Integrating dynamic models and neural networks to discover the mechanism of meteorological factors on Aedes population

Aedes mosquitoes, known as vectors of mosquito-borne diseases, pose significant risks to public health and safety. Modeling the population dynamics of Aedes mosquitoes requires comprehensive approaches due to the complex interplay between biological mechanisms and environmental factors. This study developed a model that couples differential equations with a neural network to simulate the dynamics of mosquito population, and explore the relationships between oviposition rate, temperature, and precipitation. Data from nine cities in Guangdong Province spanning four years were used for model training and parameter estimation, while data from the remaining three cities were reserved for model validation. The trained model successfully simulated the mosquito population dynamics across all twelve cities using the same set of parameters. Correlation coefficients between simulated results and observed data exceeded 0.7 across all cities, with some cities surpassing 0.85, demonstrating high model performance. The coupled neural network in the model effectively revealed the relationships among oviposition rate, temperature, and precipitation, aligning with biological patterns. Furthermore, symbolic regression was used to identify the optimal functional expression for these relationships. By integrating the traditional dynamic model with machine learning, our model can adhere to specific biological mechanisms while extracting patterns from data, thus enhancing its interpretability in biology. Our approach provides both accurate modeling and an avenue for uncovering potential unknown biological mechanisms. Our conclusions can provide valuable insights into designing strategies for controlling mosquito-borne diseases and developing related prediction and early warning systems.

Identification of molecular subtypes for endometrial carcinoma using a 46-gene next-generation sequencing panel: a retrospective study on a consecutive cohort

BACKGROUND

Traditional classification tools for endometrial carcinoma (EC), such as DNA sequencing, immunohistochemistry (IHC), or PCR, are cumbersome and time-consuming. Large next-generation sequencing (NGS) panels have simplified testing but are expensive. In this study, we propose a concise NGS panel as an effectively viable approach for classifying EC.

MATERIALS AND METHODS

We retrospectively enrolled a consecutive EC cohort of hysterectomy with bilateral salpingo-oophorectomy from Fudan University Shanghai Cancer Center between 2020 and 2022. A 46-gene NGS panel was utilized to identify POLE exonuclease domain mutations, microsatellite instability-high (MSI-H), TP53 mutations, and other clinically relevant targets.

RESULTS

Tumor tissue samples from 331 EC patients were evaluated, with 284 (85.8%) cases classified as endometrioid endometrial carcinoma. The median follow-up time was 32.6 months (n = 303), during which 23 patients experienced recurrence or disease progression. Using the concise NGS panel, patients were stratified into four molecular subgroups according to the World Health Organization classification criteria: POLE mut (n = 47; 14.2%), mismatch repair deficiency (dMMR) (n = 79; 23.9%), non-specific molecular profile (n = 148; 44.7%), and abnormal p53 expression (p53 abn) (n = 57; 17.2%). POLE mut displayed the most favorable prognosis, while p53 abn had the worst prognosis (P < 0.001). The concordance between NGS and IHC was 91.8% (269/293) for detecting MMR status and 65.3% (201/308) for detecting p53 status. Patients detected solely by NGS had significantly worse prognosis than those detected solely by IHC, indicating higher accuracy of the NGS panel. With the molecular subtyping information, adjuvant treatment plans for 19.6% of patients could potentially be altered, mainly concentrated in the POLE mut and p53 abn subtypes. This panel also aids targeted therapy and poly (ADP-ribose) polymerase (PARP) inhibitor-related gene mutation detection, as well as auxiliary genetic screening.

CONCLUSION

Our study demonstrates that the concise NGS panel is an effective 'one-stop' strategy for precisely classifying EC with high clinical availability.

Uncertainty quantification for the random HIV dynamical model driven by drug adherence

In HIV drug therapy, the high variability of CD4+ T cells and viral loads brings uncertainty to the determination of treatment options and the ultimate treatment efficacy, which may be the result of poor drug adherence. We develop a dynamical HIV model coupled with pharmacokinetics, driven by drug adherence as a random variable, and systematically study the uncertainty quantification, aiming to construct the relationship between drug adherence and therapeutic effect. Using adaptive generalized polynomial chaos, stochastic solutions are approximated as polynomials of input random parameters. Numerical simulations show that results obtained by this method are in good agreement, compared with results obtained through Monte Carlo sampling, which helps to verify the accuracy of approximation. Based on these expansions, we calculate the time-dependent probability density functions of this system theoretically and numerically. To verify the applicability of this model, we fit clinical data of four HIV patients, and the goodness of fit results demonstrate that the proposed random model depicts the dynamics of HIV well. Sensitivity analyses based on the Sobol index indicate that the randomness of drug effect has the greatest impact on both CD4+ T cells and viral loads, compared to random initial values, which further highlights the significance of drug adherence. The proposed models and qualitative analysis results, along with monitoring CD4+ T cells counts and viral loads, evaluate the influence of drug adherence on HIV treatment, which helps to better interpret clinical data with fluctuations and makes several contributions to the design of individual-based optimal antiretroviral strategies.

