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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.
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.
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.
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.
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.
Seasonal influenza has been associated with a large number of deaths, both in China and globally [
Many studies have assessed the mortality burden of influenza with statistical models [
Guangzhou, a subtropical city in the western Pacific region of southern China (location N 23°8ʹ, E 113°17ʹ), is an international transportation hub with a permanent population of approximately 15 million (in 2018) and an area of 7434.4 km2. Free influenza vaccination has been available for older residents since 2021 in Guangzhou; however, the vaccination coverage rate has been unsatisfactory overall in China [
This study was approved by the Research Ethics Committee of Southern Medical University (NFYKDX-ER2022012). The need for informed consent was waived because the data were deidentified and aggregated.
Individual data for deaths occurring between January 5, 2015, and December 30, 2018, in Guangzhou were obtained from the Guangzhou Center for Disease Control and Prevention (CDC). Individual death information included the underlying cause of death, age at death, and sex. The daily number of deaths was aggregated. Here, we considered 5 cause-of-death groupings associated with influenza virus infection: all causes (International Statistical Classification of Diseases and Related Health Problems, 10th Revision [ICD-10] codes A00-Z99), respiratory and cardiovascular diseases (ICD-10 codes I00-I99 and J00-J99), respiratory disease (ICD-10 codes J00-J99), pneumonia and influenza (ICD-10 codes J10-J18), and cardiovascular disease (ICD-10 codes I00-I99).
The Guangzhou CDC also provided influenza surveillance data, including the weekly proportions of specimens testing positive for influenza A (H1N1), A (H3N2), B/Yamagata, and B/Victoria, and the weekly proportion of consultations for influenza-like illness (ILI), that is, a body temperature ≥38 °C with cough or sore throat, among outpatient visits at sentinel hospitals in Guangzhou.
Data on annual population size were obtained from the Public Security Bureau of Guangzhou Municipality. We collected data on daily mean temperature and relative humidity from the website of the China Meteorological Data Service Center [
We defined a weekly influenza virus activity proxy by multiplying the weekly proportion of consultations for ILI and the proportion of specimens testing positive for different subtypes and lineages, and then multiplying the resulting value by 1000 [
A quasi-Poisson regression model was applied to estimate the excess mortality associated with influenza for different cause-of-death groupings, age groups (<60 years, 60-79 years, ≥80 years, and all ages), and sex. The associations of death counts with influenza and temperature were determined using a DLNM [
where Yt and μt were the observed and expected number of deaths on day t, respectively. φ is the overdispersion parameter. The logarithm of population (Popt), with a fixed regression coefficient of 1, was used as an offset. The influenza activity proxy variables for A (H1N1), A (H3N2), B/Victoria, and B/Yamagata on day t were ProxyH1,t, ProxyH3,t, ProxyBV,t, and ProxyBY,t, respectively. Cross-basis Tʹt,l(.) was constructed for the activity proxy variable of each influenza subtype/lineage, assuming a linear relationship between influenza virus activity and population mortality [
In addition, we controlled the effect of absolute humidity (Humt) using a natural cubic spline with 4
We present the relative risk (RR) and cumulative RR of death associated with an increase of 10 units in the influenza virus activity proxy relative to an influenza activity proxy of 0 across a lag of 0 to 30 days. The daily number of excess deaths related to influenza was estimated as the difference between the estimated number of deaths given the observed influenza virus activity and the estimate given that the influenza virus did not circulate (ie, the influenza virus activity proxy was 0) [
To detect whether there was a sex difference in influenza-related EMRs, we divided the male EMRs by female EMRs to obtain the male-to-female excess mortality ratios (MFRs) and derived the corresponding 95% CIs using the delta method [
To check the robustness of the results, we conducted sensitivity analyses by (1) changing the maximum number of lag days for lag-response relationships between the death and activity proxies of each influenza subtype and lineage, as well as for the relationship between death and temperature; (2) changing the way we controlled the temporal trend in the mortality rate; (3) ignoring the classifications of influenza virus types and influenza B lineages; (4) applying different cross-basis matrices to temperature; and (5) including the influenza virus activity proxy and temperature at a lag of 7 days in the model (
