scholarly journals Spreading of COVID-19 in Brazil: Impacts and uncertainties in social distancing strategies

Author(s):  
Diego T. Volpatto ◽  
Anna Claudia M. Resende ◽  
Lucas dos Anjos ◽  
João V. O. Silva ◽  
Claudia M. Dias ◽  
...  

AbstractBrazil’s continental dimension poses a challenge to the control of the spread of COVID-19. Due to the country specific scenario of high social and demographic heterogeneity, combined with limited testing capacity, lack of reliable data, under-reporting of cases, and restricted testing policy, the focus of this study is twofold: (i) to develop a generalized SEIRD model that implicitly takes into account the quarantine measures, and (ii) to estimate the response of the COVID-19 spread dynamics to perturbations/uncertainties. By investigating the projections of cumulative numbers of confirmed and death cases, as well as the effective reproduction number, we show that the model parameter related to social distancing measures is one of the most influential along all stages of the disease spread and the most influential after the infection peak. Due to such importance in the outcomes, different relaxation strategies of social distancing measures are investigated in order to determine which strategies are viable and less hazardous to the population. The results highlight the need of keeping social distancing policies to control the disease spread. Specifically, the considered scenario of abrupt social distancing relaxation implemented after the occurrence of the peak of positively diagnosed cases can prolong the epidemic, with a significant increase of the projected numbers of confirmed and death cases. An even worse scenario could occur if the quarantine relaxation policy is implemented before evidence of the epidemiological control, indicating the importance of the proper choice of when to start relaxing social distancing measures.

Author(s):  
Ashutosh Mahajan ◽  
Ravi Solanki ◽  
Namitha Sivadas

AbstractAfter originating from Wuhan, China, in late 2019, with a gradual spread in the last few months, COVID-19 has become a pandemic crossing 9 million confirmed positive cases and 450 thousand deaths. India is not only an overpopulated country but has a high population density as well, and at present, a high-risk nation where COVID-19 infection can go out of control. In this paper, we employ a compartmental epidemic model SIPHERD for COVID-19 and predict the total number of confirmed, active and death cases, and daily new cases. We analyze the impact of lockdown and the number of tests conducted per day on the prediction and bring out the scenarios in which the infection can be controlled faster. Our findings indicate that increasing the tests per day at a rapid pace (10k per day increase), stringent measures on social-distancing for the coming months and strict lockdown in the month of July all have a significant impact on the disease spread.


2020 ◽  
Author(s):  
Hyojung Lee ◽  
Yeahwon Kim ◽  
Eunsu Kim ◽  
Sunmi ‍Lee

BACKGROUND The emergence of COVID-19 has posed a serious threat to humans all around the world despite recent achievements of vaccines, antiviral drugs, and medical infrastructure. Our modern society has evolved too complex and most of the countries are tightly connected on a global scale. This makes it nearly impossible to implement perfect and prompt mitigation strategies for the COVID-19 outbreaks. Especially, due to the explosive growth of international travels, the diverse network and complexity of human mobility become an essential factor that gives rise to the spread of COVID-19 globally within a very short time. OBJECTIVE South Korea is one of the countries that have experienced the early stage of the COVID-19 pandemic. In the absence of vaccines and treatments, South Korea has implemented and maintained stringent interventions such as large-scale epidemiological investigation, rapid diagnosis, social distancing, and prompt clinical classification of severe patients with appropriate medical measures. In particular, South Korea has been implementing effective screening and quarantine at the airport. In this work, we aim to investigate the impacts of such effective interventions on international travels which can prevent local transmission of COVID-19. METHODS The relation between the number of passengers and the number of imported cases were analyzed. Based on the relation, we have assessed the country-specific risk as the spread of COVID-19 gets expanded from January to October 2020. Moreover, a renewal mathematical modeling has been employed incorporating the risk assessment to capture both imported and local cases of COVID-19 in South Korea. We have estimated the basic reproduction number and the effective reproduction number accounting for both imported and local cases. RESULTS The basic reproduction number (R_0) was estimated at 1.87 (95% CI : 1.47, 2.35) with the rate (α =0.07)of the secondary transmission caused by the imported cases. The time-varying basic reproduction number (effective reproduction number, R_t) was estimated. Our results indicate that the prompt implementation of case-isolation and quarantine were effective to reduce the. secondary cases from imported cases in spite of constant inflows from high-risk countries of COVID-19 all throughout the year 2020. Moreover, various mitigation interventions including social distancing and movement restriction have been maintained effectively to reduce the spread of local cases in South Korea. CONCLUSIONS We have investigated the relative risk of importation of COVID-19, using the country-specific epidemiological data, and passenger volume. By combining the social distancing, screening, and self-quarantine for all travelers entering Korea, the mitigation of COVID-19 transmission caused by imported cases in Korea was highly successful. Those efforts, accompanied by identification of the source of infection, the strengthened quarantine measures for travelers from overseas countries, should be continued. However, the recent new coronavirus variant originated from South Africa has been threatening to get back to the strict border control and lockdown of all around the world again. Therefore, it is urgent to assess the importation risk and maintain an effective surveillance system of COVID-19 in South Korea.


