Background The seasonal cycle of the influenza virus causes substantial morbidity and mortality globally.The impact of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)on the circulation of influenza viruses...Background The seasonal cycle of the influenza virus causes substantial morbidity and mortality globally.The impact of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)on the circulation of influenza viruses can influence influenza-associated excess mortality.Given the few studies that have explored this topic,the objective of this study was to evaluate influenza-associated excess mortality in the Chinese mainland from 2012 to 2021 and quantify the changes from 2020 to 2021 compared with 2012–2019.Methods Using data from national influenza surveillance report and disease surveillance points,we fitted a generalized additive model on all-cause(AC),pneumonia&influenza(P&I),and respiratory(R)mortality rates.In this model,we included data of influenza activity(A/H1N1,A/H3N2 and B),temperature,absolute humidity,the COVID-19 pandemic,and time trends.The excess mortality was estimated by subtracting the fitted baseline mortality from the predicted mortality,which set influenza activity to zero.Results The respiratory mortality model explained more than 90%of the variance,indicating the good performance.We found that the influenza-associated mortality was generally decreasing from 2020 to 2021,for instance,influenza A/H1N1-associated excess respiratory mortality(ERM)decreased from 2.62 per 100,000 persons(95%confidence interval:0.16–5.21)to 0.31(0.02–0.60)in the northern region and from 3.79(0.09–7.05)to 0.24(0.02–0.46)in the southern region between 2012–2019 and 2020–2021.A similar pattern was observed for A/H3N2-associated ERM.While the influenza B remained similar scale,for instance,the ERM was 2.90(0.72–4.3)and 2.26(1.76–2.76)in the southern region between 2012–2019 and 2020–2021,respectively.Distinct pattern was observed for the AC and P&I outcomes.Conclusions The COVID-19 pandemic has reduced influenza-associated excess mortality,which may be a result of the reduced activity of the influenza virus caused by nonpharmaceutical interventions.Different patterns of regional differences differed for influenza-associated AC,P&I and R mortality.It should be noticed that the contribution of influenza B was generally similar when comparing 2012–2019 and 2020–2021,which highlighted the attention on the influenza B activity.Additional studies are needed to explore the changes in influenzaassociated excess mortality afterwards.展开更多
Purpose:Hip fractures in elderly have a high mortality.However,there is limited literature on the excess mortality seen in hip fractures compared to the normal population.The purpose of this study was to compare the m...Purpose:Hip fractures in elderly have a high mortality.However,there is limited literature on the excess mortality seen in hip fractures compared to the normal population.The purpose of this study was to compare the mortality of hip fractures with that of age and gender matched Indian population.Methods:There are 283 patients with hip fractures aged above 50 years admitted at single centre prospectively enrolled in this study.Patients were followed up for 1 year and the follow-up record was available for 279 patients.Mortality was assessed during the follow-up from chart review and/or by telephonic interview.One-year mortality of Indian population was obtained from public databases.Standardized mortality ratio(SMR)(observed mortality divided by expected mortality)was calculated.Kaplan-Meir analysis was used.Results:The overall 1-year mortality was 19.0%(53/279).Mortality increased with age(p<0.001)and the highest mortality was seen in those above 80 years(aged 50-59 years:5.0%,aged 60-69 years:19.7%,aged 70-79 years:15.8%,and aged over 80 years:33.3%).Expected mortality of Indian population of similar age and gender profile was 3.7%,giving a SMR of 5.5.SMR for different age quintiles were:3.9(aged 50-59 years),6.6(aged 60-69 years),2.2(aged 70-79 years);and 2.0(aged over 80 years).SMR in males and females were 5.7 and 5.3,respectively.Conclusions:Indian patients sustaining hip fractures were about 5 times more likely to die than the general population.Although mortality rates increased with age,the highest excess mortality was seen in relatively younger patients.Hip fracture mortality was even higher than that of myocardial infarction,breast cancer,and cervical cancer.展开更多
