Open Journal of Natural Science, Journal Year: 2023, Volume and Issue: 11(06), P. 1003 - 1014
Published: Jan. 1, 2023
Language: Английский
Open Journal of Natural Science, Journal Year: 2023, Volume and Issue: 11(06), P. 1003 - 1014
Published: Jan. 1, 2023
Language: Английский
npj Climate and Atmospheric Science, Journal Year: 2025, Volume and Issue: 8(1)
Published: Feb. 25, 2025
Language: Английский
Citations
2Journal of Hazardous Materials, Journal Year: 2025, Volume and Issue: 490, P. 137865 - 137865
Published: March 6, 2025
Language: Английский
Citations
1Infectious Disease Modelling, Journal Year: 2023, Volume and Issue: 8(3), P. 822 - 831
Published: July 8, 2023
Evidence is inefficient about how meteorological factors influence the trends of influenza transmission in different regions China.We estimated time-varying reproduction number (Rt) and explored impact temperature relative humidity on Rt using generalized additive quasi-Poisson regression models combined with distribution lag non-linear model (DLNM). The effect interaction was explored. multiple random-meta analysis used to evaluate region-specific association. excess risk (ER) index defined investigate correlation between each factor modification seasonal regional characteristics.Low low contributed epidemics national level, while shapes merged cumulative plots were across regions. Compared that median temperature, RR (95%CI) northern southern 1.40(1.24,1.45) 1.20 (1.14,1.27), respectively, those high 1.10(1.03,1.17) 1.00 (0.95,1.04), respectively. There negative interactions (SI = 0.59, 95%CI: 0.57-0.61), 0.49, 0.17-0.80), 0.56,0.62). In general, increase change two factors, ER also gradually increased.Temperature have an China, there but heterogeneous among Meteorological may be considered predict trend epidemic.
Language: Английский
Citations
11Journal of Medical Virology, Journal Year: 2023, Volume and Issue: 95(10)
Published: Oct. 1, 2023
To the best of our knowledge, no previous study has quantitatively estimated dynamics and cumulative susceptibility to influenza infections after widespread lifting COVID-19 public health measures. We constructed an imitated stochastic susceptible-infected-removed model using particle-filtered Markov Chain Monte Carlo sampling estimate time-dependent reproduction number based on surveillance data in southern China, northern United States during 2022-2023 season. compared these estimates those from 2011 2019 seasons without strong social distancing interventions determine restrictions. Compared 2011-2019 a intervention with measures, season length was 45.0%, 47.1%, 57.1% shorter States, respectively, corresponding 140.1%, 74.8%, 50.9% increase scale infections, 60.3%, 72.9%, 45.1% population influenza. Large high-intensity epidemics occurred China 2022-2023. Population increased 2019-2022, especially China. recommend promoting vaccination, taking personal prevention actions at-risk populations, monitoring changes dynamic levels other respiratory prevent potential outbreaks coming
Language: Английский
Citations
11Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 2, 2025
Language: Английский
Citations
0International Journal of Environmental Health Research, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 14
Published: Feb. 8, 2025
This study investigated the relationship between air pollution and influenza incidence in Chongqing from 2013 to 2022 using a generalized additive model (GAM), analyzing 199,712 cases. Subgroup analyses were conducted investigate impact of age, gender, season, COVID-19. Influenza was positively associated with PM2.5, PM10, SO2, NO2 CO, but negatively O3. SO2 had most effect. In single-day lag models, largest percentage changes at lag0 for each pollutant were: 2.930% 1.552% -0.637% O3, 0.516% 0.405% PM10. showed change lag11 (1.376%). multi-day peaked lag011–014. Stratified revealed children aged 0–14 years as particularly vulnerable during cold season COVID-19 period. The demonstrates that short-term lags cumulative effects exposure increase incidence, significant establishing response strategies.
Language: Английский
Citations
0Communications Earth & Environment, Journal Year: 2025, Volume and Issue: 6(1)
Published: March 17, 2025
Language: Английский
Citations
0Frontiers in Public Health, Journal Year: 2025, Volume and Issue: 13
Published: April 14, 2025
Background Non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic altered influenza transmission patterns, yet age-specific effects of air pollutants on dynamics remain unclear. Methods Utilizing surveillance data Jiangsu Province from 2020 to 2024, we integrated generalized additive quasi-Poisson regression model and distributed lag non-linear models (DLNM) quantify lagged exposure-response relationships between (NO 2 , SO PM 2.5 ) risk across young, middle-aged, older adult groups. Meteorological factors, including temperature humidity, as well implementation stages NPIs, were controlled in isolate impact transmission. Results The NO both showed significant positive all age effect is most young group (RR = 5.02, 95% CI: 4.69–5.37), while exhibited pronounced middle-aged groups 4.22, 3.36–5.30; RR 8.31, 5.77–11.96, respectively). elevated risks 1.99, 1.87–2.12) 1.45, 1.07–1.94) Interactions meteorological factors (temperature, humidity) statistically insignificant. Conclusions Air pollutant impacts are age-dependent: dominates younger populations, whereas disproportionately affects adults. These findings highlight age-related vulnerability pollution need for targeted public health strategies different population subgroups.
Language: Английский
Citations
0BMC Infectious Diseases, Journal Year: 2024, Volume and Issue: 24(1)
Published: Oct. 2, 2024
Language: Английский
Citations
2Environment International, Journal Year: 2024, Volume and Issue: 189, P. 108783 - 108783
Published: May 28, 2024
Temperature affects influenza transmission; however, currently, limited evidence exists about its effect in China at the national and city levels as well how temperature can be integrated into interventions. Meteorological, pollutant, data from 201 cities mainland between 2013 2018 were analyzed both to investigate relationship prevalence. We examined impact of on time-varying reproduction number (Rt) using generalized additive quasi-Poisson regression models combined with distributed lag nonlinear model. Threshold temperatures determined for seven regions based early warning threshold serious outbreaks, set Rt = 1.2. A multivariate random-effects meta-analysis was employed assess region-specific associations. The excess risk (ER) index defined correlation temperature, modified seasonal regional characteristics. At level central, northern, northwestern, southern regions, found negatively correlated relative risk, whereas shapes curves eastern, southwestern, northeastern not defined. Low had an observable prevalence; effects high obvious. 1.2, reaching a outbreaks − 24.3 °C region, 16.6 northwestern 1℃ 10 other regions. study findings revealed that varying transmission trends across different China. By identifying thresholds more effective systems could tailored. These emphasize significance adaptation prevention control measures.
Language: Английский
Citations
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