Disappearing cities on US coasts.

The sea level along the US coastlines is projected to rise by 0.25-0.3 m by 2050, increasing the probability of more destructive flooding and inundation in major cities1-3. However, these impacts may be exacerbated by coastal subsidence-the sinking of coastal land areas4-a factor that is often underrepresented in coastal-management policies and long-term urban planning2,5. In this study, we combine high-resolution vertical land motion (that is, raising or lowering of land) and elevation datasets with projections of sea-level rise to quantify the potential inundated areas in 32 major US coastal cities. Here we show that, even when considering the current coastal-defence structures, further land area of between 1,006 and 1,389 km2 is threatened by relative sea-level rise by 2050, posing a threat to a population of 55,000-273,000 people and 31,000-171,000 properties. Our analysis shows that not accounting for spatially variable land subsidence within the cities may lead to inaccurate projections of expected exposure. These potential consequences show the scale of the adaptation challenge, which is not appreciated in most US coastal cities.

Making cities mental health friendly for adolescents and young adults.

Urban life shapes the mental health of city dwellers, and although cities provide access to health, education and economic gain, urban environments are often detrimental to mental health1,2. Increasing urbanization over the next three decades will be accompanied by a growing population of children and adolescents living in cities3. Shaping the aspects of urban life that influence youth mental health could have an enormous impact on adolescent well-being and adult trajectories4. We invited a multidisciplinary, global group of researchers, practitioners, advocates and young people to complete sequential surveys to identify and prioritize the characteristics of a mental health-friendly city for young people. Here we show a set of ranked characteristic statements, grouped by personal, interpersonal, community, organizational, policy and environmental domains of intervention. Life skills for personal development, valuing and accepting young people's ideas and choices, providing safe public space for social connection, employment and job security, centring youth input in urban planning and design, and addressing adverse social determinants were priorities by domain. We report the adversities that COVID-19 generated and link relevant actions to these data. Our findings highlight the need for intersectoral, multilevel intervention and for inclusive, equitable, participatory design of cities that support youth mental health.

Ethnic disparities in cancer mortality in the capital and northeast of the State of São Paulo, Brazil 2001-17.

PURPOSE: There is a paucity of studies investigating cancer disparities in groups defined by ethnicity in transitioning economies. We examined the influence of ethnicity on mortality for the leading cancer types in São Paulo, Brazil, comparing patterns in the capital and the northeast of the state. METHODS: Cancer deaths were obtained from a Brazilian public government database for the Barretos region (2003-2017) and the municipality of São Paulo (2001-2015). Age-standardized rates (ASR) per 100,000 persons-years, by cancer type and sex, for five self-declared racial classifications (white, black, eastern origin (Asian), mixed ethnicity (pardo), and indigenous Brazilians), were calculated using the world standard population. RESULTS: Black Brazilians had higher mortality rates for most common cancer types in Barretos, whereas in São Paulo, white Brazilians had higher rates of mortality from breast, colorectal, and lung cancer. In both regions, lung cancer was the leading cause of cancer death among white, black, and pardo Brazilians, with colorectal cancer deaths leading among Asian Brazilians. Black and pardo Brazilians had higher cervical cancer mortality rates than white Brazilians. CONCLUSION: There are substantial disparities in mortality from different cancers in São Paulo according to ethnicity, pointing to inequities in access to health care services.

Índice de riesgo de obesidad infantil (IROBIC) para áreas administrativas pequeñas en Chile / Childhood obesity risk index (IROBIC) for small administrative areas in Chile

Introducción: a pesar de la alta prevalencia de la obesidad infantil (OI) globalmente, no existen índices compuestos para estimar los aspectos territoriales asociados al riesgo de OI. Objetivo: elaborar un índice de riesgo de OI (IROBIC) para unidades administrativas pequeñas (comunas) de Chile Métodos: se utilizaron datos de 2019 de fuentes públicas con información de menores de 10 años de todas las comunas de las 2 regiones más grandes. El IROBIC incluye 16 indicadores estandarizados por comuna y agrupados en cuatro dimensiones, determinadas por análisis de componentes principales (salud, socio económica, entornos comunal y educacional). Se determinó el IROBIC mediante una media geométrica ponderada y posteriormente se calcularon las diferencias entre las 10 y 5 comunas con mayores y menores IROBIC y de cada dimensión, con el coeficiente de disparidad Resultados: aun cuando los mayores IROBIC se obtuvieran en comunas más vulnerables, su valor total y el de cada dimensión, mostraron que es posible amortiguar los efectos de la desigualdad sobre la OI. Las 10 y 5 comunas con mayor IROBIC presentan un riesgo, 2,41 y 4,05 veces mayor que las de menor valor, respectivamente. Conclusiones: el IROBIC puede monitorear el riesgo de OI —y factores asociados— desde una perspectiva territorial. (AU)

