Exposure Assessment Model Research Articles

Development of an exposure assessment industrial model for Bacillus cereus in rice matrix containing insect chitosan.

An exposure assessment model for industrial use has been developed by using kinetic data from inactivation and growth of Bacillus cereus spores. It can provide a valuable tool for estimating the concentration of B. cereus after a storage period of 24 h at a specified temperature (20 °C) and for an estimation of the percentage of contaminated portions according to the input data of the model. This model considers a rice-derived product that has undergone a standard cooking process at 95 °C for 20 min. According to the results, the presence of chitosan affects the final microbial load after storage, potentially serving as an additional control measure in the event of cold chain abuse or break. Chitosan's antimicrobial properties likely play a role in reducing microbial growth during storage, thereby contributing to enhanced food safety. In practical terms, this suggests that incorporating chitosan into food products, especially those susceptible to microbial contamination like rice derivatives, could help mitigate risks associated with temperature abuse or cold chain disruptions. By acting as a protective barrier against microbial proliferation, chitosan offers a preventive measure to maintain product quality and safety throughout the supply chain. Considering two scenarios, 104 or 107 as initial contamination the model estimated that the 55 and 100% of portions would be respectively contaminated, according to a Performance Criteria of 4 log reductions.

Determination of soil environmental criteria for high-risk trace metals in urban park soils using improved CLEA model

The trace metals (TMs) accumulated in urban park soils can pose potential threats to human health, making the management of soil quality based on health risks critically important. Based on the human health risk assessment (HHRA) model coupled with Monte Carlo Simulation, this study improved the contaminated land exposure assessment (CLEA) model. Combined with local parameters, the Soil Environmental Criteria (SEC) for high-risk trace metals (TMs) in urban park soils were calculated. Results indicated that all the mean TCR (Total carcinogenic risk) values of seven TMs exceeded the risk threshold of 1E-06, suggesting a higher likelihood of carcinogenic risks for all populations. As and Cr presented the highest potential carcinogenic risks, and were identified as high-risk TMs in the study area. The traditional CLEA model was enhanced by incorporating region-specific data, optimizing exposure parameter calculations, and addressing parameter sensitivity and uncertainty. Using the improved CLEA model, the SEC values for high-risk TMs were calculated, revealing that the SEC values gradually increased from ages 1 to 18, while significantly decreased for individuals over 80 years old. This study effectively addresses issues of parameter uncertainty and sensitivity in the CLEA model, offering new insights for the development of soil environmental quality standards.

Comparison of Combined Dissipation Behaviors and Dietary Risk Assessments of Thiamethoxam, Bifenthrin, Dinotefuran, and Their Mixtures in Tea.

In the tea-planting process, insecticides are commonly combined, potentially prolonging the pre-harvest interval and heightening the risk of dietary exposure. This study focused on three frequently used insecticides in tea cultivation: thiamethoxam, bifenthrin, and dinotefuran, aiming to investigate their dissipation behaviors and associated dietary risks upon individual and simultaneous application. The dissipation kinetics of thiamethoxam, bifenthrin, and dinotefuran were successfully characterized by first-order kinetics, yielding respective half-lives of 5.44, 9.81, and 10.16 days. Upon joint application, the dissipation half-lives of thiamethoxam and bifenthrin were notably prolonged compared with their individual applications, resulting in final concentrations after 28 days that were correspondingly elevated by 1.41 and 1.29 times. Assessment of the dietary intake risk revealed that the chronic and acute risk quotients associated with thiamethoxam and bifenthrin escalated by 1.44-1.59 times following their combined application. Although dietary risks associated with Tianmuhu white tea, as determined by the exposure assessment model, were deemed acceptable, the cumulative risks stemming from pesticide mixtures across various dietary sources warrant attention. Molecular docking analyses further unveiled that thiamethoxam and bifenthrin competitively bound to glutathione S-transferase (GST) at amino acid residues, notably at the 76th GLU and the 25th PHE, pivotal in the metabolism and absorption of exogenous substances. Moreover, the interactions between P-glycoprotein and pesticides during transport and absorption were likely to influence dissipation behaviors post-joint application. This research offers valuable insights and data support for optimizing joint pesticide application strategies and assessing risks associated with typical pesticides used in tea cultivation.

