Trends of respiratory viruses and factors associated with severe acute respiratory infection in patients presenting at a university hospital: a 6-year retrospective study across the COVID-19 pandemic

Frontiers in Public Health, Journal Year: 2025, Volume and Issue: 13

Published: March 28, 2025

The COVID-19 pandemic significantly disrupted the epidemiology of respiratory viruses, altering seasonal patterns and reducing circulation. While recovery trends have been observed, factors associated with severe acute infections (SARIs) during pre- post-pandemic periods remain underexplored in middle-income countries. This study aimed to analyze virus circulation identify SARI patients attending a tertiary care university hospital western Mexico over six-year period spanning pre-pandemic, pandemic, phases. A retrospective was conducted using data from 19,088 symptomatic tested for viruses between 2018 2024. Viral were analyzed through interrupted time series (ITS) modeling, incorporating locally estimated scatterplot smoothing (LOESS) raw positivity rates. Additionally, ITS analysis performed evaluate temporal changes proportions across different phases pandemic. Multivariate logistic regression models applied determine independent risk periods. During (2020-2021), rates declined, particularly influenza, which experienced sharp reduction but rebounded post-2022. Respiratory syncytial (RSV) demonstrated delayed resurgence, whereas other exhibited heterogeneous rebound patterns. modeling revealed significant pre-pandemic increasing trend, followed by slower rise drop early 2022, before resuming an upward trajectory. Among older adults (>65 years), marked increase observed at beginning while younger groups showed more stable Logistic identified advanced age, male sex, cardiovascular disease, obesity, immunosuppression as major SARI, vaccination consistently protective effect all subgroups. induced persistent shifts circulation, disrupting dynamics modifying burden SARI. findings underscore importance continuous surveillance, targeted programs, diagnostics mitigate outcomes. These results highlight need adaptive public health strategies countries address evolving disease threats.

Language: Английский

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Epidemic spreading on spatial higher-order network

Chaos An Interdisciplinary Journal of Nonlinear Science, Journal Year: 2024, Volume and Issue: 34(7)

Published: July 1, 2024

Higher-order interactions exist widely in mobile populations and are extremely important spreading epidemics, such as influenza. However, research on high-order interaction modeling of crowds the propagation dynamics above is still insufficient. Therefore, this study attempts to model simulate higher-order among explore their impact epidemic transmission. This simulated spread a spatial network based agent-based modeling. It explored its characteristics it. Meanwhile, we construct state-specific rate equations uniform mixing assumption for further analysis. We found that hysteresis loops an inherent feature networks space under specific scenarios. The evolution curve roughly presents three different states with initial value change, showing levels endemic balance low, medium, high, respectively. Similarly, snapshots parameter diagrams also indicate these types equilibrium states. Populations naturally form components sizes isolations, higher seeds generate network, leading infection densities. phenomenon emphasizes rates propagation. In addition, crowd density movement speed act protective inhibitory factors transmission, respectively, depending degree weaken or enhance effect loops.

Language: Английский

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Nontrivial epidemic dynamics induced by information-driven awareness-activity-resource coevolution

Physical review. E, Journal Year: 2025, Volume and Issue: 111(4)

Published: April 4, 2025

Language: Английский

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Effectiveness of catch-up vaccination from 2009 to 2011 on incidence of hepatitis B in Guangzhou, China: a time series analysis

BMC Public Health, Journal Year: 2025, Volume and Issue: 25(1)

