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Classrooms are high-risk indoor environments, so analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in classrooms is important for determining optimal interventions. Due to the absence of human behavior data, it is challenging to accurately determine virus exposure in classrooms. A wearable device for close contact behavior detection was developed, and we recorded >250,000 data points of close contact behaviors of students from grades 1 to 12. Combined with a survey on students' behaviors, we analyzed virus transmission in classrooms. Close contact rates for students were 37 ± 11% during classes and 48 ± 13% during breaks. Students in lower grades had higher close contact rates and virus transmission potential. The long-range airborne transmission route is dominant, accounting for 90 ± 3.6% and 75 ± 7.7% with and without mask wearing, respectively. During breaks, the short-range airborne route became more important, contributing 48 ± 3.1% in grades 1 to 9 (without wearing masks). Ventilation alone cannot always meet the demands of COVID-19 control; 30 m3/h/person is suggested as the threshold outdoor air ventilation rate in a classroom. This study provides scientific support for COVID-19 prevention and control in classrooms, and our proposed human behavior detection and analysis methods offer a powerful tool to understand virus transmission characteristics and can be employed in various indoor environments.

The emerging Omicron variant poses a serious threat to human health. Public transports play a critical role in infection spread. Based on the data of nearly 4 billion smartcard uses, between January 1, 2019 and January 31, 2021 from the Mass Transit Railway Corporation of Hong Kong, we analyzed the subway travel behavior of different population groups (adults, children, students and senior citizens) due to the COVID-19 pandemic and human travel behavior under different interventions (e.g. work suspension, school closure). Due to the pandemic, the number of MTR passengers (the daily number of passengers in close proximity in subway carriages) decreased by 37.4% (40.8%) for adults, 80.3% (78.5%) for children, 71.6% (71.6%) for students, and 33.5% (36.1%) for senior citizens. Due to work from home (school suspension), the number of contacted adults (students/children) in the same carriage during the rush hours decreased by 39.6% (38.6%/43.2%). If all workers, students, and children were encouraged to commute avoiding rush hours, the possible repeated contacts during rush hour of adults, children and students decreased by 73.3%, 77.9% and 79.5%, respectively. Since adults accounted for 87.3% of the total number of subway passengers during the pandemic, work from home and staggered shift pattern of workers can reduce the infection risk effectively. Our objective is to find the changes of local travel behavior due to the pandemic. From the perspective of public transports, the results provide a scientific support for COVID-19 prevention and control in cities.

Background: Coronavirus disease 2019 (COVID-19) is primarily a respiratory disease that has become a global pandemic. Close contact plays an important role in infection spread, while fomite may also be a possible transmission route. Research during the COVID-19 pandemic has identified long-range airborne transmission as one of the important transmission routes although lack solid evidence. Methods: We examined video data related to a restaurant associated COVID-19 outbreak in Guangzhou. We observed more than 40,000 surface touches and 13,000 episodes of close contacts in the restaurant during the entire lunch duration. These data allowed us to analyse infection risk via both the fomite and close contact routes. Results: There is no significant correlation between the infection risk via both fomite and close contact routes among those who were not family members of the index case. We can thus rule out virus transmission via fomite contact and interpersonal close contact routes in the Guangzhou restaurant outbreak. The absence of a fomite route agrees with the COVID-19 literature. Conclusions: These results provide indirect evidence for the long-range airborne route dominating SARS-CoV-2 transmission in the restaurant. We note that the restaurant was poorly ventilated, allowing for increasing airborne SARS-CoV-2 concentration.

During COVID-19 pandemic, analysis on virus exposure and intervention efficiency in public transports based on real passenger's close contact behaviors is critical to curb infectious disease transmission. A monitoring device was developed to gather a total of 145,821 close contact data in subways based on semi-supervision learning. A virus transmission model considering both short- and long-range inhalation and deposition was established to calculate the virus exposure. During rush-hour, short-range inhalation exposure is 3.2 times higher than deposition exposure and 7.5 times higher than long-range inhalation exposure of all passengers in the subway. The close contact rate was 56.1 % and the average interpersonal distance was 0.8 m. Face-to-back was the main pattern during close contact. Comparing with random distribution, if all passengers stand facing in the same direction, personal virus exposure through inhalation (deposition) can be reduced by 74.1 % (98.5 %). If the talk rate was decreased from 20 % to 5 %, the inhalation (deposition) exposure can be reduced by 69.3 % (73.8 %). In addition, we found that virus exposure could be reduced by 82.0 % if all passengers wear surgical masks. This study provides scientific support for COVID-19 prevention and control in subways based on real human close contact behaviors.