Probabilistic Mathematical Model for Dietary Consumption and Exposure Assessment in the Absence of Data from National Nutrition Surveys: A Case Study on Saudi Arabia

Introduction: Noncommunicable diseases, which account for 71% of annual global deaths, necessitate the implementation of targeted legislative measures to reduce exposure to risk factors, particularly those related to nutrition. Accurately assessing these risk factors is challenging owing to infrequent national surveys, high costs, and uncertainties from human behavior. Thus, addressing these issues is crucial. This study aimed to develop a model for estimating dietary exposure. Methods: Our study utilizes the National Nutrient Consumption (NNC) model, which employs a probabilistic and cost-effective approach. This model leverages open data and focuses on supply chain dynamics and uncertainties, integrating import, production, and stock levels. It estimates commodity supply, consumption, and nutrient intake using predictive coefficients from historical data. Model accuracy was assessed using mean absolute error, correlation coefficient, and one-sample t test. The findings were evaluated against the recommended intake outlined in the Technical Regulation of Food Labeling (SFDA.FD 2233). Results: The model demonstrated high accuracy in estimating dietary intake, with minimal error margins. For both genders, the 50th percentile nutrient exposure exceeded the reference values – with males consuming 3,310 kcal (+65%), 144 g of total fat (+105%), 33.8 g of saturated fat (+69%), 86 g of free sugar (+72%), and 2,545 mg of sodium daily (+0.06%); females consumed 3,306 kcal (+65%), 143 g of total fat (+104%), 33.5 g of saturated fat (+67%), 86 g of free sugar (72%), and 2,500 mg of sodium (+4%). Conclusion: The model, both cost-effective and accurate, identifies elevated nutritional risk factors in Saudi Arabia, informing targeted health policies.

Animal dietary exposure in the risk assessment of contaminants in feed.

EFSA performs dietary exposure assessments for food-producing and non-food-producing animals to deliver risk assessment for mandates on the presence of contaminants in feed. The CONTAM and FEEDAP Panels identified the need to update the animal dietary exposure assessment model used in those assessments in CONTAM Scientific Opinions since 2011 in cases where insufficient occurrence data are available on species specific compound feeds. The Panels proposed in this statement a series of model diets based on groups of feed materials with the possibility to use different feed materials in their formulation. The Panels considered that the currently proposed model diets cover the need of the CONTAM Panel to assess the dietary exposure of animals to contaminants in feed.

Swimming benefits outweigh risks of exposure to disinfection byproducts in pools

Disinfection of swimming pool water is critical to ensure the safety of the recreational activity for swimmers. However, swimming pools have a constant loading of organic matter from input water and anthropogenic contamination, leading to elevated levels of disinfection byproducts (DBPs). Epidemiological studies have associated increased risks of adverse health effects with frequent exposure to DBPs in swimming pools. Zhang et al. (2023b) investigated the occurrence of trihalomethanes (THMs), haloacetic acids (HAAs), haloacetonitriles (HANs), and haloacetaldehydes (HALs) in eight swimming pools and the corresponding input water in a city in Eastern China. The concentrations of THMs, HAAs, HANs, and HALs in swimming pools were 1–2 orders of magnitude higher than those detected in the input water. The total lifetime cancer and non-cancer health risks of swimmers through oral, dermal, inhalation, buccal, and aural exposure pathways were assessed using the United States Environmental Protection Agency's (USEPA) standard model and Swimmer Exposure Assessment Model (SWIMODEL). The results showed that dermal and inhalation pathways were the most significant for the associated cancer and non-cancer risks. This article provides an overview and perspectives of DBPs in swimming pools, the benefits of swimming, the need to improve the monitoring of DBPs, and the importance of swimmers’ hygiene practices to keep swimming pools clean. The benefits of swimming outweigh the risks from DBP exposure for the promotion of public health.

Two risk assessments: Evaluating the use of indicator HF183 Bacteroides versus pathogen measurements for modelling recreational illness risks in an urban watershed

