State-level estimates of excess hospitalizations and deaths associated with influenza

Construction and validation of a covariate-based model for district-level estimation of excess deaths due to COVID-19 in India

Background

Different statistical approaches for estimating excess deaths due to coronavirus disease 2019 (COVID-19) pandemic have led to varying estimates. In this study, we developed and validated a covariate-based model (CBM) with imputation for prediction of district-level excess deaths in India.

Methods

We used data extracted from deaths registered under the Civil Registration System for 2015-19 for 684 of 713 districts in India to estimate expected deaths for 2020 through a negative binomial regression model (NBRM) and to calculate excess observed deaths. Specifically, we used 15 covariates across four domains (state, health system, population, COVID-19) in a zero inflated NBRM to identify covariates significantly (P < 0.05) associated with excess deaths estimate in 460 districts. We then validated this CBM in 140 districts by comparing predicted and estimated excess. For 84 districts with missing covariates, we validated the imputation with CBM by comparing estimated with predicted excess deaths. We imputed covariate data to predict excess deaths for 29 districts which did not have data on deaths.

Results

The share of elderly and urban population, the under-five mortality rate, prevalence of diabetes, and bed availability were significantly associated with estimated excess deaths and were used for CBM. The mean of the CBM-predicted excess deaths per district (x̄ = 989, standard deviation (SD) = 1588) was not significantly different from the estimated one (x̄ = 1448, SD = 3062) (P = 0.25). The estimated excess deaths (n = 67 540; 95% confidence interval (CI) = 35 431, 99 648) were similar to the predicted excess death (n = 64 570; 95% CI = 54 140, 75 000) by CBM with imputation. The total national estimate of excess deaths for all 713 districts was 794 989 (95% CI = 664 895, 925 082).

Conclusions

A CBM with imputation can be used to predict excess deaths in an appropriate context.

Uncovering the burden of Influenza in children in Portugal, 2008-2018

BACKGROUND

Despite their higher risk of developing severe disease, little is known about the burden of influenza in Portugal in children aged < 5 years old. This study aims to cover this gap by estimating the clinical and economic burden of severe influenza in children, in Portugal, during ten consecutive influenza seasons (2008/09-2017/18).

METHODS

We reviewed hospitalizations in children aged < 5 years old using anonymized administrative data covering all public hospitals discharges in mainland Portugal. The burden of hospitalization and in-hospital mortality directly coded as due to influenza was supplemented by the indirect burden calculated from excess hospitalization and mortality (influenza-associated), estimated for four groups of diagnoses (pneumonia or influenza, respiratory, respiratory or cardiovascular, and all-cause), through cyclic regression models integrating the incidence of influenza. Means were reported excluding the H1N1pdm09 pandemic (2009/10).

RESULTS

The mean annual number of hospitalizations coded as due to influenza was 189 (41.3 cases per 100,000 children aged < 5 years old). Hospitalization rates decreased with increasing age. Nine-in-ten children were previously healthy, but the presence of comorbidities increased with age. Children stayed, on average, 6.1 days at the hospital. Invasive mechanical ventilation was used in 2.4% of hospitalizations and non-invasive in 3.1%. Influenza-associated excess hospitalizations between 2008 and 2018 were estimated at 1,850 in pneumonia or influenza, 1,760 in respiratory, 1,787 in respiratory or cardiovascular, and 1,879 in all-cause models. A total of 95 influenza-associated excess deaths were estimated in all-cause, 14 in respiratory or cardiovascular, and 9 in respiratory models. Over ten years, influenza hospitalizations were estimated to have cost the National Health Service at least €2.9 million, of which 66.5% from healthy children.

CONCLUSIONS

Influenza viruses led to a high number of hospitalizations in children. Most were previously healthy. Results should lead to a reflection on the adequate preventive measures to protect this age group.

Excess hospitalizations and mortality associated with seasonal influenza in Spain, 2008-2018

BACKGROUND

Influenza may trigger complications, particularly in at-risk groups, potentially leading to hospitalization or death. However, due to lack of routine testing, influenza cases are infrequently coded with influenza-specific diagnosis. Statistical models using influenza activity as an explanatory variable can be used to estimate annual hospitalizations and deaths associated with influenza. Our study aimed to estimate the clinical and economic burden of severe influenza in Spain, considering such models.