Climate change is one of the biggest health threats of the 21st century.Although China is the biggest developing country,with a large population and different climate types,its projections of large-scale heat-related ...Climate change is one of the biggest health threats of the 21st century.Although China is the biggest developing country,with a large population and different climate types,its projections of large-scale heat-related excess mortality remain understudied.In particular,the effects of climate change on aging populations have not been well studied,and may result in significantly underestimation of heat effects.In this study,we took four climate change scenarios of Tier-1 in CMIP6,which were combinations of Shared Socioeconomic Pathways(SSPs)and Representative Concentration Pathways(RCPs).We used the exposure-response functions derived from previous studies combined with baseline age-specific non-accidental mortality rates to project heat-related excess mortality.Then,we employed the Logarithmic Mean Divisia Index(LMDI)method to decompose the impacts of climate change,population growth,and aging on heat-related excess mortality.Finally,we multiplied the heat-related Years of Life Lost(YLL)with the Value of a Statistical Life Year(VSLY)to quantify the economic burden of premature mortality.We found that the heat-related excess mortality would be concentrated in central China and in the densely populated south-eastern coastal regions.When aging is considered,heat-related excess mortality will become 2.8–6.7 times than that without considering aging in 2081–2100 under different scenarios.The contribution analysis showed that the effect of aging on heat-related deaths would be much higher than that of climate change.Our findings highlighted that aging would lead to a severe increase of heat-related deaths and suggesting that regional-specific policies should be formulated in response to heat-related risks.展开更多
Time series analysis is a valuable tool in epidemiology that complements the classical epidemiological models in two different ways:Prediction and forecast.Prediction is related to explaining past and current data bas...Time series analysis is a valuable tool in epidemiology that complements the classical epidemiological models in two different ways:Prediction and forecast.Prediction is related to explaining past and current data based on various internal and external influences that may or may not have a causative role.Forecasting is an exploration of the possible future values based on the predictive ability of the model and hypothesized future values of the external and/or internal influences.The time series analysis approach has the advantage of being easier to use(in the cases of more straightforward and linear models such as Auto-Regressive Integrated Moving Average).Still,it is limited in forecasting time,unlike the classical models such as Susceptible-Exposed-Infectious-Removed.Its applicability in forecasting comes from its better accuracy for short-term prediction.In its basic form,it does not assume much theoretical knowledge of the mechanisms of spreading and mutating pathogens or the reaction of people and regulatory structures(governments,companies,etc.).Instead,it estimates from the data directly.Its predictive ability allows testing hypotheses for different factors that positively or negatively contribute to the pandemic spread;be it school closures,emerging variants,etc.It can be used in mortality or hospital risk estimation from new cases,seroprevalence studies,assessing properties of emerging variants,and estimating excess mortality and its relationship with a pandemic.展开更多
To obtain the influence of heat waves on death in the elderly, the influence of the heat waves in Nanjing in the summers (from June to August) of 2005-2008 on death among the elderly was analyzed by using statistical ...To obtain the influence of heat waves on death in the elderly, the influence of the heat waves in Nanjing in the summers (from June to August) of 2005-2008 on death among the elderly was analyzed by using statistical methods including generalized additive models. The results showed that the death toll over these four summers in Nanjing tended to increase;on an average 10.76% more males died than females, and the mortality rate of old people aged ≥65 accounted for 73.21% of all deaths. The mortality rate of older people rose with increasing maximum temperature. Furthermore, the average excess mortality rate caused by heat wave weather processes was 15.91%, while it was less affected by the duration of the heat wave. The death toll of the elderly increased with the increase in humidity, dropping of atmospheric pressure, and decrease of wind speed for 1°C increase of maximum temperature. Under the same humidity condition, atmospheric pressure, and wind speed, the death toll during heat wave days was higher than that occurring on other days, and heat waves increased the risk of death among the elderly by 26.6% (95% CI: 1.100 - 1.154). Daily mortality was mainly affected by the daily maximum temperature 1, 4, or 6 days later, particularly 4 days later. Heat wave was one of the principal factors, which caused the rise in death tolls in summer, and the elderly were most affected.展开更多