Measurements of Chemical Potentials in Pb-Pb Collisions at sqrt[s_{NN}]=5.02 TeV

This Letter presents the most precise measurement to date of the matter-antimatter imbalance at midrapidity in Pb-Pb collisions at a center-of-mass energy per nucleon pair sqrt[s_{NN}]=5.02  TeV. Using the Statistical Hadronization framework, it is possible to obtain the value of the electric charge and baryon chemical potentials, μ_{Q}=-0.18±0.90  MeV and μ_{B}=0.71±0.45  MeV, with unprecedented precision. A centrality-differential study of the antiparticle-to-particle yield ratios of charged pions, protons, Ω baryons, and light (hyper)nuclei is performed. These results indicate that the system created in Pb-Pb collisions at the LHC is on average baryon-free and electrically neutral at midrapidity.

Observation of Medium-Induced Yield Enhancement and Acoplanarity Broadening of Low-p_{T} Jets from Measurements in pp and Central Pb-Pb Collisions at sqrt[s_{NN}]=5.02 TeV

The ALICE Collaboration reports the measurement of semi-inclusive distributions of charged-particle jets recoiling from a high transverse momentum (high p_{T}) hadron trigger in proton-proton and central Pb-Pb collisions at sqrt[s_{NN}]=5.02  TeV. A data-driven statistical method is used to mitigate the large uncorrelated background in central Pb-Pb collisions. Recoil jet distributions are reported for jet resolution parameter R=0.2, 0.4, and 0.5 in the range 7 Collapse

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From economic threshold to economic injury level: Modeling the residual effect and delayed response of pesticide application

Integrated Pest Management (IPM) poses a challenge in determining the optimal timing of pesticide sprays to ensure that pest populations remain below the Economic Injury Level (EIL), due to the long-term residual effects of many pesticides and the delayed responses of pest populations to pesticide sprays. To address this issue, a specific pesticide kill-rate function is incorporated into a deterministic exponential growth model and a subsequent stochastic model. The findings suggest the existence of an optimal pesticide spraying cycle that can periodically control pests below the EIL. The results regarding stochasticity indicate that random fluctuations promote pest extinction and ensure that the pest population, under the optimal cycle, does not exceed the EIL on average, even with a finite number of IPM strategies. All those confirm that the modeling approach can accurately reveal the intrinsic relationship between the two key indicators Economic Threshold and EIL in the IPM strategy, and further realize the precise characterization of the residual effect and delayed response of pesticide application.

[A panel study on the association of organophosphate ester flame retardant exposure with thyroid function related hormones in healthy older adults]

Objective: To explore the impact of whole blood organophosphate esters (OPEs) flame retardant exposure on thyroid function-related hormones in healthy older adults. Methods: In this panel study, five repeated population-based epidemiological surveys and biological sample collection were conducted from September 2018 to January 2019, with 76 healthy older adults aged 60-69 years in the Dianliu Community of Jinan, Shandong Province. Information on the sociodemographic characteristics, diet, and health status of the respondents was systematically gathered through questionnaires and physical examinations. Fasting venous blood was collected to determine the levels of OPEs, thyroid-stimulating hormone (TSH), triiodothyronine (T3), and thyroxine (T4). A linear mixed-effects model was used to analyze the impact of OPEs exposure on thyroid function-related hormones in healthy older adults. Results: Each of the 76 subjects participated in at least two follow-up visits, resulting in a total of 350 person visits. The age of the study participants was (65.07±2.76) years, with 38 participants of both sexes. A total of eight OPEs were included with a detection rate exceeding 50%, and the M (Q1, Q3) for ∑OPEs was 3.85 (2.33, 5.74) ng/ml, with alkyl-OPEs being the major type of OPEs with an M (Q1, Q3) of 1.27 (0.64, 2.50) ng/ml. The M (Q1, Q3) for TSH, T3, and T4 was 3.74 (2.55, 5.69) μIU/ml, 1.32 (1.10, 1.60) ng/ml, and 45.04 (36.96, 53.27) ng/ml, respectively. Linear mixed-effects model showed that TSH was significantly decreased by 9.93% (95%CI:-15.17%, -4.36%) and 11.14% (95%CI:-15.94%, -6.06%) in older adults for each quartile level increase in TnBP and TEHP exposures, respectively. Gender-stratified analysis indicated that TEHP exposure was negatively associated with TSH levels in male older adults, whereas a decrease in TSH levels among female older adults was associated with TnBP exposure. Conclusion: Exposure to whole blood OPEs is associated with decreased TSH levels among healthy older adults, with notable gender differences.

