scholarly journals COVID-19 epidemic scenarios into 2021 based on observed key superdispersion events

2021 ◽  
Author(s):  
Mario Santana-Cibrian ◽  
M. Adrian Acuña-Zegarra ◽  
Carlos E. Rodríguez Hernández-Vela ◽  
Jorge X. Velasco-Hernandez ◽  
Ramsés H. Mena
Keyword(s):  
Time Scale ◽  
Reproduction Number ◽  
Social Activity ◽  
Time Dependent ◽  
Contact Rate ◽  
Main Assumption ◽  
Effective Contact ◽  
Incidence And Mortality ◽  
The Status ◽  
Calendar Dates

Key high transmission dates for the year 2020 are used to create scenarios to model the evolution of the COVID-19 pandemic in several states of Mexico for 2021. These scenarios are obtained through the estimation of a time-dependent contact rate, where the main assumption is that the dynamic of the disease is heavily determined by the mobility and social activity of the population during holidays and other important calendar dates. First, changes in the effective contact rate on predetermined dates of 2020 are estimated. Then, using the instantaneous reproduction number to characterize the status of the epidemic (Rt ≈ 1, Rt > 1 or Rt < 1), this information is used to propose different scenarios for the number of cases and deaths for 2021. The main assumption is that the effective contact rate during 2021 will maintain a similar trend to that observed during 2020 on key calendar dates. All other conditions are assumed to remain constant in the time scale of the projections. The objective is to generate a range of scenarios that could be useful to evaluate the possible evolution of the epidemic and its likely impact on incidence and mortality.

scholarly journals Fractional SIR-Model for Estimating Transmission Dynamics of COVID-19 in India

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 86-100
Author(s):  
Nita H. Shah ◽  
Ankush H. Suthar ◽  
Ekta N. Jayswal ◽  
Ankit Sikarwar
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Sir Model ◽  
Time Dependent ◽  
Contact Rate ◽  
Distribution Maps ◽  
Fundamental Parameters ◽  
Different Order ◽  
The Basic Reproduction Number

In this article, a time-dependent susceptible-infected-recovered (SIR) model is constructed to investigate the transmission rate of COVID-19 in various regions of India. The model included the fundamental parameters on which the transmission rate of the infection is dependent, like the population density, contact rate, recovery rate, and intensity of the infection in the respective region. Looking at the great diversity in different geographic locations in India, we determined to calculate the basic reproduction number for all Indian districts based on the COVID-19 data till 7 July 2020. By preparing district-wise spatial distribution maps with the help of ArcGIS 10.2, the model was employed to show the effect of complete lockdown on the transmission rate of the COVID-19 infection in Indian districts. Moreover, with the model's transformation to the fractional ordered dynamical system, we found that the nature of the proposed SIR model is different for the different order of the systems. The sensitivity analysis of the basic reproduction number is done graphically which forecasts the change in the transmission rate of COVID-19 infection with change in different parameters. In the numerical simulation section, oscillations and variations in the model compartments are shown for two different situations, with and without lockdown.

Analysis of follow-up data

2020 ◽  
pp. 93-118
Author(s):  
Bendix Carstensen
Keyword(s):  
Data Collection ◽  
Time Scale ◽  
Poisson Regression ◽  
Time Dependent ◽  
Follow Up Study ◽  
Dependent Variables ◽  
The Status ◽  
Over Time

This chapter assesses the analysis and representation of follow-up data. follow-up refers to the process of monitoring persons over time for occurrence of a (set of) prespecified event(s). Practical data collection is often via look-up in registers or databases. The basic requirements for recordings in a follow-up study include date of entry to the study, date of exit from the study, and the status of the person at the exit date. The chapter then explains the likelihood from a follow-up study and why one can analyse rates using Poisson regression. The likelihood contribution from a single person's follow-up can be subdivided in contributions from subintervals of the follow-up. The chapter details the task of splitting the follow-up time along a time-scale. Finally, it considers time-dependent variables.

scholarly journals A co-infection model for HPV and syphilis with optimal control and cost-effectiveness analysis

2021 ◽  
pp. 2150050
Author(s):  
A. Omame ◽  
D. Okuonghae ◽  
U. E. Nwafor ◽  
B. U. Odionyenma
Keyword(s):  
Optimal Control ◽  
Cost Effectiveness ◽  
Reproduction Number ◽  
Infection Model ◽  
Contact Rate ◽  
Demographic Parameter ◽  
Effective Contact ◽  
Number Formula ◽  
Syphilis Treatment ◽  
Disease Free