2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Uddipan Sarma ◽  
Bhaswar Ghosh

AbstractIn response to the COVID19 pandemic, many countries have implemented lockdowns in multiple phases to ensure social distancing and quarantining of the infected subjects. Subsequent unlocks to reopen the economies started next waves of infection and imposed an extra burden on quarantine to keep the reproduction number ($$R_{0}$$ R 0 ) < 1. However, most countries could not effectively contain the infection spread, suggesting identification of the potential sources weakening the effect of lockdowns could help design better informed lockdown-unlock cycles in the future. Here, through building quantitative epidemic models and analyzing the metadata of 50 countries from across the continents we first found that the estimated value of $$R_{0}$$ R 0 , adjusted w.r.t the distribution of medical facilities and virus clades correlates strongly with the testing rates in a country. Since the testing capacity of a country is limited by its medical resources, we investigated if a cost–benefit trade-off can be designed connecting testing rate and extent of unlocking. We present a strategy to optimize this trade-off in a country specific manner by providing a quantitative estimate of testing and quarantine rates required to allow different extents of unlocks while aiming to maintain $$R_{0} < 1$$ R 0 < 1 . We further show that a small fraction of superspreaders can dramatically increase the number of infected individuals even during strict lockdowns by strengthening the positive feedback loop driving infection spread. Harnessing the benefit of optimized country-specific testing rates would critically require minimizing the movement of these superspreaders via strict social distancing norms, such that the positive feedback driven switch-like exponential spread phase of infection can be avoided/delayed.


2021 ◽  
Author(s):  
Syeda Amna Rizvi ◽  
Muhammad Umair ◽  
Muhammad Aamir Cheema

ABSTRACTThe coronavirus has a high basic reproduction number (R0) and has caused the global COVID-19 pandemic. Governments are implementing lockdowns that are leading to economic fallout in many countries. Policy makers can take better decisions if provided with the indicators connected with the disease spread. This study is aimed to cluster the countries using social, economic, health and environmental related metrics affecting the disease spread so as to implement the policies to control the widespread of disease. Thus, countries with similar factors can take proactive steps to fight against the pandemic. The data is acquired for 79 countries and 18 different feature variables (the factors that are associated with COVID-19 spread) are selected. Pearson Product Moment Correlation Analysis is performed between all the feature variables with cumulative death cases and cumulative confirmed cases individually to get an insight of relation of these factors with the spread of COVID-19. Unsupervised k-means algorithm is used and the feature set includes economic, environmental indicators and disease prevalence along with COVID-19 variables. The learning model is able to group the countries into 4 clusters on the basis of relation with all 18 feature variables. We also present an analysis of correlation between the selected feature variables, and COVID-19 confirmed cases and deaths. Prevalence of underlying diseases shows strong correlation with COVID-19 whereas environmental health indicators are weakly correlated with COVID-19.


2019 ◽  
Vol 4 (2) ◽  
pp. 349 ◽  
Author(s):  
Oluwatayo Michael Ogunmiloro ◽  
Fatima Ohunene Abedo ◽  
Hammed Kareem

In this article, a Susceptible – Vaccinated – Infected – Recovered (SVIR) model is formulated and analysed using comprehensive mathematical techniques. The vaccination class is primarily considered as means of controlling the disease spread. The basic reproduction number (Ro) of the model is obtained, where it was shown that if Ro<1, at the model equilibrium solutions when infection is present and absent, the infection- free equilibrium is both locally and globally asymptotically stable. Also, if Ro>1, the endemic equilibrium solution is locally asymptotically stable. Furthermore, the analytical solution of the model was carried out using the Differential Transform Method (DTM) and Runge - Kutta fourth-order method. Numerical simulations were carried out to validate the theoretical results. 


2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Ruaridh A. Clark ◽  
Malcolm Macdonald

AbstractContact networks provide insights on disease spread due to the duration of close proximity interactions. For systems governed by consensus dynamics, network structure is key to optimising the spread of information. For disease spread over contact networks, the structure would be expected to be similarly influential. However, metrics that are essentially agnostic to the network’s structure, such as weighted degree (strength) centrality and its variants, perform near-optimally in selecting effective spreaders. These degree-based metrics outperform eigenvector centrality, despite disease spread over a network being a random walk process. This paper improves eigenvector-based spreader selection by introducing the non-linear relationship between contact time and the probability of disease transmission into the assessment of network dynamics. This approximation of disease spread dynamics is achieved by altering the Laplacian matrix, which in turn highlights why nodes with a high degree are such influential disease spreaders. From this approach, a trichotomy emerges on the definition of an effective spreader where, for susceptible-infected simulations, eigenvector-based selections can either optimise the initial rate of infection, the average rate of infection, or produce the fastest time to full infection of the network. Simulated and real-world human contact networks are examined, with insights also drawn on the effective adaptation of ant colony contact networks to reduce pathogen spread and protect the queen ant.