METHODS

The study comprised ten epidemic seasons (2008/2009-2017/2018) and used two approaches: (i) a direct method of estimating the seasonal influenza hospitalization, based on the number of National Health Service hospitalizations with influenza-specific International Classification of Diseases (ICD) codes (ICD-9: 487-488; ICD-10: J09-J11), as primary or secondary diagnosis; (ii) an indirect method of estimating excess hospitalizations and deaths using broader groups of ICD codes in time-series models, computed for six age groups and four groups of diagnoses: pneumonia or influenza (ICD-9: 480-488, 517.1; ICD-10: J09-J18), respiratory (ICD-9: 460-519; ICD-10: J00-J99), respiratory or cardiovascular (C&R, ICD-9: 390-459, 460-519; ICD-10: I00-I99, J00-J99), and all-cause. Means, excluding the H1N1pdm09 pandemic (2009/2010), are reported in this study.

RESULTS

The mean number of hospitalizations with a diagnosis of influenza per season was 13,063, corresponding to 28.1 cases per 100,000 people. The mean direct annual cost of these hospitalizations was €45.7 million, of which 65.7% was generated by patients with comorbidities. Mean annual influenza-associated C&R hospitalizations were estimated at 34,894 (min: 16,546; max: 52,861), corresponding to 75.0 cases per 100,000 (95% confidence interval [CI]: 63.3-86.3) for all ages and 335.3 (95% CI: 293.2-377.5) in patients aged ≥ 65 years. We estimate 3.8 influenza-associated excess C&R hospitalizations for each hospitalization coded with an influenza-specific diagnosis in patients aged ≥ 65 years. The mean direct annual cost of the estimated excess C&R hospitalizations was €142.9 million for all ages and €115.9 million for patients aged ≥ 65 years. Mean annual influenza-associated all-cause mortality per 100,000 people was estimated at 27.7 for all ages.

CONCLUSIONS

Results suggest a relevant under-detected burden of influenza mostly in the elderly population, but not neglectable in younger people.

Estimating mortality associated with seasonal influenza among adults aged 65 years and above in China from 2011 to 2016: A systematic review and model analysis

BACKGROUND

Estimation of influenza disease burden is crucial for optimizing intervention strategies against seasonal influenza. This study aimed to estimate influenza-associated excess respiratory and circulatory (R&C) and all-cause (AC) mortality among older adults aged 65 years and above in mainland China from 2011 to 2016.

METHODS

Through a systematic review, we collected influenza-associated excess R&C and AC mortality data of older adults aged 65 years and above for specific cities/provinces in mainland China. Generalized linear models were fitted to estimate the corresponding excess mortality for older adults by province and nationwide, accounting for the potential variables of influenza virus activity, demography, economics, meteorology, and health service. All statistical analyses were conducted using R software.

RESULTS

A total of 9154 studies were identified in English and Chinese databases, and 11 (0.1%) were included in the quantitative synthesis after excluding duplicates and screening the title, abstract, and full text. Using a generalized linear model, the estimates of annual national average influenza-associated excess R&C and AC mortality among older adults aged 65 years and above were 111.8 (95% CI: 92.8-141.1) and 151.6 (95% CI: 127.6-179.3) per 100,000 persons, respectively. Large variations in influenza-associated excess R&C and AC mortality among older adults were observed among 30 provinces.

CONCLUSIONS

Influenza was associated with substantial excess R&C and AC mortality among older adults aged 65 years and above in China from 2011 to 2016. This analysis provides valuable evidence for the introduction of the influenza vaccine into the National Immunization Program for the elderly in China.

Excess hospitalizations and mortality associated with seasonal influenza in Portugal, 2008-2018

Background

Influenza can have a domino effect, triggering severe conditions and leading to hospitalization or even death. Since influenza testing is not routinely performed, statistical modeling techniques are increasingly being used to estimate annual hospitalizations and deaths associated with influenza, to overcome the known underestimation from registers coded with influenza-specific diagnosis. The aim of this study was to estimate the clinical and economic burden of severe influenza in Portugal.

Methods

The study comprised ten epidemic seasons (2008/09–2017/18) and used two approaches: (i) a direct method of estimating the seasonal influenza hospitalization incidence, based on the number of National Health Service hospitalizations with influenza-specific International Classification of Diseases (ICD) codes (ICD-9: 487–488; ICD-10: J09-J11), as primary or secondary diagnosis; (ii) an indirect method of estimating excess hospitalizations and deaths using broader groups of ICD codes in time-series models, computed for six age groups and four groups of diagnoses: pneumonia or influenza (ICD-9: 480–488, 517.1; ICD-10: J09–J18), respiratory (ICD-9: 460–519; ICD-10: J00–J99), respiratory or cardiovascular (R&C, ICD-9: 390–459, 460–519; ICD-10: I00–I99, J00–J99), and all-cause. Means are reported excluding the H1N1pdm09 pandemic (2009/10).

