Infectious Disease Modelling最新文献

{"title":"Quantifying mpox transmission and control: A regional analysis of vaccination strategies in East Africa","authors":"Musa Rabiu ,&nbsp;Bosede Fagbemigun ,&nbsp;Sunday Fadugba ,&nbsp;Michael Shatalov ,&nbsp;Kekana Malesela ,&nbsp;Adejimi Adeniji","doi":"10.1016/j.idm.2025.09.001","DOIUrl":"10.1016/j.idm.2025.09.001","url":null,"abstract":"<div><div>Africa is home to the endemic mpox disease, especially in the tropical rain-forest regions of Central and West Africa. Although it is mostly found in the Democratic Republic of the Congo, reports of it have also come from other neighboring African nations. To understand the dynamics of mpox, we studied its spread in Burundi, Uganda, Rwanda, Congo, and Kenya before and after the implementation of interventions. Using a Bayesian framework, a simple mathematical model of Susceptible-Infected-Recovered type was calibrated and fitted to the 2022 mpox data covering the period before the introduction of intervention strategies. The model was then re-stratified to incorporate key epidemiological features, including vaccination with imperfect efficacy, partial immunity, exposure, and demographics. The transmission of mpox varied throughout East Africa, with Uganda exhibiting the highest basic reproduction number <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> = 2.51, suggesting the possibility of a rapid spread. Despite having the highest initial infection count and the lowest <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> (1.23), Congo may have had delayed detection. The moderate <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> values (1.35 and 1.88) in Rwanda and Burundi have implications for prompt intervention to control epidemics. Transmission and vaccination rates have a non-linear relationship with the thresholds required to contain mpox outbreaks. Our model shows that in high-transmission settings, substantially higher vaccination coverage (exceeding 80 % at an effectiveness of 70 %) is required to reduce the control reproduction number below unity, whereas in moderate-transmission contexts, coverage above 40 % may suffice. These quantitative thresholds provide actionable guidance for tailoring vaccination strategies to different epidemiological conditions. In particular, sustained vaccination strategies that achieve coverage above the threshold predicted by our model (approximately 80 %) can guarantee mpox eradication, even in situations with strong transmission rates. While real-world complexities such as heterogeneous risk groups and behavioral factors may affect outcomes, these findings shed light on potential quantitative thresholds and provide a foundation for more detailed, population-specific modeling of mpox interventions.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"11 1","pages":"Pages 29-46"},"PeriodicalIF":2.5,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of high-order time-delayed information on epidemic propagation in multiplex networks","authors":"Zehui Zhang ,&nbsp;Fang Wang ,&nbsp;Lilin Liu ,&nbsp;Lin Wang","doi":"10.1016/j.idm.2025.08.007","DOIUrl":"10.1016/j.idm.2025.08.007","url":null,"abstract":"<div><div>Traditional epidemic models often overlook disease incubation periods and high-order social interactions, limiting their ability to capture real-world transmission dynamics. To address these gaps, we develop a stochastic model that integrates both factors, investigating their combined effects on information diffusion and disease spread. Our framework consists of a two-layer network: an awareness layer, where disease-related information propagates through high-order delayed interactions, and an epidemic layer, where disease transmission follows an SIS model with incubation delays. Using a Markov chain approach, we derive outbreak thresholds and perform numerical simulations to assess the impact of delayed awareness adoption on epidemic outcomes. High-order delayed interactions accelerate information spread compared to traditional pairwise models. Interestingly, while incubation periods increase the risk of hidden transmission, they also provide a crucial window for awareness diffusion, potentially mitigating outbreaks. This dual role of incubation prolonging undetected transmission while enabling proactive awareness dissemination underscores the importance of synchronizing public health interventions with disease incubation phases.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"11 1","pages":"Pages 72-86"},"PeriodicalIF":2.