Lag Time Research Articles

Mode of Action and Mechanisms of Resistance to the Unusual Polyglycosylated Thiopeptide Antibiotic Persiathiacin A.

Persiathiacin A is a novel thiopeptide antibiotic produced by Actinokineospora species UTMC 2448. It has potent activity against methicillin-resistant Staphylococcus aureus (MRSA) and Mycobacterium tuberculosis. Thiopeptides, including persiathiacin A, exhibit antibacterial activity by inhibiting protein synthesis. In this study, we characterize the mechanism of action of persiathiacin A and investigate how resistance to this antibiotic can emerge. In vitro assays revealed that persiathiacin A inhibits translation elongation, leading to ribosome stalling. Genetic analysis of resistant Bacillus subtilis mutants identified mutations primarily in the rplK gene encoding ribosomal protein L11, which is the binding site for other 26-membered macrocycle-containing thiopeptides. The resistant mutants showed growth impairment and an increased lag time, even in the absence of persiathiacin. Comparative proteomic analysis of a resistant mutant versus the parental strain revealed multiple changes, indicative of negative effects on protein synthesis. Thus, although persiathiacin-resistant mutants can arise readily by the loss of L11 function, it is likely that such mutants would be severely compromised in pathogenesis. Furthermore, bioinformatics analysis identified differences in the key amino acids within the thiopeptide-binding region of L11 in the persiathiacin producer. These probably prevent the antibiotic from associating with its target, providing a mechanism for self-resistance.

Predictive Model for Listeria monocytogenes in RTE Meats Using Exclusive Food Matrix Data

Post-processing contamination of Listeria monocytogenes has remained a major concern for the safety of ready-to-eat (RTE) meat products that are not reheated before consumption. Mathematical models are rapid and cost-effective tools to predict pathogen behavior, product shelf life, and safety. The objective of this study was to develop and validate a comprehensive model to predict the Listeria growth rate in RTE meat products as a function of temperature, pH, water activity, nitrite, acetic, lactic, and propionic acids. The Listeria growth data in RTE food matrices, including RTE beef, pork, and poultry products (731 data sets), were collected from the literature and databases like ComBase. The growth parameters were estimated using the logistic-with-delay primary model. The good-quality growth rate data (n = 596, R2 > 0.9) were randomly divided into 80% training (n = 480) and 20% testing (n = 116) datasets. The training growth rates were used to develop a secondary gamma model, followed by validation in testing data. The growth model’s performance was evaluated by comparing the predicted and observed growth rates. The goodness-of-fit parameter of the secondary model includes R2 of 0.86 and RMSE of 0.06 (μmax) during the development stage. During validation, the gamma model with interaction included an RMSE of 0.074 (μmax), bias, and accuracy factor of 0.95 and 1.50, respectively. Overall, about 81.03% of the relative errors (RE) of the model’s predictions were within the acceptable simulation zone (RE ± 0.5 log CFU/h). In lag time model validation, predictions were 7% fail-dangerously biased, and the accuracy factor of 2.23 indicated that the lag time prediction is challenging. The model may be used to quantify the Listeria growth in naturally contaminated RTE meats. This model may be helpful in formulations, shelf-life assessment, and decision-making for the safety of RTE meat products.

The impact of meteorological conditions on cardiovascular and cerebrovascular diseases in different microclimatic zones of low-latitude mountainous areas

