Evaluation of Impacts of Control Measures, Applied in the Source Catchments, by Mathematical Models

AbstractObjectivesThe primary objective was to estimate the positivity rate of air travelers coming to Toronto, Canada in September and October, 2020, at arrival, day 7 and day 14. Secondary objectives were to estimate degree of risk based on country of origin; to assess knowledge and attitudes towards COVID-19 control measures; and subjective well-being during the quarantine period.DesignProspective cohort of arriving international travelers.SettingToronto Pearson Airport Terminal 1, Toronto, Canada.ParticipantsPassengers arriving on international flights. Inclusion criteria were those aged 18 or older who had a final destination within 100 km of the airport; spoke English or French; and provided consent. Excluded were those taking a connecting flight; who had no internet access; who exhibited symptoms of COVID-19 on arrival; or who were exempted from quarantine.Main outcome measuresPositive for SARS-CoV-2 virus on RT-PCR with self-administered nasal-oral swab, and general well-being using the WHO-5 index.ResultsOf 16,361 passengers enrolled, 248 (1·5%, 95% CI 1.3%,1.5%) tested positive. Of these, 167 (67%) were identified on arrival, 67 (27%) on day 7, and 14 (6%) on day 14. The positivity rate increased from 1% in September to 2% in October. Average well-being score declined from 19.8 (out of a maximum of 25) to 15.5 between arrival and day 7 (p<0.001).ConclusionsA single arrival test will pick up two-thirds of individuals who will become positive, with most of the rest detected on the second test at day 7. These results support strategies identified through mathematical models that a reduced quarantine combined with testing can be as effective as a 14 day quarantine.Article SummaryStrengths and limitations of this studyDecisions regarding border restrictions have been based on trial and error and mathematical models with limited empirical data to support such decision-making.This study assessed the prevalence of SARS-CoV-2 in a cohort of international travellers at arrival, day 7 and 14 of quarantine.It is limited to one airport and there is the potential from bias due to non-participation and loss to follow-up.Self-collected nasal-oral swabs were used which facilitated participation but may have reduced sensitivity.

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Real-world problems through computational thinking tools and concepts: the case of coronavirus disease (COVID-19)

Journal of Research in Innovative Teaching & Learning ◽

10.1108/jrit-12-2020-0085 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Hatice Beyza Sezer ◽

Immaculate Kizito Namukasa

Keyword(s):

Mathematical Models ◽

Real World ◽

Computational Thinking ◽

Recovery Process ◽

Control Measures ◽

Content Type ◽

Knowledge And Skills ◽

Four Dimensions ◽

And Mathematics ◽

Real World Problems

PurposeMany mathematical models have been shared to communicate about the COVID-19 outbreak; however, they require advanced mathematical skills. The main purpose of this study is to investigate in which way computational thinking (CT) tools and concepts are helpful to better understand the outbreak, and how the context of disease could be used as a real-world context to promote elementary and middle-grade students' mathematical and computational knowledge and skills.Design/methodology/approachIn this study, the authors used a qualitative research design, specifically content analysis, and analyzed two simulations of basic SIR models designed in a Scratch. The authors examine the extent to which they help with the understanding of the parameters, rates and the effect of variations in control measures in the mathematical models.FindingsThis paper investigated the four dimensions of sample simulations: initialization, movements, transmission, recovery process and their connections to school mathematical and computational concepts.Research limitations/implicationsA major limitation is that this study took place during the pandemic and the authors could not collect empirical data.Practical implicationsTeaching mathematical modeling and computer programming is enhanced by elaborating in a specific context. This may serve as a springboard for encouraging students to engage in real-world problems and to promote using their knowledge and skills in making well-informed decisions in future crises.Originality/valueThis research not only sheds light on the way of helping students respond to the challenges of the outbreak but also explores the opportunities it offers to motivate students by showing the value and relevance of CT and mathematics (Albrecht and Karabenick, 2018).