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling, analysis and optimal control of Zika virus transmission dynamics based on sterile insect technique","authors":"Zongmin Yue,&nbsp;Yingpan Zhang,&nbsp;Xiangrui Ji","doi":"10.1016/j.idm.2025.08.005","DOIUrl":"10.1016/j.idm.2025.08.005","url":null,"abstract":"<div><div>The sterile insect technique (SIT) has emerged as a promising tool for suppressing mosquito-borne diseases. This study develops a Zika virus transmission model integrating SIT, emphasizing both mosquito-borne and environmental aquatic transmission pathways. Unlike eradication-focused approaches, the model targets population suppression through sterile male releases, allowing controlled coexistence of sterile and wild mosquitoes. Dynamical analysis reveals critical thresholds: when the sterile insect release rate <em>b</em> &lt; <em>b</em>_<em>p</em> and Allee effects are weak (<em>r</em> &lt; <em>r</em>_<em>p</em>), the system stabilizes at a coexistence equilibrium; exceeding these thresholds drives population collapse. While low wild mosquito densities may theoretically risk extinction, such levels are epidemiologically insufficient to trigger outbreaks, as viral resurgence requires a critical population density. The basic reproduction number <em>R</em>₀ was derived under coexistence conditions, demonstrating that <em>R</em>₀ &gt; 1 ensures viral persistence. Additionally, a multi-objective optimal control framework prioritizes cost minimization over infection reduction, offering resource-efficient strategies. Environmental transmission, a hallmark of Zika virus, accelerates early infection spread but is effectively mitigated by SIT. These results establish actionable thresholds (<em>b</em>_<em>p</em>, <em>r</em>_<em>p</em>) for balancing mosquito suppression and disease control, while providing theoretical insights applicable to dengue, malaria, and other arboviral diseases.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"11 1","pages":"Pages 47-71"},"PeriodicalIF":2.5,"publicationDate":"2025-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling the transmission dynamics and control strategies during the 2017 diphtheria outbreak in Jakarta, Indonesia","authors":"Bimandra A. Djaafara ,&nbsp;Verry Adrian ,&nbsp;Etrina Eriawati ,&nbsp;Iqbal R.F. Elyazar ,&nbsp;Raph L. Hamers ,&nbsp;J. Kevin Baird ,&nbsp;Guy E. Thwaites ,&nbsp;Hannah E. Clapham","doi":"10.1016/j.idm.2025.08.004","DOIUrl":"10.1016/j.idm.2025.08.004","url":null,"abstract":"<div><div>Diphtheria has resurged globally, including in Indonesia, despite widespread vaccination since the 1970s. Knowledge gaps persist in understanding contemporary transmission drivers and effective outbreak control, especially in densely populated areas like Jakarta. We analyzed the 2017 Jakarta outbreak data and developed a compartmental model incorporating estimates of population susceptibility and asymptomatic carriers. Key epidemiological parameters were estimated, and various control measures were simulated. Our study found overall diphtheria susceptibility at 12.9 % (95 % CrI: 8.6 %–19.0 %) and 28.0 % (95 % CrI: 20.5 %–36.0 %) in children under 5 under different modeling scenarios, which were below the 'herd immunity threshold'. We estimated asymptomatic carriers to be highly prevalent, substantially contributing to the reproduction number. The model indicated that contact tracing and treating suspected cases and their contacts were more effective in preventing new cases than catch-up vaccination alone. These findings provide valuable insights for future outbreak management strategies in similar settings.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"11 1","pages":"Pages 1-15"},"PeriodicalIF":2.5,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel approach to extract epidemiological information from waves in epidemic's profiles","authors":"Juan Campos ,&nbsp;Maria C.A. Leite","doi":"10.1016/j.idm.2025.08.003","DOIUrl":"10.1016/j.idm.2025.08.003","url":null,"abstract":"<div><div>In this paper, we develop a novel mathematical framework based on the Kermack- McKendrick model to extract epidemiological parameters from real temporal profiles consisting of waves. The approach's key feature is the ability to obtain all model parameters from the geometry of the wave of interest.</div><div>We propose three new quantities to measure the negative impact of the epidemic wave on a specific population, called <em>Fraction of endemicity</em>, <em>Severity</em>, and <em>Asymmetry</em>. These three measures, along with a refined definition of the <em>basic reproduction number</em>, provide crucial epidemiological information.</div><div>We demonstrate analytically that there is an equivalence among these quantities, and such equivalence gives a way of obtaining all parameters in the model since the <em>Asymmetry</em> of a real epidemic wave is easily computed. This is the heart of the novel methodology we introduce. The framework is suitable for public health decision support, as its implementation does not rely on complex mathematical tools.</div><div>We present several case studies to illustrate the simplicity of the framework as well as the distinct aspects of its implementation. In all examples investigated, the numeric solution obtained with the parameterized model shows good agreement with the available data.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"11 1","pages":"Pages 87-106"},"PeriodicalIF":2.5,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparing virus incubation time in SIRC models: Deterministic versus stochastic approaches","authors":"Abdelmalik Moujahid ,&nbsp;Fernando Vadillo","doi":"10.1016/j.idm.2025.08.002","DOIUrl":"10.1016/j.idm.2025.08.002","url":null,"abstract":"<div><div>Time delays are a fundamental feature in modeling stochastic epidemic systems, as they capture the incubation period and other physiological lags inherent in disease transmission. In this work, we investigate a stochastic SIRC (Susceptible-Infectious-Recovered-Cross-immune) epidemic model where the delay is incorporated into the transmission term to reflect the incubation period. To account for environmental variability, we examine two stochastic formulations: the classical approach, which adds independent white noise to each compartment, and a probabilistic, event-driven model in which stochasticity arises directly from transition probabilities.