Urban-rural disparities in COVID-19 hospitalisations and mortality: A population-based study on national surveillance data from Germany and Italy.

PURPOSE: Recent literature has highlighted the overlapping contribution of demographic characteristics and spatial factors to urban-rural disparities in SARS-CoV-2 transmission and outcomes. Yet the interplay between individual characteristics, hospitalisation, and spatial factors for urban-rural disparities in COVID-19 mortality have received limited attention. METHODS: To fill this gap, we use national surveillance data collected by the European Centre for Disease Prevention and Control and we fit a generalized linear model to estimate the association between COVID-19 mortality and the individuals' age, sex, hospitalisation status, population density, share of the population over the age of 60, and pandemic wave across urban, intermediate and rural territories. FINDINGS: We find that in what type of territory individuals live (urban-intermediate-rural) accounts for a significant difference in their probability of dying given SARS-COV-2 infection. Hospitalisation has a large and positive effect on the probability of dying given SARS-CoV-2 infection, but with a gradient across urban, intermediate and rural territories. For those living in rural areas, the risk of dying is lower than in urban areas but only if hospitalisation was not needed; while for those who were hospitalised in rural areas the risk of dying was higher than in urban areas. CONCLUSIONS: Together with individuals' demographic characteristics (notably age), hospitalisation has the largest effect on urban-rural disparities in COVID-19 mortality net of other individual and regional characteristics, including population density and the share of the population over 60.

An immuno-epidemiological model with waning immunity after infection or vaccination.

In epidemics, waning immunity is common after infection or vaccination of individuals. Immunity levels are highly heterogeneous and dynamic. This work presents an immuno-epidemiological model that captures the fundamental dynamic features of immunity acquisition and wane after infection or vaccination and analyzes mathematically its dynamical properties. The model consists of a system of first order partial differential equations, involving nonlinear integral terms and different transfer velocities. Structurally, the equation may be interpreted as a Fokker-Planck equation for a piecewise deterministic process. However, unlike the usual models, our equation involves nonlocal effects, representing the infectivity of the whole environment. This, together with the presence of different transfer velocities, makes the proved existence of a solution novel and nontrivial. In addition, the asymptotic behavior of the model is analyzed based on the obtained qualitative properties of the solution. An optimal control problem with objective function including the total number of deaths and costs of vaccination is explored. Numerical results describe the dynamic relationship between contact rates and optimal solutions. The approach can contribute to the understanding of the dynamics of immune responses at population level and may guide public health policies.

A mathematical model for the within-host (re)infection dynamics of SARS-CoV-2.

Interactions between SARS-CoV-2 and the immune system during infection are complex. However, understanding the within-host SARS-CoV-2 dynamics is of enormous importance for clinical and public health outcomes. Current mathematical models focus on describing the within-host SARS-CoV-2 dynamics during the acute infection phase. Thereby they ignore important long-term post-acute infection effects. We present a mathematical model, which not only describes the SARS-CoV-2 infection dynamics during the acute infection phase, but extends current approaches by also recapitulating clinically observed long-term post-acute infection effects, such as the recovery of the number of susceptible epithelial cells to an initial pre-infection homeostatic level, a permanent and full clearance of the infection within the individual, immune waning, and the formation of long-term immune capacity levels after infection. Finally, we used our model and its description of the long-term post-acute infection dynamics to explore reinfection scenarios differentiating between distinct variant-specific properties of the reinfecting virus. Together, the model's ability to describe not only the acute but also the long-term post-acute infection dynamics provides a more realistic description of key outcomes and allows for its application in clinical and public health scenarios.

Effects of climatic and environmental factors on mosquito population inferred from West Nile virus surveillance in Greece.