The limitations of testicular organoids: are they truly as promising as we believe?

Organoid systems have revolutionised various facets of biological research by offering a three-dimensional (3D), physiologically relevant in vitro model to study complex organ systems. Over recent years, testicular organoids have been publicised as promising platforms for reproductive studies, disease modelling, drug screening, and fertility preservation. However, the full potential of these systems has yet to be realised due to inherent limitations. This paper offers a comprehensive analysis of the current challenges associated with testicular organoid models. Firstly, we address the inability of current organoid systems to fully replicate the intricate spatial organisation and cellular diversity of the in vivo testis. Secondly, we scrutinise the fidelity of germ cell maturation within the organoids, highlighting incomplete spermatogenesis and epigenetic inconsistencies. Thirdly, we consider the technical challenges faced during organoid culture, including nutrient diffusion limits, lack of vasculature, and the need for specialised growth factors. Finally, we discuss the ethical considerations surrounding the use of organoids for human reproduction research. Addressing these limitations in combination with integrating complementary approaches, will be essential if we are to advance our understanding of testicular biology and develop novel strategies for addressing reproductive health issues in males.

Valuation and comparison of the actual and optimal control strategy in an emerging infectious disease: Implication from a COVID-19 transmission model

To effectively combat emerging infectious diseases like COVID-19, it is crucial to adopt strict prevention and control measures promptly to effectively contain the spread of the epidemic. In this paper, we propose a transmission model to investigate the influence of two control strategies: reducing contact numbers and improving medical resources. We examine these strategies in terms of constant control and time-varying control. Through sensitivity analysis on two reproduction numbers of the model with constant control, we demonstrate that reducing contact numbers is more effective than improving medical resources. Furthermore, these two constant controls significantly influence the peak values and timing of infections. Specifically, intensifying control measures can reduce peak values, albeit at the expense of delaying the peak time. In the model with time-varying control, we initially explore the corresponding optimal control problem and derive the characteristic expression of optimal control. Subsequently, we utilize real data from January 10th to April 12th, 2020, in Wuhan city as a case study to perform parameter estimation by using our proposed improved algorithm. Our findings illustrate that implementing optimal control measures can effectively reduce infections and deaths, and shorten the duration of the epidemic. Then, we numerically explore that implementing control measures promptly and increasing intensity to reduce contact numbers can make actual control be more closer to optimized control. Finally, we utilize the real data from October 31st to November 18th, 2021, in Hebei province as a second case study to validate the feasibility of our proposed suggestions.

Emergence of Long-Range Angular Correlations in Low-Multiplicity Proton-Proton Collisions

This Letter presents the measurement of near-side associated per-trigger yields, denoted ridge yields, from the analysis of angular correlations of charged hadrons in proton-proton collisions at sqrt[s]=13  TeV. Long-range ridge yields are extracted for pairs of charged particles with a pseudorapidity difference of 1.4<|Δη|<1.8 and a transverse momentum of 1 Collapse

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[Low-dose CT reconstruction based on high-dimensional partial differential equation projection recovery]

OBJECTIVE

We propose a low-dose CT reconstruction method using partial differential equation (PDE) denoising under high-dimensional constraints.

METHODS

The projection data were mapped into a high-dimensional space to construct a high-dimensional representation of the data, which were updated by moving the points in the high-dimensional space. The data were denoised using partial differential equations and the CT image was reconstructed using the FBP algorithm.

RESULTS

Compared with those by FBP, PWLS-QM and TGV-WLS methods, the relative root mean square error of the Shepp-Logan image reconstructed by the proposed method were reduced by 68.87%, 50.15% and 27.36%, the structural similarity values were increased by 23.50%, 8.83% and 1.62%, and the feature similarity values were increased by 17.30%, 2.71% and 2.82%, respectively. For clinical image reconstruction, the proposed method, as compared with FBP, PWLS-QM and TGV-WLS methods, resulted in reduction of the relative root mean square error by 42.09%, 31.04% and 21.93%, increased the structural similarity values by 18.33%, 13.45% and 4.63%, and increased the feature similarity values by 3.13%, 1.46% and 1.10%, respectively.