The purpose of this study was to evaluate the performance of HF183 Bacteroides for estimating pathogen exposures during recreational water activities. We compared the use of Bacteroides-based exposure assessment to exposure assessment that relied on pathogen measurements. We considered two types of recreational water sites: those impacted by combined sewer overflows (CSOs) and those not impacted by CSOs. Samples from CSO-impacted and non-CSO-impacted urban creeks were analysed by quantitative polymerase chain reaction (qPCR) for HF183 Bacteroides and eight human gastrointestinal pathogens. Exposure assessment was conducted two ways for each type of site (CSO-impacted vs. non-CSO impacted): 1) by estimating pathogen concentrations from HF183 Bacteroides concentrations using published ratios of HF183 to pathogens in sewage and 2) by estimating pathogen concentrations from qPCR measurements. QMRA (quantitative microbial risk assessment) was then conducted for swimming, wading, and fishing exposures. Overall, mean risk estimates varied from 0.27 to 53 illnesses per 1,000 recreators depending on exposure assessment, site, activity, and norovirus dose-response model. HF183-based exposure assessment identified CSO-impacted sites as higher risk, and the recommended HF183 risk-based threshold of 525 genomic copies per 100 mL was generally protective of public health at the CSO-impacted sites but was not as protective at the non-CSO-impacted sites. In the context of our urban watershed, HF183-based exposure assessment over- and under-estimated risk relative to exposure assessment based on pathogen measurements, and the etiology of predicted pathogen-specific illnesses differed significantly. Across all sites, the HF183 model overestimated risk for norovirus, adenovirus, and Campylobacter jejuni, and it underestimated risk for E. coli and Cryptosporidium. To our knowledge, this study is the first to directly compare health risk estimates using HF183 and empirical pathogen measurements from the same waterways. Our work highlights the importance of site-specific hazard identification and exposure assessment to decide whether HF183 is applicable for monitoring risk.

Unravelling the complexity of environmental exposures and health: A novel exposome-centered framework for occupational and environmental epidemiology

The exposome-centered approach marks a significant shift in occupational and environmental epidemiology, prioritizing a holistic evaluation of environmental exposures throughout an individual's life to elucidate their effects on health. Unlike traditional methods that single out environmental factors for their direct health impacts, this approach seeks an integrated analysis of all non-genetic influences, encompassing specific and general external environments and internal responses. While acknowledging environmental factors' pivotal role in chronic diseases and global mortality, existing methods struggle with precisely measuring and analyzing the broad spectrum of exposures and their combined effects. The exposome framework addresses these gaps through advanced omics technologies, refined exposure assessment models, and comprehensive data analytics. Yet, its application faces hurdles like the requirement for substantial infrastructure, cross-disciplinary training, and new statistical techniques for high-dimensional data analysis. Recent endeavors in applying the exposome concept show its promise in improving our understanding of environmental and occupational health, underlining its importance in advancing epidemiological research and public health. This abstract condenses the rationale, challenges, and ongoing efforts to incorporate the exposome into epidemiol-ogical studies, emphasizing its potential in enhancing the field.

Removal and prediction of chemicals in anaerobic–anoxic–aerobic wastewater treatment system: Case study on organophosphates

Distribution and removal of chemicals in wastewater treatment plants (WWTPs) have mainly relied on mathematical models. Existing exposure assessment models such as SimpleTreat, STPWIN are based on conventional activated sludge processes. There is an urgent need to develop an A2/O-based WWTPs exposure assessment model. Organophosphates (OPEs) have different physical and chemical properties and potential environmental risks. The fate and biodegradation kinetics of three types of OPEs, including alkyl OPEs, chlorinated OPEs and triphenyl ester OPEs, were studied in a laboratory-scale anaerobic/anoxic/aerobic (A2/O) sewage treatment system and batch reactors. The three types of OPEs had different anaerobic, anoxic, and aerobic removal characteristics. A compensation mechanism was found between anaerobic and anoxic/aerobic removal. When the hydraulic retention time decreased from 82 to 20.5 h, the removal efficiencies in the anaerobic unit decreased, while those in the anoxic unit increased; as a result, the total removal efficiencies remained high (>80 %) for all OPEs except triphenyl phosphate (65.5%–75.1 %). The concept of effective sludge concentration (MLSSeff) was proposed to illustrate the compensation mechanism and calibrate the second-order kinetic equation for predicting pollutant removal in the A2/O system: MLSSeff = ken × MLSS, where ken is a constant related to the influent total organic carbon content (TOC). The influent TOC contents of the anoxic and aerobic units affected the value of MLSSeff and OPEs removal. The results are of great significance for assessing OPEs exposure and predicting exposure to emerging micropollutants in sewage treatment systems.