Mosquito-borne diseases' impact on human health is among the most prominent of all communicable diseases. With limited pool of tools to contrast these diseases, public health focus remains preventing mosquito-human contacts. Applying a hierarchical spatio-temporal Bayesian model on West Nile virus (WNV) surveillance data from Greece, we aimed to investigate the impact of climatic and environmental factors on Culex mosquitoes' population. Our spatio-temporal analysis confirmed climatic factors as major drivers of WNV-transmitting-Culex mosquitoes population dynamics, with temperature and long periods of moderate-to-warm climate having the strongest positive effect on mosquito abundance. Conversely, rainfall, high humidity, and wind showed a negative impact. The results suggest the presence of statistically significant differences in the effect of regional and seasonal characteristics, highlighting the complex interplay between climatic, geographical and environmental factors in the dynamics of mosquito populations. This study may represent a relevant tool to inform public health policymakers in planning preventive measures.

Demographic characteristics associated with West Nile virus neuroinvasive disease - A retrospective study on the wider European area 2006-2021.

BACKGROUND: With a case-fatality-risk ranging from 3.0 to >20.0% and life-long sequelae, West Nile neuroinvasive disease (WNND) is the most dangerous outcome of West Nile virus (WNV) infection in humans. As no specific prophylaxis nor therapy is available for these infections, focus is on preventive strategies. We aimed to find variables associated with WNND diagnosis, hospitalisation or death, to identify high-risk sub-groups of the population, on whom to concentrate these strategies. METHODS: We used data from The European Surveillance System-TESSy, provided by National Public Health Authorities, and released by the European Centre for Disease Prevention and Control (ECDC). In two Firth-penalised logistic regression models, we considered age, sex, clinical criteria, epidemiological link to other cases (epi-link), calendar year, and season as potential associated variables. In one model we considered also the rural/urban classification of the place of infection (RUC), while in the other the specific reporting country. FINDINGS: Among confirmed West Nile Virus cases, 2,916 WNND cases were registered, of which 2,081 (71.4%), and 383 (13.1%) resulted in the hospitalisation and death of the patient, respectively. Calendar year, RUC/country, age, sex, clinical criteria, and epi-link were associated with WNND diagnosis. Hospitalisation was associated with calendar year and RUC/country; whereas death was associated with age, sex and country. INTERPRETATION: Our results support previous findings on WNND associated variables (most notably age and sex); while by observing the whole population of WNND cases in the considered area and period, they also allow for stronger generalizations, conversely to the majority of previous studies, which used sample populations.

Demographic risk factors, healthcare utilization, and mortality during the first year of the Covid-19 pandemic in Austria, Germany, and Italy.

At the population level, there is limited empirical evidence on the characteristics of individuals who were hospitalized because of Covid-19, the role of hospitalization in mortality risk, and how both evolved over time. Through the analysis of surveillance data for 7 million people in Austria, Germany, and Italy, we investigate: (1) the demographic characteristics and outcomes of individuals hospitalized because of Covid-19; and (2) the role of demographic risk factors and healthcare utilization (as measured by hospitalization) for the individual probability of dying because of Covid-19, in both cases comparing the period February to June 2020 with July 2020 to February 2021. We find that the demographic profile of individuals who were hospitalized or died because of Covid-19 is the same in both periods, except for a younger age profile for hospitalizations in the second period. Mortality differentials across countries result from the interaction of demographic risk factors and hospitalization at the individual level.

The evolution of SARS-CoV-2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of deaths and substantial morbidity worldwide. Intense scientific effort to understand the biology of SARS-CoV-2 has resulted in daunting numbers of genomic sequences. We witnessed evolutionary events that could mostly be inferred indirectly before, such as the emergence of variants with distinct phenotypes, for example transmissibility, severity and immune evasion. This Review explores the mechanisms that generate genetic variation in SARS-CoV-2, underlying the within-host and population-level processes that underpin these events. We examine the selective forces that likely drove the evolution of higher transmissibility and, in some cases, higher severity during the first year of the pandemic and the role of antigenic evolution during the second and third years, together with the implications of immune escape and reinfections, and the increasing evidence for and potential relevance of recombination. In order to understand how major lineages, such as variants of concern (VOCs), are generated, we contrast the evidence for the chronic infection model underlying the emergence of VOCs with the possibility of an animal reservoir playing a role in SARS-CoV-2 evolution, and conclude that the former is more likely. We evaluate uncertainties and outline scenarios for the possible future evolutionary trajectories of SARS-CoV-2.

