scholarly journals Early transmission dynamics and control of COVID-19 in a southern hemisphere setting: Lima-Peru, February 29th-March 30th, 2020

2020 ◽  
Author(s):  
César V. Munayco ◽  
Amna Tariq ◽  
Gabriela G Soto-Cabezas ◽  
Mary F. Reyes ◽  
Andree Valle ◽  
...  
Keyword(s):  
Exponential Growth ◽  
Linear Growth ◽  
Great Majority ◽  
Transmission Dynamics ◽  
Growth Trend ◽  
Social Distancing ◽  
Transmission Potential ◽  
First Case ◽  
Dynamics And Control ◽  
The Government

AbstractThe COVID-19 pandemic that emerged in Wuhan China rapidly spread around the world. The daily incidence trend has been rapidly rising in Latin America since March 2020 with the great majority of the cases reported in Brazil (28320) followed by Peru (11475) as of April 15th, 2020. Although Peru implemented social distancing measures soon after the confirmation of its first case on March 6th, 2020, the daily number of new COVID-19 cases continues to increase. We assessed the early COVID-19 transmission dynamics and the effect of social distancing interventions in Lima, Peru.We estimate the transmission potential of COVID-19, R, during the early phase of the outbreak, from the daily series of imported and autochthonous cases by the date of symptoms onset as of March 30th, 2020. We also assessed the effect of social distancing interventions in Lima by generating short-term forecasts grounded on the early transmission dynamics before interventions were put in place.Prior to the implementation of the social distancing measures in Lima, we estimated the reproduction number at 2.3 (95% CI: 2.0, 2.5). Our analysis indicates that school closures and other social distancing interventions have helped stem the spread of the virus, with the nearly exponential growth trend shifting to an approximately linear growth trend after the national emergency declaration.The COVID-19 epidemic in Lima followed an early exponential growth trend, which slowed down and turned into an almost linear growth trend after broad scale social distancing interventions were put in place by the government.Peru COVID-19 working group

scholarly journals Transmission dynamics and control of COVID-19 in Chile, March-October, 2020

2020 ◽  
Author(s):  
Amna Tariq ◽  
Eduardo A. Undurraga ◽  
Carla Castillo Laborde ◽  
Katia Vogt-Geisse ◽  
Ruiyan Luo ◽  
...  
Keyword(s):  
Low Income ◽  
Exponential Growth ◽  
Reproduction Number ◽  
Growth Parameter ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Virus Spread ◽  
Growth Trend ◽  
Social Distancing ◽  
First Case

Since the detection of the first case of COVID-19 in Chile on March 3rd, 2020, a total of 513188 cases, including ~14302 deaths have been reported in Chile as of November 2nd, 2020. Here, we estimate the reproduction number throughout the epidemic in Chile and study the effectiveness of control interventions especially the effectiveness of lockdowns by conducting short-term forecasts based on the early transmission dynamics of COVID-19. Chile's incidence curve displays early sub-exponential growth dynamics with the deceleration of growth parameter, p, estimated at 0.8 (95% CI: 0.7, 0.8) and the reproduction number, R, estimated at 1.8 (95% CI: 1.6, 1.9). Our findings indicate that the control measures at the start of the epidemic significantly slowed down the spread of the virus. However, the relaxation of restrictions and spread of the virus in low-income neighborhoods in May led to a new surge of infections, followed by the reimposition of lockdowns in Greater Santiago and other municipalities. These measures have decelerated the virus spread with R estimated at ~0.96( 95% CI: 0.95, 0.98) as of November 2nd, 2020. The early sub-exponential growth trend (p ~0.8) of the COVID-19 epidemic transformed into a linear growth trend (p ~0.5) as of July 7th, 2020, after the reimposition of lockdowns. While the broad scale social distancing interventions have slowed the virus spread, the number of new COVID-19 cases continue to accrue, underscoring the need for persistent social distancing and active case detection and isolation efforts to maintain the epidemic under control.

scholarly journals Transmission dynamics and control of COVID-19 in Chile, March-October, 2020