IntroductionEpidemiological evidence suggests cerebrovascular disease (CVD) incidence is correlated to meteorological conditions. However, research on the primary meteorological factors influencing the incidence of CVD and their influence thresholds in low-latitude mountainous regions remains insufficient. We aimed to investigate the association between meteorological conditions and CVD occurrence in Guizhou province.MethodsUtilizing daily incidence cases for CVD alongside concurrent meteorological data from four microclimate representative stations in Guizhou Province during 2021-2022, we firstly performed random forest and decision tree analysis to identify the significant meteorological factors influencing the incidence of CVD, and then we applied distributed lag non-linear model (DLNM) to assess the effect of meteorological factors on CVD incidence.ResultsCritical meteorological factors associated with CVD incidence include diurnal temperature range (DTR), temperature change between neighboring days (TCN), diurnal pressure range (DPR), pressure change between neighboring days (PCN), and minimum temperature. The risk of CVD incidence markedly increased with narrow DTR, positive TCN, and colder conditions. The thresholds of minimum temperature and TCN droped with the decrease of annual average temperature in microclimate zone. In the middle subtropical region of Jiangkou, the northern subtropical region of Xishui, and the warm temperate region of Shuicheng, there was a risk of CVD when the minimum temperature falled below 12.2°C, 10.7°C, and 6.7°C, respectively. When TCN exceeded the critical threshold (0.2°C in Shuicheng, 0.3°C in Xishui, and 0.4°C in Jiangkou and Ceheng), the risk of CVD incidence increased linearly. DPR and PCN displayed varied thresholds across different microclimate without consistent patterns. DPR in middle subtropical region of Jiangkou and warm temperate region of Shuicheng played a protective role, while the risk of the disease increased linearly when DPR was lower than 3.2 hPa and 2.7 hPa in south subtropical region of Ceheng and north subtropical region of Xishui, respectively. The short-term effects within 5 days with small DTR and narrow positive TCN were more obvious. The thresholds and lag times of other meteorological environmental factors remained indistinct in the four microclimate zones.DiscussionOur findings delineated the common characteristics of the effect on the incidence of CVD of meteorological environments in various microclimate zones, and clarified the influence of minimum temperature and TCN exhibited spatial heterogeneity, Which may be assistance for meteorological risk forecasting in CVD prevention and control.

Study on the influence of gas transmission characteristics of positive pressure beam tube system under graded pressurization

The positive pressure beam tube system addresses issues related to gas composition distortion, concentration variations, and long transmission delays observed in traditional negative pressure systems. It has increasingly become the primary system for early monitoring and warning of coal spontaneous combustion in goaf areas. Nevertheless, there remains a deficiency in comprehensive research concerning critical aspects like gas transmission characteristics and transmission lag time in the positive pressure beam tube system. This study aims to construct an experimental platform for the positive pressure beam tube monitoring system and systematically investigate how the choice of pressurization device, pipe length, pipe diameter, and driving pressure in the transmission pipeline affect gas transmission characteristics. The findings indicate that the most effective pressurization occurs under conditions of two-stage high positive pressure transport, with a driving gas pressure of 0.65 MPa. The optimal diameter for positive pressure gas transmission is 7 mm. Long-distance negative pressure pipelines result in decreased transmission efficiency, necessitating increased output pressure with the lengthening of positive pressure pipelines to maintain efficiency.

Information-theory-based System-level Babcock–Leighton Flux Transport Model–Data Comparisons

Abstract System-level Babcock–Leighton flux transport model–data comparisons are performed using information theory. The model is run with a maximum meridional flow speed of 16.5 m s−1 with the flow speed systematically varied by 20% (BLFT20) and 50% (BLFT50). Overall, the comparisons show that the models qualitatively capture much of the information flow among the toroidal field (sunspot number), polar field, and meridional flow. BLFT20 generally compares better than BLFT50, suggesting that meridional flow variation of 20% may be more realistic than 50%. However, the information flow from the meridional flow to the polar field is captured better in BLFT50. There is more information flow from the sunspot number to the polar field than the other way around in BLFT20 and observations. The information flow from the polar field to the sunspot number peaks at lag times (τ) of ∼2 yr and 7–9 yr. The results can shed light on the nature of the Sun’s magnetic memory and the diffusive/dissipative processes and advection in the turbulent flux transport at the Sun.

Population pharmacokinetic analysis identifies an absorption process model for mycophenolic acid in patients with renal transplant.

The pharmacokinetics (PKs) of mycophenolic acid (MPA) exhibit considerable complexity and large variability. We developed a population pharmacokinetic (popPK) model to predict the complex PK of MPA by examining an absorption model. Forty-two patients who had undergone renal transplantation were included in this study. popPK analysis, incorporating several absorption models, was performed using the nonlinear mixed-effects modeling program NONMEM. The MPA area under the concentration-time curve at 0-12 h (AUC0-12) was simulated using the final model to calculate the recommended dose. The PK of MPA was adequately described using a two-compartment model incorporating sequential zero- and first-order absorption with lag time. Total body weight, renal function (RF), and posttransplantation day (PTD) were included as covariates affecting MPA PK. The final model estimates were 7.56, 11.6 L/h, 104.0 L, 17.3 L/h, 169.0 L, 0.0453, 0.283, and 1.95 h for apparent nonrenal clearance, apparent renal clearance, apparent central volume of distribution, apparent intercompartmental clearance, apparent peripheral volume of distribution, absorption half-life, lag time, and duration of zero-order absorption, respectively. Simulation results showed that a dose regimen of 500-1000 mg twice daily is recommended during the early posttransplantation period. However, dose reduction could be required with increased PTD and decreased RF. The complex PK of MPA was explained using an absorption model. The developed popPK model can provide useful information regarding individual dosing regimens based on PTD and RF.

