 78·2% (59·0 -94·4) when R₀ was 2·5. Assuming increasing asymptomatic fractions up to 50·0%, up to 277 000 infections were estimated to occur at day 80 with the combined intervention relative to 1800 for the baseline at R₀ of 1·5.

INTERPRETATION

Implementing the combined intervention of quarantining infected individuals and their family members, workplace distancing, and school closure once community transmission has been detected could substantially reduce the number of SARS-CoV-2 infections. We therefore recommend immediate deployment of this strategy if local secondary transmission is confirmed within Singapore. However, quarantine and workplace distancing should be prioritised over school closure because at this early stage, symptomatic children have higher withdrawal rates from school than do symptomatic adults from work. At higher asymptomatic proportions, intervention effectiveness might be substantially reduced requiring the need for effective case management and treatments, and preventive measures such as vaccines.

FUNDING

Singapore Ministry of Health, Singapore Population Health Improvement Centre.

Public Health Lessons Learned From Biases in Coronavirus Mortality Overestimation

In testimony before US Congress on March 11, 2020, members of the House Oversight and Reform Committee were informed that estimated mortality for the novel coronavirus was 10-times higher than for seasonal influenza. Additional evidence, however, suggests the validity of this estimation could benefit from vetting for biases and miscalculations. The main objective of this article is to critically appraise the coronavirus mortality estimation presented to Congress. Informational texts from the World Health Organization and the Centers for Disease Control and Prevention are compared with coronavirus mortality calculations in Congressional testimony. Results of this critical appraisal reveal information bias and selection bias in coronavirus mortality overestimation, most likely caused by misclassifying an influenza infection fatality rate as a case fatality rate. Public health lessons learned for future infectious disease pandemics include: safeguarding against research biases that may underestimate or overestimate an associated risk of disease and mortality; reassessing the ethics of fear-based public health campaigns; and providing full public disclosure of adverse effects from severe mitigation measures to contain viral transmission.

Quantifying How Different Clinical Presentations, Levels of Severity, and Healthcare Attendance Shape the Burden of Influenza-associated Illness: A Modeling Study From South Africa

BACKGROUND

Burden estimates of medically and nonmedically attended influenza-associated illness across syndromes and levels of severity are lacking.

METHODS

We estimated the national burden of medically and nonmedically attended influenza-associated illness among individuals with different clinical presentations (all-respiratory, all-circulatory, and nonrespiratory/noncirculatory) and levels of severity (mild, fatal, and severe, nonfatal) using a combination of case-based (from laboratory-confirmed influenza surveillance) and ecological studies, as well as data from healthcare utilization surveys in South Africa during 2013-2015. In addition, we compared estimates of medically attended influenza-associated respiratory illness, obtained from case-based and ecological studies. Rates were reported per 100 000 individuals in the population.

RESULTS

The estimated mean annual number of influenza-associated illness episodes was 10 737 847 (19.8% of 54 096 705 inhabitants). Of these episodes, 10 598 138 (98.7%) were mild, 128 173 (1.2%) were severe, nonfatal, and 11 536 (0.1%) were fatal. There were 2 718 140 (25.6%) mild, 56 226 (43.9%) severe, nonfatal, and 4945 (42.8%) medically attended should be after fatal episodes. Influenza-associated respiratory illness accounted for 99.2% (10 576 146) of any mild, 65.5% (83 941) of any severe, nonfatal, and 33.7% (3893) of any fatal illnesses. Ecological and case-based estimates of medically attended, influenza-associated, respiratory mild (rates: ecological, 1778.8, vs case-based, 1703.3; difference, 4.4%), severe, nonfatal (rates: ecological, 88.6, vs case-based, 75.3; difference, 15.0%), and fatal (rates: ecological, 3.8, vs case-based, 3.5; difference, 8.4%) illnesses were similar.

