Global mortality estimates for the 2009 Influenza Pandemic from the GLaMOR project: a modeling study

Monitoring the mortality impact of COVID-19 in Europe: What can be learned from 2009 influenza H1N1p mortality studies?

OBJECTIVES

Understanding the proportion of pandemic deaths captured as 'laboratory-confirmed' deaths is crucial. We assessed the ability of laboratory-confirmed deaths to capture mortality in the EU during the 2009 pandemic, and examined the likelihood that these findings are applicable to the SARS-CoV-2 pandemic.

METHODS

We present unpublished results from the Global Pandemic Mortality (GLaMOR) project, in which country-specific mortality estimates were made for the 2009 influenza H1N1p pandemic. These estimates were compared with laboratory-confirmed deaths during the 2009 pandemic to estimate the ability of surveillance systems to capture pandemic mortality.

RESULTS

For the 2009 influenza H1N1p pandemic, we estimated that the proportion of true pandemic deaths captured by laboratory-confirmed deaths was approximately 67%. Several differences between the two pandemics (e.g. age groups affected) make it unlikely that this capture rate will be equally high for SARS-CoV-2.

CONCLUSION

The surveillance of laboratory-confirmed deaths in the EU during the 2009 pandemic was more accurate than previously assumed. We hypothesize that this method is less reliable for SARS-CoV-2. Near-real-time excess all-cause mortality estimates, routinely compiled by EuroMOMO, probably offer a better indicator of pandemic mortality. We urge more countries to join this project and that national-level absolute mortality numbers are presented.

Psychosocial factors and hospitalisations for COVID-19: Prospective cohort study based on a community sample

BACKGROUND

While certain infectious diseases have been linked to socioeconomic disadvantage, mental health problems, and lower cognitive function, relationships with COVID-19 are either uncertain or untested. Our objective was to examine the association of a range of psychosocial factors with hospitalisation for COVID-19.

METHODS

UK Biobank, a prospective cohort study, comprises around half a million people who were aged 40-69 years at study induction between 2006 and 2010 when information on psychosocial factors and covariates were captured. Hospitalisations for COVID-19 were ascertained between 16th March and 26th April 2020.

RESULTS

There were 908 hospitalisations for COVID-19 in an analytical sample of 431,051 England-based study members. In age- and sex-adjusted analyses, an elevated risk of COVID-19 was related to disadvantaged levels of education (odds ratio; 95% confidence interval: 2.05; 1.70, 2.47), income (2.00; 1.63, 2,47), area deprivation (2.20; 1.86, 2.59), occupation (1.39; 1.14, 1.69), psychological distress (1.58; 1.32, 1.89), mental health (1.50; 1.25, 1.79), neuroticism (1.19; 1.00, 1.42), and performance on two tests of cognitive function - verbal and numerical reasoning (2.66; 2.06, 3.34) and reaction speed (1.27; 1.08, 1.51). These associations were graded (p-value for trend ≤ 0.038) such that effects were apparent across the full psychosocial continua. After mutual adjustment for these characteristics plus ethnicity, comorbidity, and lifestyle factors, only the relationship between lower cognitive function as measured using the reasoning test and risk of the infection remained (1.98; 1.38, 2.85).

CONCLUSIONS

A range of psychosocial factors revealed associations with hospitalisation for COVID-19 of which the relation with cognitive function, a marker of health literacy, was most robust.

Estimation of Excess Deaths Associated With the COVID-19 Pandemic in the United States, March to May 2020

IMPORTANCE

Efforts to track the severity and public health impact of coronavirus disease 2019 (COVID-19) in the United States have been hampered by state-level differences in diagnostic test availability, differing strategies for prioritization of individuals for testing, and delays between testing and reporting. Evaluating unexplained increases in deaths due to all causes or attributed to nonspecific outcomes, such as pneumonia and influenza, can provide a more complete picture of the burden of COVID-19.

OBJECTIVE

To estimate the burden of all deaths related to COVID-19 in the United States from March to May 2020.

DESIGN, SETTING, AND POPULATION

This observational study evaluated the numbers of US deaths from any cause and deaths from pneumonia, influenza, and/or COVID-19 from March 1 through May 30, 2020, using public data of the entire US population from the National Center for Health Statistics (NCHS). These numbers were compared with those from the same period of previous years. All data analyzed were accessed on June 12, 2020.

MAIN OUTCOMES AND MEASURES

Increases in weekly deaths due to any cause or deaths due to pneumonia/influenza/COVID-19 above a baseline, which was adjusted for time of year, influenza activity, and reporting delays. These estimates were compared with reported deaths attributed to COVID-19 and with testing data.

RESULTS

There were approximately 781 000 total deaths in the United States from March 1 to May 30, 2020, representing 122 300 (95% prediction interval, 116 800-127 000) more deaths than would typically be expected at that time of year. There were 95 235 reported deaths officially attributed to COVID-19 from March 1 to May 30, 2020. The number of excess all-cause deaths was 28% higher than the official tally of COVID-19-reported deaths during that period. In several states, these deaths occurred before increases in the availability of COVID-19 diagnostic tests and were not counted in official COVID-19 death records. There was substantial variability between states in the difference between official COVID-19 deaths and the estimated burden of excess deaths.

CONCLUSIONS AND RELEVANCE

Excess deaths provide an estimate of the full COVID-19 burden and indicate that official tallies likely undercount deaths due to the virus. The mortality burden and the completeness of the tallies vary markedly between states.

Estimating the severity of COVID-19: Evidence from the Italian epicenter

We provide results on the level of COVID-19 excess mortality in the Italian region of Lombardy and in the province of Bergamo using official and original data sources. Since February 2020 Lombardy and in particular the province of Bergamo have been severely hit by the novel COVID-19 infectious disease. Combining official statistics, retrospective data and original data (i.e., obituaries and death notices) we provide a tentative estimate of the number of deaths either directly or indirectly, associated with COVID-19 as well as the total number of persons infected. Our findings suggest that the reported number of deaths attributable to COVID-19 identified by public authorities accounts only for one half of the observed excess mortality between March 2020 and previous years.

