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Objectives: Although the relationship between urbanization and influenza has received increasing attention, previous studies have often examined this relationship based on single indicators, neglecting the multi-dimensions of urban development and their integrated impact on influenza incidence in neighboring cities.
Methods: A multidimensional urbanization evaluation framework was developed based on social, economic, and ecological dimensions to comprehensively assess urbanization. Then, we analyzed the impact of urbanization development on influenza incidence within and across cities using Bayesian spatiotemporal models and spatial Durbin models. Regional heterogeneity analysis was performed to investigate the impact of urbanization on influenza incidence within cities.
Results: From 2014 to 2019, there were 5,062,254 influenza cases in 283 prefecture-level cities in China. Each standard deviation increment in comprehensive, social, and economic indexes of urbanization was associated with a 14.9% (95% CI: 6.1%, 24.3%), 9.9% (95% CI: 3.5%, 16.3%), and 13.4% (95% CI: 4.5%, 23.7%) increase in influenza incidence, respectively. The effects of urban development on influenza incidence varied significantly across regions, with the greatest impact found in southern China. Additionally, a significant positive spatial spillover effect of urbanization was observed on influenza incidence in surrounding cities.
Conclusions: Urbanization and its various dimensions were linked to increased risk of local influenza incidence, which also showed substantial positive spatial spillover effect to surrounding areas. During the rapid urbanization process in China, local governments should prioritize equity and accessibility in healthcare services and strengthen the coordinated prevention and control of influenza epidemics across cities.
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http://dx.doi.org/10.1016/j.jinf.2024.106370 | DOI Listing |
Environ Int
December 2024
Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ 85724, United States. Electronic address:
Wastewater-based estimation of infectious disease prevalence in real-time assists public health authorities in developing effective responses to current outbreaks. However, wastewater-based estimation for IAV remains poorly demonstrated, partially because of a lack of knowledge about temporal variation in shedding amount of an IAV-infected person. In this study, we applied two mathematical models to previously collected wastewater and clinical data from four U.
View Article and Find Full Text PDFSex Transm Dis
December 2024
Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA USA.
Background: The etiology of nongonococcal urethritis (NGU) is incompletely understood. We sought to determine if genitourinary bacterial diversity or specific taxa were associated with incident NGU.
Methods: From August 2014-July 2018, men who have sex with women attending a sexual health clinic were clinically evaluated, including Mycoplasma genitalium (MG) and Chlamydia trachomatis (CT) testing, at enrollment and six monthly visits.
Arch Med Res
December 2024
Department of Emergency Medicine, Gold Coast Hospital and Health Service, Southport Queensland, Australia; Menzies Health Institute Queensland, Griffith University, Queensland, Australia.
Background: The SARS-CoV-2 pandemic and accompanying public health measures disrupted the normal transmission of respiratory viral pathogens. Less is known about the effects on bacterial pathogens.
Aims: To assess the impact of public health restrictions on common respiratory pathogens (influenza viruses, respiratory syncytial virus (RSV) and the following bacterial pathogens: Streptococcus pneumoniae (S.
Ann Med
December 2025
Department of Microbiology and Clinical Parasitology, College of Medicine, King Khalid University, Abha, Saudi Arabia.
Background: There is a global consensus that respiratory tract infections are the major causes of morbidity and mortality among children. In this study, we aimed to compare the clinical and epidemiological characteristics of respiratory syncytial virus (RSV), influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections among children admitted to hospital with acute respiratory infections. We also opted to identify the predictors of paediatric intensive care unit (PICU) admission.
View Article and Find Full Text PDFBMC Infect Dis
December 2024
Institute of Immunization and Prevention, Zhejiang Center for Disease Control and Prevention, No. 3399 Binsheng Road, Binjiang District, Hangzhou, P.R. China.
Background: Previous evidence had suggested age and sex affect the reporting rate of adverse events following immunization (AEFI), but with little exploration of potential their non-linear and interaction effects on AEFIs. Examining these non-linear effects could be beneficial for identifying high-risk populations.
Methods: Using AEFI records and vaccination data from national passive surveillance system of adverse event following immunization and Zhejiang provincial immunization information system in the 2021-2022 influenza season, respectively.
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