Introduction: although the prevalence of childhood obesity (CO) is high globally, there are no composite indices to estimate territorial aspects associated with its risk Objective: to develop an obesity risk index (IROBIC) for small administrative units, called “comunas” in Chile Methods: we used 2019 data from public sources on children under 10 years living in “comunas” of the two largest regions. IROBIC includes 16 indicators standardized for each “comuna” and grouped together into four domains, determined by principal component analysis (health, socio-economic, built-in and educational environments). IROBIC was calculated as a weighted geometric mean. Differences in obesity risk between the 10 and 5 “comunas” with the highest and lowest IROBIC and of each domain, were calculated with the disparity ratio. Results: in spite of the poorest “comunas” having the highest IROBIC, when its value and that for each domain were considered, we observed that the effect of inequality could be mitigated. The 10 and 5 “comunas” with the highest IROBIC have a 2.41 and 4.05 higher risk of CO compared to those with the lowest values Conclusions: IROBIC is a useful tool for monitoring the risk of CO and its factors from a territorial perspective. (AU)

Human mobility networks reveal increased segregation in large cities.

A long-standing expectation is that large, dense and cosmopolitan areas support socioeconomic mixing and exposure among diverse individuals1-6. Assessing this hypothesis has been difficult because previous measures of socioeconomic mixing have relied on static residential housing data rather than real-life exposures among people at work, in places of leisure and in home neighbourhoods7,8. Here we develop a measure of exposure segregation that captures the socioeconomic diversity of these everyday encounters. Using mobile phone mobility data to represent 1.6 billion real-world exposures among 9.6 million people in the United States, we measure exposure segregation across 382 metropolitan statistical areas (MSAs) and 2,829 counties. We find that exposure segregation is 67% higher in the ten largest MSAs than in small MSAs with fewer than 100,000 residents. This means that, contrary to expectations, residents of large cosmopolitan areas have less exposure to a socioeconomically diverse range of individuals. Second, we find that the increased socioeconomic segregation in large cities arises because they offer a greater choice of differentiated spaces targeted to specific socioeconomic groups. Third, we find that this segregation-increasing effect is countered when a city's hubs (such as shopping centres) are positioned to bridge diverse neighbourhoods and therefore attract people of all socioeconomic statuses. Our findings challenge a long-standing conjecture in human geography and highlight how urban design can both prevent and facilitate encounters among diverse individuals.

Global evidence of rapid urban growth in flood zones since 1985.

Disaster losses are increasing and evidence is mounting that climate change is driving up the probability of extreme natural shocks1-3. Yet it has also proved politically expedient to invoke climate change as an exogenous force that supposedly places disasters beyond the influence of local and national authorities4,5. However, locally determined patterns of urbanization and spatial development are key factors to the exposure and vulnerability of people to climatic shocks6. Using high-resolution annual data, this study shows that, since 1985, human settlements around the world-from villages to megacities-have expanded continuously and rapidly into present-day flood zones. In many regions, growth in the most hazardous flood zones is outpacing growth in non-exposed zones by a large margin, particularly in East Asia, where high-hazard settlements have expanded 60% faster than flood-safe settlements. These results provide systematic evidence of a divergence in the exposure of countries to flood hazards. Instead of adapting their exposure, many countries continue to actively amplify their exposure to increasingly frequent climatic shocks.

Analysis of the spatial-temporal distribution characteristics of hepatitis E in Jiangsu province from 2005 to 2020.

