scholarly journals The Impact of Universal Mask Use on SARS-COV-2 in Victoria, Australia on the Epidemic Trajectory of COVID-19

2021 ◽  
Vol 9 ◽  
Author(s):  
Valentina Costantino ◽  
Chandini Raina MacIntyre
Keyword(s):  
Mathematical Modeling ◽  
Deterministic Model ◽  
Face Mask ◽  
Control Measures ◽  
Contact Tracing ◽  
Epidemic Size ◽  
Community Transmission ◽  
Age Structured ◽  
The Impact ◽  
Mask Effectiveness

Objective(s): To estimate the impact of universal community face mask use in Victoria, Australia along with other routine disease control measures in place.Methods: A mathematical modeling study using an age structured deterministic model for Victoria, was simulated for 123 days between 1 June 2020 and 1 October 2020, incorporating lockdown, contact tracing, and case findings with and without mask use in varied scenarios. The model tested the impact of differing scenarios of the universal use of face masks in Victoria, by timing, varying mask effectiveness, and uptake.Results: A six-week lockdown with standard control measures, but no masks, would have resulted in a large resurgence by September, following the lifting of restrictions. Mask use can substantially reduce the epidemic size, with a greater impact if at least 50% of people wear a mask which has an effectiveness of at least 40%. Early mask use averts more cases than mask usage that is only implemented closer to the peak. No mask use, with a 6-week lockdown, results in 67,636 cases and 120 deaths by 1 October 2020 if no further lockdowns are used. If mask use at 70% uptake commences on 23 July 2020, this is reduced to 7,961 cases and 42 deaths. We estimated community mask effectiveness to be 11%.Conclusion(s): Lockdown and standard control measures may not have controlled the epidemic in Victoria. Mask use can substantially improve epidemic control if its uptake is higher than 50% and if moderately effective masks are used. Early mask use should be considered in other states if community transmission is present, as this has a greater effect than later mask wearing mandates.

THE IMPACT OF VACCINATION ON MALARIA PREVALENCE: A VACCINE-AGE-STRUCTURED MODELING APPROACH

2020 ◽  
Vol 28 (02) ◽  
pp. 475-513
Author(s):  
KATIA VOGT-GEISSE ◽  
CALISTUS N. NGONGHALA ◽  
ZHILAN FENG
Keyword(s):  
Booster Dose ◽  
Deterministic Model ◽  
Vaccine Dose ◽  
Threshold Value ◽  
Disease Prevalence ◽  
Control Measures ◽  
Disease Eradication ◽  
Vaccination Programs ◽  
Age Structured ◽  
The Impact

A deterministic model for the effects on disease prevalence of the most advanced pre-erythrocytic vaccine against malaria is proposed and studied. The model includes two vaccinated classes that correspond to initially vaccinated and booster dose vaccinated individuals. These two classes are structured by time-since-initial-vaccination (vaccine-age). This structure is a novelty for vector–host models; it allows us to explore the effects of parameters that describe timed and delayed delivery of a booster dose, and immunity waning on disease prevalence. Incorporating two vaccinated classes can predict more accurately threshold vaccination coverages for disease eradication under multi-dose vaccination programs. We derive a vaccine-age-structured control reproduction number [Formula: see text] and establish conditions for the existence and stability of equilibria to the system. The model is bistable when [Formula: see text]. In particular, it exhibits a backward (sub-critical) bifurcation, indicating that [Formula: see text] is no longer the threshold value for disease eradication. Thus, to achieve eradication we must identify and implement control measures that will reduce [Formula: see text] to a value smaller than unity. Therefore, it is crucial to be cautious when using [Formula: see text] to guide public health policy, although it remains a key quantity for decision making. Our results show that if the booster vaccine dose is administered with delay, individuals may not acquire its full protective effect, and that incorporating waning efficacy into the system improves the accuracy of the model outcomes. This study suggests that it is critical to follow vaccination schedules closely, and anticipate the consequences of delays in those schedules.