The Distribution and Health Risk Assessment of Potential Toxic Elements in Atmospheric Deposition from Ion-Adsorption Rare Earth Mining Areas in the Ganzhou City of Southeast China

Potential toxic elements (PTEs), including Pb, Cr, Cd, Ni, Cu, As, and Mo, are common pollutants in ion-adsorption rare earth mines (IAREEMs), and atmospheric deposition is an important method of PTE migration. However, the level of PTE atmospheric deposition in and around IAREEMs remains unknown. We established 25 stations at typical sites in the Ganzhou city of southeast China. An exposure assessment model was used to evaluate the health risks for adults and children. The results show that the concentration and fluxes of atmospheric deposition of PTEs follow the order of Pb > Cu > Cr > Ni > As > Mo > Cd, and most PTEs present no human health risk. However, due to the high toxicty of As, it poses both carcinogenic and non-carcinogenic risks to children as indicated by the analysis of an exposure assessment model of heavy rare earth minerals in Longnan county, Ganzhou city. The As concentration in atmospheric deposition ranged from 3.18 to 251.87 mg kg−1, and the As atmospheric fluxes in atmospheric deposition ranged from 0.11 to 39.4 mg m−2 y−1. This is because As-rich materials (e.g., arsenic-adsorbing clay zones and chernovite-(Y) (Y[AsO4])) are exposed in fully weathered layers, and the formed suspended particulate matter is transported into the atmosphere at Longnan county. Consequently, restoring vegetation to reduce particulate matter transport is an important method for controlling the spread of pollutants. These results provide significant insights into pollution characteristics and prevention in and around mining areas under the influence of atmospheric deposition.

Personal exposure monitoring of fine and coarse particulate matter using exposure assessment models for elderly residents in Hong Kong

This study investigated the determinants of personal exposures (PE) to coarse (PM2.5-10) and fine particulate matter (PM2.5) for elderly communities in Hong Kong. The mean PE PM2.5 and PM2.5-10 were 23.6 ± 10.8 and 13.5 ± 22.1 μg/m3, respectively during the sampling period. Approximately 76% of study subjects presented statistically significant differences between PE and ambient origin for PM2.5 compared to approximately 56% for PM2.5-10, possibly due to the coarse-size particles being more influenced by similar sources (road dust and construction dust emissions) compared to the PM2.5 particles. Individual PE to ambient (P/A) ratios for PM2.5 all exceeded unity (≥1), suggesting the dominant influences of non-ambient particles contributed towards total PE values. There were about 80% individual P/A ratios (≤1) for PM2.5-10, implying possible effective infiltration prevention of larger size particulate matter particles leading to dominant influences from the outdoor sources. The higher concentration of NO3− and SO42− in PM2.5-10 compared to PM2.5 suggests possible heterogeneous reactions of alkaline minerals leading to the formation of NO3− and SO42− in PM2.5-10 particles. The PE and ambient OC/EC ratios in PM2.5 (8.8 ± 3.3 and 10.4 ± 22.4, respectively) and in PM2.5-10 (6.0 ± 1.9 and 3.0 ± 1.1, respectively) suggest possible secondary formed OC from surrounding rural areas. Heterogeneous distributions (COD >0.2) between the PE and ambient concentrations were found for both the PM2.5 and PM2.5-10 samples. The calibration coefficient as the association between personal and surrogate exposure measure of PE to PM2.5 (0.84) was higher than PM2.5-10 (0.52). The findings further confirm that local sources were the dominant contributor to the coarse particles and these coefficients can potentially be used to estimate different PE to PM2.5 and PM2.5-10 conditions. A comprehensive understanding of the PE to determinants in coarse particles is essential to further reduce potential exposure misclassification.

Long-Term Science Goals with In Situ Observations at the Sun-Earth Lagrange Point L4

The Korean heliospheric community, led by the Korea Astronomy and Space Science Institute (KASI), is currently assessing the viability of deploying a spacecraft at the Sun-Earth Lagrange Point L4 in collaboration with National Aeronautics and Space Administration (NASA). The aim of this mission is to utilize a combination of remote sensing and in situ instruments for comprehensive observations, complementing the capabilities of the L1 and L5 observatories. The paper outlines long-term scientific objectives, underscoring the significance of multi-point in-situ observations to better understand critical heliospheric phenomena. These include coronal mass ejections, magnetic flux ropes, heliospheric current sheets, kinetic waves and instabilities, suprathermal electrons and solar energetic particle events, as well as remote detection of solar radiation phenomena. Furthermore, the mission’s significance in advancing space weather prediction and space radiation exposure assessment models through the integration of L4 observations is discussed. This article is concluded with an emphasis on the potential of L4 observations to propel advancements in heliospheric science.