SARS-CoV-2/COVID-19: Evolving Reality, Global Response, Knowledge Gaps, and Opportunities

Approximately 3 billion people around the world have gone into some form of social separation to mitigate the current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. The uncontrolled influx of patients in need of emergency care has rapidly brought several national health systems to near-collapse with deadly consequences to those afflicted by Coronavirus Disease 2019 (COVID-19) and other critical diseases associated with COVID-19. Solid scientific evidence regarding SARS-CoV-2/COVID-19 remains scarce; there is an urgent need to expand our understanding of the SARS-CoV-2 pathophysiology to facilitate precise and targeted treatments. The capacity for rapid information dissemination has emerged as a double-edged sword; the existing gap of high-quality data is frequently filled by anecdotal reports, contradictory statements, and misinformation. This review addresses several important aspects unique to the SARS-CoV-2/COVID-19 pandemic highlighting the most relevant knowledge gaps and existing windows-of-opportunity. Specifically, focus is given on SARS-CoV-2 immunopathogenesis in the context of experimental therapies and preclinical evidence and their applicability in supporting efficacious clinical trial planning. The review discusses the existing challenges of SARS-CoV-2 diagnostics and the potential application of translational technology for epidemiological predictions, patient monitoring, and treatment decision-making in COVID-19. Furthermore, solutions for enhancing international strategies in translational research, cooperative networks, and regulatory partnerships are contemplated.

The unique features of SARS-CoV-2 transmission: Comparison with SARS-CoV, MERS-CoV and 2009 H1N1 pandemic influenza virus

From 2002 to 2019, three deadly human coronaviruses (hCoVs), severe acute respiratory syndrome coronavirus (SARS‐CoV), Middle Eastern respiratory syndrome coronavirus (MERS‐CoV) and severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) emerged to produce outbreaks of SARS, MERS and coronavirus disease 2019 (Covid‐19), respectively. All three hCoVs are members of the Betacoronavirus genus in the subfamily Orthocoronavirinae and share many similarities in virology and epidemiology. However, the pattern and scale of Covid‐19 global spread is similar to 2009 pandemic H1N1 influenza (H1N1pdm09), rather than SARS or MERS. Covid‐19 exhibits high viral shedding in the upper respiratory tract at an early stage of infection, and has a high proportion of transmission competent individuals that are pre‐symptomatic, asymptomatic and mildly symptomatic, characteristics seen in H1N1pdm09 but not in SARS or MERS. These two traits of Covid‐19 and H1N1pdm09 result in reduced efficiency in identification of transmission sources by symptomatic screening and play important roles in their ability to spread unchecked to cause pandemics. To overcome these attributes of Covid‐19 in community transmission, identifying the transmission source by testing for virus shedding and interrupting chains of transmission by social distancing and public masking are required.

Effects and safety of Tanreqing injection on viral pneumonia: A protocol for systematic review and meta-analysis

BACKGROUND

Influenza-related viral pneumonia is a severe threat to human health, which has caused high morbidity and mortality each year. The objective of this study was to assess the efficacy and safety of Tanreqing Injection therapy in patients with viral pneumonia.

MATERIALS AND METHODS

This protocol established in this study has been reported following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. Web of Science, PubMed, EMBASE and the Cochrane Library were searched for clinical randomized trials in cases with viral pneumonia until 1st of July 2020. We will use a combination of Medical Subject Heading and free-text terms with various synonyms to search based on the Eligibility criteria. Two investigators independently reviewed the included studies and extracted relevant data. The relative risk (RR) and 95% confidence intervals (CIs) of were used as effect estimate. I-square (I) test, substantial heterogeneity, sensitivity analysis and publication bias assessment will be performed accordingly. Stata 14.0 and Review Manger 5.3 are used for meta-analysis and systematic review.

RESULTS

The results will be published in a peer-reviewed journal.

CONCLUSION

The results of this review will be widely disseminated through peer-reviewed publications and conference presentations. This evidence may also provide helpful evidence of whether Tanreqing Injection therapy was efficient and safe in patients with viral pneumonia.

PROSPERO REGISTRATION NUMBER

CRD42020164164.

COVID-19 in Light of Seasonal Respiratory Infections

A wide diversity of zoonotic viruses that are capable of overcoming host range barriers facilitate the emergence of new potentially pandemic viruses in the human population. When faced with a new virus that is rapidly emerging in the human population, we have a limited knowledge base to work with. The pandemic invasion of the new SARS-CoV-2 virus in 2019 provided a unique possibility to quickly learn more about the pathogenesis of respiratory viruses. In this review, the impact of pandemics on the circulation of seasonal respiratory viruses is considered. The emergence of novel respiratory viruses has often been accompanied by the disappearance of existing circulating strains. Some issues arising from the spread of pandemic viruses and underlying the choices of a strategy to fight the coronavirus infection are discussed.

The Many Faces of Emerging and Reemerging Infectious Disease

The emergence of disease threats can take many forms, from the adaptation of a traditionally zoonotic pathogen for efficient spread in humans, to the development of antibiotic resistance in well-known pathogens, to the creation of new niches for established disease through social and societal changes. In this commentary, the authors explore these various facets of disease emergence through the lens of the papers included in this issue of Epidemiologic Reviews. The authors explore multiple aspects of emergence and the ways in which emergent pathogens can be controlled with the limited tools available. In doing so, they put the papers in this issue in the context of the broader research agenda around understanding and combatting emergent pathogens.

Health Technology Assessment for Vaccines Against Rare, Severe Infections: Properly Accounting for Serogroup B Meningococcal Vaccination's Full Social and Economic Benefits

The high price of new generations of vaccines relative to their predecessors has become an important consideration in debates over whether the benefits of the new vaccines justify their costs. An increasingly central line of inquiry in the literature on valuing vaccination surrounds accounting for the full social and economic benefits of vaccination. This paper applies this emerging perspective to the particular case of vaccination against serogroup B meningococcal disease (MenB). We explore key issues involved in health technology assessments of MenB vaccination, which have led to pronounced heterogeneity in evaluation methods and recommendation outcomes across countries such as France, Germany, the US, and the UK. Accounting for typically neglected sources of socioeconomic benefit could potentially impact recommendation and reimbursement decisions. We propose a taxonomy of such benefits built around four dimensions: (i) internalized health benefits, (ii) internalized non-health benefits, (iii) externalized health benefits, and (iv) externalized non-health benefits. This approach offers a systematic, comprehensive evaluation framework that can be used in future assessment of MenB vaccines as well as other health technologies.

Comparing SARS-CoV-2 with SARS-CoV and influenza pandemics

The objective of this Personal View is to compare transmissibility, hospitalisation, and mortality rates for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with those of other epidemic coronaviruses, such as severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV), and pandemic influenza viruses. The basic reproductive rate (R₀) for SARS-CoV-2 is estimated to be 2·5 (range 1·8–3·6) compared with 2·0–3·0 for SARS-CoV and the 1918 influenza pandemic, 0·9 for MERS-CoV, and 1·5 for the 2009 influenza pandemic. SARS-CoV-2 causes mild or asymptomatic disease in most cases; however, severe to critical illness occurs in a small proportion of infected individuals, with the highest rate seen in people older than 70 years. The measured case fatality rate varies between countries, probably because of differences in testing strategies. Population-based mortality estimates vary widely across Europe, ranging from zero to high. Numbers from the first affected region in Italy, Lombardy, show an all age mortality rate of 154 per 100 000 population. Differences are most likely due to varying demographic structures, among other factors. However, this new virus has a focal dissemination; therefore, some areas have a higher disease burden and are affected more than others for reasons that are still not understood. Nevertheless, early introduction of strict physical distancing and hygiene measures have proven effective in sharply reducing R₀ and associated mortality and could in part explain the geographical differences.