scholarly journals Modelling the impact of reducing control measures on the COVID-19 pandemic in a low transmission setting

2020 ◽  
Author(s):  
Nick Scott ◽  
Anna Palmer ◽  
Dominic Delport ◽  
Romesh Abeysuriya ◽  
Robyn Stuart ◽  
...  
Keyword(s):  
Public Transport ◽  
Risk Mitigation ◽  
Mitigation Strategies ◽  
Control Measures ◽  
Contact Tracing ◽  
Policy Changes ◽  
Low Transmission ◽  
Transmission Setting ◽  
Community Transmission ◽  
The Impact

AbstractAimsWe assessed COVID-19 epidemic risks associated with relaxing a set of physical distancing restrictions in the state of Victoria, Australia – a setting with low community transmission – in line with a national framework that aims to balance sequential policy relaxations with longer-term public health and economic need.MethodsAn agent-based model, Covasim, was calibrated to the local COVID-19 epidemiological and policy environment. Contact networks were modelled to capture transmission risks in households, schools and workplaces, and a variety of community spaces (e.g. public transport, parks, bars, cafes/restaurants) and activities (e.g. community or professional sports, large events). Policy changes that could prevent or reduce transmission in specific locations (e.g. opening/closing businesses) were modelled in the context of interventions that included testing, contact tracing (including via a smartphone app), and quarantine.ResultsPolicy changes leading to the gathering of large, unstructured groups with unknown individuals (e.g. bars opening, increased public transport use) posed the greatest risk, while policy changes leading to smaller, structured gatherings with known individuals (e.g. small social gatherings) posed least risk. In the model, epidemic impact following some policy changes took more than two months to occur. Model outcomes support continuation of working from home policies to reduce public transport use, and risk mitigation strategies in the context of social venues opening, such as >30% population-uptake of a contact-tracing app, physical distancing policies within venues reducing transmissibility by >40%, or patron identification records being kept to enable >60% contact tracing.ConclusionsIn a low transmission setting, care should be taken to avoid lifting sequential COVID-19 policy restrictions within short time periods, as it could take more than two months to detect the consequences of any changes. These findings have implications for other settings with low community transmission where governments are beginning to lift restrictions.

scholarly journals A renewal equation model to assess roles and limitations of contact tracing for disease outbreak control

2021 ◽  
Vol 8 (4) ◽  
Author(s):  
Francesca Scarabel ◽  
Lorenzo Pellis ◽  
Nicholas H. Ogden ◽  
Jianhong Wu
Keyword(s):  
Deterministic Model ◽  
Infected Individual ◽  
Equation Model ◽  
Renewal Equation ◽  
Contact Tracing ◽  
Calendar Time ◽  
Individual Level ◽  
Total Incidence ◽  
Community Transmission ◽  
The Individual

We propose a deterministic model capturing essential features of contact tracing as part of public health non-pharmaceutical interventions to mitigate an outbreak of an infectious disease. By incorporating a mechanistic formulation of the processes at the individual level, we obtain an integral equation (delayed in calendar time and advanced in time since infection) for the probability that an infected individual is detected and isolated at any point in time. This is then coupled with a renewal equation for the total incidence to form a closed system describing the transmission dynamics involving contact tracing. We define and calculate basic and effective reproduction numbers in terms of pathogen characteristics and contact tracing implementation constraints. When applied to the case of SARS-CoV-2, our results show that only combinations of diagnosis of symptomatic infections and contact tracing that are almost perfect in terms of speed and coverage can attain control, unless additional measures to reduce overall community transmission are in place. Under constraints on the testing or tracing capacity, a temporary interruption of contact tracing may, depending on the overall growth rate and prevalence of the infection, lead to an irreversible loss of control even when the epidemic was previously contained.

scholarly journals Mathematical modeling of the SARS-CoV-2 epidemic in Qatar and its impact on the national response to COVID-19