Optimal vaccination strategies using a distributed model applied to COVID-19.

Optimal distribution of vaccines to achieve high population immunity levels is a desirable aim in infectious disease epidemiology. A distributed optimal control epidemiological model that accounts for vaccination was developed and applied to the case of the COVID-19 pandemic. The model proposed here is nonstandard and takes into account the heterogeneity of the infected sub-population with respect to the time since infection, which is essential in the case of COVID-19. Based on the epidemiological characteristics of COVID-19 we analyze several vaccination scenarios and an optimal vaccination policy. In particular we consider random vaccination over the whole population and the prioritization of age groups such as the elderly and compare the effects with the optimal solution. Numerical results of the model show that random vaccination is efficient in reducing the overall number of infected individuals. Prioritization of the elderly leads to lower mortality though. The optimal strategy in terms of total deaths is early prioritization of those groups having the highest contact rates.

An epidemiological model for mosquito host selection and temperature-dependent transmission of West Nile virus.

We extend a previously developed epidemiological model for West Nile virus (WNV) infection in humans in Greece, employing laboratory-confirmed WNV cases and mosquito-specific characteristics of transmission, such as host selection and temperature-dependent transmission of the virus. Host selection was defined by bird host selection and human host selection, the latter accounting only for the fraction of humans that develop symptoms after the virus is acquired. To model the role of temperature on virus transmission, we considered five temperature intervals (≤ 19.25 °C; > 19.25 and < 21.75 °C; ≥ 21.75 and < 24.25 °C; ≥ 24.25 and < 26.75 °C; and > 26.75 °C). The capacity of the new model to fit human cases and the week of first case occurrence was compared with the original model and showed improved performance. The model was also used to infer further quantities of interest, such as the force of infection for different temperatures as well as mosquito and bird abundances. Our results indicate that the inclusion of mosquito-specific characteristics in epidemiological models of mosquito-borne diseases leads to improved modelling capacity.

Host selection and forage ratio in West Nile virus-transmitting Culex mosquitoes: Challenges and knowledge gaps.

BACKGROUND: To date, no specific therapy or vaccination is available for West Nile virus (WNV) infections in humans; preventive strategies represent the only possibility to control transmission. To focus these strategies, detailed knowledge of the virus dynamics is of paramount importance. However, several aspects of WNV transmission are still unclear, especially regarding the role of potential vertebrate host species. Whereas mosquitoes' intrinsic characteristics cause them to favour certain hosts (host preference), absolute selection is impossible in natural settings. Conversely, the selection carried out among available hosts and influenced from hosts' availability and other ecological/environmental factors is defined as host selection. METHODOLOGY/PRINCIPAL FINDINGS: In July 2022, we searched PubMed database for original articles exploring host selection among WNV-transmitting Culex mosquitoes, the main WNV vector. We considered only original field studies estimating and reporting forage ratio. This index results from the ratio between the proportion of blood meals taken by mosquitoes on potential host species and the hosts' relative abundance. From the originally retrieved 585 articles, 9 matched the inclusion criteria and were included in this review. All but one of the included studies were conducted in the Americas, six in the United States, and one each in Mexico and Colombia. The remaining study was conducted in Italy. American Robin, Northern Cardinal, and House Finch were the most significantly preferred birds in the Americas, Common Blackbird in Italy. CONCLUSIONS/SIGNIFICANCE: Although ornithophilic, all observed WNV-transmitting mosquitoes presented opportunistic feeding behaviour. All the observed species showed potential to act as bridges for zoonotic diseases, feeding also on humans. All the observed mosquitoes presented host selection patterns and did not feed on hosts as expected by chance alone. The articles observe different species of mosquitoes in different environments. In addition, the way the relative host abundance was determined differed. Finally, this review is not systematic. Therefore, the translation of our results to different settings should be conducted cautiously.

Demographics of COVID-19 hospitalisations and related fatality risk patterns.

