Spatial spread of COVID-19 during the early pandemic phase in Italy

Quantifying the potential spatial spread of an infectious pathogen is key to defining effective containment and control strategies. The aim of this study is to estimate the risk of SARS-CoV-2 transmission at different distances in Italy before the first regional lockdown was imposed, identifying important sources of national spreading. To do this, we leverage on a probabilistic model applied to daily symptomatic cases retrospectively ascertained in each Italian municipality with symptom onset between January 28 and March 7, 2020. Results are validated using a multi-patch dynamic transmission model reproducing the spatiotemporal distribution of identified cases. Our results show that the contribution of short-distance ( ≤ 10 k m ) transmission increased from less than 40% in the last week of January to more than 80% in the first week of March 2020. On March 7, 2020, that is the day before the first regional lockdown was imposed, more than 200 local transmission foci were contributing to the spread of SARS-CoV-2 in Italy. At the time, isolation measures imposed only on municipalities with at least ten ascertained cases would have left uncontrolled more than 75% of spillover transmission from the already affected municipalities. In early March, national-wide restrictions were required to curb short-distance transmission of SARS-CoV-2 in Italy.

Well-posedness and stability analysis of an epidemic model with infection age and spatial diffusion

A compartment epidemic model for infectious disease spreading is investigated, where movement of individuals is governed by spatial diffusion. The model includes infection age of the infected individuals and assumes a logistic growth of the susceptibles. Global well-posedness of the equations within the class of nonnegative smooth solutions is shown. Moreover, spectral properties of the linearization around a steady state are derived. This yields the notion of linear stability which is used to determine stability properties of the disease-free and the endemic steady state.

Modelling the roles of visitor flows and returning migrants in the spatial diffusion of COVID-19 from Wuhan city in China

COVID-19 has spread to many cities and countries in the world since the major outbreak in Wuhan city in later 2019. Population flow is the main channel of COVID-19 transmission between different cities and countries. This study recognizes that the flows of different population groups such as visitors and migrants returning to hometown are different in nature due to different length of stay and exposure to infection risks, contributing to the spatial diffusion of COVID-19 differently. To model population flows and the spatial diffusion of COVID-19 more accurately, a population group based SEIR (susceptible-exposed-infectious-recovered) metapopulation model is developed consisting of 32 regions including Wuhan, the rest of Hubei and other 30 provinces in Mainland China. The paper found that, in terms of the total export, Wuhan residents as visitors and Wuhan migrants returned to hometown were the first and second largest contributors in the simulation period. In terms of the net export, Wuhan migrants returned to hometown were the largest contributor, followed by Wuhan residents as visitors.

The regional variation of a housing boom. Disparities of land prices in Austria, 2000-2018

Debates accompanying the global housing boom have primarily focussed on the economic and social implications for urban housing markets. Against this background, this paper analyses the repercussions for regional land prices of a national housing boom in and beyond agglomerations. Convergence and divergence dynamics, regional price drivers, and spatial diffusion are investigated by examining average building-land prices of 95 Austrian regions between 2000 and 2018. The results indicate a clear increase in regional disparities in land prices, with the main rise taking place during a high price-growth period. Regions with high land prices are the main drivers of divergence, while a substantial number of peripheral regions with converging land prices were hardly affected by the national price boom. Land-price growth rates are positively affected by the number of households but negatively impacted by income growth, which points to a problematic decoupling of household income and land prices. Finally, the diffusion of the land-price boom occurs along the urban hierarchy as well as via neighbouring regions, confirming the ripple-effect hypothesis.

Economic globalization and the COVID-19 pandemic: global spread and inequalities

In just a few weeks, COVID-19 has become a global crisis and there is no longer any question of it being a major pandemic. The spread of the disease and the speed of transmission need to be squared with the forms and characteristics of economic globalization, disparities in development between the world's different regions and the highly divergent degree of their interconnectedness. Combining a geographic approach based on mapping the global spread of the virus with the collection of data and socio-economic variables, we drew up an OLS model to identify the impact of certain socio-economic factors on the number of cases observed worldwide. Globalization and the geography of economic relations were the main drivers of the spatial structuring and speed of the international spread of the COVID-19.