2021 ◽  
Vol 15 (1) ◽  
pp. e0009070
Author(s):  
Amna Tariq ◽  
Eduardo A. Undurraga ◽  
Carla Castillo Laborde ◽  
Katia Vogt-Geisse ◽  
Ruiyan Luo ◽  
...  
Keyword(s):  
Low Income ◽  
Exponential Growth ◽  
Reproduction Number ◽  
Growth Parameter ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Virus Spread ◽  
Growth Trend ◽  
Social Distancing ◽  
First Case

Since the detection of the first case of COVID-19 in Chile on March 3rd, 2020, a total of 513,188 cases, including ~14,302 deaths have been reported in Chile as of November 2nd, 2020. Here, we estimate the reproduction number throughout the epidemic in Chile and study the effectiveness of control interventions especially the effectiveness of lockdowns by conducting short-term forecasts based on the early transmission dynamics of COVID-19. Chile’s incidence curve displays early sub-exponential growth dynamics with the deceleration of growth parameter, p, estimated at 0.8 (95% CI: 0.7, 0.8) and the reproduction number, R, estimated at 1.8 (95% CI: 1.6, 1.9). Our findings indicate that the control measures at the start of the epidemic significantly slowed down the spread of the virus. However, the relaxation of restrictions and spread of the virus in low-income neighborhoods in May led to a new surge of infections, followed by the reimposition of lockdowns in Greater Santiago and other municipalities. These measures have decelerated the virus spread with R estimated at ~0.96 (95% CI: 0.95, 0.98) as of November 2nd, 2020. The early sub-exponential growth trend (p ~0.8) of the COVID-19 epidemic transformed into a linear growth trend (p ~0.5) as of July 7th, 2020, after the reimposition of lockdowns. While the broad scale social distancing interventions have slowed the virus spread, the number of new COVID-19 cases continue to accrue, underscoring the need for persistent social distancing and active case detection and isolation efforts to maintain the epidemic under control.

scholarly journals Early transmission dynamics of SARS-CoV-2 in Indonesia

2021 ◽  
Vol 1 (1) ◽  
pp. 1-6
Author(s):  
Mudatsir Mudatsir ◽  
Synat Keam ◽  
Wira Winardi ◽  
Amanda Yufika ◽  
Ali A. Rabaan ◽  
...  
Keyword(s):  
Surveillance System ◽  
Disease Surveillance ◽  
Capital City ◽  
Transmission Dynamics ◽  
Disease Surveillance System ◽  
First Case ◽  
Directorate General ◽  
The Government ◽  
And Control ◽  
Importation Risk

The objective of this study was to determine the transmission dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and to evaluate the vigilance of the health system during the early phase of coronavirus disease 2019 (COVID-19) outbreak in Indonesia. The early epidemiology and transmission chains of COVID-19 were analyzed based on data from the Directorate General of Disease Prevention and Control of the Indonesian Ministry of Health. The results of this study shown although Indonesia is a country with a high relative importation risk of SARS-CoV-2, the first two cases of COVID-19 were identified on March 2, 2020. This relatively late date by regional standards raises the possibility of undetected cases beforehand. The first case was a foreigner citizen who visited the capital city of Jakarta and later was diagnosed COVID-19 after returning from Indonesia. One week later after the first case, 27 confirmed COVID-19 cases had been reported in Indonesia, and the majority of the cases were clustered together. Apart from the possibility of underdetection of COVID-19 cases in the country, the government has strengthened the disease surveillance system and established an outbreak preparedness system to diagnose and control COVID-19. 

scholarly journals COVID-19 epidemic in Sri Lanka: A mathematical and computational modelling approach to control

2020 ◽  
Author(s):  
WPTM Wickramaarachchi ◽  
SSN Perera ◽  
S Jayasignhe
Keyword(s):  
Sri Lanka ◽  
Computational Modelling ◽  
Control Measures ◽  
Critical Parameters ◽  
World Population ◽  
Sri Lankan ◽  
Social Distancing ◽  
First Case ◽  
Local Case ◽  
The Government