Background Conditional relative survival(CRS),the probability of survival given that an individual has already survived a certain period post-diagnosis,is a more clinically relevant measure for long-term survival than...Background Conditional relative survival(CRS),the probability of survival given that an individual has already survived a certain period post-diagnosis,is a more clinically relevant measure for long-term survival than standard relative survival(RS).This study aims to evaluate the 5-year CRS among adolescent and young adult(AYA)breast cancer patients by age,tumor stage,and receptor subtype to guide disclosure periods for insurance.Methods Data of all females aged 18–39 years and diagnosed with invasive breast cancer between 2003 and 2021(n=13,075)were obtained from The Netherlands Cancer Registry(NCR).The five-year CRS was calculated annually up to 10 years post-diagnosis using a hybrid analysis approach.Results For the total AYA breast cancer study population the 5-year CRS exceeded 90%from diagnosis and increased beyond 95%7 years post-diagnosis.Patients aged 18–24 reached 95%9 years post-diagnosis,those aged 25–29 after 5 years,and those aged 30–34 and 35–39 after 8 years.For stage I,the 5-year CRS reached 95%from diagnosis,for stage II after 6 years,while the 5-year CRS for stages III and IV did not reach the 95%threshold during the 10-year follow-up.Triple-negative tumors exceeded 95%after 4 years,human epidermal growth factor receptor 2(HER2)positive tumors after 6 years,while hormone receptor(HR)positive tumors did not reach 95%.Conclusion Excess mortality among AYA breast cancer patients tends to be little(CRS 90%–95%)from diagnosis and becomes minimal(CRS>95%)over time compared to the general population.These results can enhance expectation management and inform policymakers,suggesting a shorter disclosure period.展开更多
基金supported by Shanghai Municipal Science and Technology Major Project(ZD2021CY001).
文摘Background The seasonal cycle of the influenza virus causes substantial morbidity and mortality globally.The impact of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)on the circulation of influenza viruses can influence influenza-associated excess mortality.Given the few studies that have explored this topic,the objective of this study was to evaluate influenza-associated excess mortality in the Chinese mainland from 2012 to 2021 and quantify the changes from 2020 to 2021 compared with 2012–2019.Methods Using data from national influenza surveillance report and disease surveillance points,we fitted a generalized additive model on all-cause(AC),pneumonia&influenza(P&I),and respiratory(R)mortality rates.In this model,we included data of influenza activity(A/H1N1,A/H3N2 and B),temperature,absolute humidity,the COVID-19 pandemic,and time trends.The excess mortality was estimated by subtracting the fitted baseline mortality from the predicted mortality,which set influenza activity to zero.Results The respiratory mortality model explained more than 90%of the variance,indicating the good performance.We found that the influenza-associated mortality was generally decreasing from 2020 to 2021,for instance,influenza A/H1N1-associated excess respiratory mortality(ERM)decreased from 2.62 per 100,000 persons(95%confidence interval:0.16–5.21)to 0.31(0.02–0.60)in the northern region and from 3.79(0.09–7.05)to 0.24(0.02–0.46)in the southern region between 2012–2019 and 2020–2021.A similar pattern was observed for A/H3N2-associated ERM.While the influenza B remained similar scale,for instance,the ERM was 2.90(0.72–4.3)and 2.26(1.76–2.76)in the southern region between 2012–2019 and 2020–2021,respectively.Distinct pattern was observed for the AC and P&I outcomes.Conclusions The COVID-19 pandemic has reduced influenza-associated excess mortality,which may be a result of the reduced activity of the influenza virus caused by nonpharmaceutical interventions.Different patterns of regional differences differed for influenza-associated AC,P&I and R mortality.It should be noticed that the contribution of influenza B was generally similar when comparing 2012–2019 and 2020–2021,which highlighted the attention on the influenza B activity.Additional studies are needed to explore the changes in influenzaassociated excess mortality afterwards.
