Mortality attributable to seasonal influenza in Greece, 2013 to 2017: variation by type/subtype and age, and a possible harvesting effect

Safety and efficacy of onradivir in adults with acute uncomplicated influenza A infection: a multicentre, double-blind, randomised, placebo-controlled, phase 2 trial

BACKGROUND

Onradivir (ZSP1273) is a novel anti-influenza A virus inhibitor. Preclinical studies show that onradivir can inhibit influenza A H1N1 and H3N2 replication and increase the survival rate of infected animals. In this study, we aimed to evaluate the safety and efficacy of three onradivir dosing regimens versus placebo in outpatients with acute uncomplicated influenza A virus infection.

METHODS

We did a multicentre, double-blind, randomised, placebo-controlled, phase 2 trial at 20 clinical sites in China. Eligible participants were adults (18-65 years) with an influenza-like illness screened by rapid antigen testing at the first clinical visit, had the presence of a fever (axillary temperature ≥38·0°C), and had the presence of at least one moderate systemic and one respiratory symptom within 48 h of symptom onset. Patients were excluded if they were pregnant, allergic to onradivir, or had received any influenza antiviral medication within 7 days before enrolment. Participants were randomly assigned (1:1:1:1) into four groups by an interactive web response system: onradivir 200 mg twice per day group, onradivir 400 mg twice per day group, onradivir 600 mg once per day group, and a matching placebo group. A 5-day oral treatment course was initiated within 48 h after symptoms onset. The primary outcome was the time to alleviate influenza symptoms in the modified intention-to-treat population. Safety was a secondary outcome. We evaluated the patients' self-assessed severity of seven influenza symptoms on a 4-point ordinal scale, and the treatment-emergent adverse events in all patients. This trial is registered with ClinicalTrials.gov, number NCT04024137.

FINDINGS

Between Dec 7, 2019, and May 18, 2020, a total of 205 patients were screened; of whom, 172 (84%) were randomly assigned to receive onradivir (n=43 in the 200 mg twice per day group; n=43 in the 400 mg twice per day group; and n=43 in the 600 mg once per day group), or placebo (n=42). Median age was 22 years (IQR 20-26). All three onradivir groups showed decreased median time to alleviate influenza symptoms (46·92 h [IQR 24·00-81·38] in the 200 mg twice per day group, 54·87 h [23·67-110·62] in the 400 mg twice per day group, and 40·05 h [17·70-65·82] in the 600 mg once per day) compared with the placebo group (62·87 h [36·40-113·25]). The median difference between the onradivir 600 mg once per day group and the placebo group was -22·82 h (p=0·0330). The most frequently reported treatment-emergent adverse event was diarrhoea (71 [42%] of 171), ranging from 33-65% of the patients in onradivir-treated groups compared with 10% in the placebo group; no serious adverse events were observed.

INTERPRETATION

Onradivir showed a safety profile comparable to placebo, as well as higher efficacy than placebo in ameliorating influenza symptoms and lowering the viral load in adult patients with uncomplicated influenza infection, especially the onradivir 600 mg once per day regimen.

FUNDING

National Multidisciplinary Innovation Team Project of Traditional Chinese Medicine, National Natural Science Foundation of China, Guangdong Science and Technology Foundation, Guangzhou Science and Technology Planning Project, Emergency Key Program of Guangzhou Laboratory, Macao Science and Technology Development Fund, and Guangdong Raynovent Biotech.

Multilayer factors associated with excess all-cause mortality during the omicron and non-omicron waves of the COVID-19 pandemic: time series analysis in 29 countries

BACKGROUND

The COVID-19 pandemic has resulted in significant excess mortality globally. However, the differences in excess mortality between the Omicron and non-Omicron waves, as well as the contribution of local epidemiological characteristics, population immunity, and social factors to excess mortality, remain poorly understood. This study aims to solve the above problems.

METHODS

Weekly all-cause death data and covariates from 29 countries for the period 2015-2022 were collected and used. The Bayesian Structured Time Series Model predicted expected weekly deaths, stratified by gender and age groups for the period 2020-2022. The quantile-based g-computation approach accounted for the effects of factors on the excess all-cause mortality rate. Sensitivity analyses were conducted using alternative Omicron proportion thresholds.

RESULTS

From the first week of 2021 to the 30th week of 2022, the estimated cumulative number of excess deaths due to COVID-19 globally was nearly 1.39 million. The estimated weekly excess all-cause mortality rate in the 29 countries was approximately 2.17 per 100,000 (95% CI: 1.47 to 2.86). Weekly all-cause excess mortality rates were significantly higher in both male and female groups and all age groups during the non-Omicron wave, except for those younger than 15 years (P < 0.001). Sensitivity analysis confirmed the stability of the results. Positive associations with all-cause excess mortality were found for the constituent ratio of non-Omicron in all variants, new cases per million, positive rate, cardiovascular death rate, people fully vaccinated per hundred, extreme poverty, hospital patients per million humans, people vaccinated per hundred, and stringency index. Conversely, other factors demonstrated negative associations with all-cause excess mortality from the first week of 2021 to the 30th week of 2022.

