Association between the Severity of Influenza A(H7N9) Virus Infections and Length of the Incubation Period

Effects of climatic factors on human parainfluenza 1, 2, and 3 infections in Cheonan, Republic of Korea

Studying relationships between meteorological conditions and respiratory virus infections may help interpret the causality of disease outbreaks and provide a better understanding of the seasonal distribution of viruses. Therefore, in this study, we analyzed the correlations between meteorological data and the trends of infection by human parainfluenza virus-1 (HPIV-1; also known as human respirovirus 1), human parainfluenza virus-2 (human orthorubulavirus 2), and human parainfluenza virus-3 (human respirovirus 3) using 9010 viral samples collected at Dankook University Hospital from January 1, 2012, to December 31, 2018. Infection frequency data were used to detect the seasonal patterns of HPIV-1, HPIV-2, and HPIV-3 infections, and these patterns were compared with local weather data over the same period. We performed descriptive statistical analysis, frequency analysis, t test, and binomial logistic regression analysis to examine the relationships of weather and particulate matter conditions with the incidence of HPIV-1, HPIV-2, and HPIV-3 infections. The highest average infection rate with one of these three viruses (88.17%) was found in children aged 1-9 years. Specifically, the infection rate of HPIV-1 was 91.9% in children aged 1-9 years, whereas that of HPIV-2 and HPIV-3 was 86.3%. HPIV infection exhibited a meaningful relationship with climatic factors, such as temperature, wind-chill temperature, and atmospheric pressure. Our results suggest that climate changes might affect the rate of infection by HPIV. These findings may help in predicting the effectiveness of preventive strategies of HPIV infection.

Prediction of the incubation period for COVID-19 and future virus disease outbreaks

Background

A crucial factor in mitigating respiratory viral outbreaks is early determination of the duration of the incubation period and, accordingly, the required quarantine time for potentially exposed individuals. At the time of the COVID-19 pandemic, optimization of quarantine regimes becomes paramount for public health, societal well-being, and global economy. However, biological factors that determine the duration of the virus incubation period remain poorly understood.

Results

We demonstrate a strong positive correlation between the length of the incubation period and disease severity for a wide range of human pathogenic viruses. Using a machine learning approach, we develop a predictive model that accurately estimates, solely from several virus genome features, in particular, the number of protein-coding genes and the GC content, the incubation time ranges for diverse human pathogenic RNA viruses including SARS-CoV-2. The predictive approach described here can directly help in establishing the appropriate quarantine durations and thus facilitate controlling future outbreaks.

Conclusions

The length of the incubation period in viral diseases strongly correlates with disease severity, emphasizing the biological and epidemiological importance of the incubation period. Perhaps, surprisingly, incubation times of pathogenic RNA viruses can be accurately predicted solely from generic features of virus genomes. Elucidation of the biological underpinnings of the connections between these features and disease progression can be expected to reveal key aspects of virus pathogenesis.

Systematic analysis of infectious disease outcomes by age shows lowest severity in school-age children

The COVID-19 pandemic has ignited interest in age-specific manifestations of infection but surprisingly little is known about relative severity of infectious disease between the extremes of age. In a systematic analysis we identified 142 datasets with information on severity of disease by age for 32 different infectious diseases, 19 viral and 13 bacterial. For almost all infections, school-age children have the least severe disease, and severity starts to rise long before old age. Indeed, for many infections even young adults have more severe disease than children, and dengue was the only infection that was most severe in school-age children. Together with data on vaccine response in children and young adults, the findings suggest peak immune function is reached around 5-14 years of age. Relative immune senescence may begin much earlier than assumed, before accelerating in older age groups. This has major implications for understanding resilience to infection, optimal vaccine scheduling, and appropriate health protection policies across the life course.