Objective: This study attempts to analyze the spatial clustering and spatial-temporal distribution characteristics of hepatitis E (HE) at the county (city and district) level in Jiangsu province to provide a scientific basis for the prevention and control of HE. Method: The information on HE cases reported in the Chinese Center for Disease Control and Prevention Information System from 2005 to 2020 was collected for spatial autocorrelation analysis and spatial-temporal clustering analysis. Result: From 2005 to 2020, 48,456 HE cases were reported in Jiangsu province, with an average annual incidence rate of 3.87/100,000. Male cases outnumbered female cases (2.46:1), and the incidence was highest in the 30-70 years of age group (80.50%). Farmers accounted for more than half of all cases (59.86%), and in terms of the average annual incidence, the top three cities were all in Zhenjiang city. Spatial autocorrelation analysis showed that Global Moran's I of HE incidence varied from 0.232 to 0.513 for the years. From 2005 to 2020, 31 counties (cities and districts) had high and statistically significant HE incidence, and two clustering areas were detected by spatial-temporal scanning. Conclusion: HE incidence in Jiangsu province from 2005 to 2020 was stable, with age and gender differences, regional clustering, and spatial-temporal clustering. Further investigation of HE clustering areas is necessary to formulate corresponding targeted prevention and control measures.

The global wildland-urban interface.

The wildland-urban interface (WUI) is where buildings and wildland vegetation meet or intermingle1,2. It is where human-environmental conflicts and risks can be concentrated, including the loss of houses and lives to wildfire, habitat loss and fragmentation and the spread of zoonotic diseases3. However, a global analysis of the WUI has been lacking. Here, we present a global map of the 2020 WUI at 10 m resolution using a globally consistent and validated approach based on remote sensing-derived datasets of building area4 and wildland vegetation5. We show that the WUI is a global phenomenon, identify many previously undocumented WUI hotspots and highlight the wide range of population density, land cover types and biomass levels in different parts of the global WUI. The WUI covers only 4.7% of the land surface but is home to nearly half its population (3.5 billion). The WUI is especially widespread in Europe (15% of the land area) and the temperate broadleaf and mixed forests biome (18%). Of all people living near 2003-2020 wildfires (0.4 billion), two thirds have their home in the WUI, most of them in Africa (150 million). Given that wildfire activity is predicted to increase because of climate change in many regions6, there is a need to understand housing growth and vegetation patterns as drivers of WUI change.

Japanese Local Governments' Dissemination Activities for Advance Care Planning: A Descriptive Analysis of a Nationwide Survey during the COVID-19 Pandemic.

This study aims to compare the awareness-raising activities between municipalities with and without focused anti-infection measures during the 2019 coronavirus disease (COVID-19) pandemic. Descriptive analysis was conducted using a nationwide self-administered questionnaire survey on municipalities' activities for residents and for healthcare providers and care workers (HCPs) in October 2022 in Japan. This study included 433 municipalities that had conducted awareness-raising activities before 2019 Fiscal Year. Workshops for residents were conducted in 85.2% of the municipalities, and they were more likely to be conducted in areas with focused anti-infection measures than those without measures (86.8% vs. 75.4%). Additionally, 85.9% of the municipalities were impacted by the pandemic; 50.1% canceled workshops, while 26.0% switched to a web-based style. Activities for HCPs were conducted in 55.2-63.7% of the municipalities, and they were more likely to be conducted in areas with focused anti-infection measures. A total of 50.6-62.1% of the municipalities changed their workshops for HCPs to a web-based style. Comparisons between areas with and without focused anti-infection measures indicated that the percentages of those impacted for all activities were not significantly different. In conclusion, awareness-raising activities in municipalities were conducted with new methods during the COVID-19 pandemic. Using information technology is essential to further promote such activities for residents.

External Factors Impacting Residents' Participation in Waste Sorting Using NCA and fsQCA Methods on Pilot Cities in China.

Recycling waste is important as it can help to reduce environmental pollution caused by "waste siege". Source classification is an important part of the municipal solid waste (MSW) sorting process. The factors that prompt residents to participate in waste sorting have been debated by scholars in recent years; however, there are not many papers that focus on the complex relationships between them. This study reviewed the literature that concerns residents' participation in waste sorting, and it summarized the external factors that might influence residents' participation. Then, we focused on 25 pilot cities in China, and we analyzed the configuration impact of external factors on residents' participation using a necessary condition analysis (NCA) and a fuzzy-set qualitative comparative analysis (fsQCA). We found no consistency between variables, nor was there one single condition that caused residents to participate in waste sorting. There are two main methods (environment-driven and resource-driven) that can help achieve a high participation rate, and three methods that can cause a low participation rate. This study provides suggestions for the implementation of waste sorting in other cities in China, as well as developing countries, with an emphasis on the importance of public participation.

