Estimation of influenza incidence and analysis of epidemic characteristics from 2009 to 2022 in Zhejiang Province, China

Epidemic patterns of the different influenza virus types and subtypes/lineages for 10 years in Chongqing, China, 2010-2019

To optimize seasonal influenza control and prevention programs in regions with potentially complicated seasonal patterns. Descriptive epidemiology was used to analyze the etiology of influenza, and chi-square tests were used to compare the epidemic patterns among different influenza virus types and subtypes/lineages. From January 2010 to December 2019, a total of 63,626 ILI cases were reported in Chongqing and 14,136 (22.22%) were laboratory-confirmed influenza cases. The proportions of specimens positive for influenza A and influenza B were 13.32% (8,478/63,626) and 8.86% (5,639/63,626), respectively. The proportion of positive specimens for influenza A reached the highest in winter (23.33%), while the proportion of positive specimens for influenza B reached the highest in spring (11.88%). Children aged 5-14 years old had the highest proportion of positive specimens for influenza. The influenza virus types/subtypes positive was significantly different by seasons and age groups (P<.001), but not by gender (p = .436). The vaccine strains were matched to the circulating influenza virus strains in all other years except for 2018 (vaccine strain was B/Colorado/06/2017; circulating strain was B/Yamagata). The study showed significant variations in epidemic patterns, including seasonal epidemic period and age distributions, among different influenza types, subtypes/lineages in Chongqing. Influenza vaccines matched to the circulating influenza virus strain in nine of the ten years. To prevent and mitigate the influenza outbreaks in this area, high risk population, especially children aged 5-14 years, are encouraged to get vaccinated against influenza before the epidemic seasons.

Effectiveness of inactivated influenza vaccine against laboratory-confirmed influenza among Chinese elderly: a test-negative design

BACKGROUND

Evidence on the effectiveness of influenza vaccination in the elderly is limited, and results are controversial. There are also few reports from China.

METHODS

We conducted a test-negative case-control study design to estimate influenza vaccine effectiveness (VE) against laboratory-confirmed influenza-associated visits among elderly (aged ≥ 60 years) across four influenza seasons in Ningbo, China, from 2018 to 19 to 2021-22. Influenza-positive cases and negative controls were randomly matched in a 1:1 ratio according to age, sex, hospital, and date of influenza testing. We used logistic regression models to compare vaccination odds ratios (ORs) in cases to controls. We calculated the VE as [100% × (1-adjusted OR)] and calculated the 95% confidence interval (CI) around the estimate.

RESULTS

A total of 30,630 elderly patients tested for influenza with virus nucleic acid or antigen during the study period. After exclusions, we included 1 825 influenza-positive cases and 1 825 influenza-negative controls. Overall, the adjusted VE for influenza-related visits was 63.5% (95% CI, 56.3-69.5%), but varied by season. Influenza VE was 59.8% (95% CI, 51.5-66.7%) for influenza A and 89.6% (95% CI, 77.1-95.3%) for influenza B. The VE for ages 60-69 and 70-79 was 65.2% (95% CI, 55.4-72.9%) and 69.8% (95% CI, 58.7-77.9%), respectively, but only 45.4% (95% CI, 6.2-68.2%) for ages 80 and over.

CONCLUSIONS

Standard-dose inactivated influenza vaccine has shown good protection in the elderly in China. However, protection may not be satisfactory in people aged 80 years and older.

Epidemiological features of seasonal influenza transmission among 11 climate zones in Chinese Mainland

BACKGROUND

Previous studies provided some evidence of meteorological factors influence seasonal influenza transmission patterns varying across regions and latitudes. However, research on seasonal influenza activities based on climate zones are still in lack. This study aims to utilize the ecological-based Köppen Geiger climate zones classification system to compare the spatial and temporal epidemiological characteristics of seasonal influenza in Chinese Mainland and assess the feasibility of developing an early warning system.

METHODS

Weekly influenza cases number from 2014 to 2019 at the county and city level were sourced from China National Notifiable Infectious Disease Report Information System. Epidemic temporal indices, time series seasonality decomposition, spatial modelling theories including Moran's I and local indicators of spatial association were applied to identify the spatial and temporal patterns of influenza transmission.

