Adverse Effects of COVID-19 Vaccination: Machine Learning and Statistical Approach to Identify and Classify Incidences of Morbidity and Postvaccination Reactogenicity

Healthcare, Год журнала: 2022, Номер 11(1), С. 31 - 31

Опубликована: Дек. 22, 2022

Good vaccine safety and reliability are essential for successfully countering infectious disease spread. A small but significant number of adverse reactions to COVID-19 vaccines have been reported. Here, we aim identify possible common factors in such enable strategies that reduce the incidence by using patient data classify characterise those at risk. We examined medical histories documenting postvaccination effects outcomes. The analyses were conducted a range statistical approaches followed series machine learning classification algorithms. In most cases, group similar features was significantly associated with poor reactions. These included prior illnesses, admission hospitals SARS-CoV-2 reinfection. indicated age, gender, taking other medications, type-2 diabetes, hypertension, allergic history heart pre-existing risk outcome. addition, long duration hospital treatments, dyspnoea, various kinds pain, headache, cough, asthenia, physical disability clinical predictors. classifiers trained also able predict patients complication-free vaccination an accuracy score above 90%. Our study identifies profiles individuals may need extra monitoring care (e.g., location access comprehensive support) negative outcomes through approaches.

Язык: Английский

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Short-Term Adverse Effects Following Booster Dose of Inactivated-Virus vs. Adenoviral-Vector COVID-19 Vaccines in Algeria: A Cross-Sectional Study of the General Population

Vaccines, Год журнала: 2022, Номер 10(11), С. 1781 - 1781

Опубликована: Окт. 22, 2022

COVID-19 booster vaccines have been adopted in almost all countries to enhance the immune response and combat emergence of new variants. Algeria this strategy November 2021. This study was conducted consider self-reported side effects by Algerians who were vaccinated with a dose one approved inactivated-virus vaccines, such as BBIBP-CorV CoronaVac, or adenoviral-vector-based Gam-COVID-Vac, AZD1222 Ad26.COV2.S, determine eventual risk factors. A cross-sectional using an online self-administered questionnaire (SAQ) between 28 April 2022, 20 July 2022. descriptive analysis 196 individuals included showed nearly equal distribution adenoviral- (52%) (48%) males (49.5%) females (50.5%). The results that 74.7% studied population reported at least local systemic effect. These more frequent among adenoviral-vector vaccinees (87.3%) than (60.6%) (sig. < 0.001). Injection site pain (40.3%), heat injection (21.4%), arm (16.3%) most common effects. signs generally appeared first 12 h (73.3%) lasted less 24 (32.8%). More interestingly, these differed from those followed administration primer doses (48.5%) severe (37%). same observation for effects, where especially adenoviral-vaccinated group (49.4% vs. 20.8%; sig. = within day (63.6%) mostly disappeared before two days (50.8%), fatigue (41.8%), fever (41.3%), headache (30.1%) being common. Adenoviral-vector (62.7%) likely use medications manage (45.7%) 0.035) paracetamol used medication. Adenoviral-based types cause In addition, female increased developing effects; regular medication associated vaccinees; previous infection adenovirus-based vaccinees. support short-term safety has doses.

Язык: Английский

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Disease Spread Model in Structurally Complex Spaces: An Open Markov Chain Approach

Journal of Computational Biology, Год журнала: 2025, Номер unknown

Опубликована: Фев. 11, 2025

Understanding the dynamical behavior of infectious disease propagation within enclosed spaces is crucial for effectively establishing control measures. In this article, we present a modeling approach to analyze dynamics individuals in spaces, where such are comprised different chambers. Our focus on capturing movement and their infection status using an open Markov chain framework. Unlike ordinary chains, accounts entering leaving system. We categorize system into three groups: susceptible, carrier, infected. A discrete-time process employed model throughout To quantify risk infection, derive probability function that takes account total number inside distribution among groups. Furthermore, calculate mathematical expressions average infected at each time step. Additionally, determine mean stationary populations these validate our approach, compare theoretical numerical models proposed work.

Язык: Английский

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A Bayesian approach for studying COVID-19 contagion dynamics in Algeria using a Poisson autoregressive (PAR) model

Journal of Biopharmaceutical Statistics, Год журнала: 2025, Номер unknown, С. 1 - 17

Опубликована: Апрель 17, 2025

Global emphasis has been focused on tracking the trends of COVID-19 pandemic. Numerous techniques have developed or utilized for this purpose. In study, we seek to present and evaluate a model that, in our opinion, not received adequate attention, using Algeria as case study. We two distinct Poisson autoregressive (PAR) models Monte Carlo Markov Chain (MCMC) simulation method Bayesian method: one based solely short-term dependence other incorporating both short- long-term dependence. The study aimed apply these enhance prediction new infections determine whether disease is spreading declining. This information can guide decisions implementing relaxing containment measures. Our findings suggest that Algeria's epidemiological state was relatively stable at end period, with combined factors being less than 1 (α+β=0.994). indicates while epidemic decline, infection rates are expected drop significantly near future. Furthermore, parameter α=0.987constitutes significant portion (99%) total high value α experiencing strong though rate persist lower level foreseeable Given findings, it recommended authorities remain vigilant continue public health measures, including educational campaigns awareness efforts, promote vaccination adherence guidelines.