CONCLUSION

The new method can effectively reduce the streak artifacts and noises while maintaining the spatial resolution in reconstructed low-dose CT images.

First Measurement of the |t| Dependence of Incoherent J/ψ Photonuclear Production

The first measurement of the cross section for incoherent photonuclear production of J/ψ vector mesons as a function of the Mandelstam |t| variable is presented. The measurement was carried out with the ALICE detector at midrapidity, |y|<0.8, using ultraperipheral collisions of Pb nuclei at a center-of-mass energy per nucleon pair of sqrt[s_{NN}]=5.02  TeV. This rapidity interval corresponds to a Bjorken-x range (0.3-1.4)×10^{-3}. Cross sections are given in five |t| intervals in the range 0.04<|t|<1  GeV^{2} and compared to the predictions by different models. Models that ignore quantum fluctuations of the gluon density in the colliding hadron predict a |t| dependence of the cross section much steeper than in data. The inclusion of such fluctuations in the same models provides a better description of the data.

Model analysis and data validation of structured prevention and control interruptions of emerging infectious diseases

The design of optimized non-pharmaceutical interventions (NPIs) is critical to the effective control of emergent outbreaks of infectious diseases such as SARS, A/H1N1 and COVID-19 and to ensure that numbers of hospitalized cases do not exceed the carrying capacity of medical resources. To address this issue, we formulated a classic SIR model to include a close contact tracing strategy and structured prevention and control interruptions (SPCIs). The impact of the timing of SPCIs on the maximum number of non-isolated infected individuals and on the duration of an infectious disease outside quarantined areas (i.e. implementing a dynamic zero-case policy) were analyzed numerically and theoretically. These analyses revealed that to minimize the maximum number of non-isolated infected individuals, the optimal time to initiate SPCIs is when they can control the peak value of a second rebound of the epidemic to be equal to the first peak value. More individuals may be infected at the peak of the second wave with a stronger intervention during SPCIs. The longer the duration of the intervention and the stronger the contact tracing intensity during SPCIs, the more effective they are in shortening the duration of an infectious disease outside quarantined areas. The dynamic evolution of the number of isolated and non-isolated individuals, including two peaks and long tail patterns, have been confirmed by various real data sets of multiple-wave COVID-19 epidemics in China. Our results provide important theoretical support for the adjustment of NPI strategies in relation to a given carrying capacity of medical resources.

Association of epidural analgesia in labor with neurodevelopmental outcomes in premature infants born at <29 weeks of gestational age

OBJECTIVE

To explore associations between epidural administration to mothers in labor with neurodevelopmental outcomes at 3 years corrected age in preterm infants born <29 weeks gestational age.

STUDY DESIGN

Infants born <29 weeks gestational age between 2006 and 2012 were included. Our primary outcome was a composite of death or neurodevelopmental impairment at 3 years corrected age. Infants were divided into those whose mothers did or did not receive epidural analgesia in labor. Univariable and multivariable regression was used for analysis.

RESULTS

There were 548 infants in the no epidural analgesia group and 121 in the epidural analgesia group. The adjusted odds ratio (95%CI) of neurodevelopmental impairment or death in the epidural group was 1.25 (0.82-1.93). Propensity score-matched results were 1.32 (0.79-2.22).

CONCLUSION

Preterm infants born <29 weeks gestational age to mothers who received epidural analgesia during labor were not associated with poor neurodevelopmental outcomes at 3 years corrected age.

Clustering analysis for the evolutionary relationships of SARS-CoV-2 strains

To explore the differences and relationships between the available SARS-CoV-2 strains and predict the potential evolutionary direction of these strains, we employ the hierarchical clustering analysis to investigate the evolutionary relationships between the SARS-CoV-2 strains utilizing the genomic sequences collected in China till January 7, 2023. We encode the sequences of the existing SARS-CoV-2 strains into numerical data through k-mer algorithm, then propose four methods to select the representative sample from each type of strains to comprise the dataset for clustering analysis. Three hierarchical clustering algorithms named Ward-Euclidean, Ward-Jaccard, and Average-Euclidean are introduced through combing the Euclidean and Jaccard distance with the Ward and Average linkage clustering algorithms embedded in the OriginPro software. Experimental results reveal that BF.28, BE.1.1.1, BA.5.3, and BA.5.6.4 strains exhibit distinct characteristics which are not observed in other types of SARS-CoV-2 strains, suggesting their being the majority potential sources which the future SARS-CoV-2 strains' evolution from. Moreover, BA.2.75, CH.1.1, BA.2, BA.5.1.3, BF.7, and B.1.1.214 strains demonstrate enhanced abilities in terms of immune evasion, transmissibility, and pathogenicity. Hence, closely monitoring the evolutionary trends of these strains is crucial to mitigate their impact on public health and society as far as possible.