2020 ◽  
Author(s):  
Houssein H. Ayoub ◽  
Hiam Chemaitelly ◽  
Shaheen Seedat ◽  
Monia Makhoul ◽  
Zaina Al Kanaani ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Acute Care ◽  
Hospital Admissions ◽  
Deterministic Model ◽  
Infection Prevalence ◽  
Care Hospital ◽  
Healthcare Needs ◽  
National Response ◽  
The Impact ◽  
Second Wave

AbstractBackgroundMathematical modeling constitutes an important tool for planning robust responses to epidemics. This study was conducted to guide the Qatari national response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic. The study investigated the time course of the epidemic, forecasted healthcare needs, predicted the impact of social and physical distancing restrictions, and rationalized and justified easing of restrictions.MethodsAn age-structured deterministic model was constructed to describe SARS-CoV-2 transmission dynamics and disease progression throughout the population.ResultsThe enforced social and physical distancing interventions flattened the epidemic curve, reducing the peaks for incidence, prevalence, acute-care hospitalization, and intensive care unit (ICU) hospitalizations by 87%, 86%, 76%, and 78%, respectively. The daily number of new infections was predicted to peak at 12,750 on May 23, and active-infection prevalence was predicted to peak at 3.2% on May 25. Daily acute-care and ICU-care hospital admissions and occupancy were forecast accurately and precisely. By October 15, 2020, the basic reproduction number R0 had varied between 1.07-2.78, and 50.8% of the population were estimated to have been infected (1.43 million infections). The proportion of actual infections diagnosed was estimated at 11.6%. Applying the concept of Rt tuning, gradual easing of restrictions was rationalized and justified to start on June 15, 2020, when Rt declined to 0.7, to buffer the increased interpersonal contact with easing of restrictions and to minimize the risk of a second wave. No second wave has materialized as of October 15, 2020, five months after the epidemic peak.ConclusionsUse of modeling and forecasting to guide the national response proved to be a successful strategy, reducing the toll of the epidemic to a manageable level for the healthcare system.

scholarly journals Investigating the effectiveness of re-opening policies before vaccination during a pandemic: SD modelling research based on COVID-19 in Wuhan

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ying Qian ◽  
Wei Xie ◽  
Jidi Zhao ◽  
Ming Xue ◽  
Shiyong Liu ◽  
...  
Keyword(s):  
Model Simulation ◽  
Control Measures ◽  
World Health ◽  
Contact Tracing ◽  
Infection Prevention And Control ◽  
Real World Data ◽  
Medical Resources ◽  
Health Organization ◽  
The Impact ◽  
Different Levels

Abstract Background Lockdown policies were widely adopted during the coronavirus disease 2019 (COVID-19) pandemic to control the spread of the virus before vaccines became available. These policies had significant economic impacts and caused social disruptions. Early re-opening is preferable, but it introduces the risk of a resurgence of the epidemic. Although the World Health Organization has outlined criteria for re-opening, decisions on re-opening are mainly based on epidemiologic criteria. To date, the effectiveness of re-opening policies remains unclear. Methods A system dynamics COVID-19 model, SEIHR(Q), was constructed by integrating infection prevention and control measures implemented in Wuhan into the classic SEIR epidemiological model and was validated with real-world data. The input data were obtained from official websites and the published literature. Results The simulation results showed that track-and-trace measures had significant effects on the level of risk associated with re-opening. In the case of Wuhan, where comprehensive contact tracing was implemented, there would have been almost no risk associated with re-opening. With partial contact tracing, re-opening would have led to a minor second wave of the epidemic. However, if only limited contact tracing had been implemented, a more severe second outbreak of the epidemic would have occurred, overwhelming the available medical resources. If the ability to implement a track-trace-quarantine policy is fixed, the epidemiological criteria need to be further taken into account. The model simulation revealed different levels of risk associated with re-opening under different levels of track-and-trace ability and various epidemiological criteria. A matrix was developed to evaluate the effectiveness of the re-opening policies. Conclusions The SEIHR(Q) model designed in this study can quantify the impact of various re-opening policies on the spread of COVID-19. Integrating epidemiologic criteria, the contact tracing policy, and medical resources, the model simulation predicts whether the re-opening policy is likely to lead to a further outbreak of the epidemic and provides evidence-based support for decisions regarding safe re-opening during an ongoing epidemic. Keyords COVID-19; Risk of re-opening; Effectiveness of re-opening policies; IPC measures; SD modelling.

