Average Probability Research Articles

Investigating seasonal disease emergence and extinction in stochastic epidemic models.

Seasonal disease outbreaks are common in many infectious diseases such as seasonal influenza, Zika, dengue fever, Lyme disease, malaria, and cholera. Seasonal outbreaks are often due to weather patterns affecting pathogens or disease-carrying vectors or by social behavior. We investigate disease emergence and extinction in seasonal stochastic epidemic models. Specifically, we study disease emergence through seasonally varying parameters for transmission, recovery, and vector births and deaths in time-nonhomogeneous Markov chains for SIR, SEIR, and vector-host systems. A branching process approximation of the Markov chain is used to estimate the seasonal probabilities of disease extinction. Several disease outcome measures are used to compare the dynamics in seasonal and constant environments. Numerical investigations illustrate and confirm previous results derived from stochastic epidemic models. Seasonal environments often result in lower probabilities of disease emergence and smaller values of the basic reproduction number than in constant environments, and the time of peak emergence generally precedes the peak time of the seasonal driver. We identify some new results when both transmission and recovery vary seasonally. If the relative amplitude of the recovery exceeds that of transmission or if the periodicity is not synchronized in time, lower average probabilities of disease emergence occur in a constant environment than in a seasonal environment. We also investigate the timing of vector control. This investigation provides new methods and outcome measures to study seasonal infectious disease dynamics and offers new insights into the timing of prevention and control.

The politicization of influenza: partisan changes in flu vaccination before and after COVID-19.

Democrats are more likely to be vaccinated for COVID-19 than Republicans. It is unknown if political polarization surrounding the COVID-19 vaccine has affected flu vaccine uptake. The purpose of this study is to examine the partisan differences in annual flu vaccine uptake before and after the COVID-19 pandemic. This study uses longitudinal panel survey data from the Understanding America Study (UAS), spanning from 2015 to 2024. Using self-reported flu vaccination and partisanship over time, I estimate the odds ratios of flu vaccination for partisan groups before the COVID-19 pandemic, during the pre-vaccination phase of the COVID-19 pandemic, and after the rollout of the COVID-19 vaccine. In pre-COVID years, the predicted probability of flu vaccination was 0.54 ([0.52,0.56], P<.000) among Republicans and 0.63 ([0.61,0.64], P<.00) among Democrats. After the roll-out of the COVID-19 vaccine, the average flu vaccination probability was 0.44 ([0.43,0.46], P<.00) among Republicans and 0.61 ([0.59,0.62], P<.00) among Democrats. The COVID-19 pandemic increased the partisan gap in annual flu vaccination. Researchers should continue to investigate if the partisan gap in other types of vaccinations has grown post-COVID. Practitioners may need to tailor their flu vaccine messaging to vaccine-hesitant political demographics.

LDPC-cat codes for low-overhead quantum computing in 2D

The main obstacle to large scale quantum computing are the errors present in every physical qubit realization. Correcting these errors requires a large number of additional qubits. Two main avenues to reduce this overhead are (i) low-density parity check (LDPC) codes requiring very few additional qubits to correct errors (ii) cat qubits where bit-flip errors are exponentially suppressed by design. In this work, we combine both approaches to obtain an extremely low overhead architecture. Assuming a physical phase-flip error probability ϵ ≈ 0.1% per qubit and operation, one hundred logical qubits can be implemented on a 758 cat qubit chip, with a total logical error probability per cycle and per logical qubit ϵL ≤ 10−8. Our architecture also features two major advantages. First, the hardware implementation of the code can be realised with short-range qubit interactions in 2D and low-weight stabilizers, under constraints similar to those of the popular surface code architecture. Second, we demonstrate how to implement a fault-tolerant universal set of logical gates with an additional layer of routing cat qubits stacked on top of the LDPC layer, while maintaining the local connectivity. Furthermore, our architecture benefits from a high capacity of parallelization for these logical gates.

