scholarly journals Modelling and predicting the spatio-temporal spread of COVID-19 in Italy

2020 ◽  
Author(s):  
Diego Giuliani ◽  
Maria Michela Dickson ◽  
Giuseppe Espa ◽  
Flavio Santi
Keyword(s):  
Spatial Interaction ◽  
Local Level ◽  
National Level ◽  
Temporal Distribution ◽  
Control Measures ◽  
Disease Evolution ◽  
The World ◽  
The Usa ◽  
Spatio Temporal ◽  
Over Time

Abstract Background: Severe acute respiratory syndrome Coronavirus 2019 (COVID-19) has been firstly detected in China at the end of 2019 and it spread in few months all over the world. Italy is the second country in the World for number of cases, and the diffusion of COVID-19 has followed a peculiar spatial pattern. However, the interest of scientific community has been devoted almost exclusively to the prediction of the disease evolution over time so far. Methods: Official freely available data about the number of infected at the finest possible level of spatial areal aggregation (Italian provinces) are used to model the spatio-temporal distribution of COVID-19 infections at local level. An endemic-epidemic time-series mixed-effects generalized linear model for areal disease counts has been implemented to understand and predict spatio-temporal diffusion of the phenomenon. Results: Three subcomponents characterize the fitted model. The first describes the transmission of the illness within provinces; the second accounts for the transmission between nearby provinces; the third is related to the evolution of the disease over time. At the local level, the provinces first concerned by containment measures are those that are not affected by the effects of spatial neighbours. On the other hand, the component accounting for the spatial interaction with surrounding areas is prevalent for provinces that are strongly involved by contagions. Moreover, the proposed model provides good forecasts of the number of infections at local level while controlling for delayed reporting. Conclusions: A strong evidence is found that strict control measures implemented in some provinces efficiently break contagions and limit the spread to nearby areas. While containment policies may potentially be more effective if planned considering the peculiarities of local territories, the effective and homogeneous enforcement of control measures at national level is needed to prevent the disease control being delayed or missed as a whole. This may also apply at international level where, as it is for the EU or the USA, the internal border checks among states have largely been abolished.

scholarly journals Modelling and predicting the spatio-temporal spread of COVID-19 in Italy

2020 ◽  
Author(s):  
Diego Giuliani ◽  
Maria Michela Dickson ◽  
Giuseppe Espa ◽  
Flavio Santi
Keyword(s):  
Spatial Interaction ◽  
Local Level ◽  
National Level ◽  
Temporal Distribution ◽  
Control Measures ◽  
The Usa ◽  
Italian Provinces ◽  
Spatio Temporal ◽  
Surrounding Areas ◽  
Over Time

Abstract Background: The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) was first detected in China at the end of 2019 and it has since spread in few months all over the World. Italy was one of the first Western countries who faced the health emergency and is one of the countries most severely affected by the pandemic. The diffusion of Coronavirus disease 2019 (COVID-19) in Italy has followed a peculiar spatial pattern, however the attention of the scientific community has so far focussed almost exclusively on the prediction of the evolution of the disease over time. Methods: Official freely available data about the number of infected at the finest possible level of spatial areal aggregation (Italian provinces) are used to model the spatio-temporal distribution of COVID-19 infections at local level. An endemic-epidemic time-series mixed-effects generalized linear model for areal disease counts has been implemented to understand and predict spatio-temporal diffusion of the phenomenon. Results: Three subcomponents characterize the fitted model. The first describes the transmission of the illness within provinces; the second accounts for the transmission between nearby provinces; the third is related to the evolution of the disease over time. At the local level, the provinces first concerned by containment measures are those that are not affected by the effects of spatial neighbours. On the other hand, the component accounting for the spatial interaction with surrounding areas is prevalent for provinces that are strongly involved by contagions. Moreover, the proposed model provides good forecasts for the number of infections at local level while controlling for delayed reporting. Conclusions: A strong evidence is found that strict control measures implemented in some provinces efficiently break contagions and limit the spread to nearby areas. While containment policies may potentially be more effective if planned considering the peculiarities of local territories, the effective and homogeneous enforcement of control measures at national level is needed to prevent the disease control being delayed or missed as a whole. This may also apply at international level where, as it is for the EU or the USA, the internal border checks among states have largely been abolished.

scholarly journals Modelling and predicting the spatio-temporal spread of COVID-19 in Italy

