Prevalence of sexually transmitted infections in women of the Czech Republic Armed Forces: a cross-sectional pilot study.

INTRODUCTION: Sexually transmitted infections (STIs) are an everlasting health issue globally. The military environment is recognised as a high-risk setting. Human papillomavirus (HPV), Chlamydia trachomatis and Neisseria gonorrhoeae are the most frequent STIs worldwide. This prospective cross-sectional pilot study focuses on the prevalence of selected STIs in the female population of the Czech Republic's Armed Forces. METHODS: C. trachomatis, N. gonorrhoeae and HPV detection and genotyping were performed between August 2020 and December 2022 in 141 women. Participants were divided into three groups according to their military status-recruits (n=72), active soldiers (n=25) and control civilian group (n=44). Cervical smear tests were performed, and data on STI risk factors were obtained through a questionnaire. RESULTS: A significant difference in the HPV prevalence between recruits (64.5 %) and both active soldiers (46.4 %) and civilians (47.3 %) was found when adjusted for age (p=0.007 and p=0.01, respectively). Lower age of coitarche (median 16; p=0.005) and smaller agglomeration origin (p=0.013) were reported for military recruits. No difference was proven in other researched risk factors. Associations between HPV detection and the higher number of sexual partners (p=0.013), early coitarche (p=0.016) and single marital status (p=0.002) across the groups were observed. Not a single case of N. gonorrhoeae was detected in any of the 141 participants. The prevalence of C. trachomatis did not differ significantly between the three evaluated groups-recruits, control civilian group, and active soldiers (5.6%, 2.3%, 0%, respectively; p=0.567). CONCLUSIONS: This pilot study showed a significantly higher HPV prevalence in female military recruits compared with both active military and civilian women. Recruits reported earlier coitarche which is a strong STI risk factor. Further study is needed to expand on the findings of this pilot study and generate data to support adjustment of STI preventive measures within the Czech Republic Armed Forces.

New ESMO guidelines for clinical practice in metastatic colorectal cancer - commentary on changes in systemic therapy.

Commentary on the newly released European Society for Medical Oncology (ESMO) guidelines for the diagnosis and treatment of metastatic colorectal cancer (mCRC). After 6 years, individual chapters have been updated, from molecular tumor testing to diagnostic and treatment procedures to the implementation of newly registered medicinal products. The authors highlight the most important changes in the guidelines. Awareness of possible new treatments for mCRC is important to determine the treatment strategy for patients with mCRC. In this commentary, we focus primarily on the status of systemic treatment in unresectable disease.

Biomarkers as prognostic and predictive factors in patients with hepatocellular carcinoma undergoing radiological oncological interventions.

BACKGROUND: Hepatocellular carcinoma is the most common malignant liver tumor in adults and thermal ablation and transarterial embolization are important methods of therapy. Thermal ablation can be used in early stages. Methods based on the transarterial approach, especially transarterial chemoembolization, play an important role in intermediate stage diseases. The success of procedures depends not only on the biological nature and the size of the tumor, on the technical design of the procedure and on the patient's response to treatment, but also on the molecular changes associated with these procedures. In addition to classic predictive and prognostic factors including age, patient comorbidities, Child-Pugh score, tumor characteristics, presence of large surrounding vessels, and portal vein thrombosis, molecular prognostic and predictive factors (serum biomarkers) are often mentioned in studies. Currently, only a-fetoprotein is routinely used as a prognostic biomarker; however, there are studies referring to new serum biomarkers that can potentially help to classical markers and imaging methods to determine the cancer prognosis and predict the success of therapy. These biomarkers most often include g-glutamyltranspeptidase, des- g-carboxyprothrombin, some types of microRNAs, inflammatory and hypoxic substances, whose serum levels are changed by the intervention therapies. Evaluation of these molecules could lead to the optimization of the medical intervention (choice of therapy method, timing of treatment) or change the management of patient follow-up after interventions. Although several biomarkers have shown promising results, most serum biomarkers still require validation in phase III studies. PURPOSE: The aim of this work is to present a comprehensive overview of classical and molecular biomarkers that could potentially help in the prognostic stratification of patients and better predict the success and effect of radiological intervention methods.

Probabilistic predictions of SIS epidemics on networks based on population-level observations.