The assessment of hospitalisations and intensive care is crucial for planning health care resources needed over the course of the coronavirus disease 2019 (COVID-19) pandemic. Nonetheless, comparative empirical assessments of COVID-19 hospitalisations and related fatality risk patterns on a large scale are lacking. This paper exploits anonymised, individual-level data on SARS-CoV-2 confirmed infections collected and harmonized by the European Centre for Disease Prevention and Control to profile the demographics of COVID-19 hospitalised patients across nine European countries during the first pandemic wave (February - June 2020). We estimate the role of demographic factors for the risk of in-hospital mortality, and present a case study exploring individuals' comorbidities based on a subset of COVID-19 hospitalised patients available from the Dutch health system. We find that hospitalisation rates are highest among individuals with confirmed SARS-CoV-2 infection who are not only older than 70 years, but also 50-69 years. The latter group has a longer median time between COVID-19 symptoms' onset and hospitalisation than those aged 70+ years. Men have higher hospitalisation rates than women at all ages, and particularly above age 50. Consistently, men aged 50-59 years have a probability of hospitalisation almost double than women do. Although the gender imbalance in hospitalisation remains above age 70, the gap between men and women narrows at older ages. Comorbidities play a key role in explaining selection effects of COVID-19 confirmed positive cases requiring hospitalisation. Our study contributes to the evaluation of the COVID-19 burden on the demand of health-care during emergency phases. Assessing intensity and timing dimensions of hospital admissions, our findings allow for a better understanding of COVID-19 severe outcomes. Results point to the need of suitable calibrations of epidemiological projections and (re)planning of health services, enhancing preparedness to deal with infectious disease outbreaks.

The Relevance of Leisure Noise to Hearing Threshold Shifts: A Longitudinal Analysis Among Adolescents.

PURPOSE: The aim of this study was to analyze the association of total leisure noise exposure and hearing threshold shifts over 5 years among adolescents enrolled in the Ohrkan cohort study. METHOD: The Ohrkan cohort of 2,148 students aged 13-19 years was recruited from 2009 to 2011 and followed up 5 years later. Complete baseline and follow-up reports on exposure and outcome were available for 989 participants. Leisure noise exposure was assessed by questionnaires, and clinical audiometric examinations were performed. Two outcomes were defined: occurrence of the Niskar notch pattern and audiometry showing maximum hearing threshold values at 3, 4, and 6 kHz (both ears). Longitudinal analysis using generalized estimating equations was performed. RESULTS: High total leisure noise exposure, defined as an energy equivalent of a 40-hr week of > 85 dBA, was estimated for 32.7% of students at baseline and 63.8% at follow-up. A noise notch was observed in 1.1% of adolescents at baseline and 3.3% at follow-up. At baseline, the maximum measured threshold shift was 55 dB, which increased to 85 dB at the follow-up. Longitudinal analysis did not reveal an association between leisure noise exposure and hearing thresholds. Hearing threshold shifts or noise notches were associated with sex, school type, and time point of measurement. CONCLUSIONS: No relationship was found between leisure noise and hearing thresholds. Male adolescents and those attending secondary general schools, with graduation following completion of ninth or 10th grade, had a greater likelihood of developing hearing threshold shifts. Prevention programs should focus on these risk groups. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.19233462.

A climate-dependent spatial epidemiological model for the transmission risk of West Nile virus at local scale.

In this study, initial elements of a modelling framework aimed to become a spatial forecasting model for the transmission risk of West Nile virus (WNV) are presented. The model describes the dynamics of a WNV epidemic in population health states of mosquitoes, birds and humans and was applied to the case of Greece for the period 2010-2019. Calibration was performed with the available epidemiological data from the Hellenic Centre for Disease Control and Prevention and the environmental data from the European Union's earth observation program, Copernicus. Numerical results of the model for each municipality were evaluated against observations. Specifically, the occurrence of WNV, the number of infected humans and the week of incidence predicted from the model were compared to the corresponding numbers from observations. The results suggest that dynamic downscaling of a climate-dependent epidemiological model is feasible down-to roughly 80km2. This below nomenclature of territorial units for statistics (NUTS) 3 level represents the municipalities being the lowest level of administrative units, able to cope with WNV and take actions. The average detection probability in hindcast mode was 72%, improving strongly as the number of infected humans increased. Using the developed model, we were also able to show the fundamental importance of the May temperatures in shaping the WNV dynamics. The modeling framework couples epidemiological and environmental dynamical variables with surveillance data producing risk maps downscaled at a local level. The approach can be expanded to provide targeted early warning probabilistic forecasts that can be used to inform public health policy decision making.