COVID-19 threatens the world. Social distancing is a significant factor in determining the spread of this disease, and social distancing is strongly affected by the local travel behaviour of people in large cities. In this study, we analysed the changes in the local travel behaviour of various population groups in Hong Kong, between 1 January and 31 March 2020, by using second-by-second smartcard data obtained from the Mass Transit Railway Corporation (MTRC) system. Due to the pandemic, local travel volume decreased by 43%, 49% and 59% during weekdays, Saturdays and Sundays, respectively. The local travel volumes of adults, children, students and senior citizens decreased by 42%, 86%, 73% and 48%, respectively. The local travel behaviour changes for adults and seniors between non-pandemic and pandemic times were greater than those between weekdays and weekends. The opposite was true for children and students. During the pandemic, the daily commute flow decreased by 42%. Local trips to shopping areas, amusement areas and borders decreased by 42%, 81% and 99%, respectively. The effective reproduction number (R t ) of COVID-19 had the strongest association with daily population use of the MTR 7-8 days earlier.

By March 31, 2020, COVID-19 had spread to more than 200 countries. Over 750,000 confirmed cases were reported, leading to more than 36,000 deaths. In this study, we analysed the efficiency of various intervention strategies to prevent infection by the virus, SARS-CoV-2, using an agent-based SEIIR model, in the fully urbanised city of Shenzhen, Guangdong Province, China. Shortening the duration from symptom onset to hospital admission, quarantining recent arrivals from Hubei Province, and letting symptomatic individuals stay at home were found to be the three most important interventions to reduce the risk of infection in Shenzhen. The ideal time window for a mandatory quarantine of arrivals from Hubei Province was between 10 January and January 17, 2020, while the ideal time window for local intervention strategies was between 15 and 22 January. The risk of infection could have been reduced by 50% if all symptomatic individuals had immediately gone to hospital for isolation, and by 35% if a 14-day quarantine for arrivals from Hubei Province had been introduced one week earlier. Intervention strategies implemented in Shenzhen were effective, and the spread of infection would be controlled even if the initial basic reproduction number had doubled. Our results may be useful for other cities when choosing their intervention strategies to prevent outbreaks of COVID-19., Highlights • Shortening the delay to hospital is the most effective intervention in Shenzhen. • 10 to 17 January is the best time for a mandatory quarantine of Hubei's arrivals. • 15 to 22 January is the best time for local intervention strategy in Shenzhen. • Work/school closure and mask wearing are effective interventions in other countries. • Airport screening is not very effective.

Liquid fuel spill fires usually occur in the oil storage and transportation industries. The fire develops as the burning fuel spreads, posing a huge threat to the facilities nearby. In this paper, continuously released liquid fuel spill fires were experimentally investigated in one-dimensional channels with three different widths. The spread and burning behavior of the spill fire on water and on a horizontal steel plate were discussed in terms of the burning rate, spread rate and fuel thickness. The burning rate, estimated as the ratio of the discharge flow rate to the steady burning area, was slightly higher for the spill fire on water. The burning rate increased with the trench width, a similar tendency as that of the pool fire, but its value was much lower than that of the pool fire with the same dimensions. A method for estimating the burning fuel thickness at the flame front was proposed, and the estimated values corresponded well to the theoretical values calculated based on the balance between the gravitational force and surface tension. The spread rate of the spill fire was correlated as an exponent function of the ratio of the volumetric discharge flow rate to the trench width. The width of the one-dimensional liquid fuel spill fire mainly affected the burning rate and spread rate.

Personal protective behaviors and their dynamic change are known to play a major role in the community spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal pathogen of the coronavirus disease 2019 (COVID-19) pandemic. In this study, a total of 3229 students in Chinese universities completed an online survey about their knowledge on transmission and personal protective behavior before and after COVID-19 vaccination. Of the respondents, 87.6% had been vaccinated. Most students believed that the large droplet (97.0%) and short-range airborne (89.3%) routes were the two most likely SARS-CoV-2 transmission routes, whereas only 24.1% considered long-range airborne transmission to be possible. Students who would be expected to possess better knowledge about virus transmission (e.g., students of medicine) reported better personal protective behaviors. Female students reported relatively better personal hygiene practices than male students, so did the confident students than their diffident peers. Students washed their hands on average of 5.76 times per day during the pandemic. Students at universities in southern regions washed their hands more frequently but paid less attention to indoor ventilation than did their northern counterparts. Interestingly, students who are fear of being infected had the bad personal hygiene. University students wore 22% less masks in public indoor environments after vaccination. Chinese university students weakened their personal protective behavior after vaccination and it may increase the potential risk of infection in the new waves of variant virus (e.g. delta).

