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 ◽  
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 ◽  
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 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 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.

scholarly journals Spatial-temporal analysis and visualization of scarlet fever in mainland China from 2004 to 2017

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Wei-tong Li ◽  
Rui-hua Feng ◽  
Tong Li ◽  
Yan-bing Du ◽  
Nan Zhou ◽  
...  
Keyword(s):  
Surface Analysis ◽  
Scarlet Fever ◽  
Spatial Clustering ◽  
National Level ◽  
Mainland China ◽  
Temporal Distribution ◽  
Temporal Analysis ◽  
Trend Surface Analysis ◽  
Trend Surface ◽  
Spatio Temporal

This study retrospectively analyzed the spatio-temporal distribution and spatial clustering of scarlet fever in mainland China from 2004 to 2017. In recent years, the incidence of scarlet fever is increasing. Previous studies on the spatial distribution of scarlet fever in China are mainly focused at the provincial and municipal levels, and there is few systematic report on the spatial and temporal distribution characteristics of scarlet fever on the national level. Based on the incidence information of scarlet fever in mainland China between 2004 and 2017 collected from the China Center for Disease Control, this paper systematically explored the Spatio-temporal distribution of scarlet fever by three methods, contains spatial autocorrelation analysis, Spatio-temporal scanning analysis, and trend surface analysis. The results demonstrate that the incidence of scarlet fever varies by seasons, which is in line with double-peak distribution.The first peak generally occurs from May to June and the second one from November to December, while February and August is the lowest period of incidence. Trend surface analysis indicates that the incidence of scarlet fever in northern China is higher than the south, slightly higher in western compared to the east, and lower in the central part. Additionally, the results show that the clustering regions of scarlet fever centrally distributed in the northeast, northwest, north china and some provinces in the east, such as Zhejiang, Shanghai, Shandong, and Jiangsu.       

scholarly journals Spatial and seasonal patterns of FMD primary outbreaks in cattle in Zimbabwe between 1931 and 2016

2019 ◽  
Vol 50 (1) ◽  
Author(s):  
Laure Guerrini ◽  
Davies Mubika Pfukenyi ◽  
Eric Etter ◽  
Jérémy Bouyer ◽  
Chenjerai Njagu ◽  
...  
Keyword(s):  
Protected Areas ◽  
Southern Africa ◽  
Production Systems ◽  
Temporal Distribution ◽  
Foot And Mouth Disease ◽  
Control Measures ◽  
Political Crisis ◽  
Small Scale ◽  
Temporal Occurrence ◽  
Spatio Temporal

Abstract Foot and mouth disease (FMD) is an important livestock disease impacting mainly intensive production systems. In southern Africa, the FMD virus is maintained in wildlife and its control is therefore complicated. However, FMD control is an important task to allow countries access to lucrative foreign meat market and veterinary services implement drastic control measures on livestock populations living in the periphery of protected areas, negatively impacting local small-scale livestock producers. This study investigated FMD primary outbreak data in Zimbabwe from 1931 to 2016 to describe the spatio-temporal distribution of FMD outbreaks and their potential drivers. The results suggest that: (i) FMD outbreaks were not randomly distributed in space across Zimbabwe but are clustered in the Southeast Lowveld (SEL); (ii) the proximity of protected areas with African buffalos was potentially responsible for primary FMD outbreaks in cattle; (iii) rainfall per se was not associated with FMD outbreaks, but seasons impacted the temporal occurrence of FMD outbreaks across regions; (iv) the frequency of FMD outbreaks increased during periods of major socio-economic and political crisis. The differences between the spatial clusters and other areas in Zimbabwe presenting similar buffalo/cattle interfaces but with fewer FMD outbreaks can be interpreted in light of the recent better understanding of wildlife/livestock interactions in these areas. The types of wildlife/livestock interfaces are hypothesized to be the key drivers of contacts between wildlife and livestock, triggering a risk of FMD inter-species spillover. The management of wildlife/livestock interfaces is therefore crucial for the control of FMD in southern Africa.