Results

The mean number of hospitalizations coded as due to influenza per season was 1,207, resulting in 11.6 cases per 100,000 people. The mean direct annual cost of these hospitalizations was €3.9 million, of which 78.6% was generated by patients with comorbidities. Mean annual influenza-associated R&C hospitalizations were estimated at 5356 (min: 456; max: 8776), corresponding to 51.5 cases per 100,000 (95% CI: 40.9–62.0) for all age groups and 199.6 (95% CI: 163.9–235.8) for the population aged ≥ 65 years. The mean direct annual cost of the estimated excess R&C hospitalizations was €15.2 million for all age groups and €12.8 million for the population aged ≥ 65 years. Mean annual influenza-associated all-cause deaths per 100,000 people were estimated at 22.7 for all age groups.

Conclusions

The study findings suggest that there is an under-detection of influenza in the Portuguese population. A high burden of severe influenza remains to be addressed, not only in the elderly population but also in younger people.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07713-8.

Estimating the burden of influenza-related and associated hospitalizations and deaths in France: An eight-season data study, 2010-2018

Background

In France, each year, influenza viruses are responsible for seasonal epidemics leading to 2–6 million cases. Influenza can cause severe disease that may lead to hospitalization or death. As severe disease may be due to the virus itself or to disease complications, estimating the burden of severe influenza is complex. The present study aimed at estimating the epidemiological and economic burden of severe influenza in France during eight consecutive influenza seasons (2010–2018).

Methods

Influenza‐related hospitalization and mortality data and patient characteristics were taken from the French hospital information database, PMSI. An ecological approach using cyclic regression models integrating the incidence of influenza syndrome from the Sentinelles network supplemented the PMSI data analysis in estimating excess hospitalization and mortality (CépiDc—2010–2015) and medical costs.

Results

Each season, the average number of influenza‐related hospitalizations was 18,979 (range: 8627–44,024), with an average length of stay of 8 days. The average number of respiratory hospitalizations indirectly related with influenza (i.e., influenza associated) was 31,490 (95% confidence interval [CI]: 24,542–39,012), with an average cost of €141 million (range: 54–217); 70% of these hospitalizations and 77% of their costs concerned individuals ≥65 years of age (65+). More than 90% of excess mortality was in 65+ subjects.

Conclusions

The combination of two complementary approaches allowed estimation of both influenza‐related and associated hospitalizations and deaths and their burden in France, showing the substantial impact of complications. The present study highlighted the major public health burden of influenza and its severe complications, especially in 65+ subjects.

Estimated Cardiorespiratory Hospitalizations Attributable to Influenza and Respiratory Syncytial Virus Among Long-term Care Facility Residents

IMPORTANCE

Older adults residing in long-term care facilities (LTCFs) are at a high risk of being infected with respiratory viruses, such as influenza and respiratory syncytial virus (RSV). Although these infections commonly have many cardiorespiratory sequelae, the national burden of influenza- and RSV-attributable cardiorespiratory events remains unknown for the multimorbid and vulnerable LTCF population.

OBJECTIVE

To estimate the incidence of cardiorespiratory hospitalizations that were attributable to influenza and RSV among LTCF residents and to quantify the economic burden of these hospitalizations on the US health care system by estimating their associated cost and length of stay.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study used national Medicare Provider Analysis and Review inpatient claims and Minimum Data Set clinical assessments for 6 respiratory seasons (2011-2017). Long-stay residents of LTCFs were identified as those living in the facility for at least 100 days (index date), aged 65 years or older, and with 6 months of continuous enrollment in Medicare Part A were included. Follow-up occurred from the resident's index date until the first hospitalization, discharge from the LTCF, disenrollment from Medicare, death, or the end of the study. Residents could re-enter the sample; thus, long-stay episodes of care were identified. Data analysis was performed between January 1 and September 30, 2020.

EXPOSURES

Seasonal circulating pandemic 2009 influenza A(H1N1), human influenza A(H3N2), influenza B, and RSV.

MAIN OUTCOMES AND MEASURES

Cardiorespiratory hospitalizations (eg, asthma exacerbation, heart failure) were identified using primary diagnosis codes. Influenza- and RSV-attributable cardiorespiratory events were estimated using a negative binomial regression model adjusted for weekly circulating influenza and RSV testing data. Length of stay and costs of influenza- and RSV-attributable events were then estimated.

RESULTS

The study population comprised 2 909 106 LTCF residents with 3 138 962 long-stay episodes and 5 079 872 person-years of follow-up. Overall, 10 939 (95% CI, 9413-12 464) influenza- and RSV-attributable cardiorespiratory events occurred, with an incidence of 215 (95% CI, 185-245) events per 100 000 person-years. The cost of influenza- and RSV-attributable cardiorespiratory events was $91 055 393 (95% CI, $77 885 316-$104 225 470), and the length of stay was 56 858 (95% CI, 48 757-64 968) days.