A co-infection model for human papillomavirus (HPV) and syphilis with cost-effectiveness optimal control analysis is developed and presented. The full co-infection model is shown to undergo the phenomenon of backward bifurcation when a certain condition is satisfied. The global asymptotic stability of the disease-free equilibrium of the full model is shown not to exist when the associated reproduction number is less than unity. The existence of endemic equilibrium of the syphilis-only sub-model is shown to exist and the global asymptotic stability of the disease-free and endemic equilibria of the syphilis-only sub-model was established, for a special case. Sensitivity analysis is also carried out on the parameters of the model. Using the syphilis associated reproduction number, [Formula: see text], as the response function, it is observed that the five-ranked parameters that drive the dynamics of the co-infection model are the demographic parameter [Formula: see text], the effective contact rate for syphilis transmission, [Formula: see text], the progression rate to late stage of syphilis [Formula: see text], and syphilis treatment rates: [Formula: see text] and [Formula: see text] for co-infected individuals in compartments [Formula: see text] and [Formula: see text], respectively. Moreover, when the HPV associated reproduction number, [Formula: see text], is used as the response function, the five most dominant parameters that drive the dynamics of the model are the demographic parameter [Formula: see text], the effective contact rate for HPV transmission, [Formula: see text], the fraction of HPV infected who develop persistent HPV [Formula: see text], the fraction of individuals vaccinated against incident HPV infection [Formula: see text] and the HPV vaccine efficacy [Formula: see text]. Numerical simulations of the optimal control model showed that the optimal control strategy which implements syphilis treatment controls for singly infected individuals is the most cost-effective of all the control strategies in reducing the burden of HPV and syphilis co-infections.

scholarly journals Effect of 2021 Assembly Election in India on Covid-19 Transmission

2021 ◽  
Author(s):  
Souvik Manik ◽  
Sabyasachi Pal ◽  
Manoj Mandal ◽  
Mangal Hazra
Keyword(s):  
Bound States ◽  
Reproduction Number ◽  
Contact Rate ◽  
Mathematical Functions ◽  
Political Activities ◽  
Effective Contact ◽  
The Impact ◽  
Second Wave ◽  
Election Commission ◽  
Union Territory

India is one of the countries in the world which is badly affected by the Covid-19 second wave. Assembly election in four states and a union territory of India was taken place during March-May 2021 when the Covid-19 second wave was close to its peak and affected a huge number of people. We studied the impact of assembly election on the effective contact rate and the effective reproduction number of Covid-19 using different epidemiological models like SIR, SIRD, and SEIR. We also modeled the effective reproduction number for all election-bound states using different mathematical functions. We separately studied the case of all election-bound states and found all the states shown a distinct increase in the effective contact rate and the effective reproduction number during the election-bound time and just after that compared to pre-election time. States, where elections were conducted in single-phase, showed less increase in the effective contact rate and the reproduction number. The election commission imposed extra measures from the first week of April 2021 to restrict big campaign rallies, meetings, and different political activities. The effective contact rate and the reproduction number showed a trend to decrease for few states due to the imposition of the restrictions. We also compared the effective contact rate, and the effective reproduction number of all election-bound states and the rest of India and found all the parameters related to the spread of virus for election-bound states are distinctly high compared to the rest of India.

scholarly journals A data first approach to modelling Covid-19

2020 ◽  
Author(s):  
Jayanti Prasad
Keyword(s):  
Reproduction Number ◽  
Model Fitting ◽  
Time Dependent ◽  
Primary Data ◽  
Contact Rate ◽  
Multiple Sources ◽  
Transmission Coefficients ◽  
Varying Coefficients ◽  
Step Procedure ◽  
Time Varying Coefficients