There were 199,777 death certificates (86,440 for women and 113,337 for men; 34,229 for the 0-to-59-year age group, 73,552 for the 60-to-79-year age group, and 91,996 for the ≥80-year age group) included in this analysis, of which 105,998 were respiratory/cardiovascular disease deaths, 28,528 were respiratory disease deaths, and 12,255 were pneumonia/influenza deaths. In Guangzhou from 2015 to 2018, influenza viruses circulated every year. In 2015 and 2017, influenza activity peaked in the summer, while in 2016 and 2018, influenza activity was greater in the winter and early spring. A similar pattern was observed for the excess respiratory/cardiovascular disease mortality associated with influenza (
It was estimated that 2198 all-cause deaths, 1786 respiratory/cardiovascular disease deaths, 825 respiratory disease deaths, and 340 pneumonia/influenza deaths were attributable to influenza annually; correspondingly, the annual influenza-associated excess all-cause, respiratory/cardiovascular disease, respiratory disease, and pneumonia/influenza mortality rates were 25.06 (95% eCI 19.85-30.16), 20.36 (95% eCI 16.75-23.74), 9.41 (95% eCI 7.78-10.90) and 3.88 (95% eCI 2.80-4.84) per 100,000 persons, respectively (
The excess mortality due to various underlying causes associated with influenza varied across age groups. The EMR for each cause of death associated with influenza in people aged ≥80 years was higher than that in people aged 60 to 79 years. However, it should be noted that only influenza-related excess mortality due to respiratory/cardiovascular disease was statistically significant among deaths from all different causes in the 0-to-59-year age group. The EMRs for respiratory/cardiovascular disease for people aged 60 to 79 years and ≥80 years were 45.21 (95% eCI 33.31-56.74) and 452.63 (95% eCI 357.46-544.47) per 100,000 persons, respectively, which was higher than the EMR for people aged 0 to 59 years (91.50, 95% eCI 4.79-165.41). The burden in these two age groups represented 32.9% (2346/7142) and 63.7% (4549/7142) of the excess respiratory/cardiovascular disease deaths attributed to influenza, respectively (
Influenza activity and weekly influenza-associated excess respiratory and cardiovascular deaths in Guangzhou, China, from 2015 to 2018. (A) Influenza virus activity proxy (this proxy does not have units). (B) Weekly influenza-associated excess respiratory/cardiovascular deaths. The bars in B represent the estimates of excess influenza-related deaths per week and the shaded areas are the corresponding 95% empirical CIs. The influenza virus activity proxy was calculated by multiplying the weekly proportion of consultations for influenza-like illness and the proportion of specimens testing positive for different subtypes and lineages, and then multiplying the resulting value by 1000.
Average annual excess mortality rates associated with influenza by cause-of-death grouping and age group in Guangzhou, China, from 2015 to 2018.
Age groups (years) and cause of death | Deaths, n (95% eCIa) | Rate per 100,000 persons (95% eCI) | |
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|||
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All causes | 64.05 (–105.30 to 226.41) | 0.89 (–1.46 to 3.14) |
|
Respiratory/cardiovascular disease | 91.50 (4.79 to 165.41) | 1.27 (0.07 to 2.29) |
|
Respiratory disease | 32.42 (–0.99 to 56.29) | 0.45 (–0.01 to 0.78) |
|
Pneumonia/influenza | 16.80 (–13.76 to 35.73) | 0.23 (–0.19 to 0.49) |
|
Cardiovascular disease | 55.53 (–23.09 to 122.85) | 0.77 (–0.32 to 1.70) |
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|||
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All causes | 856.96 (621.47 to 1086.86) | 66.06 (47.91 to 83.79) |
|
Respiratory/cardiovascular disease | 586.48 (432.06 to 735.96) | 45.21 (33.31 to 56.74) |
|
Respiratory disease | 290.12 (223.20 to 344.15) | 22.37 (17.21 to 26.53) |
|
Pneumonia/influenza | 103.51 (60.04 to 136.67) | 7.98 (4.63 to 10.54) |
|
Cardiovascular disease | 283.58 (144.93 to 416.85) | 21.86 (11.17 to 32.13) |
≥ |
|||
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All causes | 1305.53 (996.43 to 1596.4) | 519.56 (396.54 to 635.31) |
|
Respiratory/cardiovascular disease | 1137.35 (898.22 to 1368.13) | 452.63 (357.46 to 544.47) |
|
Respiratory disease | 509.81 (384.01 to 626) | 202.89 (152.82 to 249.13) |
|
Pneumonia/influenza | 222.58 (140.17 to 293.36) | 88.58 (55.78 to 116.75) |
|
Cardiovascular disease | 619.02 (433.25 to 796.09) | 246.35 (172.42 to 316.82) |
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|||
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All causes | 2197.87 (1740.75 to 2644.78) | 25.06 (19.85 to 30.16) |
|
Respiratory/cardiovascular disease | 1785.47 (1469.03 to 2082.24) | 20.36 (16.75 to 23.74) |
|
Respiratory disease | 825.26 (682.51 to 955.75) | 9.41 (7.78 to 10.90) |
|
Pneumonia/influenza | 340.34 (245.92 to 424.18) | 3.88 (2.80 to 4.84) |
|
Cardiovascular disease | 940.06 (696.35 to 1171.28) | 10.72 (7.94 to 13.36) |
aeCI: empirical CI.