Epidemics of infectious diseases such as SARS, H1N1, and MERS threaten public health, particularly in large cities such as Hong Kong. We constructed a human behavior integrated hierarchical (HiHi) model based on the SIR (Susceptible, Infectious, and Recovered) model, the Wells-Riley equation, and population movement considering both spatial and temporal dimensions. The model considers more than 7 million people, 3 million indoor environments, and 2566 public transport routes in Hong Kong. Smallpox, which could be spread through airborne routes, is studied as an example. The simulation is based on people's daily commutes and indoor human behaviors, which were summarized by mathematical patterns. We found that 59.6%, 18.1%, and 13.4% of patients become infected in their homes, offices, and schools, respectively. If both work stoppage and school closure measures are taken when the number of infected people is greater than 1000, an infectious disease will be effectively controlled after 2 months. The peak number of infected people will be reduced by 25% compared to taking no action, and the time of peak infections will be delayed by about 40 days if 90% of the infected people go to hospital during the infectious period. When ventilation rates in indoor environments increase to five times their default settings, smallpox will be naturally controlled. Residents of Kowloon and the north part of Hong Kong Island have a high risk of infection from airborne infectious diseases. Our HiHi model reduces the calculation time for infection rates to an acceptable level while preserving accuracy., Graphical abstract Image 1, Highlights • Home and office are the top two risky locations in an infectious disease outbreak. • Work stoppage is more efficient to control infectious disease than school closure. • Infected patients had better go to hospital rather than rest at homes. • Kowloon and north part of Hong Kong Island have high infection risk. • Infection would be spontaneously controlled when ventilation increases to 500%.

Urban floods caused by sudden heavy rainstorms are becoming more frequent and causing serious problems in many cities. Developing methods to simulate urban rainstorm floods is helpful in disaster prevention and mitigation. In this paper, we establish an urban pluvial flood simulation model based on diffusion wave approximation of shallow-water equations. The model takes full account of the characteristics in urban pluvial floods, and includes many improvements in simulation details. These details include building a consideration method, a rainfall consideration method, and so on. A new calculation method of water surface gradient is established, which is suitable for complex topology in urban pluvial flood simulation and can reduce unnecessary simulation error introduced by calculation methods. The accuracy and stability of the model are verified through simple cases with analytical solution and experiments with measured data. The results show that the new model is more accurate than common diffusion wave approximation models. A new treatment to avoid ‘checkerboard oscillation’ is established. In comparison with existing methods, the new method proved to be the best. A proof of concept shows that the new model can deal with complex situations and is helpful for urban drainage system planning.

The spread of burning fuel spilled from tanks or pipes during oil storage and transportation industries may threat other facilities nearby and trigger further accidents. In this paper, the effect of substrate slope on the continuously released liquid fuel spill fire was experimentally investigated, in a one-dimensional channel with different discharge rates and substrate slope angles. The time-varying burning area was recorded and analyzed, with 5 typical phases. It is observed that the maximum burning area increases largely with the increasing slope angle, while the steady burning area increases only a little. The steady burning rate, which equals the ratio of the discharge flow rate to the steady burning area, decreases with the increasing slope angle. It is proved that the burning rate for liquid fuel spill fire is much lower than that of pool fire with the same dimensions. The facilities and data presented in this work may provide a basis for the future modeling study of the liquid fuel spill fire on inclined surface.

