scholarly journals Spatiotemporal patterns and progression of the Delta variant of COVID-19 and their health intervention linkages in Southeast Asia

Author(s):  
Wei Luo ◽  
Zhaoyin Liu ◽  
Yuxuan Zhou ◽  
Yumin Zhao ◽  
Yunyue Elita Li ◽  
...  

The global pandemic of COVID-19 presented an unprecedented challenge to all countries in the world, among which Southeast Asia (SEA) countries managed to maintain and mitigate the first wave of COVID-19 in 2020. However, these countries were caught in the crisis after the Delta variant was introduced to SEA, though many countries had immediately implemented non-pharmaceutical intervention (NPI) measures along with vaccination in order to contain the disease spread. To investigate the potential linkages between epidemic dynamics and public health interventions, we adopted a prospective space-time scan method to conduct spatiotemporal analysis at the district level in the seven selected countries in SEA from June 2021 to October 2021. Results reveal the spatial and temporal propagation and progression of COVID-19 risks relative to public health measures implemented by different countries. Our research benefits continuous improvements of public health strategies in preventing and containing this pandemic.

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Xiao-Yue Yu ◽  
Chen Xu ◽  
Hu-Wen Wang ◽  
Rui-Jie Chang ◽  
Yin-Qiao Dong ◽  
...  

Abstract In the past five months, success in control the national epidemic of coronavirus disease 2019 (COVID-19) has been witnessed in China. The implementation of public health measures accounts for the success which include different interventions in the early or later stages of the outbreak. It is clear that although not all measures were universally effective worldwide, their achievements have been significant. More solidarity is needed to deal with this global pandemic with more learning and understanding. Understanding which of the public health interventions implemented in China were effective may provide ideas for international epidemic control.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Pooja Sengupta ◽  
Bhaswati Ganguli ◽  
Sugata SenRoy ◽  
Aditya Chatterjee

Abstract Background In this study we cluster the districts of India in terms of the spread of COVID-19 and related variables such as population density and the number of specialty hospitals. Simulation using a compartment model is used to provide insight into differences in response to public health interventions. Two case studies of interest from Nizamuddin and Dharavi provide contrasting pictures of the success in curbing spread. Methods A cluster analysis of the worst affected districts in India provides insight about the similarities between them. The effects of public health interventions in flattening the curve in their respective states is studied using the individual contact SEIQHRF model, a stochastic individual compartment model which simulates disease prevalence in the susceptible, infected, recovered and fatal compartments. Results The clustering of hotspot districts provide homogeneous groups that can be discriminated in terms of number of cases and related covariates. The cluster analysis reveal that the distribution of number of COVID-19 hospitals in the districts does not correlate with the distribution of confirmed COVID-19 cases. From the SEIQHRF model for Nizamuddin we observe in the second phase the number of infected individuals had seen a multitudinous increase in the states where Nizamuddin attendees returned, increasing the risk of the disease spread. However, the simulations reveal that implementing administrative interventions, flatten the curve. In Dharavi, through tracing, tracking, testing and treating, massive breakout of COVID-19 was brought under control. Conclusions The cluster analysis performed on the districts reveal homogeneous groups of districts that can be ranked based on the burden placed on the healthcare system in terms of number of confirmed cases, population density and number of hospitals dedicated to COVID-19 treatment. The study rounds up with two important case studies on Nizamuddin basti and Dharavi to illustrate the growth curve of COVID-19 in two very densely populated regions in India. In the case of Nizamuddin, the study showed that there was a manifold increase in the risk of infection. In contrast it is seen that there was a rapid decline in the number of cases in Dharavi within a span of about one month.


2021 ◽  
pp. 002218562110000
Author(s):  
Michele Ford ◽  
Kristy Ward

The labour market effects in Southeast Asia of the COVID-19 pandemic have attracted considerable analysis from both scholars and practitioners. However, much less attention has been paid to the pandemic’s impact on legal protections for workers’ and unions’ rights, or to what might account for divergent outcomes in this respect in economies that share many characteristics, including a strong export orientation in labour-intensive industries and weak industrial relations institutions. Having described the public health measures taken to control the spread of COVID-19 in Indonesia, Cambodia and Vietnam, this article analyses governments’ employment-related responses and their impact on workers and unions in the first year of the pandemic. Based on this analysis, we conclude that the disruption caused to these countries’ economies, and societies, served to reproduce existing patterns of state–labour relations rather than overturning them.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Thomas J. Barrett ◽  
Karen C. Patterson ◽  
Timothy M. James ◽  
Peter Krüger

AbstractAs we enter a chronic phase of the SARS-CoV-2 pandemic, with uncontrolled infection rates in many places, relative regional susceptibilities are a critical unknown for policy planning. Tests for SARS-CoV-2 infection or antibodies are indicative but unreliable measures of exposure. Here instead, for four highly-affected countries, we determine population susceptibilities by directly comparing country-wide observed epidemic dynamics data with that of their main metropolitan regions. We find significant susceptibility reductions in the metropolitan regions as a result of earlier seeding, with a relatively longer phase of exponential growth before the introduction of public health interventions. During the post-growth phase, the lower susceptibility of these regions contributed to the decline in cases, independent of intervention effects. Forward projections indicate that non-metropolitan regions will be more affected during recurrent epidemic waves compared with the initially heavier-hit metropolitan regions. Our findings have consequences for disease forecasts and resource utilisation.


