Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Estimating excess septicaemia mortality and hospitalisation burden associated with influenza in Hong Kong, 1998 to 2019.

ABSTRACT: Influenza virus infections can lead to a number of secondary complications, including sepsis. We applied linear regression models to mortality and hospital admission data coded for septicaemia from 1998 to 2019 in Hong Kong, and estimated that septicaemia was associated with an annual average excess mortality rate of 0.23 (95% CI 0.04-0.40) per 100 000 persons per year and an excess septicaemia hospitalisation rate of 1.73 (95% CI 0.94-2.50) per 100 000 persons per year. The highest excess morbidity and mortality was found in older adults and young children, and during influenza A(H3N2) epidemics.

SUBMITTER: Wong JY

PROVIDER: S-EPMC9128349 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Estimating excess septicaemia mortality and hospitalisation burden associated with influenza in Hong Kong, 1998 to 2019.

Wong Jessica Y JY Cheung Chung-Mei M CM Bond Helen S HS Cheung Justin K JK Gao Huizhi H Fang Vicky J VJ Lau Eric H Y EHY Cowling Benjamin J BJ Wu Peng P

Epidemiology and infection 20220427

Influenza virus infections can lead to a number of secondary complications, including sepsis. We applied linear regression models to mortality and hospital admission data coded for septicaemia from 1998 to 2019 in Hong Kong, and estimated that septicaemia was associated with an annual average excess mortality rate of 0.23 (95% CI 0.04-0.40) per 100 000 persons per year and an excess septicaemia hospitalisation rate of 1.73 (95% CI 0.94-2.50) per 100 000 persons per year. The highest excess morbi ...[more]

PMID: 35606895

Similar Datasets

Excess mortality associated with influenza A and B virus in Hong Kong, 1998-2009.

Project description:BackgroundAlthough deaths associated with laboratory-confirmed influenza virus infections are rare, the excess mortality burden of influenza estimated from statistical models may more reliably quantify the impact of influenza in a population.MethodsWe applied age-specific multiple linear regression models to all-cause and cause-specific mortality rates in Hong Kong from 1998 through 2009. The differences between estimated mortality rates in the presence or absence of recorded influenza activity were used to estimate influenza-associated excess mortality.ResultsThe annual influenza-associated all-cause excess mortality rate was 11.1 (95% confidence interval [CI], 7.2-14.6) per 100,000 person-years. We estimated an average of 751 (95% CI, 488-990) excess deaths associated with influenza annually from 1998 through 2009, with 95% of the excess deaths occurring in persons aged ?65 years. Most of the influenza-associated excess deaths were from respiratory (53%) and cardiovascular (18%) causes. Influenza A(H3N2) epidemics were associated with more excess deaths than influenza A(H1N1) or B during the study period.ConclusionsInfluenza was associated with a substantial number of excess deaths each year, mainly among the elderly, in Hong Kong in the past decade. The influenza-associated excess mortality rates were generally similar in Hong Kong and the United States.

| S-EPMC3502382 | biostudies-literature

Dynamic interactions of influenza viruses in Hong Kong during 1998-2018.

Project description:Influenza epidemics cause substantial morbidity and mortality every year worldwide. Currently, two influenza A subtypes, A(H1N1) and A(H3N2), and type B viruses co-circulate in humans and infection with one type/subtype could provide cross-protection against the others. However, it remains unclear how such ecologic competition via cross-immunity and antigenic mutations that allow immune escape impact influenza epidemic dynamics at the population level. Here we develop a comprehensive model-inference system and apply it to study the evolutionary and epidemiological dynamics of the three influenza types/subtypes in Hong Kong, a city of global public health significance for influenza epidemic and pandemic control. Utilizing long-term influenza surveillance data since 1998, we are able to estimate the strength of cross-immunity between each virus-pairs, the timing and frequency of punctuated changes in population immunity in response to antigenic mutations in influenza viruses, and key epidemiological parameters over the last 20 years including the 2009 pandemic. We find evidence of cross-immunity in all types/subtypes, with strongest cross-immunity from A(H1N1) against A(H3N2). Our results also suggest that A(H3N2) may undergo antigenic mutations in both summers and winters and thus monitoring the virus in both seasons may be important for vaccine development. Overall, our study reveals intricate epidemiological interactions and underscores the importance of simultaneous monitoring of population immunity, incidence rates, and viral genetic and antigenic changes.

| S-EPMC7316359 | biostudies-literature

Forecasting of influenza activity and associated hospital admission burden and estimating the impact of COVID-19 pandemic on 2019/20 winter season in Hong Kong.