Язык: Английский

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The Effect of Preventive Measures and Vaccination against SARS-CoV-2 on the Infection Risk, Treatment, and Hospitalization: A Cross-Sectional Study of Algeria

Viruses, Год журнала: 2022, Номер 14(12), С. 2771 - 2771

Опубликована: Дек. 12, 2022

Coronavirus disease (COVID-19) caused by the SARS-CoV-2 virus continues to afflict many countries around world. The resurgence of COVID-19 cases and deaths in shows a complacency adhering preventive guidelines. Consequently, vaccination be crucial intervention reduce effects this pandemic. This study investigated impact measures on infection, medication, hospitalization. A cross-sectional online survey was conducted between 23 December 2021 12 March 2022 Algeria. To evaluate effectiveness strategies aimed at avoiding minimizing infection severity, questionnaire created validated. Descriptive statistics logistic regression analyses were computed identify associations dependent independent variables. Variables with p-value < 0.05 considered statistically significant. Our results indicated that out 2294 answers received, only 16% our sample vaccinated, more than 60% did not apply As result, 45% infected SARS-CoV-2, 75% took treatment (even preventive), 9% hospitalized. showed unvaccinated is significant (OR: 0.764, 95% CI = 0. 555–1.052; p 0.09). However, relationship changes significantly for people who are vaccinated 0.108, 0.047–0.248; 0.0001). also demonstrated protective non-vaccinated individuals reducing need receive anti-COVID-19 treatments 0.447, 0.321–0.623; Furthermore, population risk hospitalization 0.211, 0.081–0.548; Moreover, neglect must take medication rate 3.77 times 3.77) higher those follow vaccinated. In short, findings demonstrate importance combining order fight against Therefore, we advise Ministry Health relevant authorities put effort into enhancing public knowledge about through education awareness initiatives. Parallel implementing as additional strategy, behavioral change initiatives improved encourage adherence prevention recommendations.

Язык: Английский

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Chemometrics of the Environment: Hydrochemical Characterization of Groundwater in Lioua Plain (North Africa) Using Time Series and Multivariate Statistical Analysis

Sustainability, Год журнала: 2022, Номер 15(1), С. 20 - 20

Опубликована: Дек. 20, 2022

This study aims to analyze the chemical composition of Lioua’s groundwater in order determine geological processes influencing and origin its elements. Therefore, chemometrics techniques, such as multivariate statistical analysis (MSA) time series methods (TSM) are used. Indeed, MSA includes a component (PCA) cluster (CA), while autocorrelation (AA), supplemented by simple spectral density (SDA), is used for TMS. PCA displays three main factors explaining total variance (TV) 85.01 %. Factors 1, 2, 3 68.72%, 11.96%, 8.89 % TV, respectively. In CA, dissolved solids (TDS) electrical conductivity (EC) controlled groups. The elements SO42−, K+, Ca2+ closely related TDS, Na+, Cl−, Mg2+ CE, HCO3− NO3− indicate dissociation other AA shows linear interrelationship EC, Mg2+, SO42−. However, uncorrelated characteristics with parameters. For SDA, correlograms SO42− have similar trend EC. Nonetheless, pH, Ca2+, exhibit multiple peaks presence several distinct cyclic mechanisms. Using these authors were able draw following conclusion: geochemical impacting (i) dissolution evaporated mineral deposits, (ii) water–rock interaction, (iii) evaporation process. addition, exhibits two bipolar characteristics, one recorded negative positive charges on pH Ca+ another only NO3−. On hand, TDS major predominant groundwater’s composition. Chloride mainly increases water. lithological factor dominant overall mineralization Plio Quaternary surface aquifer waters. origins follows: has carbonate origin, whereas NO3– an anthropogenic origin. salinity was affected HCO3−, result from human activity usage fertilizers, facies outcrops, domestic sewage.