Studying the interplay of context and semantic content in the interpretation of adversative conjunctions with eye-tracking

The French adversative connective mais, much like its English counterpart but, takes two conjuncts and indicates that they stand in some kind of opposition. The nature of this opposition is often discussed in the existing literature of adversatives. Using an eyetracking experiment, we look at where and when this opposition appears to be manifested in a sentence reading task, using superiority comparatives sentences that appear degraded without a supportive context, as well as inferiority comparatives that do not seem to require such specific contextual information. We presented participants (n = 28) with four types of sentences, differing in the form of comparative, and in the information provided by the context. Some contexts contained a pivot property to help readers access the opposition of the two conjuncts, while others were neutral in that regard. Eye movements were recorded with a 250Hz Tobii Pro Fusion eyetracker, and mixed effect models were used to analyze the following eyetracking metrics : total fixation time and regression probability for the whole sentences, as well as first-fixation duration, first-gaze duration, regression-path duration, regressions-out and regressions-in for each individual words. Even if the helping context is shown to lower negative acceptability judgment on sentences with mais plus (Winterstein et al. 2014), we found no context effect in online reading processing, finding instead a persisting effect of the less/more dichotomy in all chosen measures, sometimes before fixation of those words, pointing towards a parafoveal effect of the aforementioned dichotomy, which merits closer look in future work.

Eyewitness Lineup Identity (ELI) database: Crime videos and mugshots for eyewitness identification research

There is a long history of experimental research on eyewitness identification, and this typically involves staging a crime for participants to witness and then testing their memory of the “culprit” by administering a lineup of mugshots. We created an Eyewitness Lineup Identity (ELI) database, which includes crime videos and mugshot images of 231 identities. We arranged the mugshots into 6-, 9-, and 12-member lineups, and then we tested the stimuli in an eyewitness experiment. Participants (N = 1584) completed six trials of viewing a crime video and completing a lineup identification task. In lineups that included the culprit, the average probability of correction identification was 59.0%, 95% CI [55.9, 62.0]. In lineups that did not include the culprit, the average probability of false alarm was 29.9% [27.8, 32.0]. These outcomes indicate that the ELI database is suitable for eyewitness identification research, and the large number of crime videos would enable stimulus sampling. The database is available for research approved by a research ethics board and can be requested at https://osf.io/vrj3u.

Electronic band evolution between Lieb and kagome nanoribbons

We investigate the electronic properties of nanoribbons made out of monolayer Lieb, transition, and kagome lattices using the tight-binding model with a generic Hamiltonian. It allows us to map the evolutionary stages of the interconvertibility process between Lieb and kagome nanoribbons by means of only one control parameter. Results for the energy spectra, the density of states, and spatial probability density distributions are discussed for nanoribbons with three types of edges: straight, bearded, and asymmetric. We explore for different nanoribbon terminations: (i) the semiconductor-metallic transition due to the interconvertibility of the Lieb and kagome lattices, (ii) the effect of both nanoribbon width and inclusion of the next-nearest-neighbor hopping term on the degeneracy of the quasi-flat states, (iii) the behavior of the energy gap versus the nanoribbon width, (iv) the existence and evolution of edge states, and (v) the nodal spatial distributions of the total probability densities of the non-dispersive states.

Efficient Frontier and Applications in Product Offering and Pricing

Problem definition: The joint assortment and pricing problem is notoriously difficult to solve, especially for large-scale issues subject to various operational constraints arising from business practices. In this paper, we delve into the joint optimization challenge under constrained logit choice models, accounting for product-differentiated price sensitivities across static, randomized, and dynamic contexts. Methodology/results: We develop a unified optimization methodology that applies efficient frontier and dimensional reduction and transforms the joint optimization problem into a single-variable one with respect to the total choice probability. The efficient frontier is employed to transform the nonconcave objective function equivalently into its concave counterpart. We show that the optimal prices are uniquely determined by the common target adjusted markup. The complexity of the mixed combinatorial optimization problem can be reduced by searching over efficient sets of polynomial size. In the randomized assortment and pricing problem in which the product offer sets and prices follow certain distribution, we show that randomization has the potential to elevate the total revenue to the exact efficient frontier, a feat that the static problem may fail to achieve (with a given total choice probability). For dynamic joint product selection and pricing, we find that the optimal policy adopts a simple time-threshold structure that can be precomputed. Furthermore, we illustrate the robustness of our methodology by extending the analysis to a variety of general settings, including the nested logit model. Managerial implications: The proposed methodology contributes to the increasingly popular topic in retail management by significantly reducing the computational complexity of joint product offering and pricing under different constraints. Our results regarding the effects of product set constraints and price bounds provide valuable insights and guidance to practitioners on product offering and pricing in various business scenarios. Funding: C. Ke acknowledges financial support from the National Natural Science Foundation of China [Grant 72101113]. L. Lu acknowledges financial support from the Hong Kong Research Grants Council [Grants 26501021 and 16502423]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0164 .