scholarly journals Early estimates of COVID-19 infections in small, medium and large population clusters

2020 ◽  
Vol 5 (9) ◽  
pp. e003055
Author(s):  
Amir Siraj ◽  
Alemayehu Worku ◽  
Kiros Berhane ◽  
Maru Aregawi ◽  
Munir Eshetu ◽  
...  
Keyword(s):  
Large Population ◽  
Face Mask ◽  
Sub Saharan Africa ◽  
Contact Tracing ◽  
Local Context ◽  
African Region ◽  
Social Distancing ◽  
Population Sizes ◽  
Sub Saharan ◽  
The Impact

IntroductionSince its emergence in late December 2019, COVID-19 has rapidly developed into a pandemic in mid of March with many countries suffering heavy human loss and declaring emergency conditions to contain its spread. The impact of the disease, while it has been relatively low in the sub-Saharan Africa (SSA) as of May 2020, is feared to be potentially devastating given the less developed and fragmented healthcare system in the continent. In addition, most emergency measures practised may not be effective due to their limited affordability as well as the communal way people in SSA live in relative isolation in clusters of large as well as smaller population centres.MethodsTo address the acute need for estimates of the potential impacts of the disease once it sweeps through the African region, we developed a process-based model with key parameters obtained from recent studies, taking local context into consideration. We further used the model to estimate the number of infections within a year of sustained local transmissions under scenarios that cover different population sizes, urban status, effectiveness and coverage of social distancing, contact tracing and usage of cloth face mask.ResultsWe showed that when implemented early, 50% coverage of contact tracing and face mask, with 33% effective social distancing policies can bringing the epidemic to a manageable level for all population sizes and settings we assessed. Relaxing of social distancing in urban settings from 33% to 25% could be matched by introduction and maintenance of face mask use at 43%.ConclusionsIn SSA countries with limited healthcare workforce, hospital resources and intensive care units, a robust system of social distancing, contact tracing and face mask use could yield in outcomes that prevent several millions of infections and thousands of deaths across the continent.

scholarly journals Modelling pertussis transmission to evaluate the effectiveness of an adolescent booster in Argentina

2012 ◽  
Vol 141 (4) ◽  
pp. 718-734 ◽  
Author(s):  
G. FABRICIUS ◽  
P. E. BERGERO ◽  
M. E. ORMAZABAL ◽  
A. L. MALTZ ◽  
D. F. HOZBOR
Keyword(s):  
Booster Dose ◽  
Deterministic Model ◽  
Risk Group ◽  
Age Group ◽  
Vulnerable Group ◽  
Vaccination Strategies ◽  
Epidemiological Features ◽  
Age Structured ◽  
The Impact ◽  
Positive Effect

SUMMARYDue to the current epidemiological situation of pertussis, several countries have implemented vaccination strategies that include a booster dose for adolescents. Since there is still no evidence showing that the adolescent booster has a positive effect on the most vulnerable group represented by infants, it is difficult to universalize the recommendation to include such reinforcement. In this work we present an age-structured compartmental deterministic model that considers the outstanding epidemiological features of the disease in order to assess the impact of the booster dose at age 11 years (Tdap booster) to infants. To this end, we performed different parameterizations of the model that represent distinct possible epidemiological scenarios. The results obtained show that the inclusion of a single Tdap dose at age 11 years significantly reduces the incidence of the disease within this age group, but has a very low impact on the risk group (0–1 year). An effort to improve the coverage of the first dose would have a much greater impact on infants. These results hold in the 18 scenarios considered, which demonstrates the robustness of these conclusions.

scholarly journals Modelling the impact of extended vaccination strategies on the epidemiology of pertussis