AbstractThe primary data for Covid-19 pandemic is in the form of time series for the number of confirmed, recovered and dead cases. This data is updated every day and is available for most countries from multiple sources such as [Gar20b, iD20]. In this work we present a two step procedure for model fitting to Covid-19 data. In the first step, time dependent transmission coefficients are constructed directly from the data and, in the second step, measures of those (minimum, maximum, mean, median etc.,) are used to set priors for fitting models to data. We call this approach a “data driven approach” or “data first approach”. This scheme is complementary to Bayesian approach and can be used with or without that for parameter estimation. We use the procedure to fit a set of SIR and SIRD models, with time dependent contact rate, to Covid-19 data for a set of most affected countries. We find that SIR and SIRD models with constant transmission coefficients cannot fit Covid-19 data for most countries (mainly because social distancing, lockdown etc., make those time dependent). We find that any time dependent contact rate decaying with time can help to fit SIR and SIRD models for most of the countries. We also present constraints on transmission coefficients and basic reproduction number , as well as effective reproduction number . The main contributions of our work are as follows. (1) presenting a two step procedure for model fitting to Covid-19 data (2) constraining transmission coefficients as well as and , for a set of countries and (3) releasing a python package PyCov19 [Pra20b] that can used to fit a class of compartmental models, with time varying coefficients, to Covid-19 data.

scholarly journals Dynamics of COVID-19 pandemic at constant and time-dependent contact rates

2020 ◽  
Author(s):  
Marek Kochańczyk ◽  
Frederic Grabowski ◽  
Tomasz Lipniacki
Keyword(s):  
Reproduction Number ◽  
Exponential Phase ◽  
Time Dependent ◽  
Therapeutic Interventions ◽  
Contact Rate ◽  
Epidemic Spread ◽  
Early Exponential Phase ◽  
Contact Rates ◽  
Multiplication Coefficient

We constructed a simple Susceptible–Infected–Infectious–Excluded model of the spread of COVID-19. The model is parametrised only by the average incubation period, τ, and two rate parameters: contact rate, rC, and exclusion rate, rE. The rates can be manipulated by non-therapeutic interventions and determine the basic reproduction number, R = rC/rE, and, together with τ, the daily multiplication coefficient at the early exponential phase, β. Initial β determines the reduction of rC required to contain epidemic spread. In the long-term, we consider a scenario based on typical social behaviours, in which rC first decreases in response to a surge of daily new cases, forcing people to self-isolate, and then slowly increases when people gradually accept higher risk. Consequently, initial abrupt epidemic spread is followed by a plateau and slow regression. This scenario, although economically and socially devastating, will grant time to develop, produce, and distribute a vaccine, or at least limit daily cases to a manageable number.

COVID-19: Time-Dependent Effective Reproduction Number and Sub-notification Effect Estimation Modeling (Preprint)

2020 ◽  
Author(s):  
Eduardo Atem De Carvalho ◽  
Rogerio Atem De Carvalho
Keyword(s):  
New York ◽  
Reproduction Number ◽  
Moving Average ◽  
Real Data ◽  
Time Dependent ◽  
Initial Value ◽  
Health Authorities ◽  
Reproduction Numbers ◽  
Effect Estimation ◽  
The Impact

BACKGROUND Since the beginning of the COVID-19 pandemic, researchers and health authorities have sought to identify the different parameters that govern their infection and death cycles, in order to be able to make better decisions. In particular, a series of reproduction number estimation models have been presented, with different practical results. OBJECTIVE This article aims to present an effective and efficient model for estimating the Reproduction Number and to discuss the impacts of sub-notification on these calculations. METHODS The concept of Moving Average Method with Initial value (MAMI) is used, as well as a model for Rt, the Reproduction Number, is derived from experimental data. The models are applied to real data and their performance is presented. RESULTS Analyses on Rt and sub-notification effects for Germany, Italy, Sweden, United Kingdom, South Korea, and the State of New York are presented to show the performance of the methods here introduced. CONCLUSIONS We show that, with relatively simple mathematical tools, it is possible to obtain reliable values for time-dependent, incubation period-independent Reproduction Numbers (Rt). We also demonstrate that the impact of sub-notification is relatively low, after the initial phase of the epidemic cycle has passed.

scholarly journals Stability analysis of a dynamical model of tuberculosis with incomplete treatment

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Ihsan Ullah ◽  
Saeed Ahmad ◽  
Qasem Al-Mdallal ◽  
Zareen A. Khan ◽  
Hasib Khan ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Contact Rate ◽  
Asymptotically Stable ◽  
Treatment Rate ◽  
Globally Asymptotically Stable ◽  
Reproduction Ratio ◽  
Efficient Treatment ◽  
Effective Contact ◽  
The Impact ◽  
Incomplete Treatment