China is a country that experiences a large number of disasters. The number of deaths caused by large-scale disasters and accidents in past 10 years is around 900,000. More than 92.8 percent of these deaths could be avoided if there were an effective pre-warning system deployed. Knowledge of the information dissemination characteristics of different information media taking into consideration governmental assistance (information published by a government) in disasters in urban areas, plays a critical role in increasing response time and reducing the number of deaths and economic losses. In this paper we have developed a comprehensive information dissemination model to optimize efficiency of pre-warning mechanics. This model also can be used for disseminating information for evacuees making real-time evacuation plans. We analyzed every single information dissemination models for pre-warning in disasters by considering 14 media: short message service (SMS), phone, television, radio, news portals, Wechat, microblogs, email, newspapers, loudspeaker vehicles, loudspeakers, oral communication, and passive information acquisition via visual and auditory senses. Since governmental assistance is very useful in a disaster, we calculated the sensitivity of governmental assistance ratio. The results provide useful references for information dissemination during disasters in urban areas.

With the rapid development of cities in recent years, the size of the cities is becoming bigger and bigger and the structure of the cities is becoming more and more complex. The first step to study the urban resilience is hotspots mining and POI analysis. This paper established an O-D hotspots clustering model based on Iterative Self Organizing Data Analysis Techniques Algorithm (hereinafter referred to as ISODATA) to mine the Origin-Destination (hereinafter referred to as O-D) hotspots in the rush hours in cities and study the distribution characteristics of Point of Interests (hereinafter referred to as POIs) in the hotspots area. It is found that the pick-up hotspots tend to be gathered in the residential zones and the drop-off hotspots tend to be gathered in the working zones. Besides, the distribution characteristics of POIs in both pick-up and drop-off hotspots areas and huge railway stations (special drop-off hotspots) areas are quite special. This study provides an in-depth understanding of the structure of the cities and provides an effective guidance in urban zones planning. This study also provides fundamental knowledge for urban resilience design.

Fomites can transmit some infectious diseases. Human touch behaviors are known to affect virus transmission in buildings. Using video cameras in a graduate student office, we collected more than 98,000 touch actions from 14 h of high-resolution video data of surfaces touched by fingers, palms, and backs of hands. Based on the collected data, we simulated infection spread via the fomite route. 90% of touches to mucous membranes are by fingers (70% by fingers of the nondominant hand; 20% by fingers of the dominant hand). 3% of the virus released into the atmosphere by those infected was transmitted to other students' hands, personal-use surfaces, and public surfaces. Public surfaces are responsible for 53% of virus transmission due to surface touch to susceptible students. 65% of the virus transmitted to the mucous membranes, is by nondominant hands. 93% of virus intake via mucous membranes of the susceptible was from fingers. Door handles and mobile phones transferred the most viral loads to hands of the susceptible. Total virus exposure due to touching has no significant relationship with the duration of being indoors, but human behavior does. Behavior-related intervention strategies are much more efficient than other strategies such as public surface disinfection. If we never touch other's personal surfaces, we would reduce our exposure to the virus by 80%.

Heavy rainstorms are increasingly frequent events in urban areas. Urban rainstorms lead to road waterlogging and low visibility, which affect drivers’ behavior and can thus cause traffic congestion and potential accidents. It is important to study the mechanisms of waterlogging and traffic congestion caused by rainstorms to more effectively predict them and reduce losses. In this paper, an integrated simulation method to analyze the influence of urban rainstorms on waterlogging and traffic congestion was developed. Firstly, waterlogging simulation was conducted to predict the spatiotemporal distribution of water depth on roads based on an urban storm water model. Secondly, psychological questionnaires were distributed to study the drivers’ behavior during a rainstorm. Based on the psychological questionnaires’ results, the vehicles’ speed was estimated under different water depth and visibility conditions. Finally, a microscopic traffic simulation was carried out to predict the traffic condition using the results of the previous two parts. Case studies were conducted on a simplified road model. The effects of different parameters on waterlogging and traffic congestion were analyzed. Then the method was applied to an actual urban area in Beijing, and a detailed waterlogging situation and traffic situation were obtained. Alternate future scenarios of adding drains to mitigate waterlogging and traffic congestion during heavy rainstorms were simulated, and the method’s potential to assist in decision making for urban drainage system design was shown. The integrated simulation method is helpful for early warning and risk management of urban rainstorms on waterlogging and traffic congestion.

Clean and low-carbon are overall goals of high quality development of energy. Regional development approaches should be chosen according to local situations. Taking Jiangsu Province as an example, this paper focuses on the regional high quality development of energy. The development status and characteristics of energy in Jiangsu are analysed. The amount of energy consumption is large. Coal is the dominating source of energy. Energy cleanliness is already high. A large amount of energy is moving in from other provinces or countries. According to these characteristics, some suggestions on the regional high quality development of energy in Jiangsu are given. Take multiple measures simultaneously to achieve low-carbon energy. Encourage energy cascade utilization to achieve high-efficiency energy. Develop comprehensive energy service to achieve cost-effective energy. The results are also helpful for making energy development plans in other places.