CONCLUSION

Our findings indicate that the COVID-19 Omicron wave was associated with lower excess mortality compared to the non-Omicron wave. This study's analysis of the factors influencing excess deaths suggests that effective strategies to mitigate all-cause mortality include improving economic conditions, promoting widespread vaccination, and enhancing overall population health. Implementing these measures could significantly reduce the burden of COVID-19, facilitate coexistence with the virus, and potentially contribute to its elimination.

Lack of association between vaccination rates and excess mortality in Cyprus during the COVID-19 pandemic

BACKGROUND

It has been claimed that COVID-19 vaccination is associated with excess mortality during the COVID-19 pandemic, a claim that contributes to vaccine hesitancy. We examined whether all-cause mortality has actually increased in Cyprus during the first two pandemic years, and whether any increases are associated with vaccination rates.

METHODS

We calculated weekly excess mortality for Cyprus between January 2020 and June 2022, overall and by age group, using both a Distributed Lag Nonlinear Model (DLNM) adjusted for mean daily temperature, and the EuroMOMO algorithm. Excess deaths were regressed on the weekly number of confirmed COVID-19 deaths and on weekly first-dose vaccinations, also using a DLNM to explore the lag-response dimension.

RESULTS

552 excess deaths were observed in Cyprus during the study period (95% CI: 508-597) as opposed to 1306 confirmed COVID-19 deaths. No association between excess deaths and vaccination rates was found overall and for any age group except 18-49 years, among whom 1.09 excess deaths (95% CI: 0.27-1.91) per 10,000 vaccinations were estimated during the first 8 weeks post-vaccination. However, detailed cause-of-death examination identified just two such deaths potentially linked to vaccination, therefore this association is spurious and attributable to random error.

CONCLUSIONS

Excess mortality was moderately increased in Cyprus during the COVID-19 pandemic, primarily as a result of laboratory-confirmed COVID-19 deaths. No relationship was found between vaccination rates and all-cause mortality, demonstrating the excellent safety profile of COVID-19 vaccines.

Influenza-Associated Excess Mortality by Age, Sex, and Subtype/Lineage: Population-Based Time-Series Study With a Distributed-Lag Nonlinear Model

BACKGROUND

Accurate estimation of the influenza death burden is of great significance for influenza prevention and control. However, few studies have considered the short-term harvesting effects of influenza on mortality when estimating influenza-associated excess deaths by cause of death, age, sex, and subtype/lineage.

OBJECTIVE

This study aimed to estimate the cause-, age-, and sex-specific excess mortality associated with influenza and its subtypes and lineages in Guangzhou from 2015 to 2018.

METHODS

Distributed-lag nonlinear models were fitted to estimate the excess mortality related to influenza subtypes or lineages for different causes of death, age groups, and sex based on daily time-series data for mortality, influenza, and meteorological factors.

RESULTS

A total of 199,777 death certificates were included in the study. The average annual influenza-associated excess mortality rate (EMR) was 25.06 (95% empirical CI [eCI] 19.85-30.16) per 100,000 persons; 7142 of 8791 (81.2%) deaths were due to respiratory or cardiovascular mortality (EMR 20.36, 95% eCI 16.75-23.74). Excess respiratory and cardiovascular deaths in people aged 60 to 79 years and those aged ≥80 years accounted for 32.9% (2346/7142) and 63.7% (4549/7142) of deaths, respectively. The male to female ratio (MFR) of excess death from respiratory diseases was 1.34 (95% CI 1.17-1.54), while the MFR for excess death from cardiovascular disease was 0.72 (95% CI 0.63-0.82). The average annual excess respiratory and cardiovascular mortality rates attributed to influenza A (H3N2), B/Yamagata, B/Victoria, and A (H1N1) were 8.47 (95% eCI 6.60-10.30), 5.81 (95% eCI 3.35-8.25), 3.68 (95% eCI 0.81-6.49), and 2.83 (95% eCI -1.26 to 6.71), respectively. Among these influenza subtypes/lineages, A (H3N2) had the highest excess respiratory and cardiovascular mortality rates for people aged 60 to 79 years (20.22, 95% eCI 14.56-25.63) and ≥80 years (180.15, 95% eCI 130.75-227.38), while younger people were more affected by A (H1N1), with an EMR of 1.29 (95% eCI 0.07-2.32). The mortality displacement of influenza A (H1N1), A (H3N2), and B/Yamagata was 2 to 5 days, but 5 to 13 days for B/Victoria.

CONCLUSIONS

Influenza was associated with substantial mortality in Guangzhou, occurring predominantly in the elderly, even after considering mortality displacement. The mortality burden of influenza B, particularly B/Yamagata, cannot be ignored. Contrasting sex differences were found in influenza-associated excess mortality from respiratory diseases and from cardiovascular diseases; the underlying mechanisms need to be investigated in future studies. Our findings can help us better understand the magnitude and time-course of the effect of influenza on mortality and inform targeted interventions for mitigating the influenza mortality burden, such as immunizations with quadrivalent vaccines (especially for older people), behavioral campaigns, and treatment strategies.