Published: April 25, 2025

The high prevalence of hepatitis B weighs heavily on public health in China. In 2009, a catch-up vaccination program for children aged 8-15y was implemented to curb B, while the effectiveness this intervention has not been investigated. We aimed evaluate incidence Guangzhou, obtained individual data all cases from 2005 2019 Guangzhou Center Diseases Control and Prevention. Based daily reported number cases, we constructed generalized linear models estimate each age group 11 25 years. further estimated age-standardized effectiveness. Finally, examined different subgroups by sex clinical types B. A total 58,204 among individuals 11-25y were 2019, with an average annual 117.30 per 100,000 individuals. contributed 20.02% (95% confidence interval: 15.97%, 23.87%) decrease prevented 17.40 empirical interval [eCI]: 9.24, 23.78) during study period. could better protect males (excess rate [EIR]: -21.82 [95% eCI: -30.51, -10.15] individuals), prevent chronic (EIR: -24.27 -30.62, -16.09] individuals). massive against plays important role alleviating burden

Language: Английский

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Behavior-driven forecasts of neighborhood-level COVID-19 spread in New York City

PLoS Computational Biology, Journal Year: 2025, Volume and Issue: 21(4), P. e1012979 - e1012979

Published: April 29, 2025

The COVID-19 pandemic in New York City (NYC) was characterized by marked disparities disease burdens across neighborhoods. Accurate neighborhood-level forecasts are critical for planning more equitable resource allocation to reduce health inequalities; however, such spatially high-resolution remain scarce operational use. In this study, we analyze aggregated foot traffic data derived from mobile devices measure the connectivity among 42 NYC neighborhoods driven various human activities as dining, shopping, and entertainment. Using real-world time-varying contact patterns different place categories, develop a parsimonious behavior-driven epidemic model that incorporates population mixing, indoor crowdedness, dwell time, seasonality of virus transmissibility. We fit case further couple with assimilation algorithm generate short-term cases 2020. find differential between activities. supports accurate modeling SARS-CoV-2 transmission throughout best-fitting model, estimate force infection (FOI) settings increases sublinearly crowdedness time. Retrospective forecasting demonstrates generates improved compared several baseline models. Our findings indicate foot-traffic routine can support NYC. This may be adapted use other respiratory pathogens sharing similar routes.

Language: Английский

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Integrating Human Mobility Models with Epidemic Modeling: A Framework for Generating Synthetic Temporal Contact Networks

Entropy, Journal Year: 2025, Volume and Issue: 27(5), P. 507 - 507

Published: May 8, 2025

High-resolution temporal contact networks are useful ingredients for realistic epidemic simulations. Existing solutions typically rely either on empirical studies that capture fine-grained interactions via Bluetooth or wearable sensors in confined settings large-scale simulation frameworks model entire populations using generalized assumptions. However, most modeling of spread and the evaluation countermeasures, there is a critical need highly resolved, encompass multiple venues without sacrificing intricate dynamics real-world contacts. This paper presents an integrated approach generating such by coupling Bayesian-optimized human mobility models (HuMMs) with state-of-the-art framework. Our primary contributions twofold: First, we embed empirically calibrated HuMMs into environment to create parameterizable, adaptive engine producing synthetic, high-resolution, population-wide network data. Second, demonstrate through evaluations our generated exhibit interaction structures infection dynamics. In particular, experiments reveal while variations population size do not affect underlying properties—a crucial feature scalability—altering location capacities naturally influences local connectivity outcomes. Additionally, sub-graph analyses confirm different venue types display distinct characteristics consistent their patterns. Overall, this framework provides scalable grounded method simulation, offering powerful tool simulating networks.

Language: Английский

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Measuring Chinese mobility behaviour during COVID-19 using geotagged social media data

Humanities and Social Sciences Communications, Journal Year: 2024, Volume and Issue: 11(1)

Published: April 27, 2024

Abstract COVID-19 caused widespread disruption to normal lives and human activities. In China, the mobility behaviour response pandemic at intra-city population group levels is largely unknown, mainly due a lack of individual-level publicly available data. Using 210 million geotagged posts from 10 social media users, study quantified changes in stay-at-home outings across amenities groups China during pandemic. The users were compared national census data examine their representativeness. To validate results externally, was performed post-stratified correction further comparison with commonly used sources. findings reveal that (i) there between 16.8% 57.7% decrease visits places work, retail recreation sites, parks, transit stations, grocery stores, pharmacies within one month outbreak; (ii) those who are young, have bachelor’s degree or higher, unmarried experienced greater decline outings; (iii) people preferred visit nearby locations, resulting 4.3% increase recreational sites 3-kilometer radius homes. could gain insight into asymmetric impact on public infrastructure use socio-demographic groups, helping design targeted policies promote outdoor activities, stimulate economic recovery, alleviate inequality vulnerable groups.