Religious Afterlife Beliefs Decrease Behavioral Avoidance of Symbols of Mortality.

An astonishing cultural phenomenon is where, far away from or close to a city center, people in different societies localize cemeteries that function as both sites of memory of lost ones and symbols of mortality. Yet a psychological account of such differences in behavioral responses to symbols of mortality is lacking. Across five studies (N = 1,590), we tested a psychological model that religious afterlife beliefs decrease behavioral avoidance of symbols of mortality (BASM) by developing and validating a word-position task for quantifying BASM. We showed evidence that religious believers, including Christians, Muslims, Hindus, and Buddhists, exhibited decreased BASM relative to nonbelievers. We also provide evidence for a causal relationship between religious afterlife beliefs and reduced BASM. Our findings provide new insight into the functional role of religious afterlife beliefs in modulating human avoidance behavior in response to symbols of mortality.

Nematodes and trematodes associated with terrestrial gastropods in Nottingham, England.

A parasitological survey of terrestrial slugs and snails was conducted at popular dog walking locations across the city of Nottingham, with the intensions of finding gastropods infected with parasites of medical (or veterinary) importance such as lungworm (metastrongyloid nematodes) and trematodes. A total of 800 gastropods were collected from 16 sites over a 225 km2 area. The extracted nematodes and trematodes were identified by molecular barcoding. Of the 800 gastropods collected, 227 were infected (172 had nematode infections, 37 had trematode infections and 18 had both nematode and trematode infections). Of the nematode infected gastropods genotyped, seven species were identified, Agfa flexilis, Angiostoma gandavense, Angiostoma margaretae, Cosmocerca longicauda, Phasmarhabditis hermaphrodita, Phasmarhabditis neopapillosa and an unknown Cosmocercidae species. Of the trematode infected gastropods genotyped, four species were identified, Brachylaima arcuate, Brachylaima fuscata, Brachylaima mesostoma and an unknown Plagiorchioidea species. No lungworm species were found within the city of Nottingham. To our knowledge, this study represents the first survey of gastropod-associated nematodes and trematodes in the East midlands of the United Kingdom.

Impact of COVID-19 lockdown on PM concentrations in an Italian Northern City: A year-by-year assessment.

In the last century, the increase in traffic, human activities and industrial production have led to a diffuse presence of air pollution, which causes an increase of risk of several health conditions such as respiratory diseases. In Europe, air pollution is a serious concern that affects several areas, one of the worst ones being northern Italy, and in particular the Po Valley, an area characterized by low air quality due to a combination of high population density, industrial activity, geographical factors and weather conditions. Public health authorities and local administrations are aware of this problem, and periodically intervene with temporary traffic limitations and other regulations, often insufficient to solve the problem. In February 2020, this area was the first in Europe to be severely hit by the SARS-CoV-2 virus causing the COVID-19 disease, to which the Italian government reacted with the establishment of a drastic lockdown. This situation created the condition to study how significant is the impact of car traffic and industrial activity on the pollution in the area, as these factors were strongly reduced during the lockdown. Differently from some areas in the world, a drastic decrease in pollution measured in terms of particulate matter (PM) was not observed in the Po Valley during the lockdown, suggesting that several external factors can play a role in determining the severity of pollution. In this study, we report the case study of the city of Pavia, where data coming from 23 air quality sensors were analyzed to compare the levels measured during the lockdown with the ones coming from the same period in 2019. Our results show that, on a global scale, there was a statistically significant reduction in terms of PM levels taking into account meteorological variables that can influence pollution such as wind, temperature, humidity, rain and solar radiation. Differences can be noticed analyzing daily pollution trends too, as-compared to the study period in 2019-during the study period in 2020 pollution was higher in the morning and lower in the remaining hours.

Correlation between mobility in mass transport and mortality due to COVID-19: A comparison of Mexico City, New York, and Madrid from a data science perspective.