</div><div>A key focus of our study is the comparison between different delay formulations in the transmission term, specifically contrasting the standard approach—where the delay acts only on the infected compartment—with alternative formulations that distribute the delay across both susceptible and infected populations. Through systematic numerical simulations, we find that the choice of delay formulation strongly influences the timing and magnitude of the initial epidemic peak, while the long-term (asymptotic) behavior is more robust but remains sensitive to the underlying stochastic framework. The probabilistic model, in particular, offers a more faithful depiction of correlated fluctuations and extinction phenomena, capturing the biological complexity of epidemic processes more accurately than the classical approach. These results underscore the importance of both the delay representation and the stochastic modeling strategy in shaping the qualitative and quantitative features of epidemic dynamics.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"11 1","pages":"Pages 16-28"},"PeriodicalIF":2.5,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of human papillomavirus model with vaccination and individual heterogeneity","authors":"Jing An ,&nbsp;Wenhui Hao ,&nbsp;Huifen Guo ,&nbsp;Juping Zhang","doi":"10.1016/j.idm.2025.08.001","DOIUrl":"10.1016/j.idm.2025.08.001","url":null,"abstract":"<div><div>The dynamic system of HPV transmission with age subgroups, sexual and nonsexual transmission is established based on HPV vaccination. Firstly, the transmission threshold <em>R</em>₀ of the system is given. Local asymptotically stabilization of disease-free equilibrium when <em>R</em>₀ &lt; 1 is proved. It is proved that there is a positive equilibrium and disease persistence in the system when <em>R</em>₀ &gt; 1. Secondly, parameters estimation of the system is carried out based on the data from Chinese STD surveillance sites using the least square method. Finally, optimal control theory is applied to the system, the existence of optimal control is proved, and Pontryagin maximum principle is utilized to find optimal control strategy, and the spread of human papillomavirus in different age groups is predicted. The results show that for different age groups, vaccination of 16–45 years old is more beneficial to HPV control than vaccination of 9–15 years old, and that for different control costs, low-cost control is more advantageous.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1533-1574"},"PeriodicalIF":2.5,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144894793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contributions of the elderly to the transmission of HIV/AIDS in China","authors":"Shanshan Feng ,&nbsp;Wan-Ting Cheng ,&nbsp;Xing Li,&nbsp;Xiaofeng Luo","doi":"10.1016/j.idm.2025.07.013","DOIUrl":"10.1016/j.idm.2025.07.013","url":null,"abstract":"<div><div>In recent years, the number of HIV/AIDS cases shows an upward trend in China, particularly among the elderly, exerting severe effects on public health and social economy. This paper proposes an HIV/AIDS model incorporating sexual transmission and age structure to study the influence of the elderly on HIV/AIDS spread. Theoretically, the explicit expression for the basic reproduction number is obtained, the globally asymptotically stability of disease-free equilibrium and existence and uniqueness of boundary equilibrium are proved. Numerically, we verify the theoretical results. Based on HIV/AIDS data in Sichuan Province, China, four key parameters of the model are estimated. According to the estimated parameters, we find that homosexual transmission plays an important role in newly HIV/AIDS cases among the elderly in recent years. Sensitivity analysis also shows that homosexual transmission in the elderly has the greatest effect on the basic reproduction number. This study not only contributes to a comprehensive understanding of the dynamical spread process of HIV/AIDS but also provides valuable experience for other sexually transmitted diseases.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1488-1506"},"PeriodicalIF":2.5,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144828164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A statistical model for forecasting probabilistic epidemic bands for dengue cases in Brazil","authors":"Laís Picinini Freitas ,&nbsp;Danielle Andreza da Cruz Ferreira ,&nbsp;Raquel Martins Lana ,&nbsp;Daniel Cardoso Portela Câmara ,&nbsp;Tatiana P. Portella ,&nbsp;Marilia Sá Carvalho ,&nbsp;Ayrton Sena Gouveia ,&nbsp;Iasmim Ferreira de Almeida ,&nbsp;Eduardo Correa Araujo ,&nbsp;Luã Bida Vacaro ,&nbsp;Fabiana Ganem ,&nbsp;Oswaldo Gonçalves Cruz ,&nbsp;Flávio Codeço Coelho ,&nbsp;Claudia Torres Codeço ,&nbsp;Luiz Max Carvalho ,&nbsp;Leonardo Soares Bastos","doi":"10.1016/j.idm.2025.07.014","DOIUrl":"10.1016/j.idm.2025.07.014","url":null,"abstract":"<div><div>Dengue