Certainty of success: three critical parameters in coronavirus vaccine development

Vaccines for 17 viral pathogens have been licensed for use in humans. Previously, two critical biological parameters of the pathogen and the host–pathogen interaction—incubation period and broadly protective, relative immunogenicity—were proposed to account for much of the past successes in vaccine development, and to be useful in estimating the “certainty of success” of developing an effective vaccine for viral pathogens for which a vaccine currently does not exist. In considering the “certainty of success” in development of human coronavirus vaccines, particularly SARS-CoV-2, a third, related critical parameter is proposed—infectious inoculum intensity, at an individual-level, and force of infection, at a population-level. Reducing the infectious inoculum intensity (and force of infection, at a population-level) is predicted to lengthen the incubation period, which in turn is predicted to reduce the severity of illness, and increase the opportunity for an anamnestic response upon exposure to the circulating virus. Similarly, successfully implementing individual- and population-based behaviors that reduce the infectious inoculum intensity and force of infection, respectively, while testing and deploying COVID-19 vaccines is predicted to increase the “certainty of success” of demonstrating vaccine efficacy and controlling SARS-CoV-2 infection, disease, death, and the pandemic itself.

Estimated Incubation Period and Serial Interval for Human-to-Human Influenza A(H7N9) Virus Transmission

We estimated the incubation period and serial interval for human-to-human–transmitted avian influenza A(H7N9) virus infection using case-patient clusters from epidemics in China during 2013–2017. The median incubation period was 4 days and serial interval 9 days. China’s 10-day monitoring period for close contacts of case-patients should detect most secondary infections.

Impacts of age and gender at the risk of underlying medical conditions and death in patients with avian influenza A (H7N9): a meta-analysis study

Objective

The objective of our study was to conduct a series of analyses that examined the impacts of age and gender at the risk of underlying medical conditions (UMCs) and death in patients with influenza A (H7N9).

Methods

We began by searching for potentially relevant articles in English or Chinese before February 28, 2018. Additionally, we reviewed our own files and reference lists of articles identified by this search.

Results

The association between death and UMCs was significant in H7N9 patients, with an OR of 1.49 (95% CI: 1.24–1.78). Subgroup analyses showed that having two or more UMCs of any type (OR: 2.24; P=0.044), chronic respiratory diseases (OR: 1.81; P=0.032), and chronic cardiovascular disease (OR: 1.63; P=0.013) had an association with increased fatality in H7N9 patients. Age (60 years or older) [adjusted OR (AOR): 1.86; P=0.032] and gender (male: AOR: 1.68, P=0.006; female: AOR: 1.88, P=0.044) were significantly associated with death in H7N9 patients with UMCs compared to H7N9 patients without any UMC. Stratification analyses found statistically significant increased death in H7N9 patients with UMCs who were 60 years of age and older (AOR: 2.72; P<0.001) and gender (male; AOR=1.64; P=0.033), compared to H7N9 patients without these respective conditions.

Conclusion

Impacts of age are substantial and significant at the risk of UMCs and death in H7N9 patients. This analysis did not find a significant difference in gender comparisons. Efforts should particularly focus on reducing fatality rates in patients with combined risks from UMCs and other significant impact factor such as age (60 years or older).

The temporal distribution of new H7N9 avian influenza infections based on laboratory-confirmed cases in Mainland China, 2013-2017

In this study, estimates of the growth rate of new infections, based on the growth rate of new laboratory-confirmed cases, were used to provide a statistical basis for in-depth research into the epidemiological patterns of H7N9 epidemics. The incubation period, interval from onset to laboratory confirmation, and confirmation time for all laboratory-confirmed cases of H7N9 avian influenza in Mainland China, occurring between January 2013 and June 2017, were used as the statistical data. Stochastic processes theory and maximum likelihood were used to calculate the growth rate of new infections. Time-series analysis was then performed to assess correlations between the time series of new infections and new laboratory-confirmed cases. The rate of new infections showed significant seasonal fluctuation. Laboratory confirmation was delayed by a period of time longer than that of the infection (average delay, 13 days; standard deviation, 6.8 days). At the lags of −7.5 and −15 days, respectively, the time-series of new infections and new confirmed cases were significantly correlated; the cross correlation coefficients (CCFs) were 0.61 and 0.16, respectively. The temporal distribution characteristics of new infections and new laboratory-confirmed cases were similar and strongly correlated.

