Markers of community outbreak and facility type for mitigation of COVID-19 in long-term care homes in Ontario, Canada: Insights and implications from a time-series analysis

PURPOSE

The resident deaths among Long Term Care Home (LTCH) accounted for more than 65% of total deaths in the province of Ontario, Canada, during March 29 to June 3, 2020, yet not all LTCHs were severely affected.

METHODS

We carried out a retrospective cohort study, with case control for questions for which data allowed, with LTCH COVID-19 databases obtained from Ontario's Ministry of Long Term Care. We performed a combined temporal and spatial data analysis of COVID-19 cases and deaths among LTCH residents, identified trends, contributing factors, and early markers of LTCH outbreak severity.

RESULTS

Our analysis shows that for-profit LTCHs had higher death-to-bed ratio, also with an average rate of increase of death-to-bed ratio higher for for-profit homes than other types of management. We find from uni- and multi-variable analyses (linear and nonlinear) that staff infection has the strongest association with death-to-bed ratio from among the descriptor variables considered, reflecting the risk of the disease in the health region/community. We also identify a delay of up to 8 days between the trends in fatalities among individuals outside LTCHs and that of LTCH residents. We did find an association between policy change to single LTCH/staff and reduction in weekly LTCH resident death, albeit with an expected time delay of about 7-10 days.

CONCLUSIONS

The association between the risk of COVID-19 in the health region and the deaths among LTCH residents, and the delay between fatality among individuals residing outside and inside LTCHs suggests that fatality in a health region could be a predictor of outbreak in LTCHs within the same health region.

Associations between indoor relative humidity and global COVID-19 outcomes

Globally, the spread and severity of COVID-19 have been distinctly non-uniform. Seasonality was suggested as a contributor to regional variability, but the relationship between weather and COVID-19 remains unclear and the focus of attention has been on outdoor conditions. Because humans spend most of their time indoors and because most transmission occurs indoors, we here, instead, investigate the hypothesis that indoor climate-particularly indoor relative humidity (RH)-may be the more relevant modulator of outbreaks. To study this association, we combined population-based COVID-19 statistics and meteorological measurements from 121 countries. We rigorously processed epidemiological data to reduce bias, then developed and experimentally validated a computational workflow to estimate indoor conditions based on outdoor weather data and standard indoor comfort conditions. Our comprehensive analysis shows robust and systematic relationships between regional outbreaks and indoor RH. In particular, we found intermediate RH (40-60%) to be robustly associated with better COVID-19 outbreak outcomes (versus RH < 40% or >60%). Together, these results suggest that indoor conditions, particularly indoor RH, modulate the spread and severity of COVID-19 outbreaks.

Practical Indicators for Risk of Airborne Transmission in Shared Indoor Environments and Their Application to COVID-19 Outbreaks

Some infectious diseases, including COVID-19, can undergo airborne transmission. This may happen at close proximity, but as time indoors increases, infections can occur in shared room air despite distancing. We propose two indicators of infection risk for this situation, that is, relative risk parameter (H_r) and risk parameter (H). They combine the key factors that control airborne disease transmission indoors: virus-containing aerosol generation rate, breathing flow rate, masking and its quality, ventilation and aerosol-removal rates, number of occupants, and duration of exposure. COVID-19 outbreaks show a clear trend that is consistent with airborne infection and enable recommendations to minimize transmission risk. Transmission in typical prepandemic indoor spaces is highly sensitive to mitigation efforts. Previous outbreaks of measles, influenza, and tuberculosis were also assessed. Measles outbreaks occur at much lower risk parameter values than COVID-19, while tuberculosis outbreaks are observed at higher risk parameter values. Because both diseases are accepted as airborne, the fact that COVID-19 is less contagious than measles does not rule out airborne transmission. It is important that future outbreak reports include information on masking, ventilation and aerosol-removal rates, number of occupants, and duration of exposure, to investigate airborne transmission.