is a vector-borne disease and a major public health concern in Brazil. Its continuing and rising burden has led the Brazilian Ministry of Health to request for modelling efforts to aid in the preparedness and response to the disease. In this context, we propose a Bayesian forecasting model based on historical data to predict the number of cases 52 weeks ahead for the 118 health districts of Brazil. We leverage the predictions to build probabilistic epidemics bands to be used for dengue monitoring. We define four disjoint probabilistic bands (≤50% (50%, 75%] (75%, 90%], and <span><math><mo>&gt;</mo></math></span>90%), based on the percentiles of the predicted cases distribution and interpreted according to the historical number of cases and past occurrence probability (below the median, typical; moderately high, fairly typical; fairly high, atypical; exceptionally high, very atypical). We performed out-of-sample validation for 2022–2023 and 2023–2024 and forecasted 2024–2025. In the 2022–2023 and 2023–2024 seasons, the epidemic bands followed the observed cases’ curve shape, with a sharp increase after January and a decline after the peak around April. In 2022–2023, the observed number of cases (1,436,034) was slightly above the estimated 75% percentile (1,405,191), being classified as “fairly high, atypical”. Most health districts in South Brazil showed exceptionally high numbers of cases during this season. The situation worsened in 2023–2024 and the observed number of cases (6,454,020) was way above the 90% percentile (2,221,557), characterising an “exceptionally high, very atypical” season. For the 2024–2025 season, we estimated a median number of cases of 1,526,523 (maximum value for the “below the median, typical” probabilistic epidemic band. The maximum estimated values for the upper bands were 2,213,282 (moderately high, fairly typical) and 3,803,898 (fairly high, atypical) with the upper limits of the probabilistic epidemic bands of 1,452,359. Probabilistic epidemic bands serve as a valuable monitoring tool by enabling prospective comparisons between observed case curves and historical epidemic patterns, facilitating the assessment of ongoing outbreaks about past occurrences.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1479-1487"},"PeriodicalIF":2.5,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144813861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bayesian hierarchical modeling of Mpox in the African region (2022–2024): Addressing zero-inflation and spatial autocorrelation","authors":"Woldegebriel Assefa Woldegerima ,&nbsp;Chigozie Louisa J. Ugwu","doi":"10.1016/j.idm.2025.07.011","DOIUrl":"10.1016/j.idm.2025.07.011","url":null,"abstract":"<div><div>Mpox remains a signi_cant public health challenge in endemic regions of Africa. Understanding its spatial distribution and identifying key drivers in high-risk countries is critical for guiding e_ective interventions. This study applies a Zero-Inated Poisson (ZIP) model with spatial autocorrelation to estimate the adjusted relative risk (RR) of Mpox incidence across 24 African countries, strati_ed by Human Development Index (HDI) levels. The model accounts for overdispersion and excess zeros by incorporating spatial random e_ects and socio-environmental covariates, and was validated through model diagnostics and sensitivity analysis, demonstrating robustness of results. Spatial analysis revealed substantial heterogeneity in Mpox incidence, with elevated risk in the Democratic Republic of Congo (DRC), Nigeria, and Central African Republic (CAR) persisting after covariate adjustment (p &lt; 0:001). Higher HDI levels were inversely associated with Mpox risk, with HDI quintile Q4 (very high HDI) showing a signi _cant reduction (aRR = 0.431; 95 % CrI: 0.099{0.724). Protective factors in low-risk areas included increased life expectancy at birth (aRR = 0.768; 95 % CrI: 0.688{0.892), higher educational attainment (aRR = 0.774; 95 % CrI: 0.680{0.921), nonlinear increases in gross national income (GNI) per capita, and a greater density of skilled health workers (aRR = 0.788; 95 % CrI: 0.701{0.934). Conversely, higher urban density was associated with increased Mpox risk, underscoring the inuence of population clustering on transmission dynamics. Notably, statistically signi_cant elevated-risk areas persisted in endemic countries of Western and Central Africa after covariate adjustment (p &lt; 0:001). In contrast, previously undetected risk emerged in parts of Southern and Eastern Africa post-adjustment, revealing latent patterns obscured in the crude analysis (p &lt; 0:001). Exceedance probability maps identi_ed countries with P(RR &gt; 1) &gt; 0.9 as priority areas for intensi_ed surveillance and targeted intervention. These patterns were not fully explained by the included covariates, suggesting the inuence of unmeasured factors such as environmental and climate variability, zoonotic reservoirs, or human{animal interactions. Further research is needed to deepen understanding of Mpox epidemiology and support locally tailored interventions.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1575-1591"},"PeriodicalIF":2.5,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145044219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}