2011 ◽  
Vol 140 (8) ◽  
pp. 1503-1514 ◽  
Author(s):  
M. H. ROZENBAUM ◽  
R. De VRIES ◽  
H. H. LE ◽  
M. J. POSTMA
Keyword(s):  
Booster Dose ◽  
Deterministic Model ◽  
Natural Infection ◽  
Age Groups ◽  
Vaccination Strategy ◽  
Booster Vaccination ◽  
Sensitivity Analyses ◽  
Wide Range ◽  
Age Structured ◽  
The Impact

SUMMARYThe aim of this study was to investigate the optimal pertussis booster vaccination strategy for The Netherlands. A realistic age-structured deterministic model was designed. Assuming a steady-state situation and correcting for underreporting, the model was calibrated using notification data from the period 1996–2000. Several sensitivity analyses were performed to explore the impact of different assumptions for parameters surrounded by uncertainty (e.g. duration of protection after natural infection, underreporting factors, and transmission probabilities). The optimal age of an additional booster dose is in the range of 10–15 years, and implementation of this booster dose will reduce both symptomatic and asymptomatic infections, although the incidence of symptomatic infections in older age groups will increase. The impact of the different assumptions used in the model was in general limited. We conclude that over a wide range of assumptions, an additional booster dose can reduce the incidence of pertussis in the population.

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

2021 ◽  
Author(s):  
Louise Dyson ◽  
Edward M Hill ◽  
Sam Moore ◽  
Jacob Curran-Sebastian ◽  
Michael J Tildesley ◽  
...  
Keyword(s):  
Immune Escape ◽  
Deterministic Model ◽  
Control Measures ◽  
Transmission Model ◽  
Vaccination Rates ◽  
Infection Dynamics ◽  
Potential Impact ◽  
Age Structured ◽  
Ongoing Infection ◽  
Viral Reproduction

Ongoing infection with, and associated viral reproduction of, SARS-CoV-2 provides opportunities for the virus to acquire advantageous mutations, which may alter viral transmissibility and disease severity, and allow escape from natural or vaccine-derived immunity. The number of countries reporting Variants of Concern (VOCs) with such mutations continues to rise. Here, we investigate two scenarios for third waves of the COVID pandemic: one driven by increased transmissibility, and another driven by immune escape. We do this using three mathematical models: a parsimonious susceptible-latent-infectious-recovered (SEIR) deterministic model with homogeneous mixing, an age-structured SARS-CoV-2 transmission model and a stochastic importation model. We calibrated our models to the situation in England in May 2021, although the insights will generalise to other contexts. We therefore accurately captured infection dynamics and vaccination rates, and also used these to explore the potential impact of a putative new VOC-targeted vaccine. Epidemiological trajectories for putative VOCs are wide-ranging and heavily dependent on their transmissibility, immune escape capability, and the time at which a postulated VOC-targeted vaccine may be introduced. We demonstrate that a VOC with either a substantial transmission advantage over resident variants, or the ability to evade vaccine-derived and prior immunity, is expected to generate a wave of infections and hospitalisations comparable to those seen in the winter 2020-21 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.

scholarly journals Impact of public health interventions on the COVID-19 epidemic: a stochastic model based on data from an African island

2020 ◽  
Author(s):  
D. C. Nuckchady
Keyword(s):  
Stochastic Model ◽  
Population Surveillance ◽  
Health Interventions ◽  
Contact Tracing ◽  
Point Of Entry ◽  
Highly Sensitive ◽  
Travel Restrictions ◽  
Community Transmission ◽  
The Impact ◽  
Key Interventions

AbstractA stochastic model was created to simulate the impact of various healthcare measures on the COVID-19 epidemic. Travel restrictions and point of entry or exit screening help to delay the onset of the outbreak by a few weeks. Population surveillance is critical to detect the start of community transmission early and to avoid a surge in cases. Contact reduction and contact tracing are key interventions that can help to control the outbreak. To promptly curb the number of new cases, countries should diagnose patients using a highly sensitive test.

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