CONCLUSIONS AND RELEVANCE

This study found that many cardiorespiratory hospitalizations among LTCF residents in the US were attributable to seasonal influenza and RSV. To minimize the burden these events place on the health care system and residents of LTCFs and to prevent virus transmission, additional preventive measures should be implemented.

Influence of atmospheric parameters on human mortality data at different geographical levels

Human mortality data are often modeled using a demographic approach as a function of time. This approach does not present an adequate fit model for the number of deaths with great variability. For this reason, additional information (social, economic and environmental) is required for complementing and improving demographic modelling. This article evaluated the association between human mortality data (segregated by age and sex) with meteorological and air pollutant covariates at three geographical levels: country, macro-climate regions and county. The modelling was based on a generalized linear modelling framework and takes into account the common characteristic of overdispersion in human mortality data through the application of negative binomial distribution. The proposed approach improved the dynamic behavior of the Farrington-like model (basic demographic model) and took into account the extreme meteorological and natural air pollution events. Notably, the proposed modelling worked well in cases where the amount of data was scarce.

Influenza-associated disease burden in mainland China: a systematic review and meta-analysis

Influenza causes substantial morbidity and mortality. Many original studies have been carried out to estimate disease burden of influenza in mainland China, while the full disease burden has not yet been systematically reviewed. We did a systematic review and meta-analysis to assess the burden of influenza-associated mortality, hospitalization, and outpatient visit in mainland China. We searched 3 English and 4 Chinese databases with studies published from 2005 to 2019. Studies reporting population-based rates of mortality, hospitalization, or outpatient visit attributed to seasonal influenza were included in the analysis. Fixed-effects or random-effects model was used to calculate pooled estimates of influenza-associated mortality depending on the degree of heterogeneity. Meta-regression was applied to explore the sources of heterogeneity. Publication bias was assessed by funnel plots and Egger’s test. We identified 30 studies eligible for inclusion with 17, 8, 5 studies reporting mortality, hospitalization, and outpatient visit associated with influenza, respectively. The pooled influenza-associated all-cause mortality rates were 14.33 and 122.79 per 100,000 persons for all ages and ≥ 65 years age groups, respectively. Studies were highly heterogeneous in aspects of age group, cause of death, statistical model, geographic location, and study period, and these factors could explain 60.14% of the heterogeneity in influenza-associated mortality. No significant publication bias existed in estimates of influenza-associated all-cause mortality. Children aged < 5 years were observed with the highest rates of influenza-associated hospitalizations and ILI outpatient visits. People aged ≥ 65 years and < 5 years contribute mostly to mortality and morbidity burden due to influenza, which calls for targeted vaccination policy for older adults and younger children in mainland China.

Estimation of Excess Deaths Associated With the COVID-19 Pandemic in the United States, March to May 2020

IMPORTANCE

Efforts to track the severity and public health impact of coronavirus disease 2019 (COVID-19) in the United States have been hampered by state-level differences in diagnostic test availability, differing strategies for prioritization of individuals for testing, and delays between testing and reporting. Evaluating unexplained increases in deaths due to all causes or attributed to nonspecific outcomes, such as pneumonia and influenza, can provide a more complete picture of the burden of COVID-19.

OBJECTIVE

To estimate the burden of all deaths related to COVID-19 in the United States from March to May 2020.

DESIGN, SETTING, AND POPULATION

This observational study evaluated the numbers of US deaths from any cause and deaths from pneumonia, influenza, and/or COVID-19 from March 1 through May 30, 2020, using public data of the entire US population from the National Center for Health Statistics (NCHS). These numbers were compared with those from the same period of previous years. All data analyzed were accessed on June 12, 2020.

MAIN OUTCOMES AND MEASURES

Increases in weekly deaths due to any cause or deaths due to pneumonia/influenza/COVID-19 above a baseline, which was adjusted for time of year, influenza activity, and reporting delays. These estimates were compared with reported deaths attributed to COVID-19 and with testing data.

RESULTS

There were approximately 781 000 total deaths in the United States from March 1 to May 30, 2020, representing 122 300 (95% prediction interval, 116 800-127 000) more deaths than would typically be expected at that time of year. There were 95 235 reported deaths officially attributed to COVID-19 from March 1 to May 30, 2020. The number of excess all-cause deaths was 28% higher than the official tally of COVID-19-reported deaths during that period. In several states, these deaths occurred before increases in the availability of COVID-19 diagnostic tests and were not counted in official COVID-19 death records. There was substantial variability between states in the difference between official COVID-19 deaths and the estimated burden of excess deaths.