Spectral efficiency and secrecy enhancing scheme for IRS-aided SWIPT systems

Simultaneous wireless information and power transfer (SWIPT) has emerged as a promising technology for enabling efficient and scalable wireless communication within large-scale Internet of Things (IoT) networks. Despite its substantial potential, challenges related to spectral efficiency and overall system performance remain, underscoring the need for further advancements and innovations. Furthermore, the secure transmission of information is a crucial aspect that cannot be overlooked, as it guarantees the integrity and confidentiality of data exchanged within IoT networks. In this paper, we introduce a novel generalized spatial modulation (GSM) scheme specifically designed for intelligent reflecting surface (IRS)-Aided SWIPT systems. Moreover, the proposed scheme incorporates space-time block coding (STBC) to enhance performance. To strengthen the secrecy, a novel artificial noise (AN) generation strategy that effectively disrupts eavesdroppers while minimizing the impact on legitimate receivers is proposed. Additionally, the designed AN can be utilized by the energy-harvesting receiver to enhance its energy collection capabilities. We derived the average bit error probability (ABEP) of the system using the moment-generating function (MGF) approach and validated our analytical findings through rigorous simulations. The results obtained demonstrate convincingly that the proposed GSM scheme for IRS-Aided SWIPT systems significantly outperforms traditional methods, offering remarkable improvements in performance and efficiency.

Performance of baseline quartile-stratified minimal clinically important difference estimates was superior to individual minimal clinically important difference estimates when compared with a gold standard comparator of important change.

A variety of minimal clinically important difference (MCID) estimates are available to distinguish subgroups with differing outcomes. When a true gold standard is absent, latent class growth curve analysis (LCGC) has been proposed as a suitable alternative for important change. Our purpose was to evaluate the performance of individual and baseline quartile-stratified MCIDs. The current study included data from 346 persons with baseline and 12-month postoperative outcome data from KASTPain, a no-effect randomized clinical trial conducted on persons with knee arthroplasty and pain catastrophizing. Subgroup trajectories from LCGC were used as a gold standard comparator. Minimal clinically important difference-specific trajectories of recovery were calculated for the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) Pain, Disability and EuroQol-5 Dimension Visual Analogue Scale of self-reported health. The latent Kappa (Kl) chance-corrected agreement between MCIDs and LCGCs were estimated to indicate which MCID method was best at detecting important change. For all 3 outcomes, the average latent class probabilities ranged from 0.90 to 0.99, justifying the use of LCGCs as a gold standard. The Kl for LCGC and individual MCIDs ranged from 0.21 (95% CI = 0.13, 0.28) to 0.52 (95% CI = 0.41, 0.66). Baseline quartile-stratified Kl for WOMAC Pain and Disability were 0.85 (95% CI = 0.78, 0.92) and 0.74 (95% CI = 0.68, 0.83), respectively. Classification errors in individual MCID estimates most likely result from ceiling effects. Minimal clinically important differences calculated for each baseline quartile are superior to individually calculated MCIDs and should be used when latent class methods are not available. Use of individual MCIDs likely contribute substantial error and are discouraged for clinical application.

Application of phase dynamics modeling and recurrence methods to assess the characteristics of the relationship between physiological rhythms

The purpose of this work is to apply two methods of nonlinear dynamics to assess the characteristics of the relationship between time series extracted from physiological rhythms. The analyzed time series were respiratory rhythm fluctuations, arterial pressure variability curves, and variability of neuronal activity intervals in the medulla oblongata of rats before and during pain exposure. Methods. To solve the problem of identifying the relationship and assessing the asymmetry and direction of the relationship, a method for modeling the phase dynamics of weakly coupled and weakly noisy systems and a method for calculating averaged conditional probabilities of recurrences of time series generated by interacting systems were used. As characteristics of the relationship between systems, estimates of the intensity of the influence of one system on another and estimates in the differences of the averaged conditional probabilities of recurrences were used. Results. To verify the robustness of the applied methods to noise, an analysis of a well-studied model of unidirectionally coupled Van der Pol oscillators was performed. The correct determination of the direction of coupling by both methods with weak noise and a decrease in the possibility of identifying the direction by the phase modeling method with increasing noise, and the preservation of the possibility of correctly determining the direction by the recurrence method were confirmed. For experimentally obtained and weakly noisy biological time series, an asymmetry of the coupling with a predominant influence of the respiratory rhythm on the variability of neuronal activity and arterial pressure, and the influence of arterial pressure variability on the neuronal activity of the reticular formation of the medulla oblongata was found in most of the analyzed data. Conclusion. The application of two methods for assessing the characteristics of the relationship between weakly noisy time series, both model and experimental, showed quite consistent results in the predominant influence of one system on the other.

