Epidemiology of influenza-like illness during Pandemic (H1N1) 2009, New South Wales, Australia

Developing a Research Network of Early Warning Systems for Infectious Diseases Transmission Between China and Australia

This article offers a thorough review of current early warning systems (EWS) and advocates for establishing a unified research network for EWS in infectious diseases between China and Australia. We propose that future research should focus on improving infectious disease surveillance by integrating data from both countries to enhance predictive models and intervention strategies. The article highlights the need for standardized data formats and terminologies, improved surveillance capabilities, and the development of robust spatiotemporal predictive models. It concludes by examining the potential benefits and challenges of this collaborative approach and its implications for global infectious disease surveillance. This is particularly relevant to the ongoing project, early warning systems for Infectious Diseases between China and Australia (NetEWAC), which aims to use seasonal influenza as a case study to analyze influenza trends, peak activities, and potential inter-hemispheric transmission patterns. The project seeks to integrate data from both hemispheres to improve outbreak predictions and develop a spatiotemporal predictive modeling system for seasonal influenza transmission based on socio-environmental factors.

Obesity as a risk factor for severe influenza infection in children and adolescents: a systematic review and meta-analysis

Obesity has been recently identified as a predisposing factor for a worse prognosis in viral illnesses such as SARS-CoV-2; however, its role in children with influenza is not yet clarified. The current systematic review and meta-analysis aims to assess whether obesity is a risk factor for either hospitalization or a worse prognosis when hospitalized among children infected by influenza. We systematically searched the following databases using a structured algorithm: MEDLINE, Clinicaltrials.gov, and Cochrane Central Register of Controlled Trials (CENTRAL). Statistical meta-analysis was performed using the "meta" package in R software, and included studies were evaluated using the Newcastle-Ottawa scale. Among children with influenza, obesity increased the odds of hospitalization with a pooled OR of 1.89 (95% CI [1.23, 2.9], I² = 0, p = 0.003). When hospitalized, children with obesity were also more likely to have a worse outcome than their healthy-weight counterparts, with a pooled OR of 1.24 (95% Cl [1.02; 1.51], I² = 11, p = 0.03). In an effort to lower heterogeneity, a leave-one-out meta-analysis was conducted. Publication bias was assessed with the visual inspection of funnel plots and the trim-and-fill method. Certainty assessment was evaluated using the GRADE score.

CONCLUSIONS

The findings of our meta-analysis suggest that obesity in children with influenza is associated with a worse prognosis, both hospitalization and ICU admission/death.

WHAT IS KNOWN

• Obesity has been identified as a risk factor for non-communicable as well as communicable diseases. • A previous meta-analysis failed to demonstrate a statistically significant association between obesity and influenza infection severity.

WHAT IS NEW

• Children with high BMI and influenza infection are more likely to get hospitalized. • Pediatric inpatients with increased BMI and influenza infection may have a worse prognosis.

Influenza-like illness is associated with high pneumococcal carriage density in Malawian children

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Influenza-like illness (ILI) in children is associated with high pneumococcal carriage density.

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Children with ILI harboured more viral organisms than asymptomatic healthy children.

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Children with ILI patients had higher IL-8 levels in nasal aspirates than asymptomatic healthy children.

Background

High pneumococcal carriage density is a risk factor for invasive pneumococcal disease (IPD) and transmission, but factors that increase pneumococcal carriage density are still unclear.

Methods

We undertook a cross-sectional study to evaluate the microbial composition, cytokine levels and pneumococcal carriage densities in samples from children presenting with an influenza-like illness (ILI) and asymptomatic healthy controls (HC).

Results

The proportion of children harbouring viral organisms (Relative risk (RR) 1.4, p = 0.0222) or ≥ 4 microbes at a time (RR 1.9, p < 0.0001), was higher in ILI patients than HC. ILI patients had higher IL-8 levels in nasal aspirates than HC (median [IQR], 265.7 [0 – 452.3] vs. 0 [0 – 127.3] pg/ml; p = 0.0154). Having an ILI was associated with higher pneumococcal carriage densities compared to HC (RR 4.2, p < 0.0001).

Conclusion

These findings suggest that children with an ILI have an increased propensity for high pneumococcal carriage density. This could in part contribute to increased susceptibility to IPD and transmission in the community.

Obesity is associated with increased susceptibility to influenza A (H1N1pdm) but not H3N2 infection

BACKGROUND

Obesity has been shown to increase the risk of severe outcomes and death for influenza virus infections. However, we don't understand the influence of obesity on susceptibility to infection or on non-severe influenza outcomes.