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Insights from quantitative and mathematical modelling on the proposed WHO 2030 goals for Chagas disease

Gates Open Research ◽

10.12688/gatesopenres.13069.1 ◽

2019 ◽

Vol 3 ◽

pp. 1539

Author(s):

Keyword(s):

Mathematical Models ◽

Vector Control ◽

Chagas Disease ◽

Public Health Problem ◽

Scaling Up ◽

Control Measures ◽

Transmission Dynamics ◽

World Health ◽

Seroprevalence Data ◽

Transmission Interruption

Chagas disease (CD) persists as one of the neglected tropical diseases (NTDs) with a particularly large impact in the Americas. The World Health Organization (WHO) recently proposed goals for CD elimination as a public health problem to be reached by 2030 by means of achieving intradomiciliary transmission interruption (IDTI), blood transfusion and transplant transmission interruption, diagnostic and treatment scaling-up and prevention and control of congenital transmission. The NTD Modelling Consortium has developed mathematical models to study Trypanosoma cruzi transmission dynamics and the potential impact of control measures. Modelling insights have shown that IDTI is feasible in areas with sustained vector control programmes and no presence of native triatomine vector populations. However, IDTI in areas with native vectors it is not feasible in a sustainable manner. Combining vector control with trypanocidal treatment can reduce the timeframes necessary to reach operational thresholds for IDTI (<2% seroprevalence in children aged <5 years), but the most informative age groups for serological monitoring are yet to be identified. Measuring progress towards the 2030 goals will require availability of vector surveillance and seroprevalence data at a fine scale, and a more active surveillance system, as well as a better understanding of the risks of vector re-colonization and disease resurgence after vector control cessation. Also, achieving scaling-up in terms of access to treatment to the expected levels (75%) will require a substantial increase in screening asymptomatic populations, which is anticipated to become very costly as CD prevalence decreases. Further modelling work includes refining and extending mathematical models (including transmission dynamics and statistical frameworks) to predict transmission at a sub-national scale, and developing quantitative tools to inform IDTI certification, post-certification and re-certification protocols. Potential perverse incentives associated with operational thresholds are discussed. These modelling insights aim to inform discussions on the goals and treatment guidelines for CD.

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A first study on the impact of current and future control measures on the spread of COVID-19 in Germany

10.1101/2020.04.08.20056630 ◽

2020 ◽

Cited By ~ 8

Author(s):

Maria Vittoria Barbarossa ◽

Jan Fuhrmann ◽

Julian Heidecke ◽

Hridya Vinod Varma ◽

Noemi Castelletti ◽

...

Keyword(s):

Mathematical Models ◽

Control Measures ◽

The Novel ◽

Mathematical Study ◽

Preliminary Results ◽

Novel Coronavirus ◽

The Impact ◽

Pharmaceutical Interventions

AbstractThe novel coronavirus (SARS-CoV-2), identified in China at the end of December 2019 and causing the disease COVID-19, has meanwhile led to outbreaks all over the globe, with about 571,700 confirmed cases and about 26,500 deaths as of March 28th, 2020. We present here the preliminary results of a mathematical study directed at informing on the possible application or lifting of control measures in Germany. The developed mathematical models allow to study the spread of COVID-19 among the population in Germany and to asses the impact of non-pharmaceutical interventions.

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Possible future waves of SARS-CoV-2 infection generated by variants of concern with a range of characteristics

Nature Communications ◽

10.1038/s41467-021-25915-7 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Louise Dyson ◽

Edward M. Hill ◽

Sam Moore ◽

Jacob Curran-Sebastian ◽

Michael J. Tildesley ◽

...

Keyword(s):

Mathematical Models ◽

Disease Severity ◽

Immune Escape ◽

Deterministic Model ◽

Control Measures ◽

Structured Model ◽

Age Structured ◽

Age Structured Model ◽

Viral Reproduction ◽

Importation Model

AbstractViral reproduction of SARS-CoV-2 provides opportunities for the acquisition of advantageous mutations, altering viral transmissibility, disease severity, and/or allowing escape from natural or vaccine-derived immunity. We use three mathematical models: a parsimonious deterministic model with homogeneous mixing; an age-structured model; and a stochastic importation model to investigate the effect of potential variants of concern (VOCs). Calibrating to the situation in England in May 2021, we find epidemiological trajectories for putative VOCs are wide-ranging and dependent on their transmissibility, immune escape capability, and the introduction timing of a postulated VOC-targeted vaccine. We demonstrate that a VOC with a substantial transmission advantage over resident variants, or with immune escape properties, can generate a wave of infections and hospitalisations comparable to the winter 2020-2021 wave. Moreover, a variant that is less transmissible, but shows partial immune-escape could provoke a wave of infection that would not be revealed until control measures are further relaxed.