Competition Between Advected and Local Variability Determines Coherent Propagation of Labrador Sea Water Along the DWBC

AbstractThe Deep Western Boundary Current (DWBC) is a major conduit for the equatorward export of dense waters formed in the subpolar North Atlantic and Nordic Seas that constitute the lower limb of the Atlantic Meridional Overturning Circulation. Here, we investigate the extent to which there is coherent propagation of property anomalies along the DWBC from the Labrador Sea exit to 26.5°N. Past studies have focused on relationships between DWBC anomalies at selected sites. Here we use a hydrographic data set (EN4) that covers the time period of 1970–2020 to examine coherence continuously along the boundary current. Our findings reveal sharp differences between the upper and deep Labrador Sea Water (uLSW, dLSW). Specifically, dLSW property anomalies are highly correlated at all points downstream to the Labrador Sea exit. Furthermore, the lags that yield maximum correlations uniformly increase with distance along the boundary. uLSW, however, shows a sharp decline in coherence along the boundary such that the anomalies downstream are poorly correlated with those at the Labrador Sea exit and the lag times are not monotonic. Most of the decline in uLSW coherence occurs from the Labrador Sea exit to Flemish Cap, where local variability at uLSW densities is large. Our study sheds light on the competition between advected property variability and local property variability that impacts the identification of anomalies downstream. The uLSW and dLSW differences expressed along the DWBC are also evident offshore, consistent with past Lagrangian studies.

Nodulo-Ulcerative Ocular Surface Squamous Neoplasia in 27 Patients: Clinical Presentation, Management and Outcomes

ABSTRACT Purpose To report the clinical presentation, management, and outcomes of nodulo-ulcerative ocular surface squamous neoplasia (nuOSSN). Methods Retrospective interventional clinical cohort study of 27 patients from a quaternary ocular oncology center. Results Twenty-seven patients were diagnosed with nuOSSN during the six-year study period. The mean age at presentation was 53 years (median, 51 years; range, 25 to 81 years). Misdiagnosis was noted in 7 (26%) patients, and the mean lag time from symptom onset to presentation at our center was 14 months (median, 6 months; range, 1 to 96 months). The bulbar conjunctiva was the commonest epicenter (n = 19, 70%), and the temporal quadrant was most commonly involved (n = 13, 48%). The mean tumor diameter and thickness were 18 mm (median, 16 mm; range, 8 to 60 mm) and 3 mm (median, 2 mm; range, 1 to 5 mm), respectively. Corneal, limbal, and scleral thinning were seen in 15 (56%), 18 (67%), and 10 (37%) patients, respectively. Peripheral corneal opacification was seen in 18 (67%), and thickening around the area of scleral thinning was seen in 12 (44%) patients. Tumors belonged to the American Joint Committee for Cancer classification T2 (n = 2, 7%), T3 (n = 19, 70%), and T4 (n = 6, 22%) categories. Primary treatment (n = 19) included topical 1% 5-fluorouracil (5FU) eye drops (n = 1, 4%), excisional biopsy (n = 4, 14%), extended enucleation (n = 11, 41%), and orbital exenteration (n = 3, 11%). At a mean follow-up of 9 months (median, 3 months; range 1 to 46 months) in 19 patients who received treatment, the outcomes included local tumor recurrence in 2 patients (11%), tumor control in 16 (84%), globe salvage in 3 (16%), and lymph node metastasis in 2 patients (11%). Conclusion nuOSSN is an aggressive form of the disease that is frequently misdiagnosed due to the presence of corneoscleral thinning. Globe salvage rates are poor owing to the advanced stage of presentation.

Development and evaluation of pulsatile drug delivery system of Telmisartan

The aim of the present study was the formulation of pulsatile tablets of Telmisartan by press coating technique that could release the drug time controlled manner. The core tablets and press coated pulsatile tablet of Telmisartan was prepared by direct compression technique. The core tablets were formulated using super disintegrating agent cross carmilose sodium and pulsatile tablets were by using polymer HPMC and Ethyl cellulose in various concentrations. Compatibility studies indicate that there is no interaction between the excipient and the drug. All tablets formulations were subjected to evaluation parameter. All the parameters were found within the limit. Pulsatile tablets formulation F3, F4 and F5 showed sufficient lag time of 4hr, 3hr and 4 hr respectively. The optimized formulation of F3 was consider as the best formulation with respect to drug content, hardness, lag time and In vitro drug release. Formulation F3 showed optimum lag time of 4 hour and release maximum drug in 8 hour. The developed formulation was found to be stable during the stability studies of 3 month indicating good stability of the tablets.