METHODS

We performed a case-ascertained, community-based study of influenza transmission within households in Nicaragua. To investigate whether obesity increases the likelihood of influenza infection and symptomatic infection we use logistic regression models.

RESULTS

Between 2015 and 2018, a total of 335 index cases with influenza A and 1,506 of their household contacts were enrolled. Obesity was associated with increased susceptibility to symptomatic H1N1pdm infection among adults (OR: 2.10, 95%CI: 1.08-4.06), but not children, and this association increased with age. Among adults with H1N1pdm infection, obesity was associated with increased likelihood of symptoms (OR: 3.91, 95%CI: 1.55-9.87). For middle aged and older adults with obesity there was also a slight increase in susceptibility to any H1N1pdm infection (OR: 1.20, 95%CI: 0.62-2.34). Body Mass Index (BMI) was also linearly associated with increased susceptibility to symptomatic H1N1pdm infection, primarily among middle aged and older adult women (5-unit BMI increase OR: 1.40, 95%CI: 1.00-1.97). Obesity was not associated with increased H3N2 susceptibility or associated symptoms.

CONCLUSIONS

We found that among adults obesity is associated with susceptibility to H1N1pdm infection and with symptoms associated with H1N1pdm infection, but not with susceptibility to H3N2 infection or associated symptoms. These findings will help target prevention efforts and therapeutics to this high-risk population.

Dose-response relationship between weight status and clinical outcomes in pediatric influenza-related respiratory infections

BACKGROUND

Associations between underweight/obesity and manifestations of influenza infection remain unclear, especially in children. This study investigated the dose-response relationships between weight status and clinical outcomes among children hospitalized with influenza-related respiratory infections.

METHODS

We obtained hospital discharge records of inpatients aged under 18 years with diagnoses of bronchitis/pneumonia and influenza, using a Japanese national inpatient database. The patients were classified as underweight, normal-weight, overweight, or obese groups using weight-for-length, weight-for-height, and body-mass-index for age following World Health Organization criteria. We compared need for intensive care, 30-day readmission, mean total hospitalization costs, and length of hospital stay across the four groups using multivariable regression models and restricted cubic spline functions.

RESULTS

Overall, 27 771 patients were identified, including 2637 underweight, 19 701 normal-weight, 2675 overweight, and 2758 obese patients. The underweight group showed a significantly higher 30-day readmission (adjusted odds ratio, 1.68; 95% confidence interval, 1.28-2.18) and a longer length of stay (adjusted difference, 0.23 days; 95% confidence interval, 0.12-0.23 days) than the normal-weight group did. No significant differences in the need for intensive care or hospitalization costs were observed across the four weight status groups. The threshold for a statistically significant association between weight status and 30-day readmission was a z-score for weight-for-length, weight-for-height, or BMI for age of -0.95 (17th percentile).

CONCLUSION

These findings demonstrated that underweight status is a risk factor for repeated hospital admissions because of influenza-related respiratory infections in children.

Emergency Department demand associated with seasonal influenza, 2010 through 2014, New South Wales, Australia

Introduction

Influenza’s impact on health and health care is underestimated by influenza diagnoses recorded in health-care databases. We aimed to estimate total and non-admitted influenza-attributable hospital Emergency Department (ED) demand in New South Wales (NSW), Australia.

Methods

We used generalized additive time series models to estimate the association between weekly counts of laboratory-confirmed influenza infections and weekly rates of total and non-admitted respiratory, infection, cardiovascular and all-cause ED visits in NSW, Australia for the period 2010 through 2014. Visit categories were based on the coded ED diagnosis or the free-text presenting problem if no diagnosis was recorded.

Results

The estimated all-age, annual influenza-attributable respiratory, infection, cardiovascular and all-cause visit rates/100 000 population/year were, respectively, 120.6 (99.9% confidence interval [CI] 102.3 to 138.8), 79.7 (99.9% CI: 70.6 to 88.9), 14.0 (99.9% CI: 6.8 to 21.3) and 309.0 (99.9% CI: 208.0 to 410.1). Among respiratory visits, influenza-attributable rates were highest among < 5-year-olds and ≥ 85-year-olds. For infection and all-cause visits, rates were highest among children; cardiovascular rates did not vary significantly by age. Annual rates varied substantially by year and age group, and statistically significant associations were absent in several years or age groups. Of the respiratory visits, 73.4% did not require admission. The non-admitted proportion was higher for the other clinical categories. Around 1 in 100 total visits and more than 1 in 10 respiratory or infection visits were associated with influenza.

Discussion

Influenza is associated with a substantial and annually varying burden of hospital-attended illness in NSW.