Future perspectives of wastewater-based epidemiology: Monitoring infectious disease spread and resistance to the community level

Infectious diseases are acknowledged as one of the most critical threats to global public health today. Climate change, unprecedented population growth with accelerated rates of antimicrobial resistance, have resulted in both the emergence of novel pathogenic organisms and the re-emergence of infections that were once controlled. The consequences have led to an increased vulnerability to infectious diseases globally. The ability to rapidly monitor the spread of diseases is key for prevention, intervention and control, however several limitations exist for current surveillance systems and the capacity to cope with the rapid population growth and environmental changes. Wastewater-Based Epidemiology (WBE) is a new epidemiology tool that has potential to act as a complementary approach for current infectious disease surveillance systems and an early warning system for disease outbreaks. WBE postulates that through the analysis of population pooled wastewater, infectious disease and resistance spread, the emergence of new disease outbreak to the community level can be monitored comprehensively and in real-time. This manuscript provides critical overview of current infectious disease surveillance status, as well as it introduces WBE and its recent advancements. It also provides recommendations for further development required for WBE application as an effective tool for infectious disease surveillance.

Mexico: Lessons learned from the 2009 pandemic that help us fight COVID-19

In April 2009, Mexican, American, and Canadian authorities announced a novel influenza that became the first pandemic of the century. We report on lessons learned in Mexico. The Mexican Pandemic Influenza Preparedness and Response Plan, developed and implemented since 2005, was a decisive element for the early response. Major lessons-learned were the need for flexible plans that consider different scenarios; the need to continuously strengthen routine surveillance programs and laboratory capacity and strengthen coordination between epidemiological departments, clinicians, and laboratories; maintain strategic stockpiles; establish a fund for public health emergencies; and collaboration among neighboring countries. Mexico responded with immediate reporting and transparency, implemented aggressive control measures and generous sharing of data and samples. Lessons learned induced changes leading to a better response to public health critical events.

Estimating the early death toll of COVID-19 in the United States

Background

Efforts to track the severity and public health impact of the novel coronavirus, COVID-19, in the US have been hampered by testing issues, reporting lags, and inconsistency between states. Evaluating unexplained increases in deaths attributed to broad outcomes, such as pneumonia and influenza (P&I) or all causes, can provide a more complete and consistent picture of the burden caused by COVID-19.

Methods

We evaluated increases in the occurrence of deaths due to P&I above a seasonal baseline (adjusted for influenza activity) or due to any cause across the United States in February and March 2020. These estimates are compared with reported deaths due to COVID-19 and with testing data.

Results

There were notable increases in the rate of death due to P&I in February and March 2020. In a number of states, these deaths pre-dated increases in COVID-19 testing rates and were not counted in official records as related to COVID-19. There was substantial variability between states in the discrepancy between reported rates of death due to COVID-19 and the estimated burden of excess deaths due to P&I. The increase in all-cause deaths in New York and New Jersey is 1.5-3 times higher than the official tally of COVID-19 confirmed deaths or the estimated excess death due to P&I.

Conclusions

Excess P&I deaths provide a conservative estimate of COVID-19 burden and indicate that COVID-19-related deaths are missed in locations with inadequate testing or intense pandemic activity.

The Phylodynamics of Seasonal Influenza A/H1N1pdm Virus in China Between 2009 and 2019

Since its first introduction into China in 2009, influenza A/H1N1pdm virus has undergone a rapid expansion and replaced the classical seasonal A(H1N1) virus. To characterize the ongoing evolution and national transmission dynamics of this virus, we analyzed 335 complete genome, 1259 HA, and 1043 NA sequences of the A/H1N1pdm strains detected in China. We found that the dN/dS value and relative genetic diversity of the A/H1N1pdm virus experienced a decrease from 2009 to 2017, and then a rapid increase during 2018–2019. Importantly, elevated relative genetic diversity was observed in the A/H1N1pdm and the A/H3N2 viruses, as well as two lineages (Victoria and Yamagata) of influenza B virus during 2018–2019, suggesting the simultaneous changes of these viruses in terms of genetic diversity might be associated with the recent large outbreak of seasonal influenza epidemic in China during 2018–2019. Fifteen amino acid mutations were found to be fixed along the main trunks of both HA and NA phylogenetic trees, and some of them are located in the antigen binding site or the receptor binding site. A sequential accumulation of mutations relative to the 2009-vaccine strain was observed in the circulating A/H1N1pdm strains during 2009–2016, while a rapid accumulation of mutations relative to the 2015-vaccine strain appeared in the emerging variants in 2017 shortly after the release of the vaccine. Multiple introductions of the A/H1N1pdm lineages into China were observed during 2009–2019, and East China and South China were found to serve as two major epicenters responsible for the national migration of the virus. In summary, these data provide important insights into the understanding of the evolution, epidemiology and transmission of the A/H1N1pdm virus, and highlight the importance of strengthening influenza surveillance in East China and South China.

Estimated hospitalisations attributable to seasonal and pandemic influenza in Australia: 2001- 2013

Background

Influenza continues to cause seasonal epidemics and pandemics in humans. The burden of influenza is underestimated by traditional laboratory-based surveillance, and modelled estimates are required for influenza-attributable morbidity and mortality. We aimed to estimate the influenza-attributable hospitalisation in Australia, by influenza type.

Methods

A generalised-additive regression model was used to estimate type- and age-specific influenza-attributable hospitalisation rates per 100,000 population by principal diagnosis in Australia, from 2001 through 2013. Weekly counts of laboratory-confirmed influenza notifications and by type, influenza A and B were used as covariates in the model. Main principal diagnosis categories of interest were influenza and pneumonia and respiratory admissions. A smoothing spline was used to control for unmeasured time varying factors. Results for 2009, in which the pandemic influenza A(H1N1)pdm09 virus circulated, were not included in annual averages and are reported separately.

Results

During the study period, the estimated annual average, all-age, annual respiratory hospitalisation rates attributable to seasonal influenza type A, B and total influenza were 45.4 (95% CI: 34.9, 55.9), 32.6 (95% CI: 22.8, 42.4), and 76.9 (95% CI: 73.6, 80.2) per 100,000 population, respectively. During 2009, the estimated total pandemic influenza-attributable, all-age, respiratory hospitalisation rate was 56.1 (95% CI: 47.4, 64.9) per 100,000. Older adults (≥85 years of age) experienced the highest influenza-attributable hospitalisation rates for both seasonal and 2009 pandemic influenza. Collinearity between influenza A and B time series in some years limited the ability of the model to resolve differences in influenza attribution between the two virus types.