Language: Английский

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Estimating the contribution of setting-specific contacts to SARS-CoV-2 transmission using digital contact tracing data

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: July 19, 2024

Abstract While many countries employed digital contact tracing to contain the spread of SARS-CoV-2, contribution cospace-time interaction (i.e., individuals who shared same space and time) transmission super-spreading in real world has seldom been systematically studied due lack systematic sampling testing contacts. To address this issue, we utilized data from 2230 cases 220,878 contacts with detailed epidemiological information during Omicron outbreak Beijing 2022. We observed that number per day for dwelling, workplace, interactions, community settings could be described by gamma distribution distinct parameters. Our findings revealed 38% traced transmissions occurred through interactions whilst control measures were place. However, using a mathematical model incorporate different locations, found without measures, contributed only 11% (95%CI: 10%–12%) risk setting was 4% 3%–5%), both lowest among all studied. These results suggest public health should optimized achieve balance between benefits challenges posed within setting.

Language: Английский

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Evaluating Policy Shifts on Perceived Greenspace Quality: Applying Regression Discontinuity During the COVID-19 Reopening Period

Land, Journal Year: 2024, Volume and Issue: 13(11), P. 1777 - 1777

Published: Oct. 29, 2024

Abstract: Urban greenspaces have been essential in supporting residents’ well-being during the COVID-19 pandemic, particularly under strict lockdown measures. However, impact of changing containment policies on perceived greenspace quality remains insufficiently explored. This study utilized online survey data collected between 11 October and 29 December 2022, Shanghai, coinciding with major policy shift 5 2022. A probability proportionate to size sampling was adopted residents aged 18 above who had lived city for at least six months, yielding a total 577 valid responses. We assessed using 20 park- community-level variables, focusing both overall specific features greenspaces. regression discontinuity design (RDD) applied evaluate how lifting influenced perceptions parks community Our RDD estimation indicates no statistically significant change after shift, except increased satisfaction such as plant diversity, maintenance, seating areas, trails, large open spaces. In contrast, responded reported significantly higher compared those completed before (0.609 score difference, p < 0.01), notable increases regarding areas. Perception quantity remained unchanged types Residents expressed greater sports facilities parks, while were preferred their water esthetic qualities. By adopting an unique dataset, this contributes empirical evidence current ongoing debate role urban later stages COVID-19. Specifically, it examines changes public health resulting increase mobility might affect quality. The findings can assist decision-makers planners developing more adaptive strategies address diverse needs transitional period crisis.

Language: Английский

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Behavior-driven forecasts of neighborhood-level COVID-19 spread in New York City

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: April 19, 2024

Abstract The COVID-19 pandemic in New York City (NYC) was characterized by marked disparities disease burdens across neighborhoods. Accurate neighborhood-level forecasts are critical for planning more equitable resource allocation; however, such spatially high-resolution remain scarce operational use. Here, we analyze aggregated foot traffic data derived from mobile devices to measure the connectivity among 42 NYC neighborhoods driven various human activities as dining, shopping, and entertainment. Using real-world time-varying contact patterns different place categories, develop a parsimonious behavior-driven epidemic model that incorporates population mixing, indoor crowdedness, dwell time, seasonality of virus transmissibility. This process-based supports accurate modeling SARS-CoV-2 transmission throughout 2020. In best-fitting model, estimate force infection settings increases sublinearly with crowdedness time. Retrospective forecasting demonstrates this generates improved short-term may be adapted use other respiratory pathogens sharing similar routes.

Language: Английский

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