2020 ◽  
Author(s):  
Diego Giuliani ◽  
Maria Michela Dickson ◽  
Giuseppe Espa ◽  
Flavio Santi
Keyword(s):  
Spatial Interaction ◽  
Local Level ◽  
National Level ◽  
Temporal Distribution ◽  
Control Measures ◽  
The Usa ◽  
Italian Provinces ◽  
Spatio Temporal ◽  
Surrounding Areas ◽  
Over Time

Abstract Background: The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) was first detected in China at the end of 2019 and it has since spread in few months all over the World. Italy was one of the first Western countries who faced the health emergency and is one of the countries most severely affected by the pandemic. The diffusion of COVID-19 in Italy has followed a peculiar spatial pattern, however the attention of the scientific community has so far focussed almost exclusively on the prediction of the evolution of the disease over time. Methods: Official freely available data about the number of infected at the finest possible level of spatial areal aggregation (Italian provinces) are used to model the spatio-temporal distribution of COVID-19 infections at local level. An endemic-epidemic time-series mixed-effects generalized linear model for areal disease counts has been implemented to understand and predict spatio-temporal diffusion of the phenomenon. Results: Three subcomponents characterize the fitted model. The first describes the transmission of the illness within provinces; the second accounts for the transmission between nearby provinces; the third is related to the evolution of the disease over time. At the local level, the provinces first concerned by containment measures are those that are not affected by the effects of spatial neighbours. On the other hand, the component accounting for the spatial interaction with surrounding areas is prevalent for provinces that are strongly involved by contagions. Moreover, the proposed model provides good forecasts for the number of infections at local level while controlling for delayed reporting. Conclusions: A strong evidence is found that strict control measures implemented in some provinces efficiently break contagions and limit the spread to nearby areas. While containment policies may potentially be more effective if planned considering the peculiarities of local territories, the effective and homogeneous enforcement of control measures at national level is needed to prevent the disease control being delayed or missed as a whole. This may also apply at international level where, as it is for the EU or the USA, the internal border checks among states have largely been abolished.

scholarly journals Modelling and predicting the spatio-temporal spread of COVID-19 in Italy

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Diego Giuliani ◽  
Maria Michela Dickson ◽  
Giuseppe Espa ◽  
Flavio Santi
Keyword(s):  
Spatial Interaction ◽  
Local Level ◽  
National Level ◽  
Temporal Distribution ◽  
The United States ◽  
Control Measures ◽  
The European Union ◽  
Italian Provinces ◽  
Spatio Temporal ◽  
Over Time

Abstract Background The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) was first detected in China at the end of 2019 and it has since spread in few months all over the World. Italy was one of the first Western countries who faced the health emergency and is one of the countries most severely affected by the pandemic. The diffusion of Coronavirus disease 2019 (COVID-19) in Italy has followed a peculiar spatial pattern, however the attention of the scientific community has so far focussed almost exclusively on the prediction of the evolution of the disease over time. Methods Official freely available data about the number of infected at the finest possible level of spatial areal aggregation (Italian provinces) are used to model the spatio-temporal distribution of COVID-19 infections at local level. An endemic-epidemic time-series mixed-effects generalized linear model for areal disease counts has been implemented to understand and predict spatio-temporal diffusion of the phenomenon. Results Three subcomponents characterize the fitted model. The first describes the transmission of the illness within provinces; the second accounts for the transmission between nearby provinces; the third is related to the evolution of the disease over time. At the local level, the provinces first concerned by containment measures are those that are not affected by the effects of spatial neighbours. On the other hand, the component accounting for the spatial interaction with surrounding areas is prevalent for provinces that are strongly involved by contagions. Moreover, the proposed model provides good forecasts for the number of infections at local level while controlling for delayed reporting. Conclusions A strong evidence is found that strict control measures implemented in some provinces efficiently break contagions and limit the spread to nearby areas. While containment policies may potentially be more effective if planned considering the peculiarities of local territories, the effective and homogeneous enforcement of control measures at national level is needed to prevent the disease control being delayed or missed as a whole. This may also apply at international level where, as it is for the European Union or the United States, the internal border checks among states have largely been abolished.

scholarly journals Climate drivers of plague epidemiology in British India, 1898–1949