10.2196/21685 ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. e21685
Author(s):  
Zonglin He ◽  
Casper J P Zhang ◽  
Jian Huang ◽  
Jingyan Zhai ◽  
Shuang Zhou ◽  
...  

A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.


2020 ◽  
Vol 53 (2) ◽  
pp. 385-390 ◽  
Author(s):  
Semra Sevi ◽  
Marco Mendoza Aviña ◽  
Gabrielle Péloquin-Skulski ◽  
Emmanuel Heisbourg ◽  
Paola Vegas ◽  
...  

The SARS-CoV-2 virus was first identified in Wuhan, China, in late December 2019, and it quickly spread to many countries. By March 2020, the virus had triggered a global pandemic (World Health Organization, 2020). In response to this crisis, governments have implemented unprecedented public health measures. The success of these policies will largely depend on the public's willingness to comply with new rules. A key factor in citizens’ willingness to comply is their understanding of the data that motivate government action. In this study, we examine how different ways of presenting these data visually can affect citizen's perceptions, attitudes and support for public policy.


2002 ◽  
Vol 16 (2) ◽  
pp. 35-45 ◽  
Author(s):  
Onora O'Neill

Most work in medical ethics across the last twenty-five years has centered on the ethics of clinical medicine. Even work on health and justice has, in the main, been concerned with the just distribution of (access to) clinical care for individual patients. By contrast, the ethics of public health has been widely neglected. This neglect is surprising, given that public health interventions are often the most effective (and most cost-effective) means of improving health in rich and poor societies alike.In this essay I explore two sources of contemporary neglect of public health ethics. One source of neglect is that contemporary medical ethics has been preoccupied—in my view damagingly preoccupied—with the autonomy of individual patients. Yet individual autonomy can hardly be a guiding ethical principle for public health measures, since many of them must be uniform and compulsory if they are to be effective. A second source of neglect is that contemporary political philosophy has been preoccupied—in my view damagingly preoccupied—with the requirements for justice within states or societies, and (until very recently) has hardly discussed justice across borders. Yet public health problems often cross borders, and public health interventions have to measure up to the problems they address.


2017 ◽  
Author(s):  
María Torrea ◽  
José Luis Torrea ◽  
Daniel Ortega

AbstractBackgroundDiphtheria has a big mortality rate. Vaccination practically eradicated it in industrialized countries. A decrease in vaccine coverage and public health deterioration cause a reemergence in the Soviet Union in 1990. These circumstances seem to be being reproduced in refugee camps with a potential risk of new outbreak.MethodsWe constructed a mathematical model that describes the evolution of the Soviet Union epidemic outbreak. We use it to evaluate how the epidemic would be modified by changing the rate of vaccination, and improving public health conditions.ResultsWe observe that a small decrease of 15% in vaccine coverage, translates an ascent of 47% in infected people. A coverage increase of 15% and 25% decreases a 44% and 66% respectively of infected people. Just improving health care measures a 5%, infected people decreases a 11.31%. Combining high coverage with public health measures produces a bigger reduction in the amount of infected people compare to amelioration of coverage rate or health measures alone.ConclusionsOur model estimates the evolution of a diphtheria epidemic outbreak. Small increases in vaccination rates and in public health measures can translate into large differences in the evolution of a possible epidemic. These estimates can be helpful in socioeconomic instability, to prevent and control a disease spread.


2021 ◽  
Author(s):  
Joseph Bullock ◽  
Carolina Cuesta-Lazaro ◽  
Arnau Quera-Bofarull ◽  
Anjali Katta ◽  
Katherine Hoffmann Pham ◽  
...  

AbstractThe spread of infectious diseases such as COVID-19 presents many challenges to healthcare systems and infrastructures across the world, exacerbating inequalities and leaving the world’s most vulnerable populations most affected. Given their density and available infrastructure, refugee and internally displaced person (IDP) settlements can be particularly susceptible to disease spread. Non-pharmaceutical public health interventions can be used to mitigate transmission, and modeling efforts can provide crucial insights on the potential effectiveness of such interventions to help inform decision making processes. In this paper we present an agent-based modeling approach to simulating the spread of disease in refugee and IDP settlements. The model, based on the JUNE open-source framework, is informed by data on geography, demographics, comorbidities, physical infrastructure and other parameters obtained from real-world observations and previous literature. Furthermore, we present a visual analytics tool which allows decision makers to distill insights by comparing the results of different simulations and scenarios. Through simulating their effects on the epidemiological development of COVID-19, we evaluate several public health interventions ranging from increasing mask wearing compliance to the reopening of learning institutions. The development and testing of this approach focuses on the Cox’s Bazar refugee settlement in Bangladesh, although our model is designed to be generalizable to other informal settings.


2020 ◽  
Author(s):  
Zonglin He ◽  
Casper J P Zhang ◽  
Jian Huang ◽  
Jingyan Zhai ◽  
Shuang Zhou ◽  
...  

UNSTRUCTURED A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.


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