Time-Dependent Satellite Explosion Probabilities for Long-Term Orbital Debris Environment Modeling

On-orbit accidental explosions are a significant contributor to the growth of the orbital debris population. Certain types of satellites have been seen to exhibit different behaviors and timelines of explosions. Recent assessments of on-orbit explosions for three categories of satellites—Russian Sistema Obespecheniya Zapuska (SOZ, Proton 4th-stage attitude and ullage motors) units, spacecraft, and rocket bodies—suggest that on-orbit explosions can be modeled using a continuous, time-dependent probability of explosion. This paper discusses the methodology for developing a time-dependent probability of explosion as a function of the satellite’s orbital lifetime based on historical explosions. The SOZ units are found to be best modeled by a modified Gaussian probability distribution, with the peak probability of explosion occurring around 10.4 years on-orbit. Spacecraft and rocket bodies both exhibit exponentially decaying explosion probabilities, with rocket bodies showing fast-, medium-, and slow-time modes of decay. Total cumulative probabilities of explosion are approximately 57% for SOZ units, 4% for spacecraft, and 2% for rocket bodies. Examples of implementation in a simulation of the orbital debris environment using NASA’s long-term evolutionary model are given, showing that the overall explosion behavior over two centuries is significantly different from that using a previously implemented constant-probability-type-dependent explosion rate model and provides a better representation of the historical explosion record.

When should a runner on third base advance? Analyzing factors that influence the success of sacrifice flies in US Major League Baseball games

This study aims to identify factors influencing the success of sacrifice flies in US Major League Baseball. From baseball-tracking outputs of official games during 2023–2024, 3439 flyouts reaching &gt;50 m from home plate when a runner was on third base with &lt;2 outs were analyzed. A multiclass classification model was developed to predict results of runners at third base (i.e., stayed at third base, tagged out at home plate, or scored on a sacrifice fly) from batted ball kinematics, runner's sprint speed (SS), the fielder's arm strength (AS), and ballpark. Average probability scores were compared by systematically altering these inputs. The results show that (i) the model accurately predicted the runner staying at third and sacrifice flies (F-score ≥ 0.842) but could not predict tag outs (0.057), (ii) nearly all flyouts reaching &lt;70 m from home plate would result in the runner staying on third base, whereas the runner usually would score when the flyouts reach ≥85 m, and (iii) the shortest flight distance required for a sacrifice fly could be expressed by a simplified linear function: distance = 87.2–3.1SS + 0.7AS. This function will help set targets for better decision-making and greater success of sacrifice flies.

Non-Orthogonality of QAM and Sunflower-like Modulated Coherent-State Signals.

The limitations of cloning and discriminating quantum states are related to the non-orthogonality of the states. Hence, understanding the collective features of quantum states is essential for the future development of quantum communications technology. This paper investigates the non-orthogonality of different coherent-state signal constellations used in quantum communications, namely phase-shift keying (PSK), quadrature-amplitude modulation (QAM), and a newly defined signal named the sunflower-like (SUN) coherent-state signal. The non-orthogonality index (NOI) and the average probability of correct detection (detection probability) are numerically computed. Results show that PSK NOI increases faster than QAM and SUN as the number of signals increases for a given number of signal photons. QAM and SUN exhibit similar NOI and detection probability, behaving similarly to randomly generated signals for a larger number of signals. Approximation formulas are provided for the detection probability as a function of NOI for each signal type. While similar to QAM, SUN signal offers potential advantages for applications requiring uniform signal-space distribution. The findings provide valuable insights for designing useful quantum signal constellations.

New insights into strange-quark hadronization measuring multiple (multi-)strange hadron production in small collision systems with ALICE

Among the most important results from the Run-1 and Run-2 of the LHC is the observation of an enhanced production of (multi-)strange to non-strange hadron yields, gradually rising from low-multiplicity to highmultiplicity pp and p–Pb collisions, reaching values close to those measured in peripheral Pb–Pb collisions [1]. The observed behaviour cannot be quantitatively reproduced by any of the available QCD-inspired MC generators. In this contribution an extension of this study is presented: the measurement of the Ks0, Λ, Ξ− and Ω− (together with antiparticles) multiplicity distributions in pp collisions at √s = 5.02 TeV as a function of the charged-particle multiplicity, together with the average probability for the multiplets production, extending the study of strangeness production beyond its average. This novel method, based on counting the number of strange particles event-by-event, represents a new test bench for production mechanisms, probing events with a large imbalance between strange and non-strange content.