A methodological proposal to evaluate the health hazard scenario from COVID-19 in Italy

2019 Coronavirus disease (COVID-19) had a big impact in Italy, mainly concentrated in the northern part of the Country. All this was mainly due to similarities of this area with Wuhan in Hubei Province, according to geographical, environmental and socio-economic points of view. The basic hypothesis of this research was that the presence of atmospheric pollutants can generate stress on health conditions of the population and determine pre-conditions for the development of diseases of the respiratory system and complications related to them. In most cases the attention on environmental aspects is mainly concentrated on pollution, neglecting issues such as land management which, in some way, can contribute to reducing the impact of pollution. The reduction of land take and the decrease in the loss of ecosystem services can represent an important aspect in improving environmental quality. In order to integrate policies for environmental change and human health, the main factors analyzed in this paper can be summarized in environmental, climatic and land management. The main aim of this paper was to produce three different hazard scenarios respectively related to environmental, climatic and land management-related factors. A Spatial Analytical Hierarchy Process (AHP) method has been applied over thirteen informative layers grouped in aggregation classes of environmental, climatic and land management. The results of the health hazard maps show a disparity in the distribution of territorial responses to the pandemic in Italy. The environmental components play an extremely relevant role in the definition of the red zones of hazard, with a consequent urgent need to renew sustainable development strategies. The comparison of hazard maps related to different scenarios provides decision makers with tools to orient policy choices with a different degree of priority according to a place-based approach. In particular, the geospatial representation of risks could be a tool for legitimizing the measures chosen by decision-makers, proposing a renewed approach that highlights and takes account of the differences between the spatial contexts to be considered - Regions, Provinces, Municipalities - also in terms of climatic and environmental variables.

Computer simulation of the dynamics of a spatial susceptible-infected-recovered epidemic model with time delays in transmission and treatment

BACKGROUND AND OBJECTIVE

In this work, we analyze the spatial-temporal dynamics of a susceptible-infected-recovered (SIR) epidemic model with time delays. To better describe the dynamical behavior of the model, we take into account the cumulative effects of diffusion in the population dynamics, and the time delays in both the Holling type II treatment and the disease transmission process, respectively.

METHODS

We perform linear stability analyses on the disease-free and endemic equilibria. We provide the expression of the basic reproduction number and set conditions on the backward bifurcation using Castillo's theorem. The values of the critical time transmission, the treatment delays and the relationship between them are established.

RESULTS

We show that the treatment rate decreases the basic reproduction number while the transmission rate significantly affects the bifurcation process in the system. The transmission and treatment time-delays are found to be inversely proportional to the susceptible and infected diffusion rates. The analytical results are numerically tested. The results show that the treatment rate significantly reduces the density of infected population and ensures the transition from the unstable to the stable domain. Moreover, the system is more sensible to the treatment in the stable domain.

CONCLUSIONS

The density of infected population increases with respect to the infected and susceptible diffusion rates. Both effects of treatment and transmission delays significantly affect the behavior of the system. The transmission time-delay at the critical point ensures the transition from the stable (low density) to the unstable (high density) domain.

Monitoring the distribution of euro coins across borders (2002-2010): A dataset on the contents of 22,500 European citizens' wallet

The Euro Spatial Diffusion Observatory (ESDO) database records face-to-face questionnaire surveys conducted between March 2002 and December 2011 in France, in December 2003 in Belgium and in December 2005 in Germany. The data provides information on the coins contained in the respondents' wallets at the time of the survey, classified by country of origin and value. A series of control variables provide information on the socioeconomic profile of the respondents and the location of their place of residence at the NUTS 3 level. In total, more than 22,500 people opened their wallets and about 300,000 coins were registered allowing the tracking of euro coins circulation from their country of introduction on January 1, 2002 (or later for countries that joined the euro zone afterwards) to their place of observation at the time of the survey.

The socio-spatial determinants of COVID-19 diffusion: the impact of globalisation, settlement characteristics and population

BACKGROUND

COVID-19 is an emergent infectious disease that has spread geographically to become a global pandemic. While much research focuses on the epidemiological and virological aspects of COVID-19 transmission, there remains an important gap in knowledge regarding the drivers of geographical diffusion between places, in particular at the global scale. Here, we use quantile regression to model the roles of globalisation, human settlement and population characteristics as socio-spatial determinants of reported COVID-19 diffusion over a six-week period in March and April 2020. Our exploratory analysis is based on reported COVID-19 data published by Johns Hopkins University which, despite its limitations, serves as the best repository of reported COVID-19 cases across nations.

RESULTS

The quantile regression model suggests that globalisation, settlement, and population characteristics related to high human mobility and interaction predict reported disease diffusion. Human development level (HDI) and total population predict COVID-19 diffusion in countries with a high number of total reported cases (per million) whereas larger household size, older populations, and globalisation tied to human interaction predict COVID-19 diffusion in countries with a low number of total reported cases (per million). Population density, and population characteristics such as total population, older populations, and household size are strong predictors in early weeks but have a muted impact over time on reported COVID-19 diffusion. In contrast, the impacts of interpersonal and trade globalisation are enhanced over time, indicating that human mobility may best explain sustained disease diffusion.