Conclusion

Both seasonal and pandemic influenza caused considerable morbidity in Australia during the years studied, particularly among older adults. The pandemic hospitalisation rate in 2009 was lower than the average overall annual rate for seasonal influenza, but young to middle aged adults experience a hospitalisation rate similar to that of severe seasonal influenza.

Narrative synthesis of psychological and coping responses towards emerging infectious disease outbreaks in the general population: practical considerations for the COVID-19 pandemic

INTRODUCTION

Emerging infectious disease outbreaks, such as the present coronavirus disease 2019 (COVID-19) pandemic, often have a psychological impact on the well-being of the general population, including survivors and caregivers. Our study aimed to synthesise extant literature regarding the combined psychological responses and coping methods used by the general population in past outbreaks.

METHODS

We conducted a narrative synthesis of the published literature over the last two decades with a quality appraisal of included articles that reported both psychological responses and coping strategies within infectious disease outbreaks.

RESULTS

A total of 144 papers were identified from the search, 24 of which were included in the review. Overall, 18 studies examined the psychosocial responses of the general population towards the severe acute respiratory syndrome epidemic, four studies focused on the Ebola epidemic and two studies covered the H1N1 outbreak. Common themes in psychological responses included anxiety/fears, depression, anger, guilt, grief and loss, post-traumatic stress and stigmatisation, but also a greater sense of empowerment and compassion towards others. Coping strategies adopted included problem-focused coping (seeking alternatives, self- and other-preservation), seeking social support, avoidance, and positive appraisal of the situation.

CONCLUSION

Amid the range of psychosocial responses seen in past infectious disease outbreaks, practical considerations for the current COVID-19 pandemic need to focus on the individual in the context of the larger social environment, with an emphasis on raising awareness of the range of possible psychosocial responses, access to psychological help, self-care, empowering self-support groups and sustained engagement with updated, reliable information about the outbreak.

Real-time estimation of the influenza-associated excess mortality in Hong Kong

Statistical models are commonly employed in the estimation of influenza-associated excess mortality that, due to various reasons, is often underestimated by laboratory-confirmed influenza deaths reported by healthcare facilities. However, methodology for timely and reliable estimation of that impact remains limited because of the delay in mortality data reporting. We explored real-time estimation of influenza-associated excess mortality by types/subtypes in each year between 2012 and 2018 in Hong Kong using linear regression models fitted to historical mortality and influenza surveillance data. We could predict that during the winter of 2017/2018, there were ~634 (95% confidence interval (CI): (190, 1033)) influenza-associated excess all-cause deaths in Hong Kong in population ⩾18 years, compared to 259 reported laboratory-confirmed deaths. We estimated that influenza was associated with substantial excess deaths in older adults, suggesting the implementation of control measures, such as administration of antivirals and vaccination, in that age group. The approach that we developed appears to provide robust real-time estimates of the impact of influenza circulation and complement surveillance data on laboratory-confirmed deaths. These results improve our understanding of the impact of influenza epidemics and provide a practical approach for a timely estimation of the mortality burden of influenza circulation during an ongoing epidemic.

Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study

Background

As the outbreak of coronavirus disease 2019 (COVID-19) progresses, epidemiological data are needed to guide situational awareness and intervention strategies. Here we describe efforts to compile and disseminate epidemiological information on COVID-19 from news media and social networks.

Methods

In this population-level observational study, we searched DXY.cn, a health-care-oriented social network that is currently streaming news reports on COVID-19 from local and national Chinese health agencies. We compiled a list of individual patients with COVID-19 and daily province-level case counts between Jan 13 and Jan 31, 2020, in China. We also compiled a list of internationally exported cases of COVID-19 from global news media sources (Kyodo News, The Straits Times, and CNN), national governments, and health authorities. We assessed trends in the epidemiology of COVID-19 and studied the outbreak progression across China, assessing delays between symptom onset, seeking care at a hospital or clinic, and reporting, before and after Jan 18, 2020, as awareness of the outbreak increased. All data were made publicly available in real time.

Findings

We collected data for 507 patients with COVID-19 reported between Jan 13 and Jan 31, 2020, including 364 from mainland China and 143 from outside of China. 281 (55%) patients were male and the median age was 46 years (IQR 35-60). Few patients (13 [3%]) were younger than 15 years and the age profile of Chinese patients adjusted for baseline demographics confirmed a deficit of infections among children. Across the analysed period, delays between symptom onset and seeking care at a hospital or clinic were longer in Hubei province than in other provinces in mainland China and internationally. In mainland China, these delays decreased from 5 days before Jan 18, 2020, to 2 days thereafter until Jan 31, 2020 (p=0·0009). Although our sample captures only 507 (5·2%) of 9826 patients with COVID-19 reported by official sources during the analysed period, our data align with an official report published by Chinese authorities on Jan 28, 2020.

Interpretation

News reports and social media can help reconstruct the progression of an outbreak and provide detailed patient-level data in the context of a health emergency. The availability of a central physician-oriented social network facilitated the compilation of publicly available COVID-19 data in China. As the outbreak progresses, social media and news reports will probably capture a diminishing fraction of COVID-19 cases globally due to reporting fatigue and overwhelmed health-care systems. In the early stages of an outbreak, availability of public datasets is important to encourage analytical efforts by independent teams and provide robust evidence to guide interventions.

Funding

Fogarty International Center, US National Institutes of Health.

Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study

BACKGROUND

As the outbreak of coronavirus disease 2019 (COVID-19) progresses, epidemiological data are needed to guide situational awareness and intervention strategies. Here we describe efforts to compile and disseminate epidemiological information on COVID-19 from news media and social networks.

METHODS

In this population-level observational study, we searched DXY.cn, a health-care-oriented social network that is currently streaming news reports on COVID-19 from local and national Chinese health agencies. We compiled a list of individual patients with COVID-19 and daily province-level case counts between Jan 13 and Jan 31, 2020, in China. We also compiled a list of internationally exported cases of COVID-19 from global news media sources (Kyodo News, The Straits Times, and CNN), national governments, and health authorities. We assessed trends in the epidemiology of COVID-19 and studied the outbreak progression across China, assessing delays between symptom onset, seeking care at a hospital or clinic, and reporting, before and after Jan 18, 2020, as awareness of the outbreak increased. All data were made publicly available in real time.