Knowledge of human behaviors is important for improving indoor-environment design, building-energy efficiency, and productivity, and for studies of infection spread. However, such data are lacking. In this study, we designed a device for detecting and recording, second by second, the 3D indoor positioning and head and body motions of each graduate student in an office. From more than 400 person hours of data. Students spent 92.2%, 4.1%, 2.9%, and 0.8% of their time in their own office cubicles, other office cubicles, aisles, and areas near public facilities, respectively. They spent 9.7% of time in close contact, and each student averagely had 4.0 close contacts/h. Students spent long time on close contact in the office which may lead to high infection risk. The average interpersonal distance during close contact was 0.81 m. When sitting, students preferred small relative face orientation angle. Pairs of standing students preferred a face-to-face orientation during close contact which means this pattern had a lower infection risk via close contact. Probability of close contact decreased exponentially with the increasing distance between two students&rsquo, cubicles. Data on human behaviour during close contact is helpful for infection risk analysis and infection control and prevention.

Rapid urbanization is causing serious PM2.5 (particulate matter ≤2.5 μm) pollution in China. However, the impacts of human activities (including industrial production, energy production, agriculture, and transportation) on PM2.5 concentrations have not been thoroughly studied. In this study, we obtained a regression formula for PM2.5 concentration based on more than 1 million PM2.5 recorded values and data from meteorology, industrial production, energy production, agriculture, and transportation for 31 provinces of mainland China between January 2013 and May 2017. We used stepwise regression to process 49 factors that influence PM2.5 concentration, and obtained the 10 primary influencing factors. Data of PM2.5 concentration and 10 factors from June to December, 2017 was used to verify the robustness of the model. Excluding meteorological factors, production of natural gas, industrial boilers, and ore production have the highest association with PM2.5 concentration, while nuclear power generation is the most positive factor in decreasing PM2.5 concentration. Tianjin, Beijing, and Hebei provinces are the most vulnerable to high PM2.5 concentrations caused by industrial production, energy production, agriculture, and transportation (IEAT).

Knowing the dynamic road risk for pedestrian evacuation and having an efficient evacuation plan play a very important role in the serious disasters such as earthquake, tsunami and hurricane. In this paper, the dynamic road risk for pedestrian evacuation in a densely populated area of Beijing was studied with consideration of different influencing factors. Firstly, the eight influencing factors including road width, node degree, safety betweenness, road resistor coefficient, building threat, pedestrian counterflow, illegal vehicle parking and traffic flow were considered to assess the road risk for pedestrian evacuation. Secondly, based on complex network theory, electric circuit theory and real situation of the roads, the comprehensive assessment function for road risk was developed quantitatively based on the eight influencing factors. Thirdly, we analyzed road risk for pedestrian evacuation considering different situations: current condition, regular condition, and optimal condition; the risk distribution maps were drawn to directly show the risk level. Through assessments, the roads with high risk for pedestrian evacuation were found, and an optimized evacuation plan was obtained and analyzed. This mathematical model can guide the emergency evacuation in real time. The process and the results are essential for improving the efficiency of evacuations which should considerably reduce the possibility of injuries, deaths and other losses in the disaster.

With the rapid development of information networks, negative impacts of rumor propagation become more serious. Nowadays, knowing the mechanisms of rumor propagation and having an efficient official rumor refutation plan play very important roles in reducing losses and ensuring social safety. In this paper we first develop the dynamic 8-state ICSAR (Ignorance, Information Carrier, Information Spreader, Information Advocate, Removal) rumor propagation model to study the mechanism of rumor propagation. Eight influencing factors including information attraction, objective identification of rumors, subjective identification of people, the degree of trust of information media, spread probability, reinforcement coefficient, block value and expert effects which are related to rumor propagation were analyzed. Next, considering these factors and mechanisms of rumor propagation and refutation, the dynamic 8-state ICSAR rumor propagation model is verified by the SIR epidemic model, computer simulation and actual data. Thirdly, through quantitative sensitivity analysis, the detailed function of each influencing factor was studied and shown in the figure directly. According to these mechanisms, we could understand how to block a rumor in a very efficient way and which methods should be chosen in different situations. The ICSAR model can divide people into 8 states and analyze rumor and anti-rumor dissemination in an accurate way. Furthermore, official rumor refutation is considered in rumor propagation. The models and the results are essential for improving the efficiency of rumor refutation and making emergency plans, which help to reduce the possibility of losses in disasters and rumor propagation.