2020 ◽  
Vol 287 (1928) ◽  
pp. 20200538
Author(s):  
Warren S. D. Tennant ◽  
Mike J. Tildesley ◽  
Simon E. F. Spencer ◽  
Matt J. Keeling
Keyword(s):  
Predictive Models ◽  
Control Measures ◽  
Climate Data ◽  
British India ◽  
Middle Income ◽  
Middle Income Countries ◽  
Complex Interactions ◽  
The World ◽  
Spatio Temporal

Plague, caused by Yersinia pestis infection, continues to threaten low- and middle-income countries throughout the world. The complex interactions between rodents and fleas with their respective environments challenge our understanding of human plague epidemiology. Historical long-term datasets of reported plague cases offer a unique opportunity to elucidate the effects of climate on plague outbreaks in detail. Here, we analyse monthly plague deaths and climate data from 25 provinces in British India from 1898 to 1949 to generate insights into the influence of temperature, rainfall and humidity on the occurrence, severity and timing of plague outbreaks. We find that moderate relative humidity levels of between 60% and 80% were strongly associated with outbreaks. Using wavelet analysis, we determine that the nationwide spread of plague was driven by changes in humidity, where, on average, a one-month delay in the onset of rising humidity translated into a one-month delay in the timing of plague outbreaks. This work can inform modern spatio-temporal predictive models for the disease and aid in the development of early-warning strategies for the deployment of prophylactic treatments and other control measures.

scholarly journals Geographical and temporal distribution of SARS-CoV-2 clades in the WHO European Region, January to June 2020

2020 ◽  
Vol 25 (32) ◽  
Author(s):  
Erik Alm ◽  
Eeva K Broberg ◽  
Thomas Connor ◽  
Emma B Hodcroft ◽  
Andrey B Komissarov ◽  
...  
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
World Health Organization ◽  
Data Dissemination ◽  
Sequence Data ◽  
Temporal Distribution ◽  
World Health ◽  
European Region ◽  
The World ◽  
Health Organization ◽  
Over Time

We show the distribution of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genetic clades over time and between countries and outline potential genomic surveillance objectives. We applied three genomic nomenclature systems to all sequence data from the World Health Organization European Region available until 10 July 2020. We highlight the importance of real-time sequencing and data dissemination in a pandemic situation, compare the nomenclatures and lay a foundation for future European genomic surveillance of SARS-CoV-2.

scholarly journals Seducing for Truth and Justice: Civil Society Initiatives for the 1965 Mass Violence in Indonesia

2013 ◽  
Vol 32 (3) ◽  
pp. 115-142 ◽  
Author(s):  
Sri Lestari Wahyuningroem
Keyword(s):  
Civil Society ◽  
Transitional Justice ◽  
Local Governments ◽  
Central Government ◽  
Local Level ◽  
National Level ◽  
Policy Reforms ◽  
Mass Violence ◽  
The World

The article examines both civil society initiatives that seek to address the mass violence of 1965 and 1966 and the state's responses to them. Unlike other political-transition contexts in the world, a transitional justice approach is apparently a formula that state authorities have found difficult to implement nationally for this particular case. The central government has, through its institutions, sporadically responded to some of the calls from civil society groups and has even initiated policy reforms to support such initiatives. Nevertheless, these responses were not sustained and any suggested programmes have always failed to be completed or implemented. Simultaneously, however, NGOs and victims are also voicing their demands at the local level. Many of their initiatives involve not only communities but also local authorities, including in some cases the local governments. In some aspects, these “bottom-up” approaches are more successful than attempts to create change at the national level. Such approaches challenge what Kieran McEvoy refers to as an innate “seductive” quality of transitional justice, but at the same time these approaches do, in fact, aim to “seduce” the state to adopt measures for truth and justice.

The Geographically Uneven Development of Privatisation: Towards a Theoretical Approach

1992 ◽  
Vol 24 (8) ◽  
pp. 1117-1135 ◽  
Author(s):  
J G Stubbs ◽  
J R Barnett
Keyword(s):  
Public Hospital ◽  
Local Level ◽  
National Level ◽  
Regional Hospital ◽  
Uneven Development ◽  
Ancillary Services ◽  
Nation States ◽  
The World ◽  
Private Contracting ◽  
Surprising Finding

Over the least decade a plethora of privatisation policies have been initiated in many countries of the world both at national level and at local level. Few attempts, however, have been made to analyse, within a theoretical framework, the geographically uneven development of privatisation policies both within, and between, regions and nation-states. This paper is an examination of the uneven growth between regional hospital authorities in the private contracting of public hospital ancillary services in New Zealand. A significant, if somewhat surprising, finding is that, after a surge in privatisation in the early 1980s, the process has virtually stagnated in the last few years. Possible reasons for this, and the more general spatial uneven development of this form of privatisation, are advanced and, on the basis of this study, some avenues for further research are indicated.