文摘Purpose:Hip fractures in elderly have a high mortality.However,there is limited literature on the excess mortality seen in hip fractures compared to the normal population.The purpose of this study was to compare the mortality of hip fractures with that of age and gender matched Indian population.Methods:There are 283 patients with hip fractures aged above 50 years admitted at single centre prospectively enrolled in this study.Patients were followed up for 1 year and the follow-up record was available for 279 patients.Mortality was assessed during the follow-up from chart review and/or by telephonic interview.One-year mortality of Indian population was obtained from public databases.Standardized mortality ratio(SMR)(observed mortality divided by expected mortality)was calculated.Kaplan-Meir analysis was used.Results:The overall 1-year mortality was 19.0%(53/279).Mortality increased with age(p<0.001)and the highest mortality was seen in those above 80 years(aged 50-59 years:5.0%,aged 60-69 years:19.7%,aged 70-79 years:15.8%,and aged over 80 years:33.3%).Expected mortality of Indian population of similar age and gender profile was 3.7%,giving a SMR of 5.5.SMR for different age quintiles were:3.9(aged 50-59 years),6.6(aged 60-69 years),2.2(aged 70-79 years);and 2.0(aged over 80 years).SMR in males and females were 5.7 and 5.3,respectively.Conclusions:Indian patients sustaining hip fractures were about 5 times more likely to die than the general population.Although mortality rates increased with age,the highest excess mortality was seen in relatively younger patients.Hip fracture mortality was even higher than that of myocardial infarction,breast cancer,and cervical cancer.
基金supported by the National Natural Science Foundation of China(No.72091514)the Energy Foundation(No.G-2206-33982)+1 种基金the Tsinghua-Toyota Joint Research Fund,Wellcome Trust(No.209734/Z/17/Z)the GEIGC Science and Technology Project in the framework of the“Research on Comprehensive Path Evaluation Methods and Practical Models for the Synergetic Development of Global Energy,Atmospheric Environment and Human Health”(No.SGGEIG00JYJS2100056).
文摘Climate change is one of the biggest health threats of the 21st century.Although China is the biggest developing country,with a large population and different climate types,its projections of large-scale heat-related excess mortality remain understudied.In particular,the effects of climate change on aging populations have not been well studied,and may result in significantly underestimation of heat effects.In this study,we took four climate change scenarios of Tier-1 in CMIP6,which were combinations of Shared Socioeconomic Pathways(SSPs)and Representative Concentration Pathways(RCPs).We used the exposure-response functions derived from previous studies combined with baseline age-specific non-accidental mortality rates to project heat-related excess mortality.Then,we employed the Logarithmic Mean Divisia Index(LMDI)method to decompose the impacts of climate change,population growth,and aging on heat-related excess mortality.Finally,we multiplied the heat-related Years of Life Lost(YLL)with the Value of a Statistical Life Year(VSLY)to quantify the economic burden of premature mortality.We found that the heat-related excess mortality would be concentrated in central China and in the densely populated south-eastern coastal regions.When aging is considered,heat-related excess mortality will become 2.8–6.7 times than that without considering aging in 2081–2100 under different scenarios.The contribution analysis showed that the effect of aging on heat-related deaths would be much higher than that of climate change.Our findings highlighted that aging would lead to a severe increase of heat-related deaths and suggesting that regional-specific policies should be formulated in response to heat-related risks.
基金Supported by European Union-NextGenerationEU,Through the National Recovery and Resilience Plan of the Republic of Bulgaria,No.BG-RRP-2.004-0008-C01.