Greece since the 1960s: the mortality transition revisited: a joinpoint regression analysis

Mortality transition in Greece is a well-studied phenomenon in several of its aspects. It is characterised by an almost constant increase in life expectancy at birth and other ages and a parallel decrease in death probabilities. The scope of this paper is a comprehensive assessment of the mortality transition in Greece since 1961, in the light of holistic analysis. Within this paper, life tables by gender were calculated and the temporal trends of life expectancy at several ages were examined. Moreover, a cluster analysis was used in order to verify the temporal changes in the mortality patterns. The probabilities of death in large age classes are presented. Furthermore, the death distribution was analysed in relation to various parameters: the modal age at death, mode, left and right inflexion points and the length of the old age heap. Before that, a non-linear regression method, originating from the stochastic analysis, was applied. Additionally, the Gini coefficient, average inter-individual differences, and interquartile range of survival curves were examined. Finally, the standardised rates of the major causes of death are presented. All the analysis variables were scholastically examined for their temporal trends with the method of Joinpoint Regression analysis. Mortality transition in Greece after the year 1961 is asymmetrical with a gender and an age-specific component, leading to the elevation of life expectancy at birth over time. During this period, the older ages' mortality decreases, but at a slower pace than that of the younger ones. The modal age at death, mode, the left and right inflexion points and the width of the old age heap denote the compression of mortality in the country. The old age death heap shifts towards older ages, while at the same time, the variability of ages at death decreases, being verified by the Gini Coefficient and average inter-individual differences. As a result, the rectangularization of survival curves is evident. These changes have a different pace of transition over time, especially after the emergence of the economic crisis. Finally, the major causes of death were the diseases of the circulatory system, neoplasms, diseases of the respiratory system and others. The temporal trends of these diseases differ according to the diseases and gender. Greece's mortality transition is an asymmetrical stepwise process characterised by its gender and age-specific characteristics. This process, despite being a continuous one, is not linear. Instead, a combination of serious developments over time governs the country's modern mortality regime. The evaluation of Greece's mortality transition through the lens of more advanced analytical methods may provide new insights and methodological alternatives for assessing mortality transition in other countries of the world.

The influence of air quality and meteorological variations on influenza A and B virus infections in a paediatric population in Singapore

INTRODUCTION

Influenza is an important cause of paediatric illness across the globe. However, information about the relationships between air pollution, meteorological variability and paediatric influenza A and B infections in tropical settings is limited.

METHODS

We analysed all daily reports of influenza A and B infections in children <5 years old obtained from the largest specialist women and children's hospital in Singapore. In separate negative binomial regression models, we assessed the dependence of paediatric influenza A and B infections on air quality and meteorological variability, using multivariable fractional polynomial modelling and adjusting for time-varying confounders.

RESULTS

Approximately 80% of 7329 laboratory-confirmed reports were caused by influenza A. We observed positive associations between sulphur dioxide (SO₂) exposure and the subsequent risk of infection with both influenza types. We observed evidence of a harvesting effect of SO₂ on Influenza A but not Influenza B. Ambient temperature was associated with a decline in influenza A reports (Relative Risk at lag 5 [RR_lag5]: 0.949, 95% CI: 0.916-0.983). Rainfall was positively associated with a subsequent increase in influenza A reports (RR_lag3: 1.044, 95% CI: 1.017-1.071). Nitrogen dioxide (NO₂) concentration was positively associated with influenza B reports (RR_lag5: 1.015, 95% CI: 1.005-1.025). There was a non-linear association between CO and influenza B reports. Absolute humidity increased the ensuing risk of influenza B (RR_lag5: 4.799, 95% CI: 2.277-10.118). Influenza A and B infections displayed dissimilar but predictable within-year seasonal patterns.

CONCLUSIONS

We observed different independent associations between air quality and meteorological variability with paediatric influenza A and B infections. Anticipated seasonal infection peaks and variations in air quality and meteorological parameters can inform the timing of community measures aimed at reducing influenza infection risk.

Evaluation of the Clinical Effectiveness of Oseltamivir for Influenza Treatment in Children

Objective: To estimate the clinical effectiveness of oseltamivir in children with different subtypes of influenza virus infection.

Methods: A total of 998 children with acute respiratory infection were enrolled from January to March 2018, and were divided into influenza A, influenza B, influenza A + B, and non-influenza infection (IV-negative) groups. Influenza-like symptoms and duration of fever were evaluated and compared between oseltamivir-treated and non-treated groups.

Results: There were no significant differences in the reduction in total febrile period and duration of fever from the onset of therapy between the oseltamivir treated and non-treated children infected with influenza A (p = 0.6885 for total febrile period and 0.7904 for the duration of fever from the onset of treatment), influenza B (p = 0.1462 and 0.1966), influenza A + B (p = 0.5568 and 0.9320), and IV-negative (p = 0.7631 and 0.4655). The duration of fever in children received oseltamivir therapy within 48 h was not significantly shorter than that beyond 48 h (p > 0.05). Additionally, percentages and severities of influenza-like symptoms, including headache, myalgia, fatigue, bellyache, vomiting, diarrhea, sore throat, cough, and coryza were not decreased and alleviated after treatment of oseltamivir.

Conclusion: Oseltamivir treatment does not significantly shorten the duration of fever, nor does it significantly relieve influenza-like symptoms in children with infection of influenza.