Investigating obesity as a risk factor for influenza-like illness during the 2009 H1N1 influenza pandemic using the Health Survey for England

Background

Following the 2009 H1N1 influenza pandemic, obesity was shown to be associated with severe influenza outcomes. It remains unclear whether obesity was a risk factor for milder influenza‐like illness (ILI).

Objectives

To determine whether obesity was associated with an increased risk of self‐reported ILI during the 2009 H1N1 influenza pandemic using Health Survey for England (HSE) 2010 cross‐sectional data.

Methods

This study used HSE data collected from English households between January and December 2010. Weight and height measurements were taken by trained fieldworkers to determine obesity. ILI was defined as a positive response to the question “Have you had a flu‐like illness where you felt feverish and had a cough or sore throat?” with illness occurring between May and December 2009. Multivariable logistic regression was used to evaluate the association between obesity and ILI.

Results

The study comprised 8407 participants (6984 adults, 1436 children), among whom 24.7% (95% CI: 23.6–25.9) were classified as obese. Of obese participants, 12.8% (95% CI: 11.1–14.8) reported ILI compared to 11.8% (95% CI: 10.8–12.8) of non‐obese participants. The adjusted OR for ILI associated with obesity was 1.16 (95% CI: 0.98–1.38, P=.093). For adults and children, the adjusted ORs were 1.16 (95% CI: 0.97–1.38, P=.101) and 1.26 (95% CI: 0.72–2.21, P=.422), respectively.

Conclusion

Household survey data showed no evidence that obesity was associated with an increase in self‐reported ILI during the 2009 H1N1 influenza pandemic in England. Further studies using active prospective ILI surveillance combined with laboratory reporting would reduce bias and improve accuracy of outcome measurements.

Transmission of the First Influenza A(H1N1)pdm09 Pandemic Wave in Australia Was Driven by Undetected Infections: Pandemic Response Implications

Background

During the first wave of influenza A(H1N1)pdm09 in Victoria, Australia the rapid increase in notified cases and the high proportion with relatively mild symptoms suggested that community transmission was established before cases were identified. This lead to the hypothesis that those with low-level infections were the main drivers of the pandemic.

Methods

A deterministic susceptible-infected-recovered model was constructed to describe the first pandemic wave in a population structured by disease severity levels of asymptomatic, low-level symptoms, moderate symptoms and severe symptoms requiring hospitalisation. The model incorporated mixing, infectivity and duration of infectiousness parameters to calculate subgroup-specific reproduction numbers for each severity level.

Results

With stratum-specific effective reproduction numbers of 1.82 and 1.32 respectively, those with low-level symptoms, and those with asymptomatic infections were responsible for most of the transmission. The effective reproduction numbers for infections resulting in moderate symptoms and hospitalisation were less than one. Sensitivity analyses confirmed the importance of parameters relating to asymptomatic individuals and those with low-level symptoms.

Conclusions

Transmission of influenza A(H1N1)pdm09 was largely driven by those invisible to the health system. This has implications for control measures–such as distribution of antivirals to cases and contacts and quarantine/isolation–that rely on detection of infected cases. Pandemic plans need to incorporate milder scenarios, with a graded approach to implementation of control measures.

Description of hospitalized cases of influenza A(H1N1)pdm09 infection on the basis of the national hospitalized-case surveillance, 2009-2010, Japan

This study reports the epidemiological characteristics of hospitalized cases of influenza A(H1N1)pdm09 infection analyzed on the basis of surveillance data collected from July 24, 2009, the date on which the hospital-based surveillance of influenza cases was implemented in Japan, to September 5, 2010. During the study period, 13,581 confirmed cases were reported. Among those cases with information regarding the reason for hospitalization, 39% were admitted to hospitals for non-therapeutic purposes such as medical observation and laboratory testing. The overall hospitalization rate was 5.8 cases per 100,000 population when cases hospitalized for non-therapeutic purposes were excluded. While those aged under 20 years accounted for over 85% of hospitalized cases, the largest proportion of fatal cases was observed in those aged over 65 years. The overall case fatality rate for all hospitalized cases was 1.5%. The year-round surveillance for hospitalized influenza-like illness cases was launched in 2011, and it was expected that this surveillance system could add value by monitoring changes in the epidemiological characteristics of hospitalized cases of seasonal influenza.

Pandemic influenza A/H1N1 2009 antibodies in the metropolitan area of Buenos Aires in Argentina

OBJECTIVE

To estimate the infection prevalence in Buenos Aires during the outbreak of pandemic influenza A/H1N1 2009 virus (A(H1N1)pdm09).