FINDINGS

We collected data for 507 patients with COVID-19 reported between Jan 13 and Jan 31, 2020, including 364 from mainland China and 143 from outside of China. 281 (55%) patients were male and the median age was 46 years (IQR 35-60). Few patients (13 [3%]) were younger than 15 years and the age profile of Chinese patients adjusted for baseline demographics confirmed a deficit of infections among children. Across the analysed period, delays between symptom onset and seeking care at a hospital or clinic were longer in Hubei province than in other provinces in mainland China and internationally. In mainland China, these delays decreased from 5 days before Jan 18, 2020, to 2 days thereafter until Jan 31, 2020 (p=0·0009). Although our sample captures only 507 (5·2%) of 9826 patients with COVID-19 reported by official sources during the analysed period, our data align with an official report published by Chinese authorities on Jan 28, 2020.

INTERPRETATION

News reports and social media can help reconstruct the progression of an outbreak and provide detailed patient-level data in the context of a health emergency. The availability of a central physician-oriented social network facilitated the compilation of publicly available COVID-19 data in China. As the outbreak progresses, social media and news reports will probably capture a diminishing fraction of COVID-19 cases globally due to reporting fatigue and overwhelmed health-care systems. In the early stages of an outbreak, availability of public datasets is important to encourage analytical efforts by independent teams and provide robust evidence to guide interventions.

FUNDING

Fogarty International Center, US National Institutes of Health.

Use of corticosteroids in influenza-associated acute respiratory distress syndrome and severe pneumonia: a systemic review and meta-analysis

Influenza-related severe pneumonia and acute respiratory distress syndrome (ARDS) are severe threats to human health. The objective of this study was to assess the effects of systematic corticosteroid therapy in patients with pneumonia or ARDS. The PubMed, EMBASE, Web of Science and SCOPUS databases were searched up to July, 2019. Nineteen studies including 6637 individuals were identified, and fifteen studies (6427 patients) were included in the meta-analysis of mortality. Eighteen were observational studies and one was a randomized controlled trial (RCT). The meta-analysis results showed that corticosteroid therapy was associated with significantly higher mortality (OR 1.53, 95% CI [1.16, 2.01]) and incidence of nosocomial infection (OR 3.15, 95% CI [1.54, 6.45]). Subgroup analysis showed that among patients with unadjusted estimates, the odds of mortality were higher in patients receiving corticosteroid treatment (OR 1.98, 95% CI [1.23, 3.17]), however, among patients with adjusted estimates, the result showed no statistically significant difference between corticosteroid group and control group (OR 1.31, 95% CI [0.95, 1.80]). Current data do not support the routine use of corticosteroids in patients with influenza severe pneumonia or ARDS. RCTs are needed to provide more robust evidence.

Global mortality associated with seasonal influenza epidemics: New burden estimates and predictors from the GLaMOR Project

Background

Until recently, the World Health Organization (WHO) estimated the annual mortality burden of influenza to be 250 000 to 500 000 all-cause deaths globally; however, a 2017 study indicated a substantially higher mortality burden, at 290 000-650 000 influenza-associated deaths from respiratory causes alone, and a 2019 study estimated 99 000-200 000 deaths from lower respiratory tract infections directly caused by influenza. Here we revisit global and regional estimates of influenza mortality burden and explore mortality trends over time and geography.

Methods

We compiled influenza-associated excess respiratory mortality estimates for 31 countries representing 5 WHO regions during 2002-2011. From these we extrapolated the influenza burden for all 193 countries of the world using a multiple imputation approach. We then used mixed linear regression models to identify factors associated with high seasonal influenza mortality burden, including influenza types and subtypes, health care and socio-demographic development indicators, and baseline mortality levels.

Results

We estimated an average of 389 000 (uncertainty range 294 000-518 000) respiratory deaths were associated with influenza globally each year during the study period, corresponding to ~ 2% of all annual respiratory deaths. Of these, 67% were among people 65 years and older. Global burden estimates were robust to the choice of countries included in the extrapolation model. For people <65 years, higher baseline respiratory mortality, lower level of access to health care and seasons dominated by the A(H1N1)pdm09 subtype were associated with higher influenza-associated mortality, while lower level of socio-demographic development and A(H3N2) dominance was associated with higher influenza mortality in adults ≥65 years.

Conclusions

Our global estimate of influenza-associated excess respiratory mortality is consistent with the 2017 estimate, despite a different modelling strategy, and the lower 2019 estimate which only captured deaths directly caused by influenza. Our finding that baseline respiratory mortality and access to health care are associated with influenza-related mortality in persons <65 years suggests that health care improvements in low and middle-income countries might substantially reduce seasonal influenza mortality. Our estimates add to the body of evidence on the variation in influenza burden over time and geography, and begin to address the relationship between influenza-associated mortality, health and development.

The effects of age on clinical characteristics, hospitalization and mortality of patients with influenza-related illness at a tertiary care centre in Malaysia

Background

Age is an established risk factor for poor outcomes in individuals with influenza‐related illness, and data on its influence on clinical presentations and outcomes in the South‐East Asian settings are scarce. The aim of this study was to determine the above among adults with influenza‐related upper respiratory tract infection at a teaching hospital in Malaysia.

Methods

A retrospective case‐note analysis was conducted on a cohort of 3935 patients attending primary care at the University Malaya Medical Centre, Malaysia from February 2012 till May 2014 with URTI symptoms. Demographics, clinical characteristics, medical and vaccination history were obtained from electronic medical records, and mortality data from the National Registration Department. Comparisons were made between those aged <25, ≥25 to <65 and ≥65 years.

Results

470 (11.9%) had PCR‐confirmed influenza virus infection. Six (1.3%) received prior influenza vaccination. Those aged ≥65 years were more likely to have ≥2 comorbidities (P < .001) and were less likely to present with fever (P = .004). One‐third of those aged ≥65 years experienced hospitalization, intensive care admission or death within a year compared to 10% in the ≥25 to <65 years. Age ≥65 years was an independent predictor of hospitalization and death (OR = 9.97; 95% CI = 3.11‐31.93) compared to those aged <25 years.

Conclusion

Older patients in our cohort were more likely to have comorbidities and present with atypical features, with older age being an independent predictor of poor health outcomes. Our findings will now inform future health policies on older persons and economic modelling of adult vaccination programmes.

Genome-wide CRISPR screen identifies host dependency factors for influenza A virus infection

Host dependency factors that are required for influenza A virus infection may serve as therapeutic targets as the virus is less likely to bypass them under drug-mediated selection pressure. Previous attempts to identify host factors have produced largely divergent results, with few overlapping hits across different studies. Here, we perform a genome-wide CRISPR/Cas9 screen and devise a new approach, meta-analysis by information content (MAIC) to systematically combine our results with prior evidence for influenza host factors. MAIC out-performs other meta-analysis methods when using our CRISPR screen as validation data. We validate the host factors, WDR7, CCDC115 and TMEM199, demonstrating that these genes are essential for viral entry and regulation of V-type ATPase assembly. We also find that CMTR1, a human mRNA cap methyltransferase, is required for efficient viral cap snatching and regulation of a cell autonomous immune response, and provides synergistic protection with the influenza endonuclease inhibitor Xofluza.