Underestimation in Reporting Excess COVID-19 Death Data in Poland during the First Three Pandemic Waves

The issue whether official Polish COVID-19 death statistics correctly reflect the actual number of deaths is a contentious issue in public discourse and an important policy-wise question in Poland although it has not been the subject of thorough research so far. There had been clearly elevated excess mortality—5100 (death rate of 2.3 per 10,000) during the first wave, 77,500 (21.0 per 10,000) during the second one, and 48,900 (13.5 per 10,000) in the third. This study finds that during the second and the third pandemic wave, our data on excess mortality will match very well the somewhat belatedly officially reported COVID-19 deaths if we assume that only 60% of cases were officially detected. Based on principal component analysis of death timing, except for the age bracket below 40, where COVID-19 deaths calculated on the basis of our model explain 55% of excess mortality, for the remaining age groups, combined COVID-19 deaths explain 95% of excess mortality. Based on the share of excess mortality attributable to COVID-19 during the second wave, this infection in Poland caused the death of 73,300 people and not of 37,600 as officially reported. The third wave caused 46,200 deaths instead of the reported 34,700. The first wave was, indeed, as officially reported, very mild, and the number of excess deaths was too low to be used to calculate COVID-19 deaths directly. However, assuming that the detection rate remained comparable to the average in subsequent waves, we can set the number of deaths at 3500 instead of the reported 2100.

Short-term impact of ambient temperature on the incidence of influenza in Wuhan, China

Few studies have estimated the nonlinear association of ambient temperature with the risk of influenza. We therefore applied a time-series analysis to explore the short-term effect of ambient temperature on the incidence of influenza in Wuhan, China. Daily influenza cases were collected from Hubei Provincial Center for Disease Control and Prevention (Hubei CDC) from January 1, 2014, to December 31, 2017. The meteorological and daily pollutant data was obtained from the Hubei Meteorological Service Center and National Air Quality Monitoring Stations, respectively. We used a generalized additive model (GAM) coupled with the distributed lag nonlinear model (DLNM) to explore the exposure-lag-response relationship between the short-term risk of influenza and daily average ambient temperature. Analyses were also performed to assess the extreme cold and hot temperature effects. We observed that the ambient temperature was statistically significant, and the exposure-response curve is approximately S-shaped, with a peak observed at 23.57 ℃. The single-day lag curve showed that extreme hot and cold temperatures were both significantly associated with influenza. The extreme hot temperature has an acute effect on influenza, with the most significant effect observed at lag 0-1. The extreme cold temperature has a relatively smaller effect but lasts longer, with the effect exerted continuously during a lag of 2-4 days. Our study found significant nonlinear and delayed associations between ambient temperature and the incidence of influenza. Our finding contributes to the establishment of an early warning system for airborne infectious diseases.

Weight of risk factors for mortality and short-term mortality displacement during the COVID-19 pandemic

Background

We conducted a population-based cohort study to estimate mortality before, during and after the COVID-19 peak and to compare mortality in 2020 with rates reported in previous years, with a view to helping decision makers to apply containment measures for high-risk groups.

Methods

All deaths were collected between 2015 and 2020 from municipal registry database. In 2020, weeks 1-26 were stratified in three periods: before, during and after the COVID mortality peak. The Poisson Generalized Linear regression Model showed the "harvesting effect". Three logistic regressions for 8 dependent variables (age and comorbidities) and a t-test of differences described all-cause mortality risk factors in 2019 and 2020 and differences between COVID and non-COVID patients.

Results

A total of 47,876 deaths were collected. All-cause deaths increased by 38.5% during the COVID peak and decreased by 18% during the post-peak period in comparison with the average registered during the control period (2015-19), with significant mortality displacement in 2020. Except for chronic renal injuries in subjects aged 45-64 years, diabetes and chronic cardiovascular diseases in those aged 65-84 years, and neuropathies in those aged > 84 years, the weight of comorbidities in deaths was similar or lower in COVID subjects than in non-COVID subjects.

Discussions

Surprisingly, the weight of comorbidities in death, compared to weight in non-COVID subjects allows you to highlight some surprising results such as COPD, IBD and Cancer. The excess mortality that we observed in the entire period were modest in comparison with initial estimates during the peak, owing to the mild influenza season and the harvesting effect starting from the second half of May.

An exploratory study to assess patterns of influenza- and pneumonia-related mortality among the Italian elderly

Older adults are at disproportionately high risk of severe influenza-related outcomes and represent the main target of the annual influenza vaccination. The protective effect of seasonal influenza vaccination on the observed mortality indicators is controversial. In this ecological study, spatiotemporal patterns of pneumonia- and influenza-related mortality registered in the Italian elderly over seven (2011–2017) consecutive seasons were explored and the epidemiological association between the observed local pneumonia- and influenza-related mortality and influenza vaccination campaign features were modeled by using both fixed- and random-effects panel regression models. The descriptive spatiotemporal analysis showed a clear North–South gradient, where northern regions tended to report more pneumonia- and influenza-related deaths. After adjustment for potential confounders, it was found that each 1% increase in influenza vaccination coverage rate would be associated (P < .001) with a 1.6–1.9% decrease in pneumonia- and influenza-related mortality. Moreover, each 1% increase in the use of MF59®-adjuvanted trivalent influenza vaccine would be associated (P < .05) with a further 0.4% decrease in pneumonia- and influenza-related mortality. This study supports the increase in annual influenza vaccination in Italy and suggests that a higher level of use of the adjuvanted influenza vaccine in the elderly may be beneficial.