Comparison of Exposure Estimates Using Consumer Exposure Assessment Models and the Korean Exposure Algorithm

Comparison of Exposure Estimates Using Consumer Exposure Assessment Models and the Korean Exposure Algorithm

Development of handling energy factors for use of dustiness data in exposure assessment modelling.

Several exposure assessment models use dustiness as an input parameter for scaling or estimating exposure during powder handling. Use of different dustiness methods will result in considerable differences in the dustiness values as they are based on different emission generation principles. EN17199:2019 offers 4 different dustiness test methods considering different dust release scenarios (e.g. powder pouring, mixing and gentle agitation, and vibration). Conceptually, the dustiness value by a given method can be multiplied with a scenario-specific modifier, called a handling energy factor (Hi), that allows conversion of a dustiness value to a release constant. Therefore, a Hi, scaling the effective mechanical energy in the process to the energy supplied in the specific dustiness test, needs to be applied. To improve the accuracy in predictive exposure modelling, we derived experimental Hi to be used in exposure algorithms considering both the mass- and number-based dust release fraction determined by the EN17199-3 continuous drop (CD) and the EN17199-4 small rotating drum (SRD) test methods. Three materials were used to evaluate the relationship between dustiness and dust levels during pouring powder from different heights in a controlled environment. The results showed increasing scatter and difference between the Hi derived for the 2 test methods with increasing pouring height. Nearly all the Hi values obtained for both SRD and CD were <1 indicating that the dustiness tests involved more energy input than the simulated pouring activity and consequently de-agglomeration and dust generation were higher. This effect was most pronounced in CD method showing that SRD mechanistically resembles more closely the powder pouring.

Comparative Study of Exposure Assessment of Dust in Building Materials Enterprises Using ART and Monte Carlo

BackgroundDust generated during the processing of building materials enterprises can pose a serious health risk. The study aimed to compare and analyze the results of ART and the Monte Carlo model for the dust exposure assessment in building materials enterprises, to derive the application scope of the two models. MethodsFirst, ART and the Monte Carlo model were used to assess the exposure to dust in each of the 15 building materials enterprises. Then, a comparative analysis of the exposure assessment results was conducted. Finally, the model factors were analyzed using correlation analysis and the scope of application of the models was determined. ResultsThe results show that ART is mainly influenced by four factors, namely, localized controls, segregation, dispersion, surface contamination, and fugitive emissions, and applies to scenarios where the workplace information of the building materials enterprises is specific and the average dust concentration is greater than or equal to 1.5 mg/m3. The Monte Carlo model is mainly influenced by the dust concentration in the workplace of building materials enterprises and is suitable for scenarios where the dust concentration in the workplace of the building materials enterprises is relatively uniform and the average dust concentration is less than or equal to 6mg/m3. ConclusionART is most accurate when workplace information is specific and average dust concentration is > 1.5 mg/m3; whereas, The Monte Carlo model is the best when dust concentration is homogeneous and average dust concentration is < 6 mg/m3.

Invited Perspective: Cutting through the Noise-the National Park Service Anthropogenic Noise Model for Exposure Assessment.

Invited Perspective: Cutting through the Noise-the National Park Service Anthropogenic Noise Model for Exposure Assessment.

Refined urban disaster vulnerability assessment based on elements at risk: A case study of Dalian, China

With the rapid development of global urbanization, cities tend to suffer higher frequencies and risks of various hazards and are becoming more vulnerable, especially under the circumstance of global warming. Hence, people have begun to attach importance to the study of urban disaster vulnerability gradually. However, existing studies focus more on the multi-dimensional expression and comprehensive measurement of disaster vulnerability at the macro scale, which cannot reflect the changes of disaster vulnerability within the small scale. It is difficult for the research results to provide practical information for accurate disaster prevention and reduction. For this purpose, this study proposed a framework for refined urban disaster vulnerability assessment from the perspective of elements at risk, which includes three quantitative models: exposure assessment model, sensibility assessment model, and coping capability assessment model. Then, the framework and its quantitative models were applied to assess the disaster vulnerability of Dalian at the scale of 30 × 30 m grid. Furthermore, the main factors contributing to vulnerability were highlighted based on of exposure, sensibility, and coping capability indexs. Results showed that the disaster vulnerability of Dalian was autocorrelative and heterogeneous spatially. This research could provides some implications for disaster mitigation and risk reduction strategies at the urban scale.

A pruned feed-forward neural network (pruned-FNN) approach to measure air pollution exposure.

