Modelling aerosol transport and virus exposure with numerical simulations in relation to SARS-CoV-2 transmission by inhalation indoors.

We provide research findings on the physics of aerosol and droplet dispersion relevant to the hypothesized aerosol transmission of SARS-CoV-2 during the current pandemic. We utilize physics-based modeling at different levels of complexity, along with previous literature on coronaviruses, to investigate the possibility of airborne transmission. The previous literature, our 0D-3D simulations by various physics-based models, and theoretical calculations, indicate that the typical size range of speech and cough originated droplets ( d ⩽ 20 µ m ) allows lingering in the air for O ( 1 h ) so that they could be inhaled. Consistent with the previous literature, numerical evidence on the rapid drying process of even large droplets, up to sizes O ( 100 µ m ) , into droplet nuclei/aerosols is provided. Based on the literature and the public media sources, we provide evidence that the individuals, who have been tested positive on COVID-19, could have been exposed to aerosols/droplet nuclei by inhaling them in significant numbers e.g. O ( 100 ) . By 3D scale-resolving computational fluid dynamics (CFD) simulations, we give various examples on the transport and dilution of aerosols ( d ⩽ 20 µ m ) over distances O ( 10 m ) in generic environments. We study susceptible and infected individuals in generic public places by Monte-Carlo modelling. The developed model takes into account the locally varying aerosol concentration levels which the susceptible accumulate via inhalation. The introduced concept, 'exposure time' to virus containing aerosols is proposed to complement the traditional 'safety distance' thinking. We show that the exposure time to inhale O ( 100 ) aerosols could range from O ( 1 s ) to O ( 1 min ) or even to O ( 1 h ) depending on the situation. The Monte-Carlo simulations, along with the theory, provide clear quantitative insight to the exposure time in different public indoor environments.

Evaluation of the incidence and risk of hypoglycemic coma associated with selection of basal insulin in the treatment of diabetes: a Finnish register linkage study.

OBJECTIVE: Long-acting basal insulin analogs have demonstrated positive effects on the balance between effective glycemic control and risk of hypoglycemia versus neutral protamine Hagedorn (NPH) insulin in randomized controlled trials. Evidence of severe hypoglycemic risk with insulin detemir, insulin glargine, or NPH insulin is presented from a nationwide retrospective database study. RESEARCH DESIGN AND METHODS: Data from hospital and secondary healthcare visits due to hypoglycemic coma from 75 682 insulin-naïve type 1 or 2 diabetes patients initiating therapy with NPH insulin, insulin glargine, or insulin detemir in Finland between 2000 and 2009 were analyzed. Incidence rates with 95% confidence intervals (CIs) were calculated using Poisson regression. Hazard ratios were estimated using Cox's regression with adjustments for relevant background variables. RESULTS: The adjusted risk of hospital/secondary healthcare visits due to the first severe hypoglycemic event was 21.7% (95% CI 9.6-32.1%, p < 0.001) lower for insulin detemir and 9.9% (95% CI 1.5-17.6%, p = 0.022) lower for insulin glargine versus NPH insulin. Risk of hypoglycemic coma recurrence was 36.3% (95% CI 8.9-55.5%, p = 0.014) lower for detemir and 9.5% but not significantly (95% CI -10.2 to 25.7%, p = 0.318) lower for glargine versus NPH insulin. Risk of all hypoglycemic coma events was 30.8% (95% CI 16.2-42.8%, p-value <0.001) lower for detemir and 15.6% (95% CI 5.1-25.0%, p-value 0.005) lower for glargine versus NPH. Insulin detemir had a significantly lower risk for first (13.1% lower [p = 0.034]), recurrent (29.6% lower [p = 0.021]), and all (17.9% lower [p = 0.016]) severe hypoglycemic events than insulin glargine. CONCLUSIONS: There were considerable differences in risk of hospitalization or secondary healthcare visits due to hypoglycemic coma between basal insulin treatments in real-life clinical practice.

Modeling transmission of multitype infectious agents: application to carriage of Streptococcus pneumoniae.

We describe a novel Bayesian approach to estimate acquisition and clearance rates for many competing subtypes of a pathogen in a susceptible-infected-susceptible model. The inference relies on repeated measurements of the current status of being a non-carrier (susceptible) or a carrier (infected) of one of the n(q) > 1 subtypes. We typically collect the measurements with sampling intervals that may not catch the true speed of the underlying dynamics. We tackle the problem of incompletely observed data with Bayesian data augmentation, which integrates over possible carriage histories, allowing the data to contain intermittently missing values, complete dropouts of study subjects, or inclusion of new study subjects during the follow-up. We investigate the performance of the described method through simulations by using two different mixing groups (family and daycare) and different sampling intervals. For comparison, we describe crude maximum likelihood-based estimates derived directly from the observations. We apply the estimation algorithm to data about transmission of Streptococcus pneumonia in Bangladeshi families. The computationally intensive Bayesian approach is a valid method to account for incomplete observations, and we found that it performs generally better than the simple crude method, in particular with large amount of missing data.

Outbreaks of Streptococcus pneumoniae carriage in day care cohorts in Finland - implications for elimination of transmission.

BACKGROUND: Day care centre (DCC) attendees play a central role in maintaining the circulation of Streptococcus pneumoniae (pneumococcus) in the population. Exposure within families and within DCCs are the main risk factors for colonisation with pneumococcal serotypes in DCC attendees. METHODS: Transmission of serotype specific carriage was analysed with a continuous time event history model, based on longitudinal data from day care attendees and their family members. Rates of acquisition, conditional on exposure, were estimated in a Bayesian framework utilising latent processes of carriage. To ensure a correct level of exposure, non-participating day care attendees and their family members were included in the analysis. Posterior predictive simulations were used to quantify transmission patterns within day care cohorts, to estimate the basic reproduction number for pneumococcal carriage in a population of day care cohorts, and to assess the critical vaccine efficacy against carriage to eliminate pneumococcal transmission. RESULTS: The model, validated by posterior predictive sampling, was successful in capturing the strong temporal clustering of pneumococcal serotypes in the day care cohorts. In average 2.7 new outbreaks of pneumococcal carriage initiate in a day care cohort each month. While 39% of outbreaks were of size one, the mean outbreak size was 7.6 individuals and the mean length of an outbreak was 2.8 months. The role of families in creating and maintaining transmission was minimal, as only 10% of acquisitions in day care attendees were from family members. Considering a population of day care cohorts, a child-to-child basic reproduction number was estimated as 1.4 and the critical vaccine efficacy against acquisition of carriage as 0.3. CONCLUSION: Pneumococcal transmission occurs in serotype specific outbreaks of carriage, driven by within-day-care transmission and between-serotype competition. An amplifying effect of the day care cohorts enhances the spread of pneumococcal serotypes within the population. The effect of vaccination, in addition to reducing susceptibility to pneumococcal carriage in the vaccinated, induces a herd effect, thus creating a counter-effect to the amplifying effect of the cohort. Consequently, the critical vaccine efficacy against carriage, required for elimination of transmission, is relatively low. Use of pneumococcal conjugate vaccines is expected to induce a notable herd protection against pneumococcal disease.