Assessing coughing-induced influenza droplet transmission and implications for infection risk control.

Indoor transmission of respiratory droplets bearing influenza within humans poses high risks to respiratory function deterioration and death. Therefore, we aimed to develop a framework for quantifying the influenza infection risk based on the relationships between inhaled/exhaled respiratory droplets and airborne transmission dynamics in a ventilated airspace. An experiment was conducted to measure the size distribution of influenza-containing droplets produced by coughing for a better understanding of potential influenza spread. Here we integrated influenza population transmission dynamics, a human respiratory tract model, and a control measure approach to examine the indoor environment-virus-host interactions. A probabilistic risk model was implemented to assess size-specific infection risk for potentially transmissible influenza droplets indoors. Our results found that there was a 50% probability of the basic reproduction number (R0) exceeding 1 for small-size influenza droplets of 0·3-0·4 µm, implicating a potentially high indoor infection risk to humans. However, a combination of public health interventions with enhanced ventilation could substantially contain indoor influenza infection. Moreover, the present dynamic simulation and control measure assessment provide insights into why indoor transmissible influenza droplet-induced infection is occurring not only in upper lung regions but also in the lower respiratory tract, not normally considered at infection risk.

Assessing dengue infection risk in the southern region of Taiwan: implications for control.

Dengue, one of the most important mosquito-borne diseases, is a major international public health concern. This study aimed to assess potential dengue infection risk from Aedes aegypti in Kaohsiung and the implications for vector control. Here we investigated the impact of dengue transmission on human infection risk using a well-established dengue-mosquito-human transmission dynamics model. A basic reproduction number (R 0)-based probabilistic risk model was also developed to estimate dengue infection risk. Our findings confirm that the effect of biting rate plays a crucial role in shaping R 0 estimates. We demonstrated that there was 50% risk probability for increased dengue incidence rates exceeding 0.5-0.8 wk-1 for temperatures ranging from 26°C to 32°C. We further demonstrated that the weekly increased dengue incidence rate can be decreased to zero if vector control efficiencies reach 30-80% at temperatures of 19-32°C. We conclude that our analysis on dengue infection risk and control implications in Kaohsiung provide crucial information for policy-making on disease control.

Using experimental human influenza infections to validate a viral dynamic model and the implications for prediction.

The aim of this work was to use experimental infection data of human influenza to assess a simple viral dynamics model in epithelial cells and better understand the underlying complex factors governing the infection process. The developed study model expands on previous reports of a target cell-limited model with delayed virus production. Data from 10 published experimental infection studies of human influenza was used to validate the model. Our results elucidate, mechanistically, the associations between epithelial cells, human immune responses, and viral titres and were supported by the experimental infection data. We report that the maximum total number of free virions following infection is 10(3)-fold higher than the initial introduced titre. Our results indicated that the infection rates of unprotected epithelial cells probably play an important role in affecting viral dynamics. By simulating an advanced model of viral dynamics and applying it to experimental infection data of human influenza, we obtained important estimates of the infection rate. This work provides epidemiologically meaningful results, meriting further efforts to understand the causes and consequences of influenza A infection.

Understanding influenza virus-specific epidemiological properties by analysis of experimental human infections.

This study aimed to estimate the natural history and transmission parameters based on experimental viral shedding and symptom dynamics in order to understand the key epidemiological factors that characterize influenza (sub)type epidemics. A simple statistical algorithm was developed by combining a well-defined mathematical scheme of epidemiological determinants and experimental human influenza infection. Here we showed that (i) the observed viral shedding dynamics mapped successfully the estimated time-profile of infectiousness and (ii) the profile of asymptomatic probability was obtained based on observed temporal variation of symptom scores. Our derived estimates permitted evaluation of relationships between various model-derived and data-based estimations, allowing evaluation of trends proposed previously but not tested fully. As well as providing insights into the dynamics of viral shedding and symptom scores, a more profound understanding of influenza epidemiological parameters and determinants could enhance the viral kinetic studies of influenza during infection in the respiratory tracts of experimentally infected individuals.

Viral kinetics and exhaled droplet size affect indoor transmission dynamics of influenza infection.

The purpose of this paper was to investigate the effects of viral kinetics and exhaled droplet size on indoor transmission dynamics of influenza infection. The target cell-limited model with delayed virus production was adopted to strengthen the inner mechanisms of virus infection on human epithelial cell. The particle number and volume involved in the viral kinetics were linked with Wells-Riley mathematical equation to quantify the infection risk. We investigated population dynamics in a specific elementary school by using the seasonal susceptible - exposed - infected - recovery (SEIR) model. We found that exhaled pulmonary bioaerosol of sneeze (particle diameter <10 microm) have 10(2)-fold estimate higher than that of cough. Sneeze and cough caused risk probabilities range from 0.075 to 0.30 and 0.076, respectively; whereas basic reproduction numbers (R(0)) estimates range from 4 to 17 for sneeze and nearly 4 for cough, indicating sneeze-posed higher infection risk. The viral kinetics and exhaled droplet size for sneeze affect indoor transmission dynamics of influenza infection since date post-infection 1-7. This study provides direct mechanistic support that indoor influenza virus transmission can be characterized by viral kinetics in human upper respiratory tracts that are modulated by exhaled droplet size. Practical Implications This paper provides a predictive model that can integrate the influenza viral kinetics (target cell-limited model), indoor aerosol transmission potential (Wells-Riley mathematical equation), and population dynamic model [susceptible - exposed - infected - recovery (SEIR) model] in a proposed susceptible population. Viral kinetics expresses the competed results of human immunity ability with influenza virus generation. By linking the viral kinetics and different exposure parameters and environmental factors in a proposed school setting with five age groups, the influenza infection risk can be estimated. On the other hand, we implicated a new simple means of inhaling to mitigate exhaled bioaerosols through an inhaled non-toxic aerosol. The proposed predictive model may serve as a tool for further investigation of specific control measure such as the personal protection masks to alter the particle size and number concentration characteristics and minimize the exhaled bioaerosol droplet to decrease the infection risk in indoor environment settings.

Characteristics of aerosols collected in central Taiwan during an Asian dust event in spring 2000.

Aerosol samples for PM(2.5) and PM(2.5-10) were collected at four locations in central Taiwan from 26 to 31 March 2000, a period that experienced exceedingly high PM levels from 29 to 30 March due to the passage of an Asian dust storm. The samples were analyzed for mass, metallic elements, ions, and carbon. The purpose of this paper is to investigate the influence of the dust storm on the characteristics of local ambient particulate matter. The results indicate that the concentrations of the crustal elements Ca, Mg, Al, Fe and the sea salt species Na+ and Cl- in PM(2.5-10) during the dust episode exceed the mean concentrations in the non-dust period by factors of 3.1, 2.9, 2.6, 2.2, 2.3 and 2.1 respectively. Enrichment factors of Ca, Fe, and Mg in PM(2.5-10) during the dust event are close to unity, indicating that these elements are from soil. Reconstruction of aerosol compositions revealed that soil of coarse particulates elevated approximately 50% in the dust event. It is noted that during the dust event, the ratio of Mg/Al in PM(2.5-10) ranged from 0.21 to 0.25 while that of Ca/Al ranged from 0.6 to 0.9, levels more constant than those obtained in non-dust period.