CONCLUSIONS

There was a substantial burden of influenza-associated symptomatic illness, including severe, nonfatal and fatal illnesses, and a large proportion was nonmedically attended. Estimates, including only influenza-associated respiratory illness, substantially underestimated influenza-associated, severe, nonfatal and fatal illnesses. Ecological and case-based estimates were found to be similar for the compared categories.

Predicting seasonal influenza epidemics using cross-hemisphere influenza surveillance data and local internet query data

Can early warning systems be developed to predict influenza epidemics? Using Australian influenza surveillance and local internet search query data, this study investigated whether seasonal influenza epidemics in China, the US and the UK can be predicted using empirical time series analysis. Weekly national number of respiratory cases positive for influenza virus infection that were reported to the FluNet surveillance system in Australia, China, the US and the UK were obtained from World Health Organization FluNet surveillance between week 1, 2010, and week 9, 2018. We collected combined search query data for the US and the UK from Google Trends, and for China from Baidu Index. A multivariate seasonal autoregressive integrated moving average model was developed to track influenza epidemics using Australian influenza and local search data. Parameter estimates for this model were generally consistent with the observed values. The inclusion of search metrics improved the performance of the model with high correlation coefficients (China = 0.96, the US = 0.97, the UK = 0.96, p < 0.01) and low Maximum Absolute Percent Error (MAPE) values (China = 16.76, the US = 96.97, the UK = 125.42). This study demonstrates the feasibility of combining (Australia) influenza and local search query data to predict influenza epidemics a different (northern hemisphere) scales.

Accuracy of comprehensive PCR analysis of nasopharyngeal and oropharyngeal swabs for CT-scan-confirmed pneumonia in elderly patients: a prospective cohort study

OBJECTIVES

We aimed to assess the accuracy of PCR detection of viruses and bacteria on nasopharyngeal and oropharyngeal swabs (NPS) for the diagnosis of pneumonia in elderly individuals.

METHODS

We included consecutive hospitalized elderly individuals suspected of having pneumonia. At inclusion, NPS were collected from all participants and tested by PCR for the presence of viral and bacterial respiratory pathogens (index test, defined as comprehensive molecular testing). Routine diagnostic tests (blood and sputum culture, urine antigen detection) were also performed. The reference standard was the presence of pneumonia on a low-dose CT scan as assessed by two independent expert radiologists.

RESULTS

The diagnosis of pneumonia was confirmed in 127 of 199 (64%) included patients (mean age 83 years, community-acquired pneumonia in 105 (83%)). A pathogen was identified by comprehensive molecular testing in 114 patients (57%) and by routine methods in 22 (11%). Comprehensive molecular testing was positive for viruses in 62 patients (31%) and for bacteria in 73 (37%). The sensitivity and specificity were 61% (95% CI 53%-69%) and 50% (95% CI 39%-61%) for comprehensive molecular testing, and 14% (95% CI 82%-21%) and 94% (95% CI 86%-98%) for routine testing, respectively. Positive likelihood ratio was 2.55 for routine methods and 1.23 for comprehensive molecular testing.

CONCLUSION

Comprehensive molecular testing of NPS increases the number of pathogens detected compared with routine methods, but results are poorly predictive of the presence of pneumonia. Hence, comprehensive molecular testing is unlikely to impact clinical decision-making (NCT02467192).

CLINICAL TRIALS REGISTRATION

NCT02467192.

Asymptomatic Middle East Respiratory Syndrome Coronavirus (MERS-CoV) infection: Extent and implications for infection control: A systematic review

Background

The Middle East Respiratory Syndrome Coronavirus (MERS-CoV) emerged in 2012 and attracted an international attention as the virus caused multiple healthcare associated outbreaks. There are reports of the role of asymptomatic individuals in the transmission of MERS-CoV, however, the exact role is not known.

Method

The MEDLINE/PubMed and Scopus databases were searched for relevant papers published till August 2018 describing asymptomatic MERS-CoV infection.