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Design and Analysis of Optimal Pre-Control of Brucellosis Model by Dynamic Threshold-Based Microcomputer Model (Preprint)

10.2196/preprints.18497 ◽

2020 ◽

Author(s):

Yihao Huang ◽

Mingtao Li

Keyword(s):

Infectious Diseases ◽

Mathematical Models ◽

Control Method ◽

Control Measures ◽

Transmission Model ◽

Dynamic Threshold ◽

Key Populations ◽

Theoretical Support ◽

The Difference ◽

Susceptible Populations

BACKGROUND Mathematical models have become a very important tool for the study of infectious diseases. Mathematical models can reflect the spread of infectious diseases, and can also be used to study the effect of different inhibition methods on the suppression of infectious diseases. The effect of control measures to obtain effective suppression programs can provide theoretical support for the suppression of infectious diseases. Therefore, it is the major objective of this study to build a suitable mathematical model for Brucellosis infection. OBJECTIVE To study the optimized pre-control method of Brucellosis model by the dynamic threshold-based microcomputer model, and to provide critical theoretical support for the prevention and control of Brucellosis. METHODS By studying the transmission characteristics of Brucella and building a Brucella transmission model, a pre-control method for key populations (Brucella susceptible populations) is designed according to these characteristics, thereby exploring the utilization of protective tools by key groups before and after pre-control. RESULTS The improvement in “whether wearing gloves” is the most obvious, which increases from 51.01% before the pre-control to 66.22% after the pre-control, with an increase of 15.21%. The difference is statistically significant (P<0.001). However, for “whether wearing hats”, the conditions of key populations are not improved significantly, which increases from 57.3% before the pre-control to 58.6% after the pre-control, with an increase of 1.3%. The difference is not statistically significant (P>0.05). CONCLUSIONS The research results of Brucellosis have provided theoretical support for the suppression of Brucella and the protective measures for key populations.

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Temporal progress of teak rust in a tropical area of Tocantins State, Brazil

Acta Amazonica ◽

10.1590/1809-4392201603212 ◽

2017 ◽

Vol 47 (3) ◽

pp. 277-280 ◽

Cited By ~ 2

Author(s):

Nathana Izabela Silva SALES ◽

Evelynne Urzêdo LEÃO ◽

Lucas Caius Moreira do Amaral CORREIA ◽

Chrystian de Assis SIQUEIRA ◽

Gil Rodrigues dos SANTOS

Keyword(s):

Mathematical Models ◽

Negative Correlation ◽

Minimum Temperature ◽

Growth Stage ◽

Gompertz Model ◽

Control Measures ◽

Climate Variables ◽

Disease Progress ◽

Tropical Area ◽

Temporal Progress

ABSTRACT Rust, caused by Olivea neotectonae, stands out as the main teak disease, causing premature defoliation regardless of the tree’s growth stage. In this study, we aimed to assess the temporal progress of rust in adult teak plants in southern Tocantins State (Brazil). Both rust incidence and severity were evaluated and the disease progress curves were obtained, adjusting to monomolecular, logistic and Gompertz mathematical models. Data from incidence and severity were correlated with climate variables collected by the agrometeorological station located in the study area. Rust incidence reached 100% at 98 days after beginning of the evaluations (DBE). The highest severity (equal or above 75%) was observed at 147 DBE. There was a significant and negative correlation between severity and minimum temperature. The adjustment of the Gompertz model suggests that control measures should be aimed primarily to reduce the rate of disease progress.

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