CONCLUSIONS AND RELEVANCE

Excess deaths provide an estimate of the full COVID-19 burden and indicate that official tallies likely undercount deaths due to the virus. The mortality burden and the completeness of the tallies vary markedly between states.

COVID-19 Preparedness Among Emergency Departments: A Cross-Sectional Study in France

Objectives:

The aim of this study was to evaluate hospital and emergency department (ED) preparedness in France facing the coronavirus disease 2019 (COVID-19) rapid growth epidemic-phase, and to determine the link between preparedness and responsiveness.

Methods:

In this cross-sectional study, from March 7 to March 11, 2020, all heads of ED departments in France were contacted to answer an electronic survey, including 23 questions. Quality, Organization, Training, Resources, Management, Interoperability, and Responsiveness were evaluated by calculating scores (10 points). Multivariate analysis of variance was used to compare scores. Spearman’s correlation coefficient and multifaceted regression analysis were performed between Responsiveness and dimensions scores.

Results:

A total of 287 of 636 French EDs were included (45.1%). Calculated scores showed (median): Quality 5.38; Organization 6.4; Training 4.6; Resources 4.13; Management 2.38; Interoperability 4.0; Responsiveness 6.25; seasonal influenza score was 5. Significant differences between scores as a function of hospital and ED main characteristics were found. Furthermore, we found significant correlations (P < 0.01) between Responsiveness and all preparedness dimensions. Organization (adjusted-R² 0.2897), Management (aR² 0.321), and Interoperability (aR² 0.422) were significantly associated with Responsiveness.

Conclusions:

Preparedness in all its dimensions is low, indicating vulnerability. Preparedness and responsiveness face a certain and ongoing risk are close linked, and that Organizational, Management, and Interoperability dimensions are main determinants.

Estimating the early death toll of COVID-19 in the United States

Background

Efforts to track the severity and public health impact of the novel coronavirus, COVID-19, in the US have been hampered by testing issues, reporting lags, and inconsistency between states. Evaluating unexplained increases in deaths attributed to broad outcomes, such as pneumonia and influenza (P&I) or all causes, can provide a more complete and consistent picture of the burden caused by COVID-19.

Methods

We evaluated increases in the occurrence of deaths due to P&I above a seasonal baseline (adjusted for influenza activity) or due to any cause across the United States in February and March 2020. These estimates are compared with reported deaths due to COVID-19 and with testing data.

Results

There were notable increases in the rate of death due to P&I in February and March 2020. In a number of states, these deaths pre-dated increases in COVID-19 testing rates and were not counted in official records as related to COVID-19. There was substantial variability between states in the discrepancy between reported rates of death due to COVID-19 and the estimated burden of excess deaths due to P&I. The increase in all-cause deaths in New York and New Jersey is 1.5-3 times higher than the official tally of COVID-19 confirmed deaths or the estimated excess death due to P&I.

Conclusions

Excess P&I deaths provide a conservative estimate of COVID-19 burden and indicate that COVID-19-related deaths are missed in locations with inadequate testing or intense pandemic activity.

State-level estimates of excess hospitalizations and deaths associated with influenza

Background

National estimates of influenza burden may not reflect state‐level influenza activity, and local surveillance may not capture the full burden of influenza.

Methods

To provide state‐level information about influenza burden, we estimated excess pneumonia and influenza (P&I) and respiratory and circulatory (R&C) hospitalizations and deaths in Colorado from local hospital discharge records, death certificates, and influenza virus surveillance using negative binomial models.

Results

From July 2007 to June 2016, influenza was associated with an excess of 17 911 P&I hospitalizations (95%CI: 15 227, 20 354), 30 811 R&C hospitalizations (95%CI: 24 344, 37 176), 1,064 P&I deaths (95%CI: 757, 1298), and 3828 R&C deaths (95%CI: 2060, 5433). There was a large burden of influenza A(H1N1) among persons aged 0‐64 years, with high median seasonal rates of excess hospitalization among persons aged 0‐4 years. Persons aged ≥65 years experienced the largest numbers and highest median seasonal rates of excess hospitalization and death associated with influenza A (H3N2). The burden of influenza B was generally lower, with elevated median seasonal rates of excess hospitalization among persons aged 0‐4 years and ≥65 years.

Conclusions

These findings complement existing influenza surveillance. Periodic state‐level estimates of influenza disease burden may be useful for setting state public health priorities and planning prevention and control initiatives.