We predict the future course of ongoing susceptible-infected-susceptible (SIS) epidemics on regular, Erdos-Rényi and Barabási-Albert networks. It is known that the contact network influences the spread of an epidemic within a population. Therefore, observations of an epidemic, in this case at the population-level, contain information about the underlying network. This information, in turn, is useful for predicting the future course of an ongoing epidemic. To exploit this in a prediction framework, the exact high-dimensional stochastic model of an SIS epidemic on a network is approximated by a lower-dimensional surrogate model. The surrogate model is based on a birth-and-death process; the effect of the underlying network is described by a parametric model for the birth rates. We demonstrate empirically that the surrogate model captures the intrinsic stochasticity of the epidemic once it reaches a point from which it will not die out. Bayesian parameter inference allows for uncertainty about the model parameters and the class of the underlying network to be incorporated directly into probabilistic predictions. An evaluation of a number of scenarios shows that in most cases the resulting prediction intervals adequately quantify the prediction uncertainty. As long as the population-level data is available over a long-enough period, even if not sampled frequently, the model leads to excellent predictions where the underlying network is correctly identified and prediction uncertainty mainly reflects the intrinsic stochasticity of the spreading epidemic. For predictions inferred from shorter observational periods, uncertainty about parameters and network class dominate prediction uncertainty. The proposed method relies on minimal data at population-level, which is always likely to be available. This, combined with its numerical efficiency, makes the proposed method attractive to be used either as a standalone inference and prediction scheme or in conjunction with other inference and/or predictive models.

Network analysis of England's single parent household COVID-19 control policy impact: a proof-of-concept study.

Lockdowns have been a core infection control measure in many countries during the coronavirus disease 2019 (COVID-19) pandemic. In England's first lockdown, children of single parent households (SPHs) were permitted to move between parental homes. By the second lockdown, SPH support bubbles between households were also permitted, enabling larger within-household networks. We investigated the combined impact of these approaches on household transmission dynamics, to inform policymaking for control and support mechanisms in a respiratory pandemic context. This network modelling study applied percolation theory to a base model of SPHs constructed using population survey estimates of SPH family size. To explore putative impact, varying estimates were applied regarding extent of bubbling and proportion of different-parentage within SPHs (DSPHs) (in which children do not share both the same parents). Results indicate that the formation of giant components (in which COVID-19 household transmission accelerates) are more contingent on DSPHs than on formation of bubbles between SPHs, and that bubbling with another SPH will accelerate giant component formation where one or both are DSPHs. Public health guidance should include supportive measures that mitigate the increased transmission risk afforded by support bubbling among DSPHs. Future network, mathematical and epidemiological studies should examine both independent and combined impact of policies.

Incidence of fatigue associated with immune checkpoint inhibitors in patients with cancer: a meta-analysis.

BACKGROUND: Fatigue is one of the most common adverse effects associated with cancer immunotherapy using checkpoint inhibitors (CPIs). Because treatment-related fatigue also frequently occurs in patients treated with non-immunological therapies, our study aimed to compare the incidence of fatigue in CPI-treated patients with that associated with non-immune therapies in randomised trials. METHODS: PubMed and ClinicalTrials.gov were searched for phase III studies using a CPI alone or in combination with chemotherapy or non-immunologic targeted therapy in the experimental arm and control arm using inactive therapies such as placebo or observation, chemotherapy, or non-immunologic targeted therapy. Adverse events listed in the full texts as well as those available from clinicaltrials.gov were reviewed for all identified studies. RESULTS: A total of 60 studies involving 41 435 patients were included in the analysis. All-grade fatigue was reported in 30.4% of patients [95% confidence interval (CI) 29.9% to 31.0%] in the immunotherapy arms of the analysed studies. Using anti-programmed cell death protein 1 agents as reference, the odds ratio (OR) for fatigue was significantly higher both for anti-cytotoxic T lymphocyte-associated antigen 4 agents (OR 1.46, 95% CI 1.04-2.04) and the combination of anti-cytotoxic T lymphocyte-associated antigen 4 and anti-programmed cell death protein agents (OR 1.43, 95% CI 1.12-1.83). Fatigue was significantly less likely to occur in patients treated with CPI compared with patients receiving chemotherapy (OR 0.79, 95% CI 0.73-0.85), but significantly was more common in patients receiving the combination of CPI/chemotherapy compared with patients receiving chemotherapy alone (OR 1.12, 95% CI 1.03-1.22). CONCLUSIONS: Although immunotherapy using CPIs was associated with treatment-related fatigue, the occurrence of all-grade fatigue was significantly higher in patients treated with chemotherapy compared with patients receiving CPIs. The risk of fatigue was higher for CPI/chemotherapy combinations than for chemotherapy alone. These results suggest that although the effects of CPIs and chemotherapy are additive, chemotherapy was the dominant cause of treatment-related fatigue in the analysed trials.