ψ(2S) Suppression in Pb-Pb Collisions at the LHC

The production of the ψ(2S) charmonium state was measured with ALICE in Pb-Pb collisions at sqrt[s_{NN}]=5.02  TeV, in the dimuon decay channel. A significant signal was observed for the first time at LHC energies down to zero transverse momentum, at forward rapidity (2.5 Collapse

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Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

BACKGROUND

The EMPA-KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population.

METHODS

EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110.

FINDINGS

Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62-0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16-1·59), representing a 50% (42-58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1).

INTERPRETATION

In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease.

FUNDING

Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council.

Measurements of Groomed-Jet Substructure of Charm Jets Tagged by D^{0} Mesons in Proton-Proton Collisions at sqrt[s]=13 TeV

Understanding the role of parton mass and Casimir color factors in the quantum chromodynamics parton shower represents an important step in characterizing the emission properties of heavy quarks. Recent experimental advances in jet substructure techniques have provided the opportunity to isolate and characterize gluon emissions from heavy quarks. In this Letter, the first direct experimental constraint on the charm-quark splitting function is presented, obtained via the measurement of the groomed shared momentum fraction of the first splitting in charm jets, tagged by a reconstructed D^{0} meson. The measurement is made in proton-proton collisions at sqrt[s]=13  TeV, in the low jet transverse-momentum interval of 15≤p_{T}^{jet ch}<30  GeV/c where the emission properties are sensitive to parton mass effects. In addition, the opening angle of the first perturbative emission of the charm quark, as well as the number of perturbative emissions it undergoes, is reported. Comparisons to measurements of an inclusive-jet sample show a steeper splitting function for charm quarks compared with gluons and light quarks. Charm quarks also undergo fewer perturbative emissions in the parton shower, with a reduced probability of large-angle emissions.

[Study on formulation and revision of standard limits for total bacteria count in "Standards for indoor air quality（GB/T 18883-2022）" in China]

The total bacteria count has been attracting attention as an important pollutant in indoor air, and its standard limit was tightened to 1500 CFU/m3 in "Standards for indoor air quality (GB/T 18883-2022)".The technical contents related to the determination of the indoor air standard limits for total bacteria count were analyzed and studied, including the environmental existence level, exposure status, the health effects and the derivation of the limit value. It also proposed prospects for the future development and revision of quality standards for total bacteria count in indoor air.

Hormetic and synergistic effects of cancer treatments revealed by modelling combinations of radio - or chemotherapy with immunotherapy

BACKGROUND

Radio/chemotherapy and immune systems provide examples of hormesis, as tumours can be stimulated (or reduced) at low radio/chemical or antibody doses but inhibited (or stimulated) by high doses.

METHODS

Interactions between effector cells, tumour cells and cytokines with pulsed radio/chemo-immunotherapy were modelled using a pulse differential system.

RESULTS

Our results show that radio/chemotherapy (dose) response curves (RCRC) and/or immune response curves (IRC) or a combination of both, undergo homeostatic changes or catastrophic shifts revealing hormesis in many parameter regions. Some mixed response curves had multiple humps, posing challenges for interpretation of clinical trials and experimental design, due to a fuzzy region between an hormetic zone and the toxic threshold. Mixed response curves from two parameter bifurcation analyses demonstrated that low-dose radio/chemotherapy and strong immunotherapy counteract side-effects of radio/chemotherapy on effector cells and cytokines and stimulate effects of immunotherapy on tumour growth. The implications for clinical applications were confirmed by good fits to our model of RCRC and IRC data.

CONCLUSIONS

The combination of low-dose radio/chemotherapy and high-dose immunotherapy is very effective for many solid tumours. The net benefit and synergistic effect of combined therapy is conducive to the treatment and inhibition of tumour cells.