METHODS

A(H1N1)pdm09-specific antibodies were measured by hemagglutination inhibition assay in human serum samples collected 6 months after the outbreak and before the introduction of the A(H1N1)pdm09 vaccine in Argentina. Baseline levels of cross-reactive antibodies to A(H1N1)pdm09 were determined by testing 162 serum samples collected before 2009.

RESULTS

The overall seroprevalence of A(H1N1)pdm09 in 150 children and 427 adults was 28.9% (95% confidence interval (CI) 25-33%), with a 58.0% prevalence in children <19 years of age and an 18.7% prevalence in adults ≥19 years of age (p<0.001). The prevalence was 43.5% in children <5 years old and 60.6% among children aged 5-18 years. The prevalence in adults declined with increasing age: 24.9% in 19-39-year-olds, 9.7% in 40-59-year-olds, and 8.1% in those ≥60 years old. The prevalence of specific A(H1N1)pdm09 antibodies was higher compared with the baseline in children (p=0.014), adolescents (p<0.001), and adults <40 years old (p=0.017). Seroprevalence in health care workers was not different from the rest of the population (13.6% vs. 19.3%, respectively; p=0.421).

CONCLUSIONS

The prevalence of specific A(H1N1)pdm09 antibodies was high at 28.9%. The highest prevalence was observed in children, adolescents, and young adults.

Mortality attributable to seasonal and pandemic influenza, Australia, 2003 to 2009, using a novel time series smoothing approach

BACKGROUND

Official statistics under-estimate influenza deaths. Time series methods allow the estimation of influenza-attributable mortality. The methods often model background, non-influenza mortality using a cyclic, harmonic regression model based on the Serfling approach. This approach assumes that the seasonal pattern of non-influenza mortality is the same each year, which may not always be accurate.

AIM

To estimate Australian seasonal and pandemic influenza-attributable mortality from 2003 to 2009, and to assess a more flexible influenza mortality estimation approach.

METHODS

We used a semi-parametric generalized additive model (GAM) to replace the conventional seasonal harmonic terms with a smoothing spline of time ('spline model') to estimate influenza-attributable respiratory, respiratory and circulatory, and all-cause mortality in persons aged <65 and ≥ 65 years. Influenza A(H1N1)pdm09, seasonal influenza A and B virus laboratory detection time series were used as independent variables. Model fit and estimates were compared with those of a harmonic model.

RESULTS

Compared with the harmonic model, the spline model improved model fit by up to 20%. In <65 year-olds, the estimated respiratory mortality attributable to pandemic influenza A(H1N1)pdm09 was 0.5 (95% confidence interval (CI), 0.3, 0.7) per 100,000; similar to that of the years with the highest seasonal influenza A mortality, 2003 and 2007 (A/H3N2 years). In ≥ 65 year-olds, the highest annual seasonal influenza A mortality estimate was 25.8 (95% CI 22.2, 29.5) per 100,000 in 2003, five-fold higher than the non-statistically significant 2009 pandemic influenza estimate in that age group. Seasonal influenza B mortality estimates were negligible.

CONCLUSIONS

The spline model achieved a better model fit. The study provides additional evidence that seasonal influenza, particularly A/H3N2, remains an important cause of mortality in Australia and that the epidemic of pandemic influenza A (H1N1)pdm09 virus in 2009 did not result in mortality greater than seasonal A/H3N2 influenza mortality, even in younger age groups.

Pertussis in older adults: prospective study of risk factors and morbidity

BACKGROUND

There is limited information on the incidence, morbidity and risk factors for pertussis in adults, particularly those aged over 65 years.

METHODS

Population-based prospective cohort study of 263094 adults aged over 45 years (mean 62.8 years) recruited in the Australian state of New South Wales (the 45 and Up Study) between 2006 and 2008, and followed by record-linkage to laboratory-confirmed pertussis notifications, hospitalizations, and death records. The incidence of pertussis notifications and hospitalizations and relative risk (RR) of pertussis according to various participant characteristics was estimated using proportional hazards models.

RESULTS

Over a total follow-up of 217524 person-years, 205 adults had a pertussis notification and 12 were hospitalized; the incidence rate was 94 (95% confidence interval [CI], 82-108) and 5.5 (95% CI, 3.1-9.7) per 100000 person-years, respectively. The incidence of a pertussis notification did not differ by age but hospitalization rates progressively increased (2.2, 8.5, and 13.5 per 100000 person-years in age groups 45-64, 65-74, and 75+ years, respectively; P(trend) = .01). After adjusting for age, sex, and other factors, adults with a high body mass index (BMI; RR=1.52; 95% CI, 1.06-2.19 for BMI 30+kg/m(2) vs BMI <25 kg/m(2)) and with preexisting asthma (RR=1.64; 95% CI, 1.06-2.55 compared to those without asthma) were more likely to be notified.