Environmental epidemiology studies require accurate estimations of exposure intensities to air pollution. The process from air pollutant emission to individual exposure is however complex and nonlinear, which poses significant modeling challenges. This study aims to develop an exposure assessment model that can strike a balance between accuracy, complexity, and usability. In this regard, neural networks offer one possible approach. This study employed a custom-designed pruned feed-forward neural network (pruned-FNN) approach to calculate the air pollution exposure index based on emission time and rates, terrain factors, meteorological conditions, and proximity measurements. The model's performance was evaluated by cross-validating the estimated exposure indexes with ground-based monitoring records. The pruned FNN can predict pollution exposure indexes (PEIs) that are highly and stably correlated with the monitored air pollutant concentrations (Spearman's rank correlation coefficients for tenfold cross-validation (mean ± standard deviation: 0.906 ± 0.028) and for random cross-validation (0.913 ± 0.024)). The predicted values are also close to the ground truth in most cases (95.5% of the predicted PEIs have relative errors smaller than 10%) when the training datasets are sufficiently large and well-covered. The pruned-FNN method can make accurate exposure estimations using a flexible number of variables and less extensive data in a less money/time-consuming manner. Compared to other exposure assessment models, the pruned FNN is an appropriate and effective approach for exposure assessment that covers a large geographic area over a long period of time.

Modelling potential human exposure to the urease inhibitor NBPT through the environment-food pathway

The urease inhibitor N-(n-butyl) thiophosphoric triamide (NBPT) has recently attracted a lot of attention attributing to its efficiency in reducing ammonia loss from urea fertiliser applied to temperate grassland soils. Ammonia gas lost to the environment causes soil acidification, eutrophication and contributes to global warming through increased greenhouse gas emissions and ozone layer depletion. The active chemical NBPT blocks the soil microbial enzyme (urease) and reduces ammonia emission. Furthermore, NBPT’s use in agriculture might benefit farmers by reducing reliance on expensive nitrate fertiliser and aiding in a shift to more urea-based fertiliser (using NBPT co-applied with urea is more cost-effective). The present study was carried out to characterise the potential transfer of NBPT from grass to liquid milk and compute the associated human health risks. Using probabilistic risk assessment techniques, an exposure assessment model was developed to calculate the Estimated Daily Intake (EDI) of NBPT from milk, following co-application of NBPT with a urea N-fertiliser. Results show that the predicted mean concentration of NBPT in milk is 2.5 × 10−8 mg NBPT/kg milk, while the mean daily intake (EDI) of NBPT is 5 × 10−11 mg NBPT /kg BW/day). Back-calculations revealed that, under the studied conditions, for the EDI to exceed ADI of 3 × 10−2 mg NBPT/kg BW/ day, the NBPT application rate would need to exceed the NBPT fertiliser limit (0.09–0.2% by mass of urea nitrogen) set in the Commission Regulation (EC) No 1107/2008, and the bio-transfer factor would need to be over 100% (implausible). Sensitivity analysis revealed soil pH (SPH), phytoaccumulation factor (PF), NBPT permissible levels in fertiliser (NBPT%), pasture cover (P), and grazing rotation length (t) as critical factors influencing the EDI of NBPT. The present study concludes that NBPT presents negligible risk to human health under the conditions and assumptions studied.

Population pharmacokinetic modeling and simulation for nirmatrelvir exposure assessment in Chinese older patients with COVID-19 infection

Nirmatrelvir is an effective component of Paxlovid, the first oral antiviral drug granted emergency use authorization by the FDA. Nirmatrelvir is prescribed extensively in older adult patients to treat the coronavirus disease 2019 (COVID-19) infection. In this study, population pharmacokinetic modeling with clinical study data was employed to explore the pharmacokinetic profile of nirmatrelvir in older adult Chinese patients with COVID-19 infection. The result suggests that the pharmacokinetic profile of nirmatrelvir can be described by a one-compartment model with first-order absorption and elimination in this study population. The calculated apparent clearance (CL/F), apparent volumes of distribution (V/F), and absorption rate constant (ka) for the typical patient were 4.16 L/h, 39.1 L, and 0.776, respectively. The area under the curve (AUC) of nirmatrelvir in the typical Chinese older adult was approximately three-fold higher than the AUCs in Chinese and Western young adult volunteers. At the same doses, the simulated AUCs were increased by 26%, 43%, 72%, and 135% in virtual populations with creatinine clearances of 60, 45, 30, and 15 mL/min, respectively. Our research provides an instructive reference for nirmatrelvir dose selection in older Chinese adults.