Results

A total of 10 papers were retrieved and included in the final analysis and review. The extent of asymptomatic MERS infection had increased with change in the policy of testing asymptomatic contacts. In early cases in April 2012–October 2013, 12.5% were asymptomatic among 144 PCR laboratory-confirmed MERS-CoV cases while in 2014 the proportion rose to 25.1% among 255 confirmed cases. The proportion of asymptomatic cases reported among pediatric confirmed MERS-CoV cases were higher (41.9%–81.8%). Overall, the detection rate of MERS infection among asymptomatic contacts was 1-3.9% in studies included in this review. Asymptomatic individuals were less likely to have underlying condition compared to fatal cases. Of particular interest is that most of the identified pediatric cases were asymptomatic with no clear explanation.

Conclusions

The proportion of asymptomatic MERS cases were detected with increasing frequency as the disease progressed overtime. Those patients were less likely to have comorbid disease and may contribute to the transmission of the virus.

Cooperative Metabolic Adaptations in the Host Can Favor Asymptomatic Infection and Select for Attenuated Virulence in an Enteric Pathogen

Pathogen virulence exists on a continuum. The strategies that drive symptomatic or asymptomatic infections remain largely unknown. We took advantage of the concept of lethal dose 50 (LD50) to ask which component of individual non-genetic variation between hosts defines whether they survive or succumb to infection. Using the enteric pathogen Citrobacter, we found no difference in pathogen burdens between healthy and symptomatic populations. Iron metabolism-related genes were induced in asymptomatic hosts compared to symptomatic or naive mice. Dietary iron conferred complete protection without influencing pathogen burdens, even at 1000× the lethal dose of Citrobacter. Dietary iron induced insulin resistance, increasing glucose levels in the intestine that were necessary and sufficient to suppress pathogen virulence. A short course of dietary iron drove the selection of attenuated Citrobacter strains that can transmit and asymptomatically colonize naive hosts, demonstrating that environmental factors and cooperative metabolic strategies can drive conversion of pathogens toward commensalism.

Prevalence of asymptomatic Zika virus infection: a systematic review

Objective

To conduct a systematic review to estimate the prevalence of asymptomatic Zika virus infection in the general population and in specific population groups.

Methods

We searched PubMed®, Embase® and LILACS online databases from inception to 26 January 2018. We included observational epidemiological studies where laboratory testing was used to confirm positive exposure of participants to Zika virus and in which Zika virus symptom status was also recorded. We excluded studies in which having symptoms of Zika virus was a criterion for inclusion. The main outcome assessed was percentage of all Zika virus-positive participants who were asymptomatic. We used a quality-effects approach and the double arcsine transformation for the meta-analysis.

Findings

We assessed 753 studies for inclusion, of which 23 were included in the meta-analysis, totalling 11 305 Zika virus-positive participants. The high degree of heterogeneity in the studies (I² = 99%) suggests that the pooled prevalence of asymptomatic Zika virus-positive participants was probably not a robust estimate. Analysis based on subgroups of the population (general population, returned travellers, blood donors, adults with Guillain–Barré syndrome, pregnant women and babies with microcephaly) was not able to explain the heterogeneity. Funnel and Doi plots showed major asymmetry, suggesting selection bias or true heterogeneity.

Conclusion

Better-quality research is needed, using standardized methods, to determine the true prevalence of asymptomatic Zika virus and whether it varies between populations or over time.

Use of social network analysis and global sensitivity and uncertainty analyses to better understand an influenza outbreak

In the summer of 2014, an influenza A(H3N2) outbreak occurred in Yichang city, Hubei province, China. A retrospective study was conducted to collect and interpret hospital and epidemiological data on it using social network analysis and global sensitivity and uncertainty analyses. Results for degree (χ²=17.6619, P<0.0001) and betweenness(χ²=21.4186, P<0.0001) centrality suggested that the selection of sampling objects were different between traditional epidemiological methods and newer statistical approaches. Clique and network diagrams demonstrated that the outbreak actually consisted of two independent transmission networks. Sensitivity analysis showed that the contact coefficient (k) was the most important factor in the dynamic model. Using uncertainty analysis, we were able to better understand the properties and variations over space and time on the outbreak. We concluded that use of newer approaches were significantly more efficient for managing and controlling infectious diseases outbreaks, as well as saving time and public health resources, and could be widely applied on similar local outbreaks.

