Unambiguous Linkage Between the Vaccination Coverage and the Spread of COVID-19: Geostatistical Evidence from the Slovak LAU 1 Regions

This case study refutes some controversial findings about a minor connection between the vaccination coverage and the spread of COVID-19. We try to eliminate some methodological shortcomings and risks, which are included in such previously published studies. Firstly, our selection comprises all regional units in one country. Secondly, the quality of data is basically identical in all examined regions within the country. Thirdly, all Slovak regions had an equal starting position. They were at the same stages of the COVID-19 wave, and the measures taken were analogous in all regions. Slovakia with a significantly different vaccination rates among regions is a very suitable study case. We used the empirical data at the level of its LAU 1 regions for the two latest COVID-19 waves at that time (Delta, Omicron). The methods of regression analysis and geostatistical methods were applied in the study. Indubitably, there is an obvious link between the vaccination coverage and the spread of COVID-19. We have shown that the incidence-trajectories among regions vary based on the vaccination rates. The positivity and incidence in the most vaccinated regional populations were significantly lower than in the least vaccinated regions in a whole analyzed period. Their values in the best vaccinated regions were lower by roughly 20-25 % during the delta and omicron wave-peaks. Using the spatial autocorrelation, we also managed to clearly identify a close relationship between vaccination on the one hand and standardized incidence and positivity on the other hand, although some regions deviated from this general finding.

Assessing the spread risk of COVID-19 associated with multi-mode transportation networks in China

The spatial spread of COVID-19 during early 2020 in China was primarily driven by outbound travelers leaving the epicenter, Wuhan, Hubei province. Existing studies focus on the influence of aggregated out-bound popula-tion flows originating from Wuhan;however, the impacts of different modes of transportation and the network structure of transportation systems on the early spread of COVID-19 in China are not well understood. Here, we assess the roles of the road, railway, and air transportation networks in driving the spatial spread of COVID-19 in China. We find that the short-range spread within Hubei province was dominated by ground traffic, notably, the railway transportation. In contrast, long-range spread to cities in other provinces was mediated by multiple factors, including a higher risk of case importation associated with air transportation and a larger outbreak size in hub cities located at the center of transportation networks. We further show that, although the dissemination of SARS-CoV-2 across countries and continents is determined by the worldwide air transportation network, the early geographic dispersal of COVID-19 within China is better predicted by the railway traffic. Given the recent emergence of multiple more transmissible variants of SARS-CoV-2, our findings can support a better assessment of the spread risk of those variants and improve future pandemic preparedness and responses.

Socio-economic and demographic determinants of COVID-19 infections and spread at household level: case study from Nigeria

Many studies have associated the dynamics of diseases' prevalence with differences in social, economic and demographic status, but it is not yet clear if the same variables explain the spatial distribution of COVID-19 infections in parts of sub-Saharan Africa. This study assessed the spatial spread of COVID-19 infections in relation to socio-demographic risk factors in a typical administrative state – a relatively typical ethnocentric community – in Southwestern Nigeria. Data used were socio-demographics, income variables, COVID-19 status and travel history of 40,300 households. Data were analysed for frequency, prevalence and spatial distributions. The results revealed that COVID-19 cases were heterogeneously distributed within the state. The number of cases was relatively higher in the north and south-eastern parts of the State than in other areas. Male respondents had a higher prevalence (3.7%) of COVID-19 cases compared to their female (2.4%) counterparts. Transmission was most dominant among respondents aged above 70 years old (3.5%), widowed (3.3%) and those who lived in households with between 6 and 10 (4.9%) members. Transmission was also relatively high among those with travel history within the State (9.1%), those that aquired tertiary education (3.8%) and self-employed (3.0%). The study associated imbalanced socio-economic distributions to a diverse range of COVID-19 transmission in the area and therefore advocated for improved policy on residents' education and sustainable living.

Relative timing of respiratory syncytial virus epidemics in summer 2021 across the United States was similar to a typical winter season.

We used a validated proxy of respiratory syncytial virus (RSV) activity in the United States (Google search data) to evaluate the onsets of RSV epidemics in 2021 and 2016-2019. Despite the unusual out-of-season summer timing, the relative timing of RSV epidemics between states in 2021 shared a similar spatial pattern with typical winter RSV seasons. Our results suggest that the onset of RSV epidemics in Florida can serve as a baseline to adjust the initiation of prophylaxis administration and clinical trials in other states regardless of the seasonality of RSV epidemics.

Assessing the spread risk of COVID-19 associated with multi-mode transportation networks in China

The spatial spread of COVID-19 during early 2020 in China was primarily driven by outbound travelers leaving the epicenter, Wuhan, Hubei province. Existing studies focus on the influence of aggregated out-bound population flows originating from Wuhan;however, the impacts of different modes of transportation and the network structure of transportation systems on the early spread of COVID-19 in China are not well understood. Here, we assess the roles of the road, railway, and air transportation networks in driving the spatial spread of COVID-19 in China. We find that the short-range spread within Hubei province was dominated by ground traffic, notably, the railway transportation. In contrast, long-range spread to cities in other provinces was mediated by multiple factors, including a higher risk of case importation associated with air transportation and a larger outbreak size in hub cities located at the center of transportation networks. We further show that, although the dissemination of SARS-CoV-2 across countries and continents is determined by the worldwide air transportation network, the early geographic dispersal of COVID-19 within China is better predicted by the railway traffic. Given the recent emergence of multiple more transmissible variants of SARS-CoV-2, our findings can support a better assessment of the spread risk of those variants and improve future pandemic preparedness and responses.

Front Propagation of Exponentially Truncated Fractional-Order Epidemics

The existence of landscape constraints in the home range of living organisms that adopt Lévy-flight movement patterns, prevents them from making arbitrarily large displacements. Their random movements indeed occur in a finite space with an upper bound. In order to make realistic models, by introducing exponentially truncated Lévy flights, such an upper bound can thus be taken into account in the reaction-diffusion models. In this work, we have investigated the influence of the λ-truncated fractional-order diffusion operator on the spatial propagation of the epidemics caused by infectious diseases, where λ is the truncation parameter. Analytical and numerical simulations show that depending on the value of λ, different asymptotic behaviours of the travelling-wave solutions can be identified. For small values of λ (λ≳0), the tails of the infective waves can decay algebraically leading to an exponential growth of the epidemic speed. In that case, the truncation has no impact on the superdiffusive epidemics. By increasing the value of λ, the algebraic decaying tails can be tamed leading to either an upper bound on the epidemic speed representing the maximum speed value or the generation of the infective waves of a constant shape propagating at a minimum constant speed as observed in the classical models (second-order diffusion epidemic models). Our findings suggest that the truncated fractional-order diffusion equations have the potential to model the epidemics of animals performing Lévy flights, as the animal diseases can spread more smoothly than the exponential acceleration of the human disease epidemics.