Here, Li et al. perform a genome-wide CRISPR screen to identify host dependency factors for influenza A virus infection and show that the host mRNA cap methyltransferase CMTR1 is important for viral cap snatching and that it affects expression of antiviral genes.

The inducible amphisome isolates viral hemagglutinin and defends against influenza A virus infection

The emergence of drug-resistant influenza type A viruses (IAVs) necessitates the development of novel anti-IAV agents. Here, we target the IAV hemagglutinin (HA) protein using multivalent peptide library screens and identify PVF-tet, a peptide-based HA inhibitor. PVF-tet inhibits IAV cytopathicity and propagation in cells by binding to newly synthesized HA, rather than to the HA of the parental virus, thus inducing the accumulation of HA within a unique structure, the inducible amphisome, whose production from the autophagosome is accelerated by PVF-tet. The amphisome is also produced in response to IAV infection in the absence of PVF-tet by cells overexpressing ABC transporter subfamily A3, which plays an essential role in the maturation of multivesicular endosomes into the lamellar body, a lipid-sorting organelle. Our results show that the inducible amphisomes can function as a type of organelle-based anti-viral machinery by sequestering HA. PVF-tet efficiently rescues mice from the lethality of IAV infection.

Childhood immune imprinting to influenza A shapes birth year-specific risk during seasonal H1N1 and H3N2 epidemics

Across decades of co-circulation in humans, influenza A subtypes H1N1 and H3N2 have caused seasonal epidemics characterized by different age distributions of cases and mortality. H3N2 causes the majority of severe, clinically attended cases in high-risk elderly cohorts, and the majority of overall deaths, whereas H1N1 causes fewer deaths overall, and cases shifted towards young and middle-aged adults. These contrasting age profiles may result from differences in childhood imprinting to H1N1 and H3N2 or from differences in evolutionary rate between subtypes. Here we analyze a large epidemiological surveillance dataset to test whether childhood immune imprinting shapes seasonal influenza epidemiology, and if so, whether it acts primarily via homosubtypic immune memory or via broader, heterosubtypic memory. We also test the impact of evolutionary differences between influenza subtypes on age distributions of cases. Likelihood-based model comparison shows that narrow, within-subtype imprinting shapes seasonal influenza risk alongside age-specific risk factors. The data do not support a strong effect of evolutionary rate, or of broadly protective imprinting that acts across subtypes. Our findings emphasize that childhood exposures can imprint a lifelong immunological bias toward particular influenza subtypes, and that these cohort-specific biases shape epidemic age distributions. As a consequence, newer and less "senior" antibody responses acquired later in life do not provide the same strength of protection as responses imprinted in childhood. Finally, we project that the relatively low mortality burden of H1N1 may increase in the coming decades, as cohorts that lack H1N1-specific imprinting eventually reach old age.

Flying, phones and flu: Anonymized call records suggest that Keflavik International Airport introduced pandemic H1N1 into Iceland in 2009

Background

Data collected by mobile devices can augment surveillance of epidemics in real time. However, methods and evidence for the integration of these data into modern surveillance systems are sparse. We linked call detail records (CDR) with an influenza‐like illness (ILI) registry and evaluated the role that Icelandic international travellers played in the introduction and propagation of influenza A/H1N1pdm09 virus in Iceland through the course of the 2009 pandemic.

Methods

This nested case‐control study compared odds of exposure to Keflavik International Airport among cases and matched controls producing longitudinal two‐week matched odds ratios (mORs) from August to December 2009. We further evaluated rates of ILI among 1st‐ and 2nd‐degree phone connections of cases compared to their matched controls.

Results

The mOR was elevated in the initial stages of the epidemic from 7 August until 21 August (mOR = 2.53; 95% confidence interval (CI) = 1.35, 4.78). During the two‐week period from 17 August through 31 August, we calculated the two‐week incidence density ratio of ILI among 1st‐degree connections to be 2.96 (95% CI: 1.43, 5.84).

Conclusions

Exposure to Keflavik International Airport increased the risk of incident ILI diagnoses during the initial stages of the epidemic. Using these methods for other regions of Iceland, we evaluated the geographic spread of ILI over the course of the epidemic. Our methods were validated through similar evaluation of a domestic airport. The techniques described in this study can be used for hypothesis‐driven evaluations of locations and behaviours during an epidemic and their associations with health outcomes.

Using Clinical Research Networks to Assess Severity of an Emerging Influenza Pandemic

Background

Early clinical severity assessments during the 2009 influenza A H1N1 pandemic (pH1N1) overestimated clinical severity due to selection bias and other factors. We retrospectively investigated how to use data from the International Network for Strategic Initiatives in Global HIV Trials, a global clinical influenza research network, to make more accurate case fatality ratio (CFR) estimates early in a future pandemic, an essential part of pandemic response.

Methods

We estimated the CFR of medically attended influenza (CFR_MA) as the product of probability of hospitalization given confirmed outpatient influenza and the probability of death given hospitalization with confirmed influenza for the pandemic (2009–2011) and post-pandemic (2012–2015) periods. We used literature survey results on health-seeking behavior to convert that estimate to CFR among all infected persons (CFR_AR).

Results

During the pandemic period, 5.0% (3.1%–6.9%) of 561 pH1N1-positive outpatients were hospitalized. Of 282 pH1N1-positive inpatients, 8.5% (5.7%–12.6%) died. CFR_MA for pH1N1 was 0.4% (0.2%–0.6%) in the pandemic period 2009–2011 but declined 5-fold in young adults during the post-pandemic period compared to the level of seasonal influenza in the post-pandemic period 2012–2015. CFR for influenza-negative patients did not change over time. We estimated the 2009 pandemic CFR_AR to be 0.025%, 16-fold lower than CFR_MA.

Conclusions

Data from a clinical research network yielded accurate pandemic severity estimates, including increased severity among younger people. Going forward, clinical research networks with a global presence and standardized protocols would substantially aid rapid assessment of clinical severity.

Clinical Trials Registration

NCT01056354 and NCT010561.

Are Community Acquired Respiratory Viral Infections an Underestimated Burden in Hematology Patients?

Despite a plethora of studies demonstrating significant morbidity and mortality due to community-acquired respiratory viral (CRV) infections in intensively treated hematology patients, and despite the availability of evidence-based guidelines for the diagnosis and management of respiratory viral infections in this setting, there is no uniform inclusion of respiratory viral infection management in the clinical hematology routine. Nevertheless, timely diagnosis and systematic management of CRV infections in intensively treated hematology patients has a demonstrated potential to significantly improve outcome. We have briefly summarized the recently published data on CRV infection epidemiology, as well as guidelines on the diagnosis and management of CRV infections in patients intensively treated for hematological malignancies. We have also assessed available treatment options, as well as mentioned novel agents currently in development.