[Analysis of late-diagnosis and associated factors in newly reported HIV infections among men who have sex with men in Guangxi Zhuang Autonomous Region, 2005-2021]

Objective: To analyze the trend of late-diagnosis of HIV-infected men who have sex with men (MSM) before and after the AIDS Conquering Project in Guangxi Zhuang Autonomous Region (Guangxi) and its influencing factors, in order to find out the population groups that need priority intervention at the present stage. Methods: The HIV-infected MSM in Guangxi from 2005-2021 were selected from the National Integrated HIV/AIDS Control and Prevention Data System. The Joinpoint 4.9.1.0 software was used to test the time trend of late-diagnosis and non-late-diagnosis cases, and logistic regression was applied to analyze the factors influencing the proportion of late-diagnosis at each stage. Results: From 2005 to 2021, 5 764 HIV-infected MSM were reported in Guangxi from 2005 to 2021, with an overall late-diagnosis of 28.45% (1 640 cases). Under the 2015 baseline data as the boundary, the proportion of late-diagnosis cases showed a trend of sharp decline followed by stabilization from 2005 to 2015, average annual percent change= -6.90% (P<0.001). The effect of factors such as resident population, occupation as a farmer or worker, and sample originating from medical consultation on late-diagnosis changed considerably before and after the implementation of the project, and the factors influencing late-diagnosis at this stage were age, resident population, occupation as a farmer, worker or student. The factors influencing late-diagnosis at this stage are age, resident population, and occupation as a farmer, worker and a student. Conclusions: The proportion of late diagnosis cases of HIV-infected MSM in Guangxi decreased significantly before and after the project. However, late-diagnosis should not be neglected and precise prevention and control should be carried out for the resident population, farmers, workers or students.

Non-smooth dynamics of a SIR model with nonlinear state-dependent impulsive control

The classic SIR model is often used to evaluate the effectiveness of controlling infectious diseases. Moreover, when adopting strategies such as isolation and vaccination based on changes in the size of susceptible populations and other states, it is necessary to develop a non-smooth SIR infectious disease model. To do this, we first add a non-linear term to the classical SIR model to describe the impact of limited medical resources or treatment capacity on infectious disease transmission, and then involve the state-dependent impulsive feedback control, which is determined by the convex combinations of the size of the susceptible population and its growth rates, into the model. Further, the analytical methods have been developed to address the existence of non-trivial periodic solutions, the existence and stability of a disease-free periodic solution (DFPS) and its bifurcation. Based on the properties of the established Poincaré map, we conclude that DFPS exists, which is stable under certain conditions. In particular, we show that the non-trivial order-1 periodic solutions may exist and a non-trivial order-$ k $ ($ k\geq 1 $) periodic solution in some special cases may not exist. Moreover, the transcritical bifurcations around the DFPS with respect to the parameters $ p $ and $ AT $ have been investigated by employing the bifurcation theorems of discrete maps.

Combining the dynamic model and deep neural networks to identify the intensity of interventions during COVID-19 pandemic

During the COVID-19 pandemic, control measures, especially massive contact tracing following prompt quarantine and isolation, play an important role in mitigating the disease spread, and quantifying the dynamic contact rate and quarantine rate and estimate their impacts remain challenging. To precisely quantify the intensity of interventions, we develop the mechanism of physics-informed neural network (PINN) to propose the extended transmission-dynamics-informed neural network (TDINN) algorithm by combining scattered observational data with deep learning and epidemic models. The TDINN algorithm can not only avoid assuming the specific rate functions in advance but also make neural networks follow the rules of epidemic systems in the process of learning. We show that the proposed algorithm can fit the multi-source epidemic data in Xi'an, Guangzhou and Yangzhou cities well, and moreover reconstruct the epidemic development trend in Hainan and Xinjiang with incomplete reported data. We inferred the temporal evolution patterns of contact/quarantine rates, selected the best combination from the family of functions to accurately simulate the contact/quarantine time series learned by TDINN algorithm, and consequently reconstructed the epidemic process. The selected rate functions based on the time series inferred by deep learning have epidemiologically reasonable meanings. In addition, the proposed TDINN algorithm has also been verified by COVID-19 epidemic data with multiple waves in Liaoning province and shows good performance. We find the significant fluctuations in estimated contact/quarantine rates, and a feedback loop between the strengthening/relaxation of intervention strategies and the recurrence of the outbreaks. Moreover, the findings show that there is diversity in the shape of the temporal evolution curves of the inferred contact/quarantine rates in the considered regions, which indicates variation in the intensity of control strategies adopted in various regions.