The difference in influenza-associated excess respiratory/cardiovascular disease mortality rate by sex was not statistically significant. However, the excess respiratory mortality was significantly higher in males than in females, with an MFR of 1.34 (95% CI 1.17-1.54). Conversely, the MFR of influenza-associated EMR for cardiovascular disease was 0.72 (95% CI 0.63-0.82;
Temporal trends of influenza virus activity varied by subtype and lineage (
Between 2015 and 2018, the predominant circulating influenza virus subtypes and lineages varied. Correspondingly, the EMRs per 100,000 persons for respiratory and cardiovascular disease associated with influenza A (H1N1), A (H3N2), B/Victoria, and B/Yamagata ranged between 0.21 (95% eCI –0.13 to 0.54) and 5.62 (95% eCI –2.74 to 13.19), between 0.15 (95% eCI 0.10-0.19) and 21.25 (95% eCI 16.61-25.59), between 0.32 (95% eCI 0.09-0.56) and 9.52 (95% eCI 2.58-16.29), and between 0.63 (95% eCI –0.62 to 1.77) and 10.84 (95% eCI 6.74-14.83), respectively (
The RR of respiratory/cardiovascular disease death associated with influenza virus subtypes/lineages changed with lag time. For influenza A (H1N1), the highest RR occurred on the current day, and there seemed to be a displacement effect during days 2 to 5. This effect lasted approximately 14 days. Similar patterns were observed in the RRs for influenza A (H3N2) and B/Yamagata. For B/Victoria, RR peaked at a lag of 3 days. The displacement effect was observed on days 5 to 13 (
Average annual excess mortality associated with influenza by cause-of-death grouping and sex in Guangzhou, China, from 2015-2018.
Underlying cause | Male | Female | Male-to-female excess mortality ratio (95% CI) | |||
|
Deaths, n (95% eCIa) | Rate per 100,000 persons (95% eCI) | Deaths, n (95% eCI) | Rate per 100,000 persons (95% eCI) |
|
|
All causes | 1060.79 (755.56-1358.70) | 24.12 (17.18-30.89) | 1132.64 (859.06-1385.33) | 25.91 (19.65-31.69) | 0.93 (0.86-1.01) | .09 |
Respiratory/ cardiovascular diseases | 876.90 (674.64-1071.51) | 19.94 (15.34-24.36) | 906.37 (716.96-1086.57) | 20.73 (16.40-24.85) | 0.96 (0.88-1.06) | .41 |
Respiratory diseases | 472.95 (362.98-571.77) | 10.75 (8.25-13.00) | 351.06 (263.27-428.41) | 8.03 (6.02-9.80) | 1.34 (1.17-1.54) | <.001 |
Pneumonia/ influenza | 177.27 (109.82-232.72) | 4.03 (2.50-5.29) | 162.02 (100.26-216.15) | 3.71 (2.29-4.94) | 1.09 (0.88-1.34) | .46 |
Cardiovascular diseases | 393.08 (227.15-553.88) | 8.94 (5.16-12.59) | 543.79 (375.64-705.39) | 12.44 (8.59-16.14) | 0.72 (0.63-0.82) | <.001 |
aeCI: empirical CI.
Annual influenza-associated excess respiratory/cardiovascular mortality rates and influenza activity in Guangzhou, China, from 2015 to 2018. (A) Annual influenza-associated excess respiratory/cardiovascular mortality rates per 100,000 persons by influenza subtype/lineage. (B) Influenza virus activity proxies by influenza subtype/lineage (this proxy does not have units). The dots in A indicate point estimates of excess respiratory/cardiovascular mortality, while vertical line segments indicate the corresponding 95% empirical CIs.
Excess respiratory and cardiovascular mortality rates associated with different influenza subtypes and lineages.