Practical Indicators for Risk of Airborne Transmission in Shared Indoor Environments and Their Application to COVID-19 Outbreaks

Some infectious diseases, including COVID-19, can undergo airborne transmission. This may happen at close proximity, but as time indoors increases, infections can occur in shared room air despite distancing. We propose two indicators of infection risk for this situation, that is, relative risk parameter (H_r) and risk parameter (H). They combine the key factors that control airborne disease transmission indoors: virus-containing aerosol generation rate, breathing flow rate, masking and its quality, ventilation and aerosol-removal rates, number of occupants, and duration of exposure. COVID-19 outbreaks show a clear trend that is consistent with airborne infection and enable recommendations to minimize transmission risk. Transmission in typical prepandemic indoor spaces is highly sensitive to mitigation efforts. Previous outbreaks of measles, influenza, and tuberculosis were also assessed. Measles outbreaks occur at much lower risk parameter values than COVID-19, while tuberculosis outbreaks are observed at higher risk parameter values. Because both diseases are accepted as airborne, the fact that COVID-19 is less contagious than measles does not rule out airborne transmission. It is important that future outbreak reports include information on masking, ventilation and aerosol-removal rates, number of occupants, and duration of exposure, to investigate airborne transmission.

Mitigating bias in estimating epidemic severity due to heterogeneity of epidemic onset and data aggregation

Outbreaks of infectious diseases, such as influenza, are a major societal burden. Mitigation policies during an outbreak or pandemic are guided by the analysis of data of ongoing or preceding epidemics. The reproduction number, R0, defined as the expected number of secondary infections arising from a single individual in a population of susceptibles is critical to epidemiology. For typical compartmental models such as the Susceptible-Infected-Recovered (SIR) R0 represents the severity of an epidemic. It is an estimate of the early-stage growth rate of an epidemic and is an important threshold parameter used to gain insights into the spread or decay of an outbreak. Models typically use incidence counts as indicators of cases within a single large population; however, epidemic data are the result of a hierarchical aggregation, where incidence counts from spatially separated monitoring sites (or sub-regions) are pooled and used to infer R0. Is this aggregation approach valid when the epidemic has different dynamics across the regions monitored? We characterize bias in the estimation of R0 from a merged data set when the epidemics of the sub-regions, used in the merger, exhibit delays in onset. We propose a method to mitigate this bias, and study its efficacy on synthetic data as well as real-world influenza and COVID-19 data.

How did we get here: what are droplets and aerosols and how far do they go? A historical perspective on the transmission of respiratory infectious diseases

The COVID-19 pandemic has exposed major gaps in our understanding of the transmission of viruses through the air. These gaps slowed recognition of airborne transmission of the disease, contributed to muddled public health policies and impeded clear messaging on how best to slow transmission of COVID-19. In particular, current recommendations have been based on four tenets: (i) respiratory disease transmission routes can be viewed mostly in a binary manner of ‘droplets’ versus ‘aerosols’; (ii) this dichotomy depends on droplet size alone; (iii) the cut-off size between these routes of transmission is 5 µm; and (iv) there is a dichotomy in the distance at which transmission by each route is relevant. Yet, a relationship between these assertions is not supported by current scientific knowledge. Here, we revisit the historical foundation of these notions, and how they became entangled from the 1800s to today, with a complex interplay among various fields of science and medicine. This journey into the past highlights potential solutions for better collaboration and integration of scientific results into practice for building a more resilient society with more sound, far-sighted and effective public health policies.

Enhanced wall shear stress prevents obstruction by astrocytes in ventricular catheters