CONCLUSIONS

Model results confirm that globalisation, settlement and population characteristics, and variables tied to high human mobility lead to greater reported disease diffusion. These outcomes serve to inform suppression strategies, particularly as they are related to anticipated relocation diffusion from more- to less-developed countries and regions, and hierarchical diffusion from countries with higher population and density. It is likely that many of these processes are replicated at smaller geographical scales both within countries and within regions. Epidemiological strategies must therefore be tailored according to human mobility patterns, as well as countries' settlement and population characteristics. We suggest that limiting human mobility to the greatest extent practical will best restrain COVID-19 diffusion, which in the absence of widespread vaccination may be one of the best lines of epidemiological defense.

Epidemiology and evolution of Middle East respiratory syndrome coronavirus, 2012-2020

BACKGROUND

The ongoing transmission of the Middle East respiratory syndrome coronavirus (MERS-CoV) in the Middle East and its expansion to other regions are raising concerns of a potential pandemic. An in-depth analysis about both population and molecular epidemiology of this pathogen is needed.

METHODS

MERS cases reported globally as of June 2020 were collected mainly from World Health Organization official reports, supplemented by other reliable sources. Determinants for case fatality and spatial diffusion of MERS were assessed with Logistic regressions and Cox proportional hazard models, respectively. Phylogenetic and phylogeographic analyses were performed to examine the evolution and migration history of MERS-CoV.

RESULTS

A total of 2562 confirmed MERS cases with 150 case clusters were reported with a case fatality rate of 32.7% (95% CI: 30.9‒34.6%). Saudi Arabia accounted for 83.6% of the cases. Age of ≥ 65 years old, underlying conditions and ≥ 5 days delay in diagnosis were independent risk factors for death. However, a history of animal contact was associated with a higher risk (adjusted OR = 2.97, 95% CI: 1.10-7.98) among female cases < 65 years but with a lower risk (adjusted OR = 0.31, 95% CI: 0.18-0.51) among male cases ≥ 65 years old. Diffusion of the disease was fastest from its origin in Saudi Arabia to the east, and was primarily driven by the transportation network. The most recent sub-clade C5.1 (since 2013) was associated with non-synonymous mutations and a higher mortality rate. Phylogeographic analyses pointed to Riyadh of Saudi Arabia and Abu Dhabi of the United Arab Emirates as the hubs for both local and international spread of MERS-CoV.

CONCLUSIONS

MERS-CoV remains primarily locally transmitted in the Middle East, with opportunistic exportation to other continents and a potential of causing transmission clusters of human cases. Animal contact is associated with a higher risk of death, but the association differs by age and sex. Transportation network is the leading driver for the spatial diffusion of the disease. These findings how this pathogen spread are helpful for targeting public health surveillance and interventions to control endemics and to prevent a potential pandemic.

Epidemiological dynamics of dengue fever in mainland China, 2014-2018

OBJECTIVE

To explore the epidemiological dynamics of dengue fever.

METHODS

Epidemiological dynamics of imported and indigenous dengue cases during 2014-2018, including demographic, time-series, spatial and spatio-temporal features, were analyzed.

RESULTS

There were 5 458 imported dengue cases and 59 183 indigenous dengue cases during 2014-2018. Both imported and indigenous dengue cases show seasonal patterns from August to November. 12.9% (12.9/100) of dengue cases were from businessmen. 58.2% (58.2/100) of dengue cases were from individuals between 21-50 years old. Imported dengue cases, mainly from Southeastern Asia, had doubled, and were distributed in 734 counties, 29 provinces, with 50% (50/100) in Yunnan. Except in 2014, indigenous dengue cases were under 5 000 every year, but the number in counties increased dramatically from 51 to 127. The total cases were distributed in 314 districts, 13 provinces. They were clustered in Yunnan border and southern Guangdong. They emerged gradually from southwestern and southern provinces to southeastern coastal provinces, and then to central and northern provinces every year. They spread from the southern regions to the central and northern regions in 2014-2018.

CONCLUSIONS

The findings of epidemiological dynamics of dengue fever are helpful to formulate targeted, strategic plans and implement effective public health prevention and control measures.

Examining determinants of geographic variation in colorectal cancer mortality in North Carolina: A spatial analysis approach

PURPOSE

A recent study using national data from 2000 to 2009 identified colorectal cancer (CRC) mortality "hotspots" in 11 counties of North Carolina (NC). In this study, we used more recent, state-specific data to investigate the county-level determinants of geographic variation in NC through a geospatial analytic approach.

METHOD

Using NC CRC mortality data from 2003 to 2013, we first conducted clustering analysis to confirm spatial dependence. Spatial economic models were then used to incorporate spatial structure to estimate the association between determinants and CRC mortality. We included county-level data on socio-demographic characteristics, access and quality of healthcare, behavioral risk factors (CRC screening, obesity, and cigarette smoking), and urbanicity. Due to correlation among screening, obesity and quality of healthcare, we combined these factors to form a cumulative risk group variable in the analysis.