文摘Time series analysis is a valuable tool in epidemiology that complements the classical epidemiological models in two different ways:Prediction and forecast.Prediction is related to explaining past and current data based on various internal and external influences that may or may not have a causative role.Forecasting is an exploration of the possible future values based on the predictive ability of the model and hypothesized future values of the external and/or internal influences.The time series analysis approach has the advantage of being easier to use(in the cases of more straightforward and linear models such as Auto-Regressive Integrated Moving Average).Still,it is limited in forecasting time,unlike the classical models such as Susceptible-Exposed-Infectious-Removed.Its applicability in forecasting comes from its better accuracy for short-term prediction.In its basic form,it does not assume much theoretical knowledge of the mechanisms of spreading and mutating pathogens or the reaction of people and regulatory structures(governments,companies,etc.).Instead,it estimates from the data directly.Its predictive ability allows testing hypotheses for different factors that positively or negatively contribute to the pandemic spread;be it school closures,emerging variants,etc.It can be used in mortality or hospital risk estimation from new cases,seroprevalence studies,assessing properties of emerging variants,and estimating excess mortality and its relationship with a pandemic.
文摘To obtain the influence of heat waves on death in the elderly, the influence of the heat waves in Nanjing in the summers (from June to August) of 2005-2008 on death among the elderly was analyzed by using statistical methods including generalized additive models. The results showed that the death toll over these four summers in Nanjing tended to increase;on an average 10.76% more males died than females, and the mortality rate of old people aged ≥65 accounted for 73.21% of all deaths. The mortality rate of older people rose with increasing maximum temperature. Furthermore, the average excess mortality rate caused by heat wave weather processes was 15.91%, while it was less affected by the duration of the heat wave. The death toll of the elderly increased with the increase in humidity, dropping of atmospheric pressure, and decrease of wind speed for 1°C increase of maximum temperature. Under the same humidity condition, atmospheric pressure, and wind speed, the death toll during heat wave days was higher than that occurring on other days, and heat waves increased the risk of death among the elderly by 26.6% (95% CI: 1.100 - 1.154). Daily mortality was mainly affected by the daily maximum temperature 1, 4, or 6 days later, particularly 4 days later. Heat wave was one of the principal factors, which caused the rise in death tolls in summer, and the elderly were most affected.
基金supported by The Netherlands Organization for Scientific Research VIDI(grant number:198.007).
文摘Background Conditional relative survival(CRS),the probability of survival given that an individual has already survived a certain period post-diagnosis,is a more clinically relevant measure for long-term survival than standard relative survival(RS).This study aims to evaluate the 5-year CRS among adolescent and young adult(AYA)breast cancer patients by age,tumor stage,and receptor subtype to guide disclosure periods for insurance.Methods Data of all females aged 18–39 years and diagnosed with invasive breast cancer between 2003 and 2021(n=13,075)were obtained from The Netherlands Cancer Registry(NCR).The five-year CRS was calculated annually up to 10 years post-diagnosis using a hybrid analysis approach.Results For the total AYA breast cancer study population the 5-year CRS exceeded 90%from diagnosis and increased beyond 95%7 years post-diagnosis.Patients aged 18–24 reached 95%9 years post-diagnosis,those aged 25–29 after 5 years,and those aged 30–34 and 35–39 after 8 years.For stage I,the 5-year CRS reached 95%from diagnosis,for stage II after 6 years,while the 5-year CRS for stages III and IV did not reach the 95%threshold during the 10-year follow-up.Triple-negative tumors exceeded 95%after 4 years,human epidermal growth factor receptor 2(HER2)positive tumors after 6 years,while hormone receptor(HR)positive tumors did not reach 95%.Conclusion Excess mortality among AYA breast cancer patients tends to be little(CRS 90%–95%)from diagnosis and becomes minimal(CRS>95%)over time compared to the general population.These results can enhance expectation management and inform policymakers,suggesting a shorter disclosure period.