Implications of asymptomatic carriers for infectious disease transmission and control

For infectious pathogens such as Staphylococcus aureus and Streptococcus pneumoniae, some hosts may carry the pathogen and transmit it to others, yet display no symptoms themselves. These asymptomatic carriers contribute to the spread of disease but go largely undetected and can therefore undermine efforts to control transmission. Understanding the natural history of carriage and its relationship to disease is important for the design of effective interventions to control transmission. Mathematical models of infectious diseases are frequently used to inform decisions about control and should therefore accurately capture the role played by asymptomatic carriers. In practice, incorporating asymptomatic carriers into models is challenging due to the sparsity of direct evidence. This absence of data leads to uncertainty in estimates of model parameters and, more fundamentally, in the selection of an appropriate model structure. To assess the implications of this uncertainty, we systematically reviewed published models of carriage and propose a new model of disease transmission with asymptomatic carriage. Analysis of our model shows how different assumptions about the role of asymptomatic carriers can lead to different conclusions about the transmission and control of disease. Critically, selecting an inappropriate model structure, even when parameters are correctly estimated, may lead to over- or under-estimates of intervention effectiveness. Our results provide a more complete understanding of the role of asymptomatic carriers in transmission and highlight the importance of accurately incorporating carriers into models used to make decisions about disease control.

The interplay between individual social behavior and clinical symptoms in small clustered groups

Background

Mixing patterns of human populations play a crucial role in shaping the spreading paths of infectious diseases. The diffusion of mobile and wearable devices able to record close proximity interactions represents a great opportunity for gathering detailed data on social interactions and mixing patterns in human populations. The aim of this study is to investigate how social interactions are affected by the onset of symptomatic conditions and to what extent the heterogeneity in human behavior can reflect a different risk of infection.

Methods

We study the relation between individuals’ social behavior and the onset of different symptoms, by making use of data collected in 2009 among students sharing a dormitory in a North America university campus. The dataset combines Bluetooth proximity records between study participants with self-reported daily records on their health state. Specifically, we investigate whether individuals’ social activity significantly changes during different symptomatic conditions, including those defining Influenza-like illness, and highlight to what extent possible heterogeneities in social behaviors among individuals with similar age and daily routines may be responsible for a different risk of infection for influenza.

Results

Our results suggest that symptoms associated with Influenza-like illness can be responsible of a reduction of about 40% in the average duration of contacts and of 30% in the daily time spent in social interactions, possibly driven by the onset of fever. However, differences in the number of daily contacts were found to be not statistically significant. In addition, we found that individuals who experienced clinical influenza during the study period were characterized by a significantly higher social activity. In particular, both the number of person-to-person contacts and the time spent in social interactions emerged as significant risk factors for influenza infection.

Conclusions

Our findings highlight that Influenza-like illness can remarkably reduce the social activity of individuals and strengthen the idea that the heterogeneity in social habits among individuals can significantly contribute in shaping differences among the individuals’ risk of infection.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-017-2623-2) contains supplementary material, which is available to authorized users.

H5 influenza, a global update

H5 influenza viruses have caused much alarm globally due to their high pathogenic potential. As yet we have not seen sustained spread of the virus amongst humans despite a high prevalence of the virus in avian populations. Nevertheless, isolated human cases of infection have demonstrated high mortality and there are substantial efforts being taken to monitor the evolution of the virus and to undertake preparedness activities. Here we review and discuss the evolution of the A/goose/Guangdong/1/96 (H5N1) virus with emphasis on recent events.