Magnitude, change over time, demographic characteristics and geographic distribution of excess deaths among nursing home residents during the first wave of COVID-19 in France: a nationwide cohort study

BACKGROUND

The objectives were to assess the excess deaths among Nursing Home (NH) residents during the first wave of the COVID-19 pandemic, to determine their part in the total excess deaths and whether there was a mortality displacement.

METHODS

We studied a cohort of 494,753 adults in 6,515 NHs in France exposed to COVID-19 pandemic (from 1 March to 31 May 2020) and compared with the 2014-2019 cohorts using data from the French National Health Data System. The main outcome was death. Excess deaths and standardized mortality ratios (SMRs) were estimated.

RESULT

There were 13,505 excess deaths. Mortality increased by 43% (SMR: 1.43). The mortality excess was higher among males than females (SMR: 1.51 and 1.38) and decreased with increasing age (SMRs in females: 1.61 in the 60-74 age group, 1.58 for 75-84, 1.41 for 85-94 and 1.31 for 95 or over; males: SMRs: 1.59 for 60-74, 1.69 for 75-84, 1.47 for 85-94 and 1.41 for 95 or over). No mortality displacement effect was observed up until 30 August 2020. By extrapolating to all NH residents nationally (N = 570,003), we estimated that they accounted for 51% of the general population excess deaths (N = 15,114 out of 29,563).

CONCLUSION

NH residents accounted for half of the total excess deaths in France during the first wave of the COVID-19 pandemic. The excess death rate was higher among males than females and among younger than older residents.

The association between ambient temperature and mortality of the coronavirus disease 2019 (COVID-19) in Wuhan, China: a time-series analysis

Background

The COVID-19 has caused a sizeable global outbreak and has been declared as a public health emergency of international concern. Sufficient evidence shows that temperature has an essential link with respiratory infectious diseases. The objectives of this study were to describe the exposure-response relationship between ambient temperature, including extreme temperatures, and mortality of COVID-19.

Methods

The Poisson distributed lag non-linear model (DLNM) was constructed to evaluate the non-linear delayed effects of ambient temperature on death, by using the daily new death of COVID-19 and ambient temperature data from January 10 to March 31, 2020, in Wuhan, China.

Results

During the period mentioned above, the average daily number of COVID-19 deaths was approximately 45.2. Poisson distributed lag non-linear model showed that there was a non-linear relationship (U-shape) between the effect of ambient temperature and mortality. With confounding factors controlled, the daily cumulative relative death risk decreased by 12.3% (95% CI [3.4, 20.4%]) for every 1.0 °C increase in temperature. Moreover, the delayed effects of the low temperature are acute and short-term, with the most considerable risk occurring in 5–7 days of exposure. The delayed effects of the high temperature appeared quickly, then decrease rapidly, and increased sharply 15 days of exposure, mainly manifested as acute and long-term effects. Sensitivity analysis results demonstrated that the results were robust.

Conclusions

The relationship between ambient temperature and COVID-19 mortality was non-linear. There was a negative correlation between the cumulative relative risk of death and temperature. Additionally, exposure to high and low temperatures had divergent impacts on mortality.

Illness Severity in Hospitalized Influenza Patients by Virus Type and Subtype, Spain, 2010-2017

Influenza A(H1N1)pdm09 caused more hospitalizations, intensive care unit admissions, and deaths than influenza A(H3N2) or B.

We conducted a retrospective cohort study to assess the effect of influenza virus type and subtype on disease severity among hospitalized influenza patients in Spain. We analyzed the cases of 8,985 laboratory-confirmed case-patients hospitalized for severe influenza by using data from a national surveillance system for the period 2010–2017. Hospitalized patients with influenza A(H1N1)pdm09 virus were significantly younger, more frequently had class III obesity, and had a higher risk for pneumonia or acute respiratory distress syndrome than patients infected with influenza A(H3N2) or B (p<0.05). Hospitalized patients with influenza A(H1N1)pdm09 also had a higher risk for intensive care unit admission, death, or both than patients with influenza A(H3N2) or B, independent of other factors. Determining the patterns of influenza-associated severity and how they might differ by virus type and subtype can help guide planning and implementation of adequate control and preventive measures during influenza epidemics.

Effects of heavy rainfall on waterborne disease hospitalizations among young children in wet and dry areas of New Zealand

Heavy rainfall is associated with increased risk of waterborne disease. However, it is not known whether the risk increment differs between wet and dry regions. We examined this question in New Zealand, which has a wide geographical variation of annual rainfall totals (10^th-90^th percentile difference ≥3000 mm). We conducted a nested case-crossover study within a prospective child cohort (born in 2009-2010) for assessing transient health effects when modified by longitudinal exposures to rainfall. Short-term heavy rainfall effects on hospitalizations due to enteric bacterial and viral infectious causes at lag of 0-14 days were assessed using a Cox regression model adjusted for daily temperature, relative humidity and evapotranspiration. We derived quantiles of time-weighted long-term rainfall levels at the children's homes and these were added as an interaction term to the short-term effect model. Hospitalization risks were higher two days after heavy rainfall days (hazard ratio [95% confidence interval]: 1.73 [1.10-2.70]). The lowest-observable-adverse-effect-level was detected at the 94^th percentile of daily rainfall total. Hospital admissions 1-2 days after heavy rainfall increased most in locations with the lowest and highest long-term rainfall. An interaction of this kind between short-term weather and long-term climate has not been reported previously. It is relevant to climate change risk assessments given global projections of increasing intensity of precipitation, against a background of more severe, and possibly more frequent, droughts and flooding.