scholarly journals The Coronavirus Pandemic and Global Governance: The Domestic Diffusion of Health Norms in Global Health Security Crises

2021 ◽  
pp. 097359842110420
Author(s):  
Shreejita Biswas
Keyword(s):  
Global Health ◽  
Global Governance ◽  
Diffusion Processes ◽  
Local Level ◽  
National Level ◽  
Security Threat ◽  
Health Security ◽  
Norm Diffusion ◽  
The Usa ◽  
National Boundaries

The recent outbreak of the COVID-19 pandemic demands imperative discussions in the field of health security and global governance. Traditional studies on health care and global governance have acknowledged the significance of “global” as it rested on the fact that epidemics and pandemics are not restricted within national boundaries. The COVID-19 pandemic has challenged the hierarchical division of norm diffusion. Despite the structural inequalities, the patterns of behavior of various countries, such as China, the USA, Italy, South Korea, and India, in managing the crisis suggest a favorable ground for bringing in the importance of national-level decision-making in the global versus local debate. Building upon the arguments from norm theories of diffusion, the article contributes to our understanding that for an effective analysis of the politics of global health governance, the power of local channels in the diffusion of essential health norms cannot be undermined. The article studies the role played by the local-level diffusion processes, in this case, the national state actors in reshaping and integrating essential health norms to make it workable for broader global relevance. As a result, following the norm theories of diffusion, this article analyzes the global–local dynamics with regard to public health in the context of the spread of the COVID-19 health security threat.

scholarly journals RESEARCH ON VISUAL ANALYSIS METHODS OF TERRORISM EVENTS

2016 ◽  
Vol XLI-B2 ◽  
pp. 191-196
Author(s):  
Wenyue Guo ◽  
Haiyan Liu ◽  
Anzhu Yu ◽  
Jing Li
Keyword(s):  
Visual Analysis ◽  
Temporal Distribution ◽  
Development Trend ◽  
Event Data ◽  
Thematic Map ◽  
The World ◽  
Spatio Temporal ◽  
Global Terrorism Database ◽  
The Development Trend ◽  
Security Incidents

Under the situation that terrorism events occur more and more frequency throughout the world, improving the response capability of social security incidents has become an important aspect to test governments govern ability. Visual analysis has become an important method of event analysing for its advantage of intuitive and effective. To analyse events’ spatio-temporal distribution characteristics, correlations among event items and the development trend, terrorism event’s spatio-temporal characteristics are discussed. Suitable event data table structure based on “5W” theory is designed. Then, six types of visual analysis are purposed, and how to use thematic map and statistical charts to realize visual analysis on terrorism events is studied. Finally, experiments have been carried out by using the data provided by Global Terrorism Database, and the results of experiments proves the availability of the methods.

scholarly journals Hot spot detection and spatio-temporal dynamics of dengue in Queensland, Australia

2014 ◽  
Vol XL-8 ◽  
pp. 197-204 ◽  
Author(s):  
S. Naish ◽  
S. Tong
Keyword(s):  
Temporal Variation ◽  
Temporal Dynamics ◽  
Hot Spot ◽  
Seasonal Pattern ◽  
Temporal Distribution ◽  
Health Concern ◽  
Spatial And Temporal Variation ◽  
Dengue Case ◽  
Spatio Temporal ◽  
Over Time

Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992–1993. This study explored spatio-temporal distribution and clustering of locally-acquired dengue cases in Queensland State, Australia and identified target areas for effective interventions. A computerised locally-acquired dengue case dataset was collected from Queensland Health for Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. Dengue hot spots were detected using SatScan method. Descriptive spatial analysis showed that a total of 2,398 locally-acquired dengue cases were recorded in central and northern regions of tropical Queensland. A seasonal pattern was observed with most of the cases occurring in autumn. Spatial and temporal variation of dengue cases was observed in the geographic areas affected by dengue over time. Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in tropical Queensland, Australia. There is a clear evidence for the existence of statistically significant clusters of dengue and these clusters varied over time. These findings enabled us to detect and target dengue clusters suggesting that the use of geospatial information can assist the health authority in planning dengue control activities and it would allow for better design and implementation of dengue management programs.

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