Influenza type or lineage and age groups (years) | Rate per 100,000 persons (95% eCIa) | |
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0-59 | 1.29 (0.07 to 2.32) |
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60-79 | 5.74 (–8.61 to 19.15) |
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≥80 | 55.75 (–60.87 to 166.10) |
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All ages | 2.83 (–1.26 to 6.71) |
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0-59 | 0.33 (–0.24 to 0.85) |
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60-79 | 20.22 (14.56 to 25.63) |
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≥80 | 180.15 (130.75 to 227.38) |
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All ages | 8.47 (6.60 to 10.30) |
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||
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0-59 | –0.47 (–1.59 to 0.45) |
|
60-79 | 7.36 (–2.87 to 16.65) |
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≥80 | 88.82 (6.18 to 168.44) |
|
All ages | 3.68 (0.81 to 6.49) |
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0-59 | 0.02 (–0.78 to 0.74) |
|
60-79 | 12.87 (4.60 to 20.74) |
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≥80 | 138.21 (70.53 to 204.40) |
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All ages | 5.81 (3.35 to 8.25) |
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0-59 | 1.27 (0.07 to 2.29) |
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60-79 | 45.21 (33.31 to 56.74) |
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≥80 | 452.63 (357.46 to 544.47) |
|
All ages | 20.36 (16.75 to 23.74) |
aeCI: empirical CI.
Relative risks and cumulative relative risks of death associated with influenza subtypes/lineages. (A) Relative risks of death on each single day and (B) cumulative relative risks of death associated with an increase of 10 units in influenza virus activity proxy for influenza A (H1N1), A (H3N2), B/Victoria, and B/Yamagata. The solid lines represent the estimates of relative risk over time, and the shaded areas are the corresponding 95% empirical CIs.
Estimates of influenza-associated excess respiratory and cardiovascular disease mortality rates did not change significantly after changing the method of controlling for the temporal trend in mortality rate, changing the maximum lag, or the function used for the lag-response dimension in the cross-basis matrices of influenza and temperature, ignoring the classification of influenza B lineages (
In this study, we report excess mortality associated with influenza and its subtypes/lineages from 2015 to 2018 in Guangzhou, a subtropical city of China. We estimate that 1786 respiratory/cardiovascular disease deaths were attributable to influenza annually, accounting for 6.7% (7142/105,998) of all respiratory/cardiovascular disease deaths. We found that influenza-associated excess mortality was higher in the elderly, which is consistent with the conclusions of other studies [
Variations were observed in the estimates of influenza-associated excess mortality by subtype/lineage. The mortality burden of influenza B/Yamagata was higher than that of B/Victoria, which is consistent with previous studies [
We also noted that the mortality burden of influenza virus subtypes and lineages differed according to age group. For people aged ≥60 years, the fatality rate caused by influenza A (H3N2) was higher than that of A (H1N1), B/Victoria, and B/Yamagata. The risk of influenza virus infection and severe complications, including death, is increased by the stronger antigenic drift and virulence of influenza A (H3N2) [
Consistently with previous studies performed in Shanghai, we did not find a statistically significant difference in influenza-related excess respiratory/cardiovascular disease deaths between males and females [
Our estimate of average annual influenza-associated excess all-cause mortality (25.06 per 100,000 individuals) was higher than that of previous studies in countries/cities and time periods including Greece from 2013 to 2017 (23.60) [
Previous studies have estimated excess mortality based on the association between influenza activity proxies at a lag of 0, 1, or 2 weeks and mortality [
This study had some limitations. First, we did not use age-specific influenza virus activity proxies to estimate influenza-associated excess mortality, and a proxy for all-age activity was used instead. Second, the study period was relatively short (ie, 4 years), which may have influenced the comparison of the mortality burden of different influenza subtypes and lineages. This is mainly because the virology data included samples that tested positive for influenza B, but information on lineage was unavailable before 2015. Data from 2019 onwards were not collected. Moreover, we did not consider the influence of factors such as respiratory syncytial virus and vaccination coverage on the estimate of influenza-associated excess mortality, since such data were not available.
In conclusion, after considering the observed mortality displacement, influenza was associated with substantial mortality in Guangzhou, occurring predominantly in the elderly. 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, and the underlying mechanisms need to be investigated in further 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 individuals), behavioral campaigns, and treatment strategies.
Additional details of the methods.
Average annual excess respiratory mortality rates related to influenza by sex and age.
Average annual excess cardiovascular mortality rates related to influenza by sex and age.
Comparison of average annual excess respiratory and cardiovascular mortality rates attributable to all influenza estimated from different models in the sensitivity analysis.
Center for Disease Control and Prevention
distributed-lag nonlinear model
excess mortality rate
influenza-like illness
male-to-female excess mortality ratio
relative risk
We thank the staff members of the Guangzhou Center for Disease Control and Prevention for administrative work and data collection. This work was supported by the National Natural Science Foundation of China (grants 82003555 and 81903406).
The data sets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
CQO supervised the study. L Li, L Luo, and CQO conceived the study. ZLY, L Luo, WHL, ZY, CS, and BWM collected the data. L Li, ZLY, JY, and PHC analyzed the data. L Li and ZLY wrote the first draft of the manuscript. All authors contributed to the interpretation of the results and edited the manuscript.
None declared.