FORMULATION AND EVALUATION OF FLOATING BIOADHESIVE TABLET OF GLYBURIDE FOR DIABETES

The Floating tablets of Glyburide were prepared by granulation technique based on effervescent approach. HPMC and polyethylene oxide were used as polymer, for gas generation sodium bicarbonate was used. Talc, avicel, and magnesium stearate were used. In the present study, on the basis of results it was concluded that with increase in the concentration of polymers decrease the drug release profile. On the other hand there was no effect on release of drug by changing the HPMC viscosity grades. Increased sodium bicarbonate concentration can decrease the floating lag time and there is no significant change on drug release profile. So by using appropriate concentration of polymer and sodium bicarbonate can develop sustained release floating tablet.

The price elasticity of natural gas demand of small consumers in Germany during the energy crisis 2022

Understanding how consumers respond to turbulent market conditions is crucial for planning security of natural gas supply. This paper estimates the price elasticity of demand of small consumers in Germany in the period with both high price fluctuations and a fear of natural gas shortage in the aftermath of the Russian invasion of Ukraine. Using granular data between 2018 and 2023, we estimate an Auto Regressive Distributed Lag (ARDL) time series cointegrating model. We find a price elasticity of demand for natural gas of -0.01 for wholesale prices and -0.04 for retail prices. Additionally, we quantify the effects of weather conditions and public awareness on the energy crisis. The results suggest i) that extreme price changes would be required to trigger short-term demand adjustments, and ii) demonstrate the importance of public attention on the crisis situation.

Insolation Cycles Control the Timing and Pattern of Resonance Frequency Drifts at a Natural Rock Tower, Utah, USA

Resonance frequency monitoring can detect structural changes during progressive rock slope failure; however, reversible environmentally-driven frequency drifts may inhibit identification of permanent changes. Frequency drifts are commonly correlated with air temperature, lagging temperature changes by zero to 35–60 days. Here we report observations from two years of monitoring at a rock tower in Utah, USA where annual resonance frequency changes appear to precede air temperature cycles by ~35 days. Using correlations with meteorological data supplemented by numerical modeling, we identify changes in insolation as the primary driver of annual frequency drifts, giving rise to the negative lag time. Sparse in-situ insolation data show that the daily frequency increase lags sunrise by several hours, while frequencies decrease at sunset, responses we attribute to the west facing aspect of the tower. Modeled daily insolation patterns match frequency data for months when in-situ measurements are not available. Numerical models offer the advantage of predicting insolation patterns for different aspects of the rock tower, such as the west facing cliff where measurements would be challenging. Our study highlights the value of long-term datasets in identifying mechanisms driving environmentally associated frequency drifts, understanding that is crucial to facilitate detection of permanent changes during progressive failure.

Investigation on the safety of 30,000-ton combined train with different lag times of slave control locomotives

To investigate the influence of the lag time in braking response of the slave control locomotives caused by the LOCOTROL wireless synchronous control system on the longitudinal impulse of the train, a 30,000-ton heavy-haul train model was established. The model is in the form of ‘1+1+1+1’. The simulation accuracy of the air braking system was verified by comparing with static tests. A dynamic model consisting of two HXD1 locomotives and a 100-type couple was established for study the middle locomotive’s running safety. Results show that, under normal transmission delays, the lag time in the braking response of the slave control locomotives is approximately 2–3 s. The lag time significantly influence the coupler force and its distribution law. During emergency braking, the lag time increased from 0 s to 6 s, and the maximum coupler force increased by 1877.1 kN. Among the three slave control locomotives, the one positioned in the middle has the greatest impact on the coupler force, while the one closest to the leading locomotive has the least impact. When the lag time reaches 5 s, the middle locomotive’s coupler becomes unstable. Increasing the lateral stiffness of the secondary suspension is beneficial for enhancing the locomotive's ability to stabilise the coupler.