Estimating the incubation period of hand, foot and mouth disease for children in different age groups

Hand, foot and mouth disease (HFMD) is a childhood disease causing large outbreaks frequently in Asia and occasionally in Europe and the US. The incubation period of HFMD was typically described as about 3-7 days but empirical evidence is lacking. In this study, we estimated the incubation period of HFMD from school outbreaks in Hong Kong, utilizing information on symptom onset and sick absence dates of students diagnosed with HFMD. A total of 99 HFMD cases from 12 schools were selected for analysis. We fitted parametric models accounting for interval censoring. Based on the best-fitted distributions, the estimated median incubation periods were 4.4 (95% CI 3.8-5.1) days, 4.7 (95% CI 4.5-5.1) days and 5.7 (95% CI 4.6-7.0) days for children in kindergartens, primary schools and secondary schools respectively. From the fitted distribution, the estimated incubation periods can be longer than 10 days for 8.8% and 23.2% of the HFMD cases in kindergarten and secondary schools respectively. Our results show that the incubation period of HFMD for secondary schools students can be longer than the ranges commonly described. An extended period of enhanced personal hygiene practice and disinfection of the environment may be needed to control outbreaks.

Influenza and other respiratory viruses: standardizing disease severity in surveillance and clinical trials

INTRODUCTION

Influenza-Like Illness is a leading cause of hospitalization in children. Disease burden due to influenza and other respiratory viral infections is reported on a population level, but clinical scores measuring individual changes in disease severity are urgently needed. Areas covered: We present a composite clinical score allowing individual patient data analyses of disease severity based on systematic literature review and WHO-criteria for uncomplicated and complicated disease. The 22-item ViVI Disease Severity Score showed a normal distribution in a pediatric cohort of 6073 children aged 0-18 years (mean age 3.13; S.D. 3.89; range: 0 to 18.79). Expert commentary: The ViVI Score was correlated with risk of antibiotic use as well as need for hospitalization and intensive care. The ViVI Score was used to track children with influenza, respiratory syncytial virus, human metapneumovirus, human rhinovirus, and adenovirus infections and is fully compliant with regulatory data standards. The ViVI Disease Severity Score mobile application allows physicians to measure disease severity at the point-of care thereby taking clinical trials to the next level.

Expression of inflammation-related genes in the lung of BALB/c mice response to H7N9 influenza A virus with different pathogenicity

H7N9 influenza A virus (IAV)-infected human cases are increasing and reported over 200 mortalities since its first emergence in 2013. Host inflammatory response contributes to the clearance of influenza virus; meanwhile, the induced "cytokine storm" also leads to pathological lesions. However, what inflammation-related response of the host for H7N9 influenza A virus infection to survival from injures of exuberant cytokine release is still obscure. In this research, expression pattern and histological distribution of inflammation-related genes, RIP3, NLRP3, IL-1β, TNF-α, Slit2 and Robo4 in the lung of BALB/c mice infected with two H7N9 IAV strains with only a PB2 residue 627 difference were investigated, as well as the histopathological injury of the lung. Results showed that significantly higher expression level of NLRP3, RIP3, IL-1β and TNF-α in H7N9-infected groups compared with the control would play a key role in driving lung pathological lesion. While the expression level of Slit2 and Robo4 in H7N9 rVK627E group had significantly increased trend than VK627 which might be the main factor to inhibit the interstitial pneumonia and infiltration. Also, H7N9 induced the histopathological changes in the lung of infected mice, and RIP3, NLRP3, IL-1β, TNF-α, Slit2 and Robo4 showed cell-specific distribution in the lung. The results will provide basic data for further research on the mechanism of inflammatory response and understanding of the role of site 627 in PB2 in H7N9 IAVs infection. In addition, enhancing the resilience of the host vascular system to the inflammatory response by regulation of Slit2-Robo4 signaling pathway might provide a novel strategy for H7N9 IAVs infection.