Droplets and aerosols: An artificial dichotomy in respiratory virus transmission.

In the medical literature, three mutually non-exclusive modes of pathogen transmission associated with respiratory droplets are usually identified: contact, droplet, and airborne (or aerosol) transmission. The demarcation between droplet and airborne transmission is often based on a cut-off droplet diameter, most commonly 5 µm. We argue here that the infectivity of a droplet, and consequently the transmissivity of the virus, as a function of droplet size is a continuum, depending on numerous factors (gravitational settling rate, transport, and dispersion in a turbulent air jet, viral load and viral shedding, virus inactivation) that cannot be adequately characterized by a single droplet diameter. We propose instead that droplet and aerosol transmission should be replaced by a unique airborne transmission mode, to be distinguished from contact transmission.

On the Transmission Dynamics of SARS-CoV-2 in a Temperate Climate.

An epidemiological model, which describes the transmission dynamics of SARS-CoV-2 under specific consideration of the incubation period including the population with subclinical infections and being infective is presented. The COVID-19 epidemic in Greece was explored through a Monte Carlo uncertainty analysis framework, and the optimal values for the parameters that determined the transmission dynamics could be obtained before, during, and after the interventions to control the epidemic. The dynamic change of the fraction of asymptomatic individuals was shown. The analysis of the modelling results at the intra-annual climatic scale allowed for in depth investigation of the transmission dynamics of SARS-CoV-2 and the significance and relative importance of the model parameters. Moreover, the analysis at this scale incorporated the exploration of the forecast horizon and its variability. Three discrete peaks were found in the transmission rates throughout the investigated period (15 February-15 December 2020). Two of them corresponded to the timing of the spring and autumn epidemic waves while the third one occurred in mid-summer, implying that relaxation of social distancing and increased mobility may have a strong effect on rekindling the epidemic dynamics offsetting positive effects from factors such as decreased household crowding and increased environmental ultraviolet radiation. In addition, the epidemiological state was found to constitute a significant indicator of the forecast reliability horizon, spanning from as low as few days to more than four weeks. Embedding the model in an ensemble framework may extend the predictability horizon. Therefore, it may contribute to the accuracy of health risk assessment and inform public health decision making of more efficient control measures.

Assessment of West nile virus transmission risk from a weather-dependent epidemiological model and a global sensitivity analysis framework.

West Nile virus (WNV) transmission risk is strongly related to weather conditions due to the sensitivity of the mosquitoes to climatic factors. We assess the WNV transmission risk of humans to seasonal weather conditions and the relative effects of parameters affecting the transmission dynamics. The assessment involves a known epidemiological model we extend to account for temperature and precipitation and a global uncertainty and sensitivity analysis framework. We focus on three relevant quantities, the basic reproduction number (R0), the minimum infection rate (MIR), and the number of infected individuals. The highest-priority weather-related WNV transmission risks can be attributed to the birth and death rate of mosquitoes, the biting rate of mosquitoes to birds, and the probability of transmission from birds to mosquitoes. Global sensitivity analysis indicates that these parameters make up a big part of the explained variance in R0 and MIR. The analysis allows for a dynamic assessment over time capturing the period parameters are more relevant than others. Global uncertainty and sensitivity analysis of WNV transmission risk to humans enable insights into the relative importance of individual parameters of the transmission cycle of the virus facilitating the understanding of the dynamics and the implementation of tailored control strategies.