Sublingual permeability of model drugs in New Zealand White Rabbits: In Vitro-In vivo correlation

This study investigated sublingual drug permeation and administration using five model drugs with diverse physicochemical properties, employing New Zealand White Rabbit sublingual mucosa for in vitro experiments and New Zealand White Rabbits for in vivo studies. The research aimed to determine key permeation parameters, specifically permeability and lag time. A strong linear correlation (r = 0.93, n = 5) was established between in vitro permeability and the distribution coefficient of the model drugs at pH 6.8. The study revealed no significant difference between in vitro and in vivo permeability, suggesting that in vitro studies can reliably predict in vivo permeability for these drugs. However, the in vivo lag time was significantly shorter than the in vitro lag time due to the presence of capillaries in the sublingual mucosa, which provided direct access to the systemic circulation and the absence of an aqueous boundary layer.

Assessment of water retention dynamic in water resource formation area: A case study of the northern slope of the Qinling Mountains in China

Study RegionThe northern slope of Qinling Mountains (NQL) is an important water retention (WR) area in China, which guarantees the utilization of water resources in the plain area. However, the effects of significant changes in climate and land cover on WR have not been quantitatively studied in recent years. Study FocusIn this study, we quantified the relative impacts of climate and land cover changes on WR at NQL and predicted the future changes of WR under different climate scenarios (SSP2–4.5 and SSP5–8.5). New Hydrological Insights for the RegionThe results indicated that WR in NQL has exhibited an overall increase from 1985 to 2020 at a rate of 1.10 mm/a, with climate and land cover change explaining 86.3 % and 13.7 % of this change, respectively. Although precipitation has increased since 1998, the compounding effects of land cover change and precipitation intensity increase have led to a slight decline of WR magnitude and efficiency due to their offsetting impacts. Under future climate change, the WR capacity changes in the SSP2–4.5 are relatively stable, while the significant increase in temperature under the SSP5–8.5 lead to a decreasing trend in WR efficiency. In addition, we proposed an indicator framework to evaluate WR using WR efficiency and baseflow lag time. Our results may provide valuable insights for sustainable utilization and scientific management of water resources.

Enhancing Construction Management Digital Twins Through Process Mining of Progress Logs

Large-scale infrastructure projects involve numerous complex processes, and even small construction management (CM) deficiencies can lead to significant resource waste. Digital twins (DTs) offer a potential solution to the management side of the problem. The current DT models focus on real-time physical space mapping, which causes the fragmentation of process data in servers and limits lifecycle algorithm implementation. In this paper, we propose a DT framework that integrates process twins to achieve process discovery through process mining and that serves as a supplement to DTs. The proposed framework was validated in a highway project. Based on BIM, GIS, and UAV physical entity twins, construction logs were collected, and process discovery was performed on them using process mining techniques, achieving process mapping and conformance checking for the process twins. The main conclusions are as follows: (1) the process twins accurately reflect the actual construction process, addressing the lack of process information in CM DTs; (2) process variants can be used to analyze abnormal changes in construction methods and identify potential construction risks in advance; (3) sudden changes in construction nodes during activities can affect resource allocation across multiple subsequent stages; (4) process twins can be used to visualize construction schedule risks, such as lead and lag times. The significance of this paper lies in the construction of process twins to complement the existing DT framework, providing a solution to the lost process relationships in DTs, enabling better process reproduction, and facilitating prediction and optimization. In future work, we will concentrate on conducting more in-depth research on process twins, drawing from a wider range of data sources and advancing intelligent process prediction techniques.

Temporal Associations Between Polarimetric Updraft Proxies and Signatures of Inflow and Hail in Supercells

Recurring polarimetric radar signatures in supercells include deep and persistent differential reflectivity (ZDR) columns, hail inferred in low-level scans, and the ZDR arc signature. Prior investigations of supercell polarimetric signatures reveal positive correlations between the ZDR column depth and cross-sectional area and quantitative characteristics of the radar reflectivity field. This study expands upon prior work by examining temporal associations between supercell polarimetric radar signatures, incorporating a dataset of relatively discrete, right-moving supercells from the continental United States observed by the Weather Surveillance Radar 1988-Doppler (WSR-88D) network. Cross-correlation coefficients were calculated between the ZDR column area and depth and the base-scan hail area, ZDR arc area, and mean ZDR arc value. These correlation values were computed with a positive and negative lag time of up to 45 min. Results of the lag correlation analysis are consistent with prior observations indicative of storm cycling, including temporal associations between ZDR columns and inferred hail signatures/ZDR arcs in both tornadic and nontornadic supercells, but were most pronounced in tornadic storms.

Using machine learning techniques to predict viral suppression among people with HIV.