RESULTS

All climate zones had peaks in Winter-Spring season. Arid, desert, cold (BWk) showed up the first peak. Only Tropical, savannah (Aw) and Temperate, dry winter with hot summer (Cwa) zones had unique summer peak. Temperate, no dry season and hot summer (Cfa) zone had highest average incidence rate (IR) at 1.047/100,000. The Global Moran's I showed that average IR had significant clustered trend (z = 53.69, P < 0.001), with local Moran's I identified high-high cluster in Cfa and Cwa. IR differed among three age groups between climate zones (0-14 years old: F = 26.80, P < 0.001; 15-64 years old: F = 25.04, P < 0.001; Above 65 years old: F = 5.27, P < 0.001). Age group 0-14 years had highest average IR in Cwa and Cfa (IR = 6.23 and 6.21) with unique dual peaks in winter and spring season showed by seasonality decomposition.

CONCLUSIONS

Seasonal influenza exhibited distinct spatial and temporal patterns in different climate zones. Seasonal influenza primarily emerged in BWk, subsequently in Cfa and Cwa. Cfa, Cwa and BSk pose high risk for seasonal influenza epidemics. The research finds will provide scientific evidence for developing seasonal influenza early warning system based on climate zones.

Scaling law characteristics and spatiotemporal multicomponent analysis of syphilis from 2016 to 2022 in Zhejiang Province, China

Background

Syphilis has caused epidemics for hundreds of years, and the global syphilis situation remains serious. The reported incidence rate of syphilis in Zhejiang Province has ranked first in the province in terms of notifiable infectious diseases for many years and is the highest in China. This study attempts to use the scaling law theory to study the relationship between population size and different types of syphilis epidemics, while also exploring the main driving factors affecting the incidence of syphilis in different regions.

Methods

Data on syphilis cases and affected populations at the county level were obtained from the China Disease Control and Prevention Information System. The scaling relationship between different stages of syphilis and population size was explained by scaling law. The trend of the incidence from 2016 to 2022 was tested by the joinpoint regression. The index of distance between indices of simulation and observation (DISO) was applied to evaluate the overall performance of joinpoint regression model. Furthermore, a multivariate time series model was employed to identify the main driving components that affected the occurrence of syphilis at the county level. The p value less than 0.05 or confidence interval (CI) does not include 0 represented statistical significance for all the tests.

Results

From 2016 to 2022, a total of 204,719 cases of syphilis were reported in Zhejiang Province, including 2 deaths, all of which were congenital syphilis. Latent syphilis accounted for 79.47% of total syphilis cases. The annual percent change (APCs) of all types of syphilis, including primary syphilis, secondary syphilis, tertiary syphilis, congenital syphilis and latent syphilis, were - 21.70% (p < 0.001, 95% CI: -26.70 to -16.30), -16.80% (p < 0.001, 95% CI: -20.30 to -13.30), -8.70% (p < 0.001, 95% CI: -11.30 to -6.00), -39.00% (p = 0.001, 95% CI: -49.30 to -26.60) and - 7.10% (p = 0.008, 95% CI: -11.20 to -2.80), respectively. The combined scaling exponents of primary syphilis, secondary syphilis, tertiary syphilis, congenital syphilis and latent syphilis based on the random effects model were 0.95 (95% CI: 0.88 to 1.01), 1.14 (95% CI: 1.12 to 1.16), 0.43 (95% CI: 0.37 to 0.49), 0.0264 (95% CI: -0.0047 to 0.0575) and 0.88 (95% CI: 0.82 to 0.93), respectively. The overall average effect values of the endemic component, spatiotemporal component and autoregressive component for all counties were 0.24, 0.035 and 0.72, respectively. The values of the autoregressive component for most counties were greater than 0.7. The endemic component of the top 10 counties with the highest values was greater than 0.34. Two counties with value of the spatiotemporal component higher than 0.1 were Xihu landscape county and Shengsi county. From 2016 to 2022, the endemic and autoregressive components of each county showed obvious seasonal changes.

Conclusion

The scaling exponent had both temporal trend characteristics and significant heterogeneity in the association between each type of syphilis and population size. Primary syphilis and latent syphilis exhibited a linear pattern, secondary syphilis presented a superlinear pattern, and tertiary syphilis exhibited a sublinear pattern. This suggested that further prevention of infection and transmission among high-risk populations and improvement of diagnostic accuracy in underdeveloped areas is needed. The autoregressive components and the endemic components were the main driving factors that affected the occurrence of syphilis. Targeted prevention and control strategies must be developed based on the main driving modes of the epidemic in each county.