Approaches to use the WHO respiratory syncytial virus surveillance platform to estimate disease burden

The World Health Organization (WHO) recently completed the first phase of a RSV surveillance pilot study in fourteen countries (two to three in each WHO region) building on the Global Influenza Surveillance and Response System (GISRS). This active surveillance strategy had several objectives including understanding RSV-related health burden in a variety of settings. A range of approaches can be used to estimate disease burden; most approaches could not be applied by participating countries in the WHO surveillance pilot. This article provides the recommendations made by WHO for strengthening and expanding the scope of the RSV surveillance in the next phase to enable burden estimation.

RNA Sequence Features Are at the Core of Influenza A Virus Genome Packaging

The influenza A virus (IAV), a respiratory pathogen for humans, poses serious medical and economic challenges to global healthcare systems. The IAV genome, consisting of eight single-stranded viral RNA segments, is incorporated into virions by a complex process known as genome packaging. Specific RNA sequences within the viral RNA segments serve as signals that are necessary for genome packaging. Although efficient packaging is a prerequisite for viral infectivity, many of the mechanistic details about this process are still missing. In this review, we discuss the recent advances toward the understanding of IAV genome packaging and focus on the RNA features that play a role in this process.

The Role of Innate Leukocytes during Influenza Virus Infection

Influenza virus infection is a serious threat to humans and animals, with the potential to cause severe pneumonia and death. Annual vaccination strategies are a mainstay to prevent complications related to influenza. However, protection from the emerging subtypes of influenza A viruses (IAV) even in vaccinated individuals is challenging. Innate immune cells are the first cells to respond to IAV infection in the respiratory tract. Virus replication-induced production of cytokines from airway epithelium recruits innate immune cells to the site of infection. These leukocytes, namely, neutrophils, monocytes, macrophages, dendritic cells, eosinophils, natural killer cells, innate lymphoid cells, and γδ T cells, become activated in response to IAV, to contain the virus and protect the airway epithelium while triggering the adaptive arm of the immune system. This review addresses different anti-influenza virus schemes of innate immune cells and how these cells fine-tune the balance between immunoprotection and immunopathology during IAV infection. Detailed understanding on how these innate responders execute anti-influenza activity will help to identify novel therapeutic targets to halt IAV replication and associated immunopathology.

Host susceptibility to severe influenza A virus infection

Most people exposed to a new flu virus do not notice any symptoms. A small minority develops critical illness. Some of this extremely broad variation in susceptibility is explained by the size of the initial inoculum or the influenza exposure history of the individual; some is explained by generic host factors, such as frailty, that decrease resilience following any systemic insult. Some demographic factors (pregnancy, obesity, and advanced age) appear to confer a more specific susceptibility to severe illness following infection with influenza viruses. As with other infectious diseases, a substantial component of susceptibility is determined by host genetics. Several genetic susceptibility variants have now been reported with varying levels of evidence. Susceptible hosts may have impaired intracellular controls of viral replication (e.g. IFITM3, TMPRS22 variants), defective interferon responses (e.g. GLDC, IRF7/9 variants), or defects in cell-mediated immunity with increased baseline levels of systemic inflammation (obesity, pregnancy, advanced age). These mechanisms may explain the prolonged viral replication reported in critically ill patients with influenza: patients with life-threatening disease are, by definition, abnormal hosts. Understanding these molecular mechanisms of susceptibility may in the future enable the design of host-directed therapies to promote resilience.

Clinical and economic analysis of the 2009 H1N1 influenza pandemic among pregnant Korean women

BACKGROUND/AIMS

Unlike Western countries, the 2009 pandemic influenza infection among pregnant women was reported as mild in a previous interim study in South Korea. However, several mortalities were reported thereafter, suggesting that nationwide data were lacking.

METHODS

This case-control study covers the entire 2009 pandemic inf luenza period, from May 2009 to February 2010. The clinical and economic data of pregnant (case) and age-matched non-pregnant (control) women with influenza A (H1N1) pdm09 virus (H1N1pdm09) infection were retrospectively collected from nine hospitals in South Korea.

RESULTS

A total of 130 pregnant women with H1N1pdm09 infection were identified. The mean age of the pregnant women was 31.1 years (range, 19 to 41) and mean gestational age was 18.4 weeks (range, 3 to 40). Both case and control groups were similar in terms of age (p = 0.43) and comorbidities (p = 0.18). The overall rate of complications was comparable between the two groups (p = 0.648). However, mortality was reported only among the cases, so mean economic per capita burden is estimated to be higher for pregnant women compared to the control (4,821,992 Korean won [KRW] vs. 351,233 KRW, p = 0.31). Obstetric complications were observed in 12 cases, including preterm labor (n = 7), low birth-weight (n = 3), miscarriage (n = 1), stillbirth (n = 1), and cleft lip (n = 1).

CONCLUSION

Although statistically insignificant, the detrimental impact of influenza A H1N1pdm09 on pregnancy can be serious in some complicated cases in South Korea. Thus, the strong recommendation of influenza vaccination should be maintained for pregnant women as a high priority.

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.

Phylodynamics of Influenza A/H1N1pdm09 in India Reveals Circulation Patterns and Increased Selection for Clade 6b Residues and Other High Mortality Mutants

The clinical severity and observed case fatality ratio of influenza A/H1N1pdm09 in India, particularly in 2015 and 2017 far exceeds current global estimates. Reasons for these frequent and severe epidemic waves remain unclear. We used Bayesian phylodynamic methods to uncover possible genetic explanations for this, while also identifying the transmission dynamics of A/H1N1pdm09 between 2009 and 2017 to inform future public health interventions. We reveal a disproportionate selection at haemagglutinin residue positions associated with increased morbidity and mortality in India such as position 222 and clade 6B characteristic residues, relative to equivalent isolates circulating globally. We also identify for the first time, increased selection at position 186 as potentially explaining the severity of recent A/H1N1pdm09 epidemics in India. We reveal national routes of A/H1N1pdm09 transmission, identifying Maharashtra as the most important state for the spread throughout India, while quantifying climactic, ecological, and transport factors as drivers of within-country transmission. Together these results have important implications for future A/H1N1pdm09 surveillance and control within India, but also for epidemic and pandemic risk prediction around the world.

Are social inequalities in influenza vaccination coverage in Japan reduced by health policy?