Excess mortality in the United States during the first three months of the COVID-19 pandemic

Deaths are frequently under-estimated during emergencies, times when accurate mortality estimates are crucial for emergency response. This study estimates excess all-cause, pneumonia and influenza mortality during the coronavirus disease 2019 (COVID-19) pandemic using the 11 September 2020 release of weekly mortality data from the United States (U.S.) Mortality Surveillance System (MSS) from 27 September 2015 to 9 May 2020, using semiparametric and conventional time-series models in 13 states with high reported COVID-19 deaths and apparently complete mortality data: California, Colorado, Connecticut, Florida, Illinois, Indiana, Louisiana, Massachusetts, Michigan, New Jersey, New York, Pennsylvania and Washington. We estimated greater excess mortality than official COVID-19 mortality in the U.S. (excess mortality 95% confidence interval (CI) 100 013-127 501 vs. 78 834 COVID-19 deaths) and 9 states: California (excess mortality 95% CI 3338-6344) vs. 2849 COVID-19 deaths); Connecticut (excess mortality 95% CI 3095-3952) vs. 2932 COVID-19 deaths); Illinois (95% CI 4646-6111) vs. 3525 COVID-19 deaths); Louisiana (excess mortality 95% CI 2341-3183 vs. 2267 COVID-19 deaths); Massachusetts (95% CI 5562-7201 vs. 5050 COVID-19 deaths); New Jersey (95% CI 13 170-16 058 vs. 10 465 COVID-19 deaths); New York (95% CI 32 538-39 960 vs. 26 584 COVID-19 deaths); and Pennsylvania (95% CI 5125-6560 vs. 3793 COVID-19 deaths). Conventional model results were consistent with semiparametric results but less precise. Significant excess pneumonia deaths were also found for all locations and we estimated hundreds of excess influenza deaths in New York. We find that official COVID-19 mortality substantially understates actual mortality, excess deaths cannot be explained entirely by official COVID-19 death counts. Mortality reporting lags appeared to worsen during the pandemic, when timeliness in surveillance systems was most crucial for improving pandemic response.

Ambient temperature, seasonal influenza and risk of cardiovascular disease in a subtropical area in Southern China

BACKGROUND

Given the regular winter recurrence of influenza epidemics and the biologically plausible association between seasonal influenza and cardiovascular events, researchers assumed a valid and reliable influenza forecast could envision the timing and burden of winter surge in cardiovascular (CVD) hospitalizations. This, however, is well justified only in temperate regions. In this study, we aim to investigate the temporal association between ambient temperature, seasonal influenza and risk of cardiovascular events in a subtropical city.

METHODS

Generalized additive model was used in conjunction with distributed-lag non-linear model of quasi-Poisson family to estimate the association of interest with daily CVD admissions as outcome and daily influenza admissions as predictor, while controlling for meteorological factors (i.e. temperature, relative humidity, wind speed and total rainfall) and respiratory pollutants (i.e. nitrogen dioxide, sulphur dioxide, ozone and PM₁₀). Results were expressed in the form of relative risk (RR).

RESULTS

Using median as the reference value, a U-shaped association was observed between CVD admissions and temperature. A slight decrease in RR was detected mainly towards the lower end of the temperature scale after adjusting for influenza admissions. Risk of CVD admission was found to be positively associated with the number of influenza hospitalization cases; this association remained consistent and statistically significant across subgroups of age except for those aged 5-49 years.

CONCLUSION

The slight reduction in CVD admission risk towards the lower end of the temperature scale after controlling for influenza activity might be attributed to the winter peaks of influenza, meaning that the effect of low temperature on CVD admissions might be partly mediated by influenza infection. In summary, this study reassures us that ambient temperature is independently associated with CVD hospital admissions and offers support for a positive association between seasonal influenza activity and cardiovascular events in Hong Kong.

Epidemiological analysis of association between lagged meteorological variables and pneumonia in wet-dry tropical North Australia, 2006-2016

Pneumonia accounts for 1.5% of all overnight hospital admission in Australia. We investigated the nonlinear and delay effect of weather (temperature and rainfall) on pneumonia. This study was based on a large cohort of inpatients that were hospitalized due to pneumonia between 2006 and 2016. Cases were identified using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD10-AM) codes J10.0*-J18.0*. A time-varying distributed lag nonlinear model was used to estimate the burden of the disease attributable to varying weather-lag pneumonia relationships and identify vulnerable groups. The relative risk (presented as logRR) associated with temperature was immediate and highest in late winter at the lowest temperature of 16 °C (logRR = 1.13, 95% confidence intervals (CI): 0.59, 1.66). The cumulative effect over the lag range 0-8 weeks revealed two peaks for low (12 mm, logRR = 0.73, 95% CI: 0.32, 1.13) and moderately high rainfall (51 mm) with logRR of 1.15 (95% CI: 0.10, 2.20). A substantial number, 22.50% (95% empirical CI: 1.83, 34.68), of pneumonia cases were attributable to temperature (mostly due to moderate low temperatures). Females and indigenous (Aboriginal and Torres Strait Islander) patients were particularly vulnerable to the impact of temperature-related pneumonia. In this study, we highlighted the delayed effects and magnitude of burden of pneumonia that is associated with low temperature and rainfall. The findings in this study can inform a better understanding of the health implications and burden associated with pneumonia to support discussion-making in healthcare and establish a strategy for prevention and control of the disease among vulnerable groups.