Язык: Английский

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Improved time-varying reproduction numbers using the generation interval for COVID-19

Frontiers in Public Health, Год журнала: 2023, Номер 11

Опубликована: Июнь 30, 2023

Estimating key epidemiological parameters, such as incubation period, serial interval (SI), generation (GI) and latent is essential to quantify the transmissibility effects of various interventions COVID-19. These parameters play a critical role in quantifying basic reproduction number. With hard work investigators South Korea, estimating these has become possible based on infector-infectee surveillance data COVID-19 between February 2020 April 2021. Herein, mean period was estimated be 4.9 days (95% CI: 4.2, 5.7) 4.3 4.4). The 4.3, with standard deviation 4.2. It also revealed that proportion presymptomatic transmission ~57%, which indicates potential risk before disease onset. We compared time-varying number GI SI found may result larger estimation Rt , refers around rapid increase cases. This highlights importance considering intervals when

Язык: Английский

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Epidemiological characteristics and transmission dynamics of the COVID-19 outbreak in Hohhot, China: a time-varying SQEIAHR model analysis

Frontiers in Public Health, Год журнала: 2023, Номер 11

Опубликована: Июнь 21, 2023

Background On September 28, 2022, the first case of Omicron subvariant BF.7 was discovered among coronavirus disease 2019 (COVID-19) infections in Hohhot, China, and then epidemic broke out on a large scale during National Day holiday. It is imminently necessary to construct mathematical model investigate transmission dynamics COVID-19 Hohhot. Methods In this study, we investigated epidemiological characteristics cases including spatiotemporal distribution sociodemographic distribution. Then, proposed time-varying Susceptible-Quarantined Susceptible-Exposed-Quarantined Exposed-Infected-Asymptomatic-Hospitalized-Removed (SQEIAHR) derive curves. The next-generation matrix method used calculate effective reproduction number ( R e ). Finally, explored effects higher stringency measures development through scenario analysis. Results Of 4,889 positive infected cases, vast majority were asymptomatic mild, mainly concentrated central areas such as Xincheng District. People 30–59 age group primarily affected by current outbreak, accounting for 53.74%, but females males almost equally (1.03:1). Community screening (35.70%) centralized isolation (26.28%) main ways identify cases. Our predicted peak October 6, dynamic zero-COVID date 15, 629, cumulative 4,963 (95% confidential interval (95%CI): 4,692 ~ 5,267), all four which highly consistent with actual situation Early basic 0 ) approximately 7.01 (95%CI: 6.93 7.09), declined sharply below 1.0 2022. Scenario analysis showed importance decreasing rate increasing quarantine shorten time peak, an 1.0, well reduce final population. Conclusion predicting trends COVID-19, implementation more stringent combination indispensable containing spread virus.

Язык: Английский

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The effect of the urban exposome on COVID-19 health outcomes: A systematic review and meta-analysis

Environmental Research, Год журнала: 2023, Номер 240, С. 117351 - 117351

Опубликована: Окт. 17, 2023

The global severity of SARS-CoV-2 illness has been associated with various urban characteristics, including exposure to ambient air pollutants. This systematic review and meta-analysis aims synthesize findings from ecological non-ecological studies investigate the impact multiple urban-related features on a variety COVID-19 health outcomes.On December 5, 2022, PubMed was searched identify all types observational that examined one or more exposome characteristics in relation outcomes such as infection severity, need for hospitalization, ICU admission, COVID pneumonia, mortality.A total 38 241 were included this review. Non-ecological highlighted significant effects population density, urbanization, pollutants, particularly PM2.5. meta-analyses revealed 1 μg/m3 increase PM2.5 higher likelihood hospitalization (pooled OR 1.08 (95% CI:1.02-1.14)) death 1.06 CI:1.03-1.09)). Ecological studies, addition confirming also indicated nitrogen dioxide (NO2), ozone (O3), sulphur (SO2), carbon monoxide (CO), well lower temperature, humidity, ultraviolet (UV) radiation, less green blue space exposure, increased morbidity mortality.This identified several key vulnerability related areas context recent pandemic. underscore importance improving policies exposures implementing measures protect individuals these harmful environmental stressors.

Язык: Английский

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COVID-19-Associated Paediatric Inflammatory Multisystem Syndrome (PIMS-TS) in Intensive Care: A Retrospective Cohort Trial (PIMS-TS INT)

Children, Год журнала: 2023, Номер 10(2), С. 348 - 348

Опубликована: Фев. 10, 2023

Paediatric inflammatory multisystem syndrome temporally associated with COVID-19 (PIMS-TS) is a new disease in children and adolescents that occurs after often asymptomatic or mild COVID-19. It can be manifested by different clinical symptomatology varying severity of based on multisystemic inflammation. The aim this retrospective cohort trial was to describe the initial presentation, diagnostics, therapy outcome paediatric patients diagnosis PIMS-TS admitted one 3 PICUs. All who were hospital SARS-CoV-2 during study period enrolled study. A total 180 analysed. most common symptoms upon admission fever (81.6%, n = 147), rash (70.6%, 127), conjunctivitis (68.9%, 124) abdominal pain (51.1%, 92). Acute respiratory failure occurred 21.1% (n 38). Vasopressor support used 20.6% 37) cases. Overall, 96.7% 174) initially tested positive for IgG antibodies. Almost all received antibiotics in-hospital stays. No patient died stay 28 days follow-up. Initial presentation organ system involvement including laboratory manifestations treatment identified trial. Early identification manifestation essential early proper management patients.

Язык: Английский

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