In most big cities, public transports are enclosed and crowded spaces. Therefore, they are considered as one of the most important triggers of COVID-19 spread. Most of the existing research related to the mobility of people and COVID-19 spread is focused on investigating highly frequented paths by analyzing data collected from mobile devices, which mainly refer to geo-positioning records. In contrast, this paper tackles the problem by studying mass mobility. The relations between daily mobility on public transport (subway or metro) in three big cities and mortality due to COVID-19 are investigated. Data collected for these purposes come from official sources, such as the web pages of the cities' local governments. To provide a systematic framework, we applied the IBM Foundational Methodology for Data Science to the epidemiological domain of this paper. Our analysis consists of moving averages with a moving window equal to seven days so as to avoid bias due to weekly tendencies. Among the main findings of this work are: a) New York City and Madrid show similar distribution on studied variables, which resemble a Gauss bell, in contrast to Mexico City, and b) Non-pharmaceutical interventions don't bring immediate results, and reductions to the number of deaths due to COVID are observed after a certain number of days. This paper yields partial evidence for assessing the effectiveness of public policies in mitigating the COVID-19 pandemic.

Quantification of industrial wastewater discharge from the major cities in Sichuan province, China.

In this study, we used spatial autocorrelation, Environmental Kuznets Curve (EKC), and Logarithmic Mean Divisia Index model to study the spatial characteristics and driving factors of industrial wastewater discharge in Sichuan province (2003-2018). We showed that the amount of industrial wastewater discharge in Sichuan province for the period was reduced from 116,580 to 42,064.96 million tons as observed from the Moran index ranging from -0.310 to 0.302. We identified that the EKC type of Sichuan province was monotonically decreasing and six types of the EKC (monotonically decreasing, monotonically increasing, U, N, inverted U, and inverted N, shape) in 18 major cities. The technical effect (from -0.0964 to -8.8912) can reduce the discharge of industrial wastewater, while the economy effect (0.2948-5.882), structure effect (0.0892-4.5183), and population effect (from -0.0059 to 0.2873) can promote the industrial wastewater discharge. Our findings suggest that industrial wastewater discharge was reduced and changed from non-significant dissociation to non-significant agglomeration to non-significant dissociation during the study period. Furthermore, technical management upgrade is the primary driver in Sichuan province to reduce industrial wastewater discharge during this period.

Evaluation of tourism competitiveness and mechanisms of spatial differentiation in Xinjiang, China.

Evaluation of tourism competitiveness is useful for measuring the level of regional tourism development. It is of great importance to understand the advantages and disadvantages of tourism development correctly and formulate corresponding development strategies. To investigate tourism competitiveness, this paper established an evaluation index system, including tourism development competitiveness, tourism resource competitiveness, and tourism-support competitiveness, for 14 prefectures and cities in Xinjiang in China. The characteristics and laws of spatial differentiation were analyzed. Factor analysis was applied to examine the spatial differentiation of regional tourism competitiveness. The results showed an obvious spatial differentiation in tourism competitiveness among the 14 prefectures and cities. In terms of development competitiveness, Yili and Urumqi constituted the spatial center, followed by Changji, Altay, and Ba Prefecture. As the provincial capital, Urumqi has political, economic, cultural, transportation, and geographic advantages, but its competitiveness is not prominent in terms of monopoly and efficiency. In terms of resource competitiveness, Yili is the core attraction, while Urumqi, Kashgar, Altay, and Ba Prefecture are dominant attractions. With respect to supporting competitiveness, Bo Prefecture has high value, followed by Urumqi City and Aksu. Hetian and Ke Prefecture have the lowest values. The comprehensive competitiveness of tourism is centered on Yili. Urumqi and Bo Prefecture are subcenters, and Changji, Altay, Ba Prefecture, Aksu, and Kashgar are characterized as multi-polar competition areas. Using the KMO and Bartlett's sphericity tests, the cumulative contribution variance of the eigenvalues of the eight factors extracted by the maximum variance rotation method was found to be 92.714%. Socio-economic conditions, tourism resources, infrastructure construction, regional cultural influence, ecological environment carrying capacity, tertiary industry development, tourism service level, and living security system are the main driving factors affecting the spatial differentiation of tourism competitiveness in Xinjiang. Analyzing the spatial evolution characteristics and the driving factors of the regional tourism competitiveness in Xinjiang, this paper seeks to promote the optimal allocation of tourism production factors in the macro regional system, and provide theoretical guidance and an empirical basis for the comprehensive and harmonic development of regional tourism.

Study on temporal and spatial differentiation of biocapacity in Shenyang from a multi-scale perspective.