Properties of winning Iterated Prisoner's Dilemma strategies.

Researchers have explored the performance of Iterated Prisoner's Dilemma strategies for decades, from the celebrated performance of Tit for Tat to the introduction of the zero-determinant strategies and the use of sophisticated learning structures such as neural networks. Many new strategies have been introduced and tested in a variety of tournaments and population dynamics. Typical results in the literature, however, rely on performance against a small number of somewhat arbitrarily selected strategies, casting doubt on the generalizability of conclusions. In this work, we analyze a large collection of 195 strategies in thousands of computer tournaments, present the top performing strategies across multiple tournament types, and distill their salient features. The results show that there is not yet a single strategy that performs well in diverse Iterated Prisoner's Dilemma scenarios, nevertheless there are several properties that heavily influence the best performing strategies. This refines the properties described by Axelrod in light of recent and more diverse opponent populations to: be nice, be provocable and generous, be a little envious, be clever, and adapt to the environment. More precisely, we find that strategies perform best when their probability of cooperation matches the total tournament population's aggregate cooperation probabilities. The features of high performing strategies help cast some light on why strategies such as Tit For Tat performed historically well in tournaments and why zero-determinant strategies typically do not fare well in tournament settings.

Cost-effectiveness of ten commonly used antipsychotics in first-episode schizophrenia in the UK: economic evaluation based on a de novo discrete event simulation model.

Previous economic evidence about interventions for schizophrenia is outdated, non-transparent and/or limited to a specific clinical context. We developed a de novo discrete event simulation (DES) model for estimating the cost-effectiveness of interventions in schizophrenia in the UK. The DES model was developed based on the structure of previous models, populated with demographic, clinical and cost data from the UK, and antipsychotics' effects from recent network meta-analyses. We simulated treatment pathways for patients with first-episode schizophrenia including events such as relapse, remission, treatment discontinuation, cardiovascular disease and death and estimated costs (2020£) taking the National Health Service perspective and quality-adjusted life years (QALYs) over ten years. Using the model, we ranked ten first-line antipsychotics based on their QALYs and cost-effectiveness. Amisulpride was associated with the highest QALYs, followed by risperidone long-acting injection (LAI), aripiprazole-LAI (6.121, 6.084, 6.070, respectively) and others (5.947-6.058). The most cost-effective antipsychotics were amisulpride, olanzapine and risperidone-LAI, with total probability of rankings of 1, ≤2, ≤3, that is, 95%, 89%, 80%, respectively; meanwhile, the least cost-effective were cariprazine, lurasidone and quetiapine, with total probability of rankings of 10, ≥9, ≥8, that is, 96%, 92%, 81%, respectively. Results were robust across sensitivity analyses and influenced primarily by relapse relevant parameters. Our findings suggest amisulpride (or risperidone-LAI where oral treatment is inappropriate) as the best overall first-line option based on QALYs and cost-effectiveness. Our ranking may be used to guide decision-making between antipsychotics. Our model is open source and could be applied to the other settings.

MOTORIZED HOSE ROLLING TOOL FOR FIREFIGHTER: DESIGN AND FABRICATION PROCESS

This paper addresses the critical problem of low back pain (LBP) among firefighters, particularly during hose rolling operations. The main objective is to lower the average probability of LBP risks by introducing a motorized hose roller for such activities. The development of this tool is guided by prior studies which included a survey. The design and fabrication processes of the motorized hose roller involved assessing existing patents for novelty, employing Solid Work software for design, using a morphological chart for concept selection, and finalizing fabrication through metal casting and wiring. Based on the experiment that had been conducted, the conventional hose rolling methods recorded an average LBP risk probabilities of 58.22%, while the motorized hose rolling tool method significantly reduced these risks to 17.44%, representing a 40.78% reduction of LBP risks. These findings highlight the effectiveness of motorized hose rolling tool and its potential as a safer alternative to existing methods, offering vital insights for improving occupational health and safety in hose rolling operation. This research further explores the design and fabrication of motorized tools, emphasizing their potential to alleviate the physical loads encountered by firefighters.