Drivers of Stasis and Change

2020 ◽  
pp. 200-208
Author(s):  
Meredith L. Weiss
Keyword(s):  
Political Change ◽  
Local Level ◽  
National Level ◽  
Authoritarian Regimes ◽  
The Public ◽  
Electoral Authoritarianism ◽  
Political Praxis ◽  
Regime Transitions ◽  
Structural Innovation ◽  
Over Time

This chapter revises the usual understanding of regimes and regime transitions, including what a genuine transition might entail. It recommends a mix of structural, political-cultural, ideological, and praxis-oriented angles to understand and assess regimes and political change. Over time the workings of politics under electoral authoritarianism may shift the contest from one of policy or ideology toward less differentiable issues of mundane management and microlevel accessibility and acquisition. The chapter focuses on structural innovation at the local level. By supplementing national-level electoral tactics, electoral authoritarian regimes discipline the public and opposition parties that gradually permeates political culture and everyday political praxis. It also points out the implications of patterns that shape politician–voter linkages, premises for accountability and assessing alternatives, and the range of players with stakes in the system-that-is.

scholarly journals Vaccine Protection Efficiency Compared with the Smart Application of Common-Sense Pandemic Control Measures

2021 ◽  
Vol 2 (9) ◽  
pp. 830-832
Author(s):  
Liviu Popa-Simil
Keyword(s):  
National Level ◽  
The Body ◽  
Control Measures ◽  
Protection Measures ◽  
Dead Person ◽  
Real Nature ◽  
The Usa ◽  
Disastrous Effect ◽  
The One ◽  
High Level

Most recent NIH studies and CDC publication were able to estimate the vaccine efficacy variation overtime, and to remove the previous vail of ultimate and absolute protection against SARS-CoV-2, known as COVID-19 with respect to delta variant, propagated in the USA. The statistical data shows clear that Vaccines as Pfizer ad Moderna works, in spite their efficacies are decreasing with about 5%/month, are still able to protect in a more complex manner than masks and nano-engineered aerodynamics based protection measures. If these measures are referring to preventing inhalation of any hazardous material, no matter the type of viruses, the vaccine is dealing with the effects of virus inside the body after the intake took place. These vaccines were considered an ultimate protection and praised as such, as being in fact big pharma business, easy to be understood by masses with a real nature hazard mitigation IQ level much lower than the one made at national level based on the actual IQ tests customized to keep happy Caucasians, but fit well on Pacific Rim Asians. The problem with engineered protection is that one needs a smart population, cooperating synergistically, and be knowledgeable on when and how to use the protection in order to stop pandemic, insulate aggressor virus, create a vaccine and terminate the hazard. The current US practice is dominated by high-level mis-information and politicization of pandemic, where the actual spike in delta variant is due to CDC suppression of masks, without reaching a heard immunity, praising and enforcing vaccination aggravated by the incompetence of conservatives, who do not understand that a sick or dead person cannot enjoy constitutional freedoms, and do not distinguish between a life threat and a right, simply opposing to government without coming with alternate measures, having a disastrous effect on US population which with only 4% of world’s population delivered more than 25% of world’s causalities. The current milestone of 610,000 deaths and 40 million infected made the world leery about US exceptionalism and its planetary leadership.

scholarly journals Spatio-Temporal Distribution and Fixed-Precision Sampling Plan of Scirtothrips dorsalis (Thysanoptera: Thripidae) in Florida Blueberry

Insects ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 256
Author(s):  
Babu R. Panthi ◽  
Justin M. Renkema ◽  
Sriyanka Lahiri ◽  
Oscar E. Liburd
Keyword(s):  
Negative Binomial ◽  
Probability Distributions ◽  
Leaf Growth ◽  
Temporal Distribution ◽  
Sampling Plan ◽  
Control Measures ◽  
Sampling Unit ◽  
Central Florida ◽  
Scirtothrips Dorsalis ◽  
Spatio Temporal

Scirtothrips dorsalis Hood is an invasive and foliar pest of Florida blueberry that reduces plant growth by feeding on new leaf growth. A sampling plan is needed to make informed control decisions for S. dorsalis in blueberry. Fourteen blueberry fields in central Florida were surveyed in 2017 and 2018 after summer pruning to determine the spatial and temporal distribution of S. dorsalis and to develop a fixed-precision sampling plan. A sampling unit of ten blueberry shoots (with four to five leaves each) was collected from one blueberry bush at each point along a 40 × 40 m grid. Field counts of S. dorsalis varied largely ranging from zero to 1122 adults and larvae per sampling unit. Scirtothrips dorsalis had aggregated distribution that was consistent within fields and temporally stable between summers, according to Taylor’s power law (TPL) (aggregation parameter, b = 1.57), probability distributions (56 out of 70 sampling occasions fit the negative binomial distribution), Lloyd’s index (b > 1 in 94% occasions), and Spatial Analysis by Distance IndicEs (31% had significant clusters). The newly developed fixed-precision sampling plan required 167, 42, seven, or three sampling units to estimate a nominal mean density of 20 S. dorsalis per sampling unit with a precision of 5%, 10%, 25%, or 40%, respectively. New knowledge on S. dorsalis distribution will aid in evaluating the timing and effectiveness of control measures.

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