Influenza vaccine effectiveness against hospitalization with laboratory-confirmed influenza in Greece: A pooled analysis across six seasons, 2013-2014 to 2018-2019

BACKGROUND

Monitoring seasonal influenza Vaccine Effectiveness (VE) is key to inform vaccination strategies and sustain uptake. Pooling data across multiple seasons increases precision and allows for subgroup analyses, providing more conclusive evidence. Our aim was to assess VE against hospitalization with laboratory-confirmed influenza in Greece over six seasons, from 2013 to 2014 to 2018-2019, using routinely collected surveillance data.

METHODS

Swab samples from hospitalized patients across the country were tested for influenza by RT-PCR. We used the test-negative design, with patients testing positive for influenza serving as cases and those testing negative serving as controls. VE was calculated as one minus the Odds Ratio (OR) for influenza vaccination, estimated by mixed-effects logistic regression and adjusted for age, sex, hospitalization type (being in intensive care or not), time from symptom onset to swabbing, and calendar time. Stratified estimates by age and hospitalization type were obtained, and also subgroup estimates by influenza type/subtype and season. Antigenic and genetic characterization of a subset of circulating influenza strains was performed.

RESULTS

A total of 3,882 test-positive cases and 5,895 test-negative controls were analyzed. Across all seasons, adjusted VE was 45.5% (95% CI: 31.6-56.6) against all influenza, 62.8% against A(H1N1)pdm09 (95% CI: 40.7-76.7), 28.2% against A(H3N2) (95% CI: 12.0-41.3) and 45.5% against influenza B (95% CI: 29.1-58.1). VE was slightly lower for patients aged 60 years and over, and similar between patients hospitalized inside or outside intensive care. Circulating A(H1N1)pdm09 and B strains were antigenically similar to the vaccine strains, whereas A(H3N2) were not.

CONCLUSION

Our results confirm the public health benefits from seasonal influenza vaccination, despite the suboptimal effectiveness against A(H3N2) strains. Continued monitoring of VE is essential, and routinely collected surveillance data can be valuable in this regard.

Impacts of heat and cold on hospitalizations for schizophrenia in Hefei, China: An assessment of disease burden

BACKGROUND

Compared with risk data (e.g., RR or OR), attributable fraction (AF) provides more information on the formulation of policies and measures in the field of public health. However, to date, existing AF evidence is scarce for the relationship between temperature and the hospitalizations for SCZ.

OBJECTIVES

Our primary goal is to estimate the attributable burden of hospitalizations for SCZ related to cold and heat, respectively. Furthermore, to identify vulnerable populations due to heat and cold.

METHODS

Poisson generalized linear models combined with DLNMs were used to estimate the association between hospitalizations for SCZ and temperature from 2005 to 2014. The minimum risk temperature (MRT) was used as a reference, to calculate the burden of disease caused by cold and heat.

RESULTS

We found that the majority hospitalizations attributed to heat (70.9%). In different individual levels, men are more sensitive to heat exposure while women are more vulnerable to cold. Among different age groups, the results showed that the attributable risk was slightly higher in the over-40s than in the under-40s. Besides, under different marital conditions, it showed that the unmarried had a little higher attributional risk than the married.

CONCLUSIONS

We should pay attention to the impact of heat on hospitalizations for SCZ, especially in those over 40 years old, men and non-married. Our research will provide a basis for policymakers to develop intervention strategies to minimize the impact of adverse temperatures on hospitalizations for SCZ, thereby reducing the burden of disease.

Association between type-specific influenza circulation and incidence of severe laboratory-confirmed cases; which subtype is the most virulent?

OBJECTIVES

Excess population mortality during winter is most often associated with influenza A(H3N2), though susceptibility differs by age. We examined differences between influenza types/subtypes in their association with severe laboratory-confirmed cases, overall and by age group, to determine which type is the most virulent.

METHODS

We used nine seasons of comprehensive nationwide surveillance data from Greece (2010-2011 to 2018-2019) to examine the association, separately for influenza A(H1N1)pdm09, A(H3N2) and B, between the number of laboratory-confirmed severe cases (intensive care hospitalizations or deaths) per type/subtype and the overall type-specific circulation during the season (expressed as a cumulative incidence proxy). Quasi-Poisson models with identity link were used, and multiple imputation to handle missing influenza A subtype.