Project description:Like other tropical and subtropical regions, influenza viruses can circulate year-round in Hong Kong. However, during the COVID-19 pandemic, there was a significant decrease in influenza activity. The objective of this study was to retrospectively forecast influenza activity during the year 2020 and assess the impact of COVID-19 public health social measures (PHSMs) on influenza activity and hospital admissions in Hong Kong. Using weekly surveillance data on influenza virus activity in Hong Kong from 2010 to 2019, we developed a statistical modeling framework to forecast influenza virus activity and associated hospital admissions. We conducted short-term forecasts (1-4 weeks ahead) and medium-term forecasts (1-13 weeks ahead) for the year 2020, assuming no PHSMs were implemented against COVID-19. We estimated the reduction in transmissibility, peak magnitude, attack rates, and influenza-associated hospitalization rate resulting from these PHSMs. For short-term forecasts, mean ambient ozone concentration and school holidays were found to contribute to better prediction performance, while absolute humidity and ozone concentration improved the accuracy of medium-term forecasts. We observed a maximum reduction of 44.6% (95% CI: 38.6% - 51.9%) in transmissibility, 75.5% (95% CI: 73.0% - 77.6%) in attack rate, 41.5% (95% CI: 13.9% - 55.7%) in peak magnitude, and 63.1% (95% CI: 59.3% - 66.3%) in cumulative influenza-associated hospitalizations during the winter-spring period of the 2019/2020 season in Hong Kong. The implementation of PHSMs to control COVID-19 had a substantial impact on influenza transmission and associated burden in Hong Kong. Incorporating information on factors influencing influenza transmission improved the accuracy of our predictions.

| S-EPMC11318919 | biostudies-literature

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

Project description: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.

| S-EPMC6627011 | biostudies-literature

A joint analysis of influenza-associated hospitalizations and mortality in Hong Kong, 1998-2013.

Project description:Influenza viruses may cause severe human infections leading to hospitalization or death. Linear regression models were fitted to population-based data on hospitalizations and deaths. Surveillance data on influenza virus activity permitted inference on influenza-associated hospitalizations and deaths. The ratios of these estimates were used as a potential indicator of severity. Influenza was associated with 431 (95% CrI: 358-503) respiratory deaths and 12,700 (95% CrI: 11,700-13,700) respiratory hospitalizations per year. Majority of the excess deaths occurred in persons ≥65 y of age. The ratios of deaths to hospitalizations in adults ≥65 y were significantly higher for influenza A(H1N1) and A(H1N1)pdm09 compared to A(H3N2) and B. Substantial disease burden associated with influenza viruses were estimated in Hong Kong particularly among children and elderly in 1998-2013. Infections with influenza A(H1N1) was suggested to be more serious than A(H3N2) in older adults.

| S-EPMC5430505 | biostudies-literature

Excess mortality impact of two epidemics of pandemic influenza A(H1N1pdm09) virus in Hong Kong.

Project description:Hong Kong experienced two large epidemics of pandemic influenza A(H1N1pdm09). We used regression methods to estimate the excess mortality associated with each epidemic. The first epidemic of H1N1pdm09 peaked in September 2009 and was associated with 2·13 [95% confidence interval (CI): -8·08, 11·82] excess all-cause deaths per 100 000 population. The second epidemic of H1N1pdm09 in early 2011 was associated with 4·72 [95% CI: -0·70, 10·50] excess deaths per 100 000 population. More than half of the estimated excess all-cause deaths were attributable to respiratory causes in each epidemic. The reasons for substantial impact in the second wave remain to be clarified.

| S-EPMC3877676 | biostudies-literature

Evaluating impact of school outreach vaccination programme in Hong Kong influenza season 2018 - 2019.