The treatment of hydrocephalus often involves the placement of a shunt catheter into the cerebrospinal ventricular space, though such ventricular catheters often fail by tissue obstruction. While diverse cell types contribute to the obstruction, astrocytes are believed to contribute to late catheter failure that can occur months after shunt insertion. Using in vitro microfluidic cultures of astrocytes, we show that applied fluid shear stress leads to a decrease of cell confluency and the loss of their typical stellate cell morphology. Furthermore, we show that astrocytes exposed to moderate shear stress for an extended period of time are detached more easily upon suddenly imposed high fluid shear stress. In light of these findings and examining the range of values of wall shear stress in a typical ventricular catheter through computational fluid dynamics (CFD) simulation, we find that the typical geometry of ventricular catheters has low wall shear stress zones that can favour the growth and adhesion of astrocytes, thus promoting obstruction. Using high-precision direct flow visualization and CFD simulations, we discover that the catheter flow can be formulated as a network of Poiseuille flows. Based on this observation, we leverage a Poiseuille network model to optimize ventricular catheter design such that the distribution of wall shear stress is above a critical threshold to minimize astrocyte adhesion and growth. Using this approach, we also suggest a novel design principle that not only optimizes the wall shear stress distribution but also eliminates a stagnation zone with low wall shear stress, which is common to current ventricular catheters.

Biosurfactants Change the Thinning of Contaminated Bubbles at Bacteria-Laden Water Interfaces

Bubbles reside at the water surface before bursting, emitting droplets that can contain chemicals and pathogens linked to disease and contamination. We discover that bacterial secretions enhance the lifetime of bubbles. We also reveal and elucidate two distinct regimes of thinning for such contaminated bubbles. Initially, marginal regeneration governs their thinning rate, similarly to clean water bubbles. However, due to their enhanced lifetime, it is eventually evaporation that governs their thinning, thus also dramatically decreasing their thickness at burst. We derive and experimentally validate the expression for the critical timescale at which the transition between the two regimes occurs. The shift in thinning law makes the droplets produced by contaminated bubbles smaller, faster, and more numerous than those produced by clean bubbles. Our findings suggest that microorganisms can manipulate the aging physics of surface bubbles to enhance their own water-to-air dispersal.

Universal Rim Thickness in Unsteady Sheet Fragmentation

Unsteady fragmentation of a fluid bulk into droplets is important for epidemiology as it governs the transport of pathogens from sneezes and coughs, or from contaminated crops in agriculture. It is also ubiquitous in industrial processes such as paint, coating, and combustion. Unsteady fragmentation is distinct from steady fragmentation on which most theoretical efforts have been focused thus far. We address this gap by studying a canonical unsteady fragmentation process: the breakup from a drop impact on a finite surface where the drop fluid is transferred to a free expanding sheet of time-varying properties and bounded by a rim of time-varying thickness. The continuous rim destabilization selects the final spray droplets, yet this process remains poorly understood. We combine theory with advanced image analysis to study the unsteady rim destabilization. We show that, at all times, the rim thickness is governed by a local instantaneous Bond number equal to unity, defined with the instantaneous, local, unsteady rim acceleration. This criterion is found to be robust and universal for a family of unsteady inviscid fluid sheet fragmentation phenomena, from impacts of drops on various surface geometries to impacts on films. We discuss under which viscous and viscoelastic conditions the criterion continues to govern the unsteady rim thickness.

Visualization of sneeze ejecta: steps of fluid fragmentation leading to respiratory droplets

Coughs and sneezes feature turbulent, multiphase flows that may contain pathogen-bearing droplets of mucosalivary fluid. As such, they can contribute to the spread of numerous infectious diseases, including influenza and SARS. The range of contamination of the droplets is largely determined by their size. However, major uncertainties on the drop size distributions persist. Here, we report direct observation of the physical mechanisms of droplet formation at the exit of the mouth during sneezing. Specifically, we use high-speed imaging to directly examine the fluid fragmentation at the exit of the mouths of healthy subjects. We reveal for the first time that the breakup of the fluid into droplets continues to occur outside of the respiratory tract during violent exhalations. We show that such breakup involves a complex cascade of events from sheets, to bag bursts, to ligaments, which finally break into droplets. Finally, we reveal that the viscoelasticity of the mucosalivary fluid plays an important role in delaying fragmentation by causing the merger of the droplet precursors that form along stretched filaments; thereby affecting the final drop size distribution farther downstream.