RESULTS

For the same level of viral circulation and across all ages, influenza A(H1N1)pdm09 was associated with twice as many intensive care hospitalizations as A(H3N2) (rate ratio (RR) 1.89, 95% CI 1.38-2.74) and three times more than influenza B (RR 3.27, 95%CI 2.54-4.20). Similar associations were observed for laboratory-confirmed deaths. A(H1N1)pdm09 affected adults over 40 years at similar rates, whereas A(H3N2) affected elderly people at a much higher rate than younger persons (≥65 vs. 40-64 years, RR for intensive care 5.42, 95% CI 3.45-8.65, and RR for death 6.19, 95%CI 4.05-9.38). Within the 40-64 years age group, A(H1N1)pdm09 was associated with an approximately five times higher rate of severe disease than both A(H3N2) and B.

DISCUSSION

Influenza A(H1N1)pdm09 is associated with many more severe laboratory-confirmed cases, likely due to a more typical clinical presentation and younger patient age, leading to more testing. A(H3N2) affects older people more, with cases less often recognized and confirmed.

Virological Surveillance of Influenza in the eight epidemic seasons after the 2009 pandemic in Emilia-Romagna (Northern Italy)

BACKGROUND AND AIM OF THE WORK

Influenza virological surveillance is essential for monitoring the evolution of influenza viruses (IVs) as well as for annual updating of the vaccine composition. The aim of this study is to analyse IVs circulation in Emilia-Romagna during the eight epidemic seasons after the 2009 pandemic and to evaluate their match with seasonal vaccine strains.

METHODS

A total of 7882 respiratory specimens from patients with influenza-like illness (ILI), were collected by regional sentinel practitioners and hospital physicians. Viral investigations were conducted by rRT-PCR assay. Genetic characterization was performed for a spatial-temporal representative number of influenza laboratory-confirmed specimens.

RESULTS

Influenza-positive samples per season ranged between 28.9% (2013-2014) and 66.8% (2012-2013). Co-circulation of IVs type A and type B was observed in all seasons, although with a different intensity. In all seasons, the highest number of positive samples was recorded in younger patients aged 5-14 years with relative frequencies ranging from 40% in the 2013-2014 season and 78% in the 2012-2013 season. Since the 2009 pandemic, A/H1N1pdm09 IVs circulating were closely related to the vaccine strain A/California/7/2009. Antigenic mismatch between vaccine strain and A/H3N2 IVs was observed in the 2011-2012 and 2014-2015 seasons. During 2015-2016, 2016-2017 and 2017-2018 seasons a complete or nearly complete mismatch between the predominant influenza B lineage of IVs type B circulating and vaccine B lineage occurred.

CONCLUSIONS

This analysis confirms the importance of the virological surveillance and highlights the need of a continuous monitoring of IVs circulation, to improve the most appropriate vaccination strategies. (www.actabiomedica.it).

Estimating Influenza-associated Mortality in Korea: The 2009-2016 Seasons

OBJECTIVES

Estimating influenza-associated mortality is important since seasonal influenza affects persons of all ages, causing severe illness or death. This study aimed to estimate influenza-associated mortality, considering both periodic changes and age-specific mortality by influenza subtypes.

METHODS

Using the Microdata Integrated Service from Statistics Korea, we collected weekly mortality data including cause of death. Laboratory surveillance data of respiratory viruses from 2009 to 2016 were obtained from the Korea Centers for Disease Control and Prevention. After adjusting for the annual age-specific population size, we used a negative binomial regression model by age group and influenza subtype.

RESULTS

Overall, 1 859 890 deaths were observed and the average rate of influenza virus positivity was 14.7% (standard deviation [SD], 5.8), with the following subtype distribution: A(H1N1), 5.0% (SD, 5.8); A(H3N2), 4.4% (SD, 3.4); and B, 5.3% (SD, 3.7). As a result, among individuals under 65 years old, 6774 (0.51%) all-cause deaths, 2521 (3.05%) respiratory or circulatory deaths, and 1048 (18.23%) influenza or pneumonia deaths were estimated. Among those 65 years of age or older, 30 414 (2.27%) all-cause deaths, 16 411 (3.42%) respiratory or circulatory deaths, and 4906 (6.87%) influenza or pneumonia deaths were estimated. Influenza A(H3N2) virus was the major contributor to influenza-associated all-cause and respiratory or circulatory deaths in both age groups. However, influenza A(H1N1) virus-associated influenza or pneumonia deaths were more common in those under 65 years old.

CONCLUSIONS

Influenza-associated mortality was substantial during this period, especially in the elderly. By subtype, influenza A(H3N2) virus made the largest contribution to influenza-associated mortality.

Life Expectancy: Frequently Used, but Hardly Understood

Period life expectancy is one of the most used summary indicators for the overall health of a population. Its levels and trends direct health policies, and researchers try to identify the determining risk factors to assess and forecast future developments. The use of period life expectancy is often based on the assumption that it directly reflects the mortality conditions of a certain year. Accordingly, the explanation for changes in life expectancy are typically sought in factors that have an immediate impact on current mortality conditions. It is frequently overlooked, however, that this indicator can also be affected by at least three kinds of effects, in particular in the situation of short-term fluctuations: cohort effects, heterogeneity effects, and tempo effects. We demonstrate their possible impact with the example of the almost Europe-wide decrease in life expectancy in 2015, which caused a series of reports about an upsurge of a health crisis, and we show that the consideration of these effects can lead to different conclusions. Therefore, we want to raise an awareness concerning the sensitivity of life expectancy to sudden changes and the menaces a misled interpretation of this indicator can cause.