RESULTS

We confirmed the existence of spatial dependence and identified clusters of elevated CRC mortality rates in NC counties. Using a spatial lag model, we found significant interaction effect between CRC risk groups and socioeconomic deprivation. Higher CRC mortality rates were also associated with rural counties with large towns compared to urban counties.

CONCLUSION

Our findings depicted a spatial diffusion process of CRC mortality rates across NC counties, demonstrated intertwined effects between SES deprivation and behavioral risks in shaping CRC mortality at area-level, and identified counties with high CRC mortality that were also deprived in multiple factors. These results suggest interventions to reduce geographic variation in CRC mortality should develop multifaceted strategies and work through shared resources in neighboring areas.

Ecocultural range-expansion scenarios for the replacement or assimilation of Neanderthals by modern humans

Recent archaeological records no longer support a simple dichotomous characterization of the cultures/behaviors of Neanderthals and modern humans, but indicate much cultural/behavioral variability over time and space. Thus, in modeling the replacement or assimilation of Neanderthals by modern humans, it is of interest to consider cultural dynamics and their relation to demographic change. The ecocultural framework for the competition between hominid species allows their carrying capacities to depend on some measure of the levels of culture they possess. In the present study both population densities and the densities of skilled individuals in Neanderthals and modern humans are spatially distributed and subject to change by spatial diffusion, ecological competition, and cultural transmission within each species. We analyze the resulting range expansions in terms of the demographic, ecological and cultural parameters that determine how the carrying capacities relate to the local densities of skilled individuals in each species. Of special interest is the case of cognitive and intrinsic-demographic equivalence of the two species. The range expansion dynamics may consist of multiple wave fronts of different speeds, each of which originates from a traveling wave solution. Properties of these traveling wave solutions are mathematically derived. Depending on the parameters, these traveling waves can result in replacement of Neanderthals by modern humans, or assimilation of the former by the latter. In both the replacement and assimilation scenarios, the first wave of intrusive modern humans is characterized by a low population density and a low density of skilled individuals, with implications for archaeological visibility. The first invasion is due to weak interspecific competition. A second wave of invasion may be induced by cultural differences between moderns and Neanderthals. Spatially and temporally extended coexistence of the two species, which would have facilitated the transfer of genes from Neanderthal into modern humans and vice versa, is observed in the traveling waves, except when niche overlap between the two species is extremely high. Archaeological findings on the spatial and temporal distributions of the Initial Upper Palaeolithic and the Early Upper Palaeolithic and of the coexistence of Neanderthals and modern humans are discussed.

Spatiotemporal study of elderly suicide in Korea by age cohort

OBJECTIVES

This study analyzed the spatiotemporal pattern and spatial diffusion of elderly suicide by age cohort, in Korea.

STUDY DESIGN

The research investigated the elderly suicide rates of the 232 municipal units in South Korea between 2001 and 2011.

METHODS

The Gi* score, which is a spatially weighted indicator of area attributes, was used to identify hot spots and the spatiotemporal pattern of elderly suicide in the nation during the last 10 years. The spatial Markov matrix and spatial dynamic panel data model were employed to identify and estimate the diffusion effect.

RESULTS

The suicide rate among elderly individuals 75 years and older was substantially higher than the rate for those between 65 and 74 years of age; however, the spatial patterns of the suicide clusters were similar between the two groups. From 2001 to 2011, the spatial distribution of elderly suicide hot spots differed each year. For both age cohorts, elderly suicide hot spots developed around the north area of South Korea in 2001 and moved to the mid-east area and the mid-western coastal area over 10 years. The spatial Markov matrix indicates that the change in the suicide rate of one area was affected by the suicide rates of neighbouring areas from the previous year, which suggests that suicide increase in one area inflates a neighbouring area's suicide rate over time. Using a spatial dynamic panel data model, elderly suicide diffusion effects were found to be statistically significant for both age cohorts even after economic and demographic indicators and a time variable are included. For individuals 75 years and older, the diffusion effect appeared to be larger.

CONCLUSIONS

This study demonstrates that elderly suicide can spread spatially over time in both age cohorts. Thus, it is necessary to design a place-based and age-differentiated intervention policy that precisely considers the spatial diffusion of elderly suicide.

Dynamics of an epidemic model with spatial diffusion

Mathematical models are very useful in analyzing the spread and control of infectious diseases which can be used to predict the developing tendency of the infectious disease, determine the key factors and to seek the optimum strategies of disease control. As a result, we investigated the pattern dynamics of a spatial epidemic model with logistic growth. By using amplitude equation, we found that there were different types of stationary patterns including spotted, mixed, and stripe patterns, which mean that spatial motion of individuals can form high density of diseases. The obtained results can be extended in other related fields, such as vegetation patterns in ecosystems.