Fluid fragmentation shapes rain-induced foliar disease transmission

Plant diseases represent a growing threat to the global food supply. The factors contributing to pathogen transmission from plant to plant remain poorly understood. Statistical correlations between rainfalls and plant disease outbreaks were reported; however, the detailed mechanisms linking the two were relegated to a black box. In this combined experimental and theoretical study, we focus on the impact dynamics of raindrops on infected leaves, one drop at a time. We find that the deposition range of most of the pathogen-bearing droplets is constrained by a hydrodynamical condition and we quantify the effect of leaf size and compliance on such constraint. Moreover, we identify and characterize two dominant fluid fragmentation scenarios as responsible for the dispersal of most pathogen-bearing droplets emitted from infected leaves: (i) the crescent-moon ejection is driven by the direct interaction between the impacting raindrop and the contaminated sessile drop and (ii) the inertial detachment is driven by the motion imparted to the leaf by the raindrop, leading to catapult-like droplet ejections. We find that at first, decreasing leaf size or increasing compliance reduces the range of pathogen-bearing droplets and the subsequent epidemic onset efficiency. However, this conclusion only applies for the crescent moon ejection. Above a certain compliance threshold a more effective mechanism of contaminated fluid ejection, the inertial detachment, emerges. This compliance threshold is determined by the ratio between the leaf velocity and the characteristic velocity of fluid fragmentation. The inertial detachment mechanism enhances the range of deposition of the larger contaminated droplets and suggests a change in epidemic onset pattern and a more efficient potential of infection of neighbouring plants. Dimensionless parameters and scaling laws are provided to rationalize our observations. Our results link for the first time the mechanical properties of foliage with the onset dynamics of foliar epidemics through the lens of fluid fragmentation. We discuss how the reported findings can inform the design of mitigation strategies acting at the early stage of a foliar disease outbreak.

Highly pathogenic avian influenza outbreak mitigated by seasonal low pathogenic strains: insights from dynamic modeling

The spread of highly pathogenic avian influenza (HPAI) H5N1 remains a threat for both wild and domestic bird populations, while low pathogenic avian influenza (LPAI) strains have been reported to induce partial immunity to HPAI in poultry and some wild birds inoculated with both HPAI and LPAI strains. Here, based on the reported data and experiments, we develop a two-strain avian influenza model to examine the extent to which this partial immunity observed at the individual level can affect the outcome of the outbreaks among migratory birds in the wild at the population level during different seasons. We find a distinct mitigating effect of LPAI on the death toll induced by HPAI strain, and this effect is particularly important for populations previously exposed to and recovered from LPAI. We further investigate the effect of the dominant mode of transmission of an HPAI strain on the outcome of the epidemic. Four combinations of contact based direct transmission and indirect fecal-to-oral (or environmental) routes are examined. For a given infection peak of HPAI, indirect fecal-to-oral transmission of HPAI can lead to a higher death toll than that associated with direct transmission. The mitigating effect of LPAI can, in turn, be dependent on the route of infection of HPAI.

Spatial dynamics of bar-headed geese migration in the context of H5N1

Virulent outbreaks of highly pathogenic avian influenza (HPAI) since 2005 have raised the question about the roles of migratory and wild birds in the transmission of HPAI. Despite increased monitoring, the role of wild waterfowl as the primary source of the highly pathogenic H5N1 has not been clearly established. The impact of outbreaks of HPAI among species of wild birds which are already endangered can nevertheless have devastating consequences for the local and non-local ecology where migratory species are established. Understanding the entangled dynamics of migration and the disease dynamics will be key to prevention and control measures for humans, migratory birds and poultry. Here, we present a spatial dynamic model of seasonal migration derived from first principles and linking the local dynamics during migratory stopovers to the larger scale migratory routes. We discuss the effect of repeated epizootic at specific migratory stopovers for bar-headed geese (Anser indicus). We find that repeated deadly outbreaks of H5N1 on stopovers during the autumn migration of bar-headed geese could lead to a larger reduction in the size of the equilibrium bird population compared with that obtained after repeated outbreaks during the spring migration. However, the opposite is true during the first few years of transition to such an equilibrium. The age-maturation process of juvenile birds which are more susceptible to H5N1 reinforces this result.