Changes In Reproduction Number Research Articles

Leakage in air handling units, the effects on the transmission of airborne infections

The possibility of unfavorable leakages, especially with infectious diseases, in heat recovery systems in air handling units (AHU) is an essential issue. Typical configurations of AHU are analyzed in this aspect, based on their pressure distribution. It is shown that analyzing only for the design conditions is insufficient and that the changing pressure drops of the air filters due to their nonuniform soiling should be taken into account. The novelty of this paper is in proposed method of considering these leaks in the Wells-Riley model, widely used in the literature for airborne transmission of infectious diseases, including the leakage correction factor fhrleak (outdoor fresh air correction factor) based on EATR (exhaust air transfer ratio). Using the proposed method, for typical rooms, on the example of the SARS-CoV-2 virus and its Delta and Omicron variants, it is shown that considering leaks in heat recovery systems in AHU increases the probability of pathogen transmission. The highest increase in the absolute value of the probability of infection is observed in the single office scenario (4.1%) and in the auditorium with a sick speaker scenario (2.7%). The highest increase in reproduction number is observed in the auditorium with a sick speaker scenario (2.69). Such significant changes in reproduction number, including its change from R < 1.0 to R > 1.0 (auditorium with sick speaker for Delta variant of the virus), are crucial from the point of view of considering event scenarios; they slow down or accelerate the pandemic.

COVID-19 non-pharmaceutical intervention portfolio effectiveness and risk communication predominance

Non-pharmaceutical interventions (NPIs) including resource allocation, risk communication, social distancing and travel restriction, are mainstream actions to control the spreading of Coronavirus disease 2019 (COVID-19) worldwide. Different countries implemented their own combinations of NPIs to prevent local epidemics and healthcare system overloaded. Portfolios, as temporal sets of NPIs have various systemic impacts on preventing cases in populations. Here, we developed a probabilistic modeling framework to evaluate the effectiveness of NPI portfolios at the macroscale. We employed a deconvolution method to back-calculate incidence of infections and estimate the effective reproduction number by using the package EpiEstim. We then evaluated the effectiveness of NPIs using ratios of the reproduction numbers and considered them individually and as a portfolio systemically. Based on estimates from Japan, we estimated time delays of symptomatic-to-confirmation and infection-to-confirmation as 7.4 and 11.4 days, respectively. These were used to correct surveillance data of other countries. Considering 50 countries, risk communication and returning to normal life were the most and least effective yielding the aggregated effectiveness of 0.11 and − 0.05 that correspond to a 22.4% and 12.2% reduction and increase in case growth. The latter is quantified by the change in reproduction number before and after intervention implementation. Countries with the optimal NPI portfolio are along an empirical Pareto frontier where mean and variance of effectiveness are maximized and minimized independently of incidence levels. Results indicate that implemented interventions, regardless of NPI portfolios, had distinct incidence reductions and a clear timing effect on infection dynamics measured by sequences of reproduction numbers. Overall, the successful suppression of the epidemic cannot work without the non-linear effect of NPI portfolios whose effectiveness optimality may relate to country-specific socio-environmental factors.

Quantifying the impact of physical distance measures on the transmission of COVID-19 in the UK

BackgroundTo mitigate and slow the spread of COVID-19, many countries have adopted unprecedented physical distancing policies, including the UK. We evaluate whether these measures might be sufficient to control the epidemic by estimating their impact on the reproduction number (R0, the average number of secondary cases generated per case).MethodsWe asked a representative sample of UK adults about their contact patterns on the previous day. The questionnaire was conducted online via email recruitment and documents the age and location of contacts and a measure of their intimacy (whether physical contact was made or not). In addition, we asked about adherence to different physical distancing measures. The first surveys were sent on Tuesday, 24 March, 1 day after a “lockdown” was implemented across the UK. We compared measured contact patterns during the “lockdown” to patterns of social contact made during a non-epidemic period. By comparing these, we estimated the change in reproduction number as a consequence of the physical distancing measures imposed. We used a meta-analysis of published estimates to inform our estimates of the reproduction number before interventions were put in place.ResultsWe found a 74% reduction in the average daily number of contacts observed per participant (from 10.8 to 2.8). This would be sufficient to reduce R0 from 2.6 prior to lockdown to 0.62 (95% confidence interval [CI] 0.37–0.89) after the lockdown, based on all types of contact and 0.37 (95% CI = 0.22–0.53) for physical (skin to skin) contacts only.ConclusionsThe physical distancing measures adopted by the UK public have substantially reduced contact levels and will likely lead to a substantial impact and a decline in cases in the coming weeks. However, this projected decline in incidence will not occur immediately as there are significant delays between infection, the onset of symptomatic disease, and hospitalisation, as well as further delays to these events being reported. Tracking behavioural change can give a more rapid assessment of the impact of physical distancing measures than routine epidemiological surveillance.

Changing social contact patterns under tropical weather conditions relevant for the spread of infectious diseases.

Weather conditions and social contact patterns provide some clues to understanding year-round influenza epidemics in the tropics. Recent studies suggest that contact patterns may direct influenza transmission in the tropics as critically as the aerosol channel in temperate regions. To examine this argument, we analysed a representative nationwide survey dataset of contact diaries with comprehensive weather data in Taiwan. Methods we used included model-free estimated relative changes in reproduction number, R 0; relative changes in the number of contacts; and model-based estimated relative changes in mean contacts using zero-inflated negative binomial regression models. Overall, social contact patterns clearly differ by demographics (such as age groups), personal idiosyncrasies (such as personality and happiness), and social institutions (such as the division of weekdays and weekend days). Further, weather conditions also turn out to be closely linked to contact patterns under various circumstances. Fleeting contacts, for example, tend to diminish when it rains hard on weekdays, while physical contacts also decrease during weekend days with heavy rain. Frequent social contacts on weekdays and under good weather conditions, including high temperature and low absolute humidity, all might facilitate the transmission of infectious diseases in tropical regions.