Material Hardship, Forced Displacement, and Negative Health Outcomes Among Unhoused People Who Use Drugs in Los Angeles, California and Denver, Colorado: A Latent Class Analysis.

Homelessness is a growing concern in the United States, especially among people who use drugs (PWUD). The degree of material hardship among this population may be linked to worse health outcomes. PWUD experiencing homelessness in urban areas are increasingly subjected to policies and social treatment, such as forced displacement, which may worsen material hardship. It is critical to describe hardship among PWUD and examine if it is linked to health outcomes. Data were collected as part of a prospective cohort study of PWUD in Los Angeles, California and Denver, Colorado (n = 476). Analysis sample size was smaller (N = 395) after selecting for people experiencing homelessness and for whom data were complete. Five indicators assessing hardship (difficulty finding food, clothing, restrooms, places to wash/shower, and shelter) in the past three months were obtained from participants at baseline and were used in latent class analysis (LCA). We chose a base latent class model after examination of global fit statistics. We then built three auxiliary models using the three-step Bolck-Croon-Hagenaars (BCH) method to test the relationship of latent class membership to several hypothesized social and health variables in this same three month time period. Fit statistics, minimum classification probabilities, and ease of interpretation indicated a three-class solution for level of material difficulty. We termed these classes "High Difficulty" (n = 82), "Mixed Difficulty" (n = 215), and "Low Difficulty" (n = 98). Average classification probabilities indicated good class separability. "High Difficulty" participants had high probabilities of usually having difficulty accessing all five resources. "Mixed Difficulty" participants indicated a range of difficulty accessing all resources, with restrooms and bathing facilities being the most difficult. "Low Difficulty" participants were defined by high probabilities of never having access difficulty. In auxiliary analyses, there were significant (p < 0.05) differences in experiences of displacement, opioid withdrawal symptoms, nonfatal overdose, and violent victimization between classes. This LCA indicates that among PWUD experiencing homelessness there exist distinct differences in resource access and material hardship, and that these differences are linked with political, social, substance use, and other health outcomes. We add to the literature on the relationship between poverty and health among PWUD. Policies which increase difficulty accessing necessary material resources may negatively impact health in this population.

Application of Large Language Models for Assessing Parameters and Possible Scenarios of Cyberattacks on Information and Communication Systems

This paper explores the use of large language models (LLMs) to evaluate parameters and identify potential hostile penetration scenarios in corporate networks, considering logical and probabilistic relationships between network nodes. The developed methodology is based on analyzing the network structure, which includes components such as the Firewall, Mail Server, Web Server, administrator and client workstations, application server, and database server. The probabilities of transitions between these nodes during adversarial attacks are determined using a swarm of virtual experts and two sets of prompts aimed at different LLMs. Among the results obtained through the swarm approach are average transition probabilities, which enable modeling the most likely attack paths from both external and internal network origins. Based on logical-probabilistic analysis, penetration scenarios are ranked according to probabilities, execution time, and resource minimization required by attackers. The proposed methodology facilitates rapid response to threats and ensures an adequate level of cybersecurity by focusing on the most probable and dangerous attack scenarios.

Numerical comparison of exhaled particle dispersion and infection probability in hospital wards heated by mixing ventilation and impinging jet ventilation

Impinging jet ventilation has sufficient supply momentum to overcome thermal buoyancy, with the potential to reduce cross-infection risk in winter. Using an Eulerian-Lagrangian approach validated by experiments, this study compared the exhaled particle dispersion in a two-bed hospital ward heated by impinging jet ventilation and mixing ventilation. Exhaled particles with ten different diameters were tracked under four typical air changes per hour. Particle concentration distribution and residence time were compared. A revised Wells-Riley model was used to calculate the airborne infection probability of coronavirus disease 2019, with the help of a custom field function in Fluent software. The results indicated that impinging jet ventilation increased the air velocity in the occupied zone compared with mixing ventilation. The higher air velocity facilitated the control and removal of fine and medium particles, resulting in lower indoor particle concentration and shorter residence time for 0.5 – 10 μm particles under impinging jet ventilation. With the same air changes per hour, the average infection probability of coronavirus disease 2019 at the breathing zone of susceptible individuals under mixing ventilation could be 1.3 to 12.8 times higher than that under impinging jet ventilation. Additionally, the local infection probability at the face of susceptible individuals was lower under impinging jet ventilation. This study showed that impinging jet ventilation can be implemented in hospital wards to reduce the cross-infection during winter.