Biocapacity of a region exhibits spatial differences owing to the limitations of regional scale and natural conditions. Based on the multi-scale perspective, we comprehensively studied and analyzed the temporal and spatial differences of the biocapacity of a region in an attempt to establish the groundwork for optimizing urban development and its utilization framework. By adopting the ecological footprint model along with multi-scale difference evaluation method, the municipal and county scales are incorporated into a unified analysis framework in this paper, thereby facilitating the exploration of the temporal and spatial differences in the biocapacity of Shenyang-a city in China-from 2005 to 2019. The results demonstrated that: 1) At the municipal scale, the biocapacity per capita fluctuated between 1.35 hm2/person and 2.22 hm2/person. It revealed an "up-down-up" trend, which appeared consistent with the Kuznets cycle; at the county scale, the biocapacity depicted spatial differences, while those of downtown and surrounding districts/counties developed a two-level ascending hierarchical structure. 2) The time series of footprint size and depth first ascended and then declined, and can be classified into four types: closed type, inverted U-type, S-type, and M-type. Among them, S-type and M-type have the phenomenon of over-utilizing the stock capital. 3) For a long time, the regional difference of biocapacity has mostly dwelt on two scales with an evident scale effect, and the biocapacity of Liaozhong District was the worst.

Novel Epidemic Metrics to Communicate Outbreak Risk at the Municipality Level: Dengue and Zika in the Dominican Republic.

Arboviruses remain a significant cause of morbidity, mortality and economic cost across the global human population. Epidemics of arboviral disease, such as Zika and dengue, also cause significant disruption to health services at local and national levels. This study examined 2014-2016 Zika and dengue epidemic data at the sub-national level to characterise transmission across the Dominican Republic. For each municipality, spatio-temporal mapping was used to characterise disease burden, while data were age and sex standardised to quantify burden distributions among the population. In separate analyses, time-ordered data were combined with the underlying disease migration interval distribution to produce a network of likely transmission chain events, displayed using transmission chain likelihood matrices. Finally, municipal-specific reproduction numbers (Rm) were established using a Wallinga-Teunis matrix. Dengue and Zika epidemics peaked during weeks 39-52 of 2015 and weeks 14-27 of 2016, respectively. At the provincial level, dengue attack rates were high in Hermanas Mirabal and San José de Ocoa (58.1 and 49.2 cases per 10,000 population, respectively), compared with the Zika burden, which was highest in Independencia and San José de Ocoa (21.2 and 13.4 cases per 10,000 population, respectively). Across municipalities, high disease burden was observed in Cotuí (622 dengue cases per 10,000 population) and Jimani (32 Zika cases per 10,000 population). Municipal infector-infectee transmission likelihood matrices identified seven 0% likelihood transmission events throughout the dengue epidemic and two 0% likelihood transmission events during the Zika epidemic. Municipality reproduction numbers (Rm) were consistently higher, and persisted for a greater duration, during the Zika epidemic (Rm = 1.0) than during the dengue epidemic (Rm < 1.0). This research highlights the importance of disease surveillance in land border municipalities as an early warning for infectious disease transmission. It also demonstrates that a high number of importation events are required to sustain transmission in endemic settings, and vice versa for newly emerged diseases. The inception of a novel epidemiological metric, Rm, reports transmission risk using standardised spatial units, and can be used to identify high transmission risk municipalities to better focus public health interventions for dengue, Zika and other infectious diseases.

Spatial correlations in geographical spreading of COVID-19 in the United States.

The global spread of the COVID-19 pandemic has followed complex pathways, largely attributed to the high virus infectivity, human travel patterns, and the implementation of multiple mitigation measures. The resulting geographic patterns describe the evolution of the epidemic and can indicate areas that are at risk of an outbreak. Here, we analyze the spatial correlations of new active cases in the USA at the county level and characterize the extent of these correlations at different times. We show that the epidemic did not progress uniformly and we identify various stages which are distinguished by significant differences in the correlation length. Our results indicate that the correlation length may be large even during periods when the number of cases declines. We find that correlations between urban centers were much more significant than between rural areas and this finding indicates that long-range spreading was mainly facilitated by travel between cities, especially at the first months of the epidemic. We also show the existence of a percolation transition in November 2020, when the largest part of the country was connected to a spanning cluster, and a smaller-scale transition in January 2021, with both times corresponding to the peak of the epidemic in the country.