Project description:School-based vaccination, as a means to mitigate seasonal influenza outbreak, depends on attaining adequate coverage rate. We evaluated the potential of a fully subsidized school outreach vaccination (SOV) program to achieve epidemic prevention potential in Hong Kong. The purpose of this study was to evaluate the impact of SOV program 2018-2019 on influenza vaccination rates and influenza-like illness (ILI) in the primary school students and their household members during the influenza season. The vaccination rate was significantly higher in the schools offering SOV (intervention schools) (69.2% vs. 34.3%) than those not offering SOV (control schools) (p < .0001). The ILI rate was significantly reduced from 14.1% among non-vaccinated to 7.7% among vaccinated students (p < .0001). Influenza vaccine effectiveness against ILI was 45.3%. The vaccination rates of the household members were the same in both intervention and control schools except in the sub-group of preschool household members with the intervention significantly higher than the control group (43.8% vs. 32%, p < .0001). SOV program significantly improved influenza vaccine coverage, and the vaccine reduced ILI incidence. Extension of SOV program to all primary schools as well as kindergartens in Hong Kong could achieve epidemic prevention potential and should be evaluated.

| S-EPMC7227703 | biostudies-literature

Forecasting Influenza Epidemics in Hong Kong.

Project description:Recent advances in mathematical modeling and inference methodologies have enabled development of systems capable of forecasting seasonal influenza epidemics in temperate regions in real-time. However, in subtropical and tropical regions, influenza epidemics can occur throughout the year, making routine forecast of influenza more challenging. Here we develop and report forecast systems that are able to predict irregular non-seasonal influenza epidemics, using either the ensemble adjustment Kalman filter or a modified particle filter in conjunction with a susceptible-infected-recovered (SIR) model. We applied these model-filter systems to retrospectively forecast influenza epidemics in Hong Kong from January 1998 to December 2013, including the 2009 pandemic. The forecast systems were able to forecast both the peak timing and peak magnitude for 44 epidemics in 16 years caused by individual influenza strains (i.e., seasonal influenza A(H1N1), pandemic A(H1N1), A(H3N2), and B), as well as 19 aggregate epidemics caused by one or more of these influenza strains. Average forecast accuracies were 37% (for both peak timing and magnitude) at 1-3 week leads, and 51% (peak timing) and 50% (peak magnitude) at 0 lead. Forecast accuracy increased as the spread of a given forecast ensemble decreased; the forecast accuracy for peak timing (peak magnitude) increased up to 43% (45%) for H1N1, 93% (89%) for H3N2, and 53% (68%) for influenza B at 1-3 week leads. These findings suggest that accurate forecasts can be made at least 3 weeks in advance for subtropical and tropical regions.

| S-EPMC4520691 | biostudies-literature

Population-Based Pediatric Hospitalization Burden of Lineage-Specific Influenza B in Hong Kong, 2004-2014.

Project description:BackgroundInfluenza B virus has been perceived to cause less disease burden and milder disease compared with influenza A, but recent studies suggest that influenza B does have a significant impact. We aimed to estimate the burden of influenza B virus infections on hospitalizations in Hong Kong, in the context of virus lineage changes over time.MethodsThe pediatric age-specific rates of influenza B hospitalization in Hong Kong for 2004-2014 were estimated based on admissions to 2 hospitals that together catered for 72.5% of all pediatric admissions on Hong Kong Island. Influenza B virus was detected by immunofluorescence and culture on nasopharyngeal aspirates. Lineage typing was performed by real-time reverse-transcription polymerase chain reaction.ResultsA total of 5085 children were recruited on 1 designated day each week, year-round during the 11 years, and 221 (4.3%) tested positive for influenza B. Hospitalization rates were highest in children aged 2 to <5 years with year-to-year variation. Victoria-lineage viruses appeared to be associated with a greater fraction of influenza B hospitalizations in children than of influenza B infections in the general community. Influenza B did not cause significant hospitalization in infants <1 year of age.ConclusionsWe report one of the first population-based, age- and lineage-specific studies of pediatric hospitalization for influenza B. We found that changes in lineage were associated with higher hospitalization rates and documented that Victoria lineage viruses were associated with greater pediatric hospitalization burden compared with Yamagata lineage viruses.

| S-EPMC5848250 | biostudies-literature

Accounting for Imported Cases in Estimating the Time-Varying Reproductive Number of Coronavirus Disease 2019 in Hong Kong.

Project description:Estimating the time-varying reproductive number, Rt, is critical for monitoring transmissibility of an infectious disease. The impact of imported cases on the estimation is rarely explored. We developed a model to estimate separately the Rt for local cases and imported cases, accounting for imperfect contact tracing of cases. We applied this framework to data on coronavirus disease 2019 outbreaks in Hong Kong. The estimated Rt for local cases rose above 1 in late March 2020, which was undetected by other commonly used methods. When imported cases account for a considerable proportion of all cases, their impact on estimating Rt is critical.

| S-EPMC8244742 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data