2021 ◽  
pp. 003335492110112
Author(s):  
Hongjie Liu ◽  
Chang Chen ◽  
Raul Cruz-Cano ◽  
Jennifer L. Guida ◽  
Minha Lee

Objective We quantified the association between public compliance with social distancing measures and the spread of SARS-CoV-2 during the first wave of the epidemic (March–May 2020) in 5 states that accounted for half of the total number of COVID-19 cases in the United States. Methods We used data on mobility and number of COVID-19 cases to longitudinally estimate associations between public compliance, as measured by human mobility, and the daily reproduction number and daily growth rate during the first wave of the COVID-19 epidemic in California, Illinois, Massachusetts, New Jersey, and New York. Results The 5 states mandated social distancing directives during March 19-24, 2020, and public compliance with mandates started to decrease in mid-April 2020. As of May 31, 2020, the daily reproduction number decreased from 2.41-5.21 to 0.72-1.19, and the daily growth rate decreased from 0.22-0.77 to –0.04 to 0.05 in the 5 states. The level of public compliance, as measured by the social distancing index (SDI) and daily encounter-density change, was high at the early stage of implementation but decreased in the 5 states. The SDI was negatively associated with the daily reproduction number (regression coefficients range, –0.04 to –0.01) and the daily growth rate (from –0.009 to –0.01). The daily encounter-density change was positively associated with the daily reproduction number (regression coefficients range, 0.24 to 1.02) and the daily growth rate (from 0.05 to 0.26). Conclusions Social distancing is an effective strategy to reduce the incidence of COVID-19 and illustrates the role of public compliance with social distancing measures to achieve public health benefits.


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Dipo Aldila ◽  
Brenda M. Samiadji ◽  
Gracia M. Simorangkir ◽  
Sarbaz H. A. Khosnaw ◽  
Muhammad Shahzad

Abstract Objective Several essential factors have played a crucial role in the spreading mechanism of COVID-19 (Coronavirus disease 2019) in the human population. These factors include undetected cases, asymptomatic cases, and several non-pharmaceutical interventions. Because of the rapid spread of COVID-19 worldwide, understanding the significance of these factors is crucial in determining whether COVID-19 will be eradicated or persist in the population. Hence, in this study, we establish a new mathematical model to predict the spread of COVID-19 considering mentioned factors. Results Infection detection and vaccination have the potential to eradicate COVID-19 from Jakarta. From the sensitivity analysis, we find that rapid testing is crucial in reducing the basic reproduction number when COVID-19 is endemic in the population rather than contact trace. Furthermore, our results indicate that a vaccination strategy has the potential to relax social distancing rules, while maintaining the basic reproduction number at the minimum possible, and also eradicate COVID-19 from the population with a higher vaccination rate. In conclusion, our model proposed a mathematical model that can be used by Jakarta’s government to relax social distancing policy by relying on future COVID-19 vaccine potential.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Sebastian Contreras ◽  
Jonas Dehning ◽  
Matthias Loidolt ◽  
Johannes Zierenberg ◽  
F. Paul Spitzner ◽  
...  

AbstractWithout a cure, vaccine, or proven long-term immunity against SARS-CoV-2, test-trace-and-isolate (TTI) strategies present a promising tool to contain its spread. For any TTI strategy, however, mitigation is challenged by pre- and asymptomatic transmission, TTI-avoiders, and undetected spreaders, which strongly contribute to ”hidden" infection chains. Here, we study a semi-analytical model and identify two tipping points between controlled and uncontrolled spread: (1) the behavior-driven reproduction number $${R}_{t}^{H}$$ R t H of the hidden chains becomes too large to be compensated by the TTI capabilities, and (2) the number of new infections exceeds the tracing capacity. Both trigger a self-accelerating spread. We investigate how these tipping points depend on challenges like limited cooperation, missing contacts, and imperfect isolation. Our results suggest that TTI alone is insufficient to contain an otherwise unhindered spread of SARS-CoV-2, implying that complementary measures like social distancing and improved hygiene remain necessary.


Author(s):  
Eunha Shim ◽  
Amna Tariq ◽  
Wongyeong Choi ◽  
Yiseul Lee ◽  
Gerardo Chowell

AbstractSince the first identified individual of 2019 novel coronavirus (COVID-19) infection on Jan 20, 2020 in South Korea, the number of confirmed cases rapidly increased. As of Feb 26, 2020, 1,261 cases of COVID-19 including 12 deaths were confirmed in South Korea. Using the incidence data of COVID-19, we estimate the reproduction number at 1.5 (95% CI: 1.4-1.6), which indicates sustained transmission and support the implementation of social distancing measures to rapidly control the outbreak.


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