AbstractThe ongoing COVID19 outbreak originated in the city of Wuhan, China has caused a significant damage to the world population and the global economy. It has claimed more than 50,000 lives worldwide and more than one million of people have been infected as of 04th April 2020.In Sri Lanka, the first case of COVI19 was reported late January 2020 was a Chinese national and the first local case was identified in the second week of March. Since then, the government of Sri Lanka introduced various sequential measures to improve social distancing such as closure of schools and education institutes, introducing work from home model to reduce the public gathering, introducing travel bans to international arrivals and more drastically, imposed island wide curfew expecting to minimize the burden of the disease to the Sri Lankan health system and the entire community. Currently, there are 159 cases with five fatalities and also reported that 24 patients are recovered and discharged from hospitals.In this study, we use the SEIR conceptual model and its modified version by decomposing infected patients into two classes; patients who show mild symptoms and patients who tend to face severe respiratory problems and are required to treat in intensive care units. We numerically simulate the models for about five months period considering three critical parameters of COVID transmission mainly in the Sri Lankan context; efficacy of control measures, rate of overseas imported cases and time to introduce social distancing measures by the respective authorities.

scholarly journals Fractional-order mathematical model for analysing impact of quarantine on transmission of COVID-19 in India

2021 ◽  
Vol 8 (2) ◽  
pp. 253-266
Author(s):  
D. D. Pawar ◽  
◽  
W. D. Patil ◽  
D. K. Raut ◽  
◽  
...  
Keyword(s):  
Mathematical Model ◽  
Fractional Order ◽  
Local Population ◽  
Euler Method ◽  
Transmission Dynamics ◽  
The Novel ◽  
First Case ◽  
Physical Interactions ◽  
The Government ◽  
Novel Coronavirus

An outbreak of the novel coronavirus disease was first reported in Wuhan, China in December 2019. In India, the first case was reported on January 30, 2020 on a person with a travel history to an affected country. Considering the fact of a heavily populated and diversified country like India, we have proposed a novel fractional-order mathematical model to elicit the transmission dynamics of the coronavirus disease (COVID-19) and the control strategy for India. The classical SEIR model is employed in three compartments, namely: quarantined immigrated population, non-quarantined asymptomatic immigrated population, and local population subjected to lockdown in the containment areas by the government of India to prevent the spread of disease in India. We have also taken into account the physical interactions between them to evaluate the coronavirus transmission dynamics. The basic reproduction number ($R_{0}$) has been derived to determine the communicability of the disease. Numerical simulation is done by using the generalised Euler method. To check the feasibility of our analysis, we have investigated some numerical simulations for various fractional orders by varying values of the parameters with help of MATLAB to fit the realistic pandemic scenario.

scholarly journals 100 Days of COVID-19 in India: Current and Future Trends

2020 ◽  
Vol 14 (suppl 1) ◽  
pp. 1043-1052
Author(s):  
Sheetal Gouda ◽  
G. Naveen ◽  
F. Sneha Kukanur
Keyword(s):  
Emerging Infectious Diseases ◽  
Sigmoid Function ◽  
Current Time ◽  
Social Distancing ◽  
Current Trends ◽  
First Case ◽  
Novel Approach ◽  
Sigmoid Curve ◽  
The Government ◽  
And Control

COVID-19 classified under emerging infectious diseases has spread across the world resulting in many casualties. India reported its first case on 30th January 2020 and has completed 100 days in this pandemic period. The government of India has issued stringent guidelines and imposed a lockdown for long periods to ensure the practising of social distancing. This paper reviews and discusses the current trends in the confirmed cases of India in comparison with the other prominent countries around the globe. A novel approach using a sigmoid function to predict and forecast the trends for cases in India are also presented in this work. By placing the current time on the sigmoid curve, forecasting the total number of confirmed cases by the end of the pandemic is made. If proper measures and stringent guidelines are not followed, India may have to endure a total confirmed case of up to 4.4 lakh. The prediction also suggests that 99.9% of the pandemic may end in India by 27th July 2020. The best possible approach is to undertake preventive measures by strictly adhering to the guidelines and policies set by the government. Performing hand hygiene, practicing social distancing, surveillance and isolation is the only means to break the chain of transmission and control the pandemic.