This study aims to develop and examine the performance of machine learning (ML) algorithms in predicting viral suppression among statewide people living with HIV (PWH) in South Carolina (SC). Extracted through the electronic reporting system in SC, the study population was adult PWH who were diagnosed between 2005-2021. Viral suppression was defined as viral load <200 copies/ml. The predictors, includingsocio-demographics, a historical information of viral load indicators (e.g., viral rebound), comorbidities, healthcare utilization, and annual county-level factors (e.g., social vulnerability) were measured in each 4-month windows. Using historic information in different lag time windows (1-, 3- or 5-lagged time windows with each 4-month as a unit), both traditional and ML approaches (e.g., Long Short-Term Memory network [LSTM]) were applied to predict viral suppression. Comparisons of prediction performance between different models were assessed by area under curve (AUC), recall, precision, F1 score, and Youden index. Machine learning approaches outperformed the generalized linear mixed model. In all the three lagged analysis of a total of 15,580 PWH, the LSTM (lag 1: AUC=0.858; lag 3: AUC=0.877; lag 5: AUC=0.881) algorithm outperformed all the other methods in terms of AUC performance for predicting viral suppression. The top-ranking predictors that were common in different models included historical information of viral suppression, viral rebound, and viral blips in the Lag-1 time window. Inclusion of county level variables did not improve the model prediction accuracy. Supervised machine learning algorithms may offer better performance for risk prediction of viral suppression than traditional statistical methods.

Accurate Inference of the Polyploid Continuum using Forward-time Simulations.

Multiple rounds of whole-genome duplication (WGD) followed by diploidization have occurred throughout the evolutionary history of angiosperms. Much work has been done to model the genomic consequences and evolutionary significance of WGD. While researchers have historically modeled polyploids as either allopolyploids or autopolyploids, the variety of natural polyploids span a continuum of differentiation across multiple parameters, such as the extent of polysomic vs. disomic inheritance, and the degree of genetic differentiation between the ancestral lineages. Here we present a forward-time polyploid genome evolution simulator called SpecKS. SpecKS models polyploid speciation as originating from a 2D continuum, whose dimensions account for both the level of genetic differentiation between the ancestral parental genomes, as well the time lag between ancestral speciation and their subsequent reunion in the derived polyploid. Using extensive simulations, we demonstrate that changes in initial conditions along either dimension of the 2D continuum deterministically affect the shape of the Ks histogram. Our findings indicate that the error in the common method of estimating WGD time from the Ks histogram peak scales with the degree of allopolyploidy, and we present an alternative, accurate estimation method that is independent of the degree of allopolyploidy. Lastly, we use SpecKS to derive tests that infer both the lag time between parental divergence and WGD time, and the diversity of the ancestral species, from an input Ks histogram. We apply the latter test to transcriptomic data from over 200 species across the plant kingdom, the results of which are concordant with the prevailing theory that the majority of angiosperm lineages are derived from diverse parental genomes and may be of allopolyploid origin.

Evaluation of wastewater percent positive for assessing epidemic trends - A case study of COVID-19 in Shangrao, China

ObjectiveThis study aims to assess the feasibility of evaluating the COVID-19 epidemic trend through monitoring the positive percentage of SARS-CoV-19 RNA in wastewater. MethodThe study collected data from January to August 2023, including the number of reported cases, the positive ratio of nucleic acid samples in sentinel hospitals, the incidence rate of influenza-like symptoms in students, and the positive ratio of wastewater samples in different counties and districts in Shangrao City. Wastewater samples were obtained through grabbing and laboratory testing was completed within 24 h. The data were then normalized using Z-score normalization and analyzed for lag time and correlation using the xcorr function and Spearman correlation coefficient. ResultsA total of 2797 wastewater samples were collected. The wastewater monitoring study, based on sampling point distribution, was divided into two phases. Wuyuan County consistently showed high levels of positive ratio in wastewater samples in both phases, reaching peak values of 91.67% and 100% respectively. The lag time analysis results indicated that the peak positive ratio in all wastewater samples in Shangrao City appeared around 2 weeks later compared to the other three indicators. The correlation analysis revealed a strong linear correlation across all four types of data, with Spearman correlation coefficients ranging from 0.783 to 0.977, all of which were statistically significant. ConclusionThe positive ratio of all wastewater samples in Shangrao City accurately reflected the COVID-19 epidemic trend from January to August 2023. This study confirmed the lag effect of wastewater percent positive and its strong correlation with the reported incidence rate and the positive ratio of nucleic acid samples in sentinel hospitals, supporting the use of wastewater percent positive monitoring as a supplementary tool for infectious disease surveillance in the regions with limited resources.