With the recent rapid development of cities, the dynamics of urban road-traffic commuting are becoming more and more complex. In this research, we study urban road-traffic commuting dynamics based on clustering analysis and a new proposed urban commuting electrostatics model. As a case study, we investigate the characteristics of urban road-traffic commuting dynamics during the morning rush hour in Beijing, China, using over 1.3 million Global Positioning System (GPS) data records of vehicle trajectories. The hotspot clusters are identified using clustering analysis, after which the urban commuting electric field is simulated based on an urban commuting electrostatics model. The results show that the areas with high electric field intensity tend to have slow traffic, and also that the vehicles in most areas tend to head in the same direction as the electric field. The results above verify the validity of the model, in that the electric field intensity can reflect the traffic pressure of an area, and that the direction of the electric field can reflect the traffic direction in that area. This new proposed urban commuting electrostatics model helps greatly in understanding urban road-traffic commuting dynamics and has broad applicability for the optimization of urban and traffic system planning.

Knowing the dynamic population vulnerability distribution and having an efficient information dissemination of disaster warnings play a very important role in the developing of a population evacuation strategy. In this paper, the evacuation of populations in a densely populated area of Beijing was studied with consideration of the spatio-temporal population vulnerability distribution and different methods of disaster information dissemination. Firstly, the population vulnerability distribution was obtained based on the population density, with consideration for dynamic population distribution, building heights, building types and population characteristics. Secondly, a disaster information dissemination model that utilizes sound trucks was developed, and an improved algorithm for finding the optimal route for the sound trucks was established. Thirdly, we ran 81 evacuation simulations that included different variables such as time periods, number of sound trucks, speeds of trucks and sound-spread radius. These were performed based on the dynamic population vulnerability distribution and the developed model. Through these simulations, the rates of population congestion in an evacuation area were understood, and an optimized evacuation plan was obtained and analyzed. The process and the results that were obtained are essential for improving the efficiency of evacuations, which should considerably reduce the possibility injury, deaths and other losses in a disaster.

Population evacuation in an area with high population density is a very serious problem which should be paid more attention. Knowing the road vulnerability for population evacuation and having efficient reconstruction plans of roads, buildings and emergency shelters play a very important role in emergency response. In this paper, a complex network was used to analyze the road vulnerability for population evacuation in an objective way instead of the traditional subjective methods like the expert evaluation approach. Through the data analysis, road-load vulnerability, accessibility and safe distance to emergency shelter of each road and intersection in population evacuation are studied in detail. Furthermore, the improvement plans of each road, intersection and emergency shelter are put forward. The process and the results that were obtained are essential for improving the efficiency of evacuations and reducing the potential risk in population evacuation, which should considerably reduce the possible injury, deaths and other losses in disasters.

Knowing the information dissemination mechanisms of different media and having an efficient information dissemination plan for disaster pre-warning plays a very important role in reducing losses and ensuring the safety of human beings. In this paper we established models of information dissemination for six typical information media, including short message service (SMS), microblogs, news portals, cell phones, television, and oral communication. Then, the information dissemination capability of each medium concerning individuals of different ages, genders, and residential areas was simulated, and the dissemination characteristics were studied. Finally, radar graphs were used to illustrate comprehensive assessments of the six media; these graphs show directly the information dissemination characteristics of all media. The models and the results are essential for improving the efficiency of information dissemination for the purpose of disaster pre-warning and for formulating emergency plans which help to reduce the possibility of injuries, deaths and other losses in a disaster.

Knowing the mechanisms of different information dissemination ways and having an efficient information dissemination of disaster prewarning plays a very important role in reducing the loss and ensuring the safety of disaster carrier. In this paper, first, the transmission characteristics of different information media are analyzed. Second, the mathematical models of information dissemination are established for three typical information media including television, telephone, and email. Finally, the information dissemination capability of each medium considering different ages, genders, and residential areas is simulated and the characteristic of each medium is studied. The models and the results are essential for improving the efficiency of information dissemination and making the emergency plan, which should considerably reduce the possibility injury, deaths, and other losses in a disaster.