Abstract A simple deterministic epidemic model for tuberculosis is addressed in this article. The impact of effective contact rate, treatment rate, and incomplete treatment versus efficient treatment is investigated. We also analyze the asymptotic behavior, spread, and possible eradication of the TB infection. It is observed that the disease transmission dynamics is characterized by the basic reproduction ratio $\Re _{0}$ ℜ 0 ; if $\Re _{0}<1$ ℜ 0 < 1 , there is only a disease-free equilibrium which is both locally and globally asymptotically stable. Moreover, for $\Re _{0}>1$ ℜ 0 > 1 , a unique positive endemic equilibrium exists which is globally asymptotically stable. The global stability of the equilibria is shown via Lyapunov function. It is also obtained that incomplete treatment of TB causes increase in disease infection while efficient treatment results in a reduction in TB. Finally, for the estimated parameters, some numerical simulations are performed to verify the analytical results. These numerical results indicate that decrease in the effective contact rate λ and increase in the treatment rate γ play a significant role in the TB infection control.

scholarly journals A simple criterion to design optimal non-pharmaceutical interventions for mitigating epidemic outbreaks

2021 ◽  
Vol 18 (178) ◽  
Author(s):  
Marco Tulio Angulo ◽  
Fernando Castaños ◽  
Rodrigo Moreno-Morton ◽  
Jorge X. Velasco-Hernández ◽  
Jaime A. Moreno
Keyword(s):  
Disease Transmission ◽  
Reproduction Number ◽  
Contact Rate ◽  
Simple Criterion ◽  
Societal Costs ◽  
Public Events ◽  
Maximum Decrease ◽  
Minimal Reduction ◽  
Theoretical Results ◽  
Pharmaceutical Interventions

For mitigating the COVID-19 pandemic, much emphasis is made on implementing non-pharmaceutical interventions to keep the reproduction number below one. However, using that objective ignores that some of these interventions, like bans of public events or lockdowns, must be transitory and as short as possible because of their significant economic and societal costs. Here, we derive a simple and mathematically rigorous criterion for designing optimal transitory non-pharmaceutical interventions for mitigating epidemic outbreaks. We find that reducing the reproduction number below one is sufficient but not necessary. Instead, our criterion prescribes the required reduction in the reproduction number according to the desired maximum of disease prevalence and the maximum decrease of disease transmission that the interventions can achieve. We study the implications of our theoretical results for designing non-pharmaceutical interventions in 16 cities and regions during the COVID-19 pandemic. In particular, we estimate the minimal reduction of each region’s contact rate necessary to control the epidemic optimally. Our results contribute to establishing a rigorous methodology to design optimal non-pharmaceutical intervention policies for mitigating epidemic outbreaks.

scholarly journals GREEN INFRASTRUCTURE SPACES AS AN INSTRUMENT PROMOTING YOUTH INTEGRATION AND PARTICIPATION IN LOCAL COMMUNITY

2018 ◽  
Vol 40 (1) ◽  
pp. 37-49 ◽  
Author(s):  
Agnieszka Jaszczak ◽  
Gintarė Vaznonienė ◽  
Bernardas Vaznonis
Keyword(s):  
Green Infrastructure ◽  
Local Community ◽  
Social Activity ◽  
Social Benefit ◽  
Community Research ◽  
Health Improvement ◽  
Activity Promotion ◽  
The Status ◽  
Local Actors

Insufficient analysis of green infrastructure spaces benefit to youth activity promotion in Lithuanian social sciences discourse enabled to formulate scientific problem – what can be possibilities of using green infrastructure spaces while strengthening youth integration and participation in local community? The aim of the article – after analyzing social benefit of green infrastructure spaces to youth, to determine their usage possibilities for strengthening youth integration and participation in local community. Research methods: scientific literature, document analysis and synthesis, abstraction and comparison methods. Šiauliai district Kuršėnai town environmentally directed school’s projects were analysed for the case study. For youth, green infrastructure spaces are the areas for environmental education, health improvement, strengthening of their integration and participation in local community through various activities. Youth gradually become involved into social activity where their status of a passive participant changes into the status of an active participant. Case study can be used by various local actors (other schools, community, teachers, parents etc.) strengthening integration and participation of youth in local community by using GI spaces.

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