CONCLUSIONS

Adults older than 65 years are more likely to be hospitalized for pertussis than those aged 45-64 years. Obesity and preexisting asthma were associated with a higher likelihood of pertussis notification. These findings suggest that pertussis vaccination would be particularly important for adults with these characteristics.

Epidemiological characteristics and underlying risk factors for mortality during the autumn 2009 pandemic wave in Mexico

Background

Elucidating the role of the underlying risk factors for severe outcomes of the 2009 A/H1N1 influenza pandemic could be crucial to define priority risk groups in resource-limited settings in future pandemics.

Methods

We use individual-level clinical data on a large series of ARI (acute respiratory infection) hospitalizations from a prospective surveillance system of the Mexican Social Security medical system to analyze clinical features at presentation, admission delays, selected comorbidities and receipt of seasonal vaccine on the risk of A/H1N1-related death. We considered ARI hospitalizations and inpatient-deaths, and recorded demographic, geographic, and medical information on individual patients during August-December, 2009.

Results

Seasonal influenza vaccination was associated with a reduced risk of death among A/H1N1 inpatients (OR = 0.43 (95% CI: 0.25, 0.74)) after adjustment for age, gender, geography, antiviral treatment, admission delays, comorbidities and medical conditions. However, this result should be interpreted with caution as it could have been affected by factors not directly measured in our study. Moreover, the effect of antiviral treatment against A/H1N1 inpatient death did not reach statistical significance (OR = 0.56 (95% CI: 0.29, 1.10)) probably because only 8.9% of A/H1N1 inpatients received antiviral treatment. Moreover, diabetes (OR = 1.6) and immune suppression (OR = 2.3) were statistically significant risk factors for death whereas asthmatic persons (OR = 0.3) or pregnant women (OR = 0.4) experienced a reduced fatality rate among A/H1N1 inpatients. We also observed an increased risk of death among A/H1N1 inpatients with admission delays >2 days after symptom onset (OR = 2.7). Similar associations were also observed for A/H1N1-negative inpatients.

Conclusions

Geographical variation in identified medical risk factors including prevalence of diabetes and immune suppression may in part explain between-country differences in pandemic mortality burden. Furthermore, access to care including hospitalization without delay and antiviral treatment and are also important factors, as well as vaccination coverage with the 2008–09 trivalent inactivated influenza vaccine.

Risk factors for mortality among 2009 A/H1N1 influenza hospitalizations in Maricopa County, Arizona, April 2009 to March 2010

We analyzed individual-level data on pandemic influenza A/H1N1pdm hospitalizations from the enhanced surveillance system of the Maricopa County Department of Public Health, AZ, USA from April 1st, 2009 to March 31st, 2010. We also assessed the the risk of death among A/H1N1 hospitalizations using multivariate logistic regression. Hospitalization rates were significantly higher among Native Americans (risk ratio (RR)  =  6.2; 95% CI: 6.15, 6.21), non-Hispanic Black (RR = 3.84; 95% CI: 3.8, 3.9), and Hispanics (RR = 2.0; 95% CI: 2.0, 2.01) compared to non-Hispanic Whites. Throughout the spring, 59.2% of hospitalized patients received antiviral treatment; the proportion of patients treated increased significantly during the fall to 74.4% (Chi-square test, P < 0.0001). In our best-fit logistic model, the adjusted risk of death among A/H1N1 inpatients was significantly higher during the fall wave (August 16, 2009 to March 31, 2010, OR = 3.94; 95% CI: 1.72, 9.03) compared to the spring wave (April 1, 2009 to August 15, 2009). Moreover, chronic lung disease (OR = 3.5; 95% CI: 1.7, 7.4), cancer within the last 12 months (OR = 4.3; 95%CI: 1.3, 14.8), immuno-suppression (OR = 4.0; 95% CI: 1.84, 8.9), and admission delays (OR = 4.6; 95% CI: 2.2, 9.5) were significantly associated with an increased the risk of death among A/H1N1 inpatients.

Pandemic influenza: a never-ending story

A novel pandemic influenza emerged in 2009, something that hasn't been seen since 1977. The following issues will be introduced and discussed in this review: the history of influenza pandemics, the emergence of the novel pandemic influenza of 2009, epidemics in the southern and northern hemispheres after the recognition of index cases in the United States, mortality, viral characteristics, prevention in the household setting, clinical aspects, diagnosis, treatment and immunization. Some questions have been answered. However, a number of other questions remain. Scientific research must follow up on these unanswered questions.