Optimal Control of Fractional Order COVID-19 Epidemic Spreading in Japan and India 2020

2020 ◽  
Vol 15 (04) ◽  
pp. 207-236 ◽  
Author(s):  
Meghadri Das ◽  
G. P. Samanta
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Incomplete Information ◽  
Fractional Order ◽  
Compartmental Model ◽  
Transmission Dynamics ◽  
Epidemic Spreading ◽  
Social Distancing ◽  
First Case

In Japan, the first case of Coronavirus disease 2019 (COVID-19) was reported on 15th January 2020. In India, on 30th January 2020, the first case of COVID-19 in India was reported in Kerala and the number of reported cases has increased rapidly. The main purpose of this work is to study numerically the epidemic peak for COVID-19 disease along with transmission dynamics of COVID-19 in Japan and India 2020. Taking into account the uncertainty due to the incomplete information about the coronavirus (COVID-19), we have taken the Susceptible-Asymptomatic-Infectious-Recovered (SAIR) compartmental model under fractional order framework for our study. We have also studied the effects of fractional order along with other parameters in transfer dynamics and epidemic peak control for both the countries. An optimal control problem has been studied by controlling social distancing parameter.

scholarly journals How to evaluate the success of the COVID-19 measures implemented by the Norwegian government by analyzing changes in doubling time

2020 ◽  
Author(s):  
Biljana Stangeland
Keyword(s):  
Real Time ◽  
Exponential Growth ◽  
Doubling Time ◽  
Growth Curves ◽  
Nordic Countries ◽  
Cumulative Number ◽  
Social Distancing ◽  
Health Authorities ◽  
The Government ◽  
Day By Day

AbstractDoubling Time (DT) is typically calculated for growth curves that show exponential growth, such as the cumulative number of COVID-19 cases day by day. DT represents the time it takes before the number of COVID-19 cases, in a certain country or area, doubles.Throughout the ongoing COVID-19 outbreak, DT values are continually changing. These changes are influenced by the measures that are recommended by the health authorities and implemented by governments.After the government-imposed shutdowns of Nordic Countries that were announced around the 12th of March 2020, we followed the development of the DT in the region. Governments put in place measures never before experienced during peace time; working from home, closed schools and kindergartens, travel bans and social distancing. We conducted analyses to evaluate the effectiveness of these measures. Does it work? The initial set of results following the shutdown are encouraging, demonstrating a trend towards slower growth; however, this could be reversed if the measures that are in place now are abandoned too early. Premature optimism can be very costly. In this report we describe a method for monitoring the epidemic in real time and evaluating the effectiveness of the implemented measures.

scholarly journals Progression of COVID-19 in Indian States - Forecasting Endpoints Using SIR and Logistic Growth Models

2020 ◽  
Author(s):  
Bhoomika Malhotra ◽  
Vishesh Kashyap
Keyword(s):  
Growth Model ◽  
Sir Model ◽  
Logistic Growth ◽  
Indian States ◽  
Health Crisis ◽  
Social Distancing ◽  
First Case ◽  
Logistic Growth Model ◽  
The Government ◽  
The Impact

COVID-19 has led to the most widespread public health crisis in recent history. The first case of the disease was detected in India on 31 January 2019, and confirmed cases stand at 74,281 as of 13 May 2020. Mathematical modeling can be utilized to forecast the final numbers as well as the endpoint of the disease in India and its states, as well as assess the impact of social distancing measures. In the present work, the Susceptible-Infected-Recovered (SIR) model and the Logistic Growth model have been implemented to predict the endpoint of COVID-19 in India as well as three states accounting for over 55% of the total cases - Maharashtra, Gujarat and Delhi. The results using the SIR model indicate that the disease will reach an endpoint in India on 12 September, while Maharashtra, Gujarat and Delhi will reach endpoints on 20 August, 30 July and 9 September respectively. Using the Logistic Regression model, the endpoint for India is predicted on 23 July, while that for Maharashtra, Gujarat and Delhi is 5 July, 23 June and 10 August respectively. It is also observed that the case numbers predicted by the SIR model are greater than those for the Logistic Growth model in each case. The results suggest that the lockdown enacted by the Government of India has had only a moderate impact on the spread of COVID-19, and emphasize the need for firm implementation of social distancing guidelines.

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