Influenza vaccination is effective to prevent influenza infection. However, findings about association between socioeconomic status and influenza vaccination coverage are controversial. Online survey was conducted among 4995 participants between 20 and 69 years of age throughout Japan, January 2017. We asked about history of receiving vaccination in previous year and socioeconomic status, with their reasons for having vaccination or not. Age stratified multivariable logistic regression model was conducted to estimate the odds ratio (ORs) and 95% confidence intervals (CIs) of receiving vaccine for each educational level and income. Sex, self-reported health status, marital status and income were included as covariates. The rate for receiving influenza vaccine among ≤64 year-olds and ≥65 year-olds was 32.9% and 35.4%, respectively. Among younger adults, vaccination varied by each education: junior high school, 23.6%; senior high school, 27.2%; college, 32.6%; university, 36.2%; and graduate school, 39.8%. Compared to junior high school, those from graduate school tended to be more vaccinated (OR1.88, 95%CI 1.07–3.24). On the contrary, those aged above ≥65 years old received vaccination with no significant differences across education. Likewise, among respondents aged ≤64 year-olds, income was significantly associated with influenza vaccination. Despite being “Managed by school or company” (32.5%), having “No particular reason” was the frequent reason for both receiving influenza vaccination (23.8%) or not (34.3%). Adults with higher educational level were significantly more likely to receive vaccination. Subsidizing influenza vaccination may reduce inequality in receiving vaccination for adults. Strengthening vaccination through various approaches is necessary, such as managing by school or company.

Flucast: A Real-Time Tool to Predict Severity of an Influenza Season

Background

Influenza causes serious illness requiring annual health system surge capacity, yet annual seasonal variation makes it difficult to forecast and plan for the severity of an upcoming season. Research shows that hospital and health system stakeholders indicate a preference for forecasting tools that are easy to use and understand to assist with surge capacity planning for influenza.

Objective

This study aimed to develop a simple risk prediction tool, Flucast, to predict the severity of an emerging influenza season.

Methods

Study data were obtained from the National Notifiable Diseases Surveillance System and Australian Influenza Surveillance Reports from the Department of Health, Australia. We tested Flucast using retrospective seasonal data for 11 Australian influenza seasons. We compared five different models using parameters known early in the season that may be associated with the severity of the season. To calibrate the tool, the resulting estimates of seasonal severity were validated against independent reports of influenza-attributable morbidity and mortality. The model with the highest predictive accuracy against retrospective seasonal activity was chosen as a best-fit model to develop the Flucast tool. The tool was prospectively tested against the 2018 and the emerging 2019 influenza season.

Results

The Flucast tool predicted the severity of all retrospectively studied years correctly for influenza seasonal activity in Australia. With the use of real-time data, the tool provided a reasonable early prediction of a low to moderate season for the 2018 and severe seasonal activity for the upcoming 2019 season. The tool meets stakeholder preferences for simplicity and ease of use to assist with surge capacity planning.

Conclusions

The Flucast tool may be useful to inform future health system influenza preparedness planning, surge capacity, and intervention programs in real time, and can be adapted for different settings and geographic locations.

Bigger and Better? Representativeness of the Influenza A Surveillance Using One Consolidated Clinical Microbiology Laboratory Data Set as Compared to the Belgian Sentinel Network of Laboratories

Infectious diseases remain a serious public health concern globally, while the need for reliable and representative surveillance systems remains as acute as ever. The public health surveillance of infectious diseases uses reported positive results from sentinel clinical laboratories or laboratory networks, to survey the presence of specific microbial agents known to constitute a threat to public health in a given population. This monitoring activity is commonly based on a representative fraction of the microbiology laboratories nationally reporting to a single central reference point. However, in recent years a number of clinical microbiology laboratories (CML) have undergone a process of consolidation involving a shift toward laboratory amalgamation and closer real-time informational linkage. This report aims to investigate whether such merging activities might have a potential impact on infectious diseases surveillance. Influenza data was used from Belgian public health surveillance 2014–2017, to evaluate whether national infection trends could be estimated equally as effectively from only just one centralized CML serving the wider Brussels area (LHUB-ULB). The overall comparison reveals that there is a close correlation and representativeness of the LHUB-ULB data to the national and international data for the same time periods, both on epidemiological and molecular grounds. Notably, the effectiveness of the LHUB-ULB surveillance remains partially subject to local regional variations. A subset of the Influenza samples had their whole genome sequenced so that the observed epidemiological trends could be correlated to molecular observations from the same period, as an added-value proposition. These results illustrate that the real-time integration of high-throughput whole genome sequencing platforms available in consolidated CMLs into the public health surveillance system is not only credible but also advantageous to use for future surveillance and prediction purposes. This can be most effective when implemented for automatic detection systems that might include multiple layers of information and timely implementation of control strategies.

Host-Pathogen Interactions in Gram-Positive Bacterial Pneumonia

Community-acquired pneumonia (CAP) is a leading cause of morbidity and mortality worldwide. Despite broad literature including basic and translational scientific studies, many gaps in our understanding of host-pathogen interactions remain. In this review, pathogen virulence factors that drive lung infection and injury are discussed in relation to their associated host immune pathways. CAP epidemiology is considered, with a focus on Staphylococcus aureus and Streptococcus pneumoniae as primary pathogens. Bacterial factors involved in nasal colonization and subsequent virulence are illuminated. A particular emphasis is placed on bacterial pore-forming toxins, host cell death, and inflammasome activation. Identified host-pathogen interactions are then examined by linking pathogen factors to aberrant host response pathways in the context of acute lung injury in both primary and secondary infection. While much is known regarding bacterial virulence and host immune responses, CAP management is still limited to mostly supportive care. It is likely that improvements in therapy will be derived from combinatorial targeting of both pathogen virulence factors and host immunomodulation.

The Symmetric Difference Distance: A New Way to Evaluate the Evolution of Interfaces along Molecular Dynamics Trajectories; Application to Influenza Hemagglutinin

We propose a new and easy approach to evaluate structural dissimilarities between frames issued from molecular dynamics, and we test this methodology on human hemagglutinin. This protein is responsible for the entry of the influenza virus into the host cell by endocytosis, and this virus causes seasonal epidemics of infectious disease, which can be estimated to result in hundreds of thousands of deaths each year around the world. We computed the three interfaces between the three protomers of the hemagglutinin H1 homotrimer (PDB code: 1RU7) for each of its conformations generated from molecular dynamics simulation. For each conformation, we considered the set of residues involved in the union of these three interfaces. The dissimilarity between each pair of conformations was measured with our new methodology, the symmetric difference distance between the associated set of residues. The main advantages of the full procedure are: (i) it is parameter free; (ii) no spatial alignment is needed and (iii) it is simple enough so that it can be implemented by a beginner in programming. It is shown to be a relevant tool to follow the evolution of the conformation along the molecular dynamics trajectories.