The role of multidisciplinary team and molecular tumor board in the treatment of a patient with lung cancer.

Nowadays, selection of appropriate therapy in patients with lung cancer is based on comprehensive molecular characteristics of their tumors. On molecular level, lung cancer is one of the best described solid tumors. Currently, there are already methods in routine clinical practice that enable a relatively quick, accurate and cost-effective analysis of dozens of genes and thus make it possible to determine a complex molecular characteristic of a tumor. This creates new possibilities to tailor the treatment to the patients to achieve long-term survival with a good quality of life. New technologies bring more and more information and to transform it into the best clinical benefit for the patient can be challenging. This is a place for the multidisciplinary approach in the form of a molecular tumor board. Its role is to try to indicate appropriate therapy based on the identified genetic alteration. Today, dozens of targeted drugs are available and new treatment options are emerging even for genetic alterations, which until now seemed to be undruggable.

Immunotherapy in the treatment of non-small cell lung cancer.

Immunotherapy with check-point inhibitors has demonstrated remarkable therapeutic benefits in many oncological diagnoses, including non-small cell lung cancer (NSCLC). Based on the data from clinical trials, it has become an important part of the NSCLC treatment algorithm. Treatment with programmed cell death protein 1 / programmed death-ligand 1 inhibitors can be indicated in various ways: as monotherapy or combination of immunotherapy with cytotox--ic T-lymphocyte antigen 4 inhibitors or in combination with other treatment modalities - chemotherapy, antiangiogenic therapy and radiotherapy. Regarding new spectrum of immune-related side effects, which require quick diagnosis and treatment, there is great urge to identify immunotherapy predictive biomarkers.

Research Note: An overview on distribution of fowl adenoviruses.

Fowl adenoviruses (FAdV), detected during routine diagnostic investigations from 38 countries (5 continents) over a decade, were partially sequenced and grouped by phylogenetic analysis. The partial polymerase gene nucleotide sequences of the 365 fowl adenovirus isolates resulted in the following species distribution: 11% FAdV-A; 3% FAdV-B; 2% FAdV-C; 34% FAdV-D; and 50% FAdV-E. Noticeably, only 79 of the detected strains could be associated with adenovirus-specific pathologic conditions: 62 (79%) with inclusion body hepatitis; 9 (11%) with gizzard erosion; and 8 (10%) with hepatitis hydropericardium syndrome. The remainder of the FAdV strains was detected as concomitant infection from other disease conditions almost exclusively in boilers of 27 to 42 d of age: the majority of them was FAdV-E followed by FAdV-D, and to a lesser extent of FAdV-A, B, and C, the latter ones have not been associated with any of the established adenovirus-caused syndromes in our collection. The highest ratio of coinfections was observed for FAdV-B (62%), while it was about 30% for the rest of the FAdV species. The most frequent coinfection, in connection with all FAdV species, was with the avian infectious bronchitis virus. The presented database will serve as the basis for comparative whole genome and cross-neutralization analysis of selected FAdV isolates.

Network inference from population-level observation of epidemics.

Using the continuous-time susceptible-infected-susceptible (SIS) model on networks, we investigate the problem of inferring the class of the underlying network when epidemic data is only available at population-level (i.e., the number of infected individuals at a finite set of discrete times of a single realisation of the epidemic), the only information likely to be available in real world settings. To tackle this, epidemics on networks are approximated by a Birth-and-Death process which keeps track of the number of infected nodes at population level. The rates of this surrogate model encode both the structure of the underlying network and disease dynamics. We use extensive simulations over Regular, Erdos-Rényi and Barabási-Albert networks to build network class-specific priors for these rates. We then use Bayesian model selection to recover the most likely underlying network class, based only on a single realisation of the epidemic. We show that the proposed methodology yields good results on both synthetic and real-world networks.

Analysis of Blood Plasma MicroRNAs to Enable Identification of Patients with Pancreatic Ductal Adenocarcinoma Who Will Benefit from Surgical Resection

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is the most common malignancy of pancreas, characterized by extremely poor prognosis largely due to problem with early diagnosis and lack of progress in personalization of therapy. Of all available treatment strategies, radical surgical resection of the tumour in its early stage remains the only possibility how to reach long-term survival. However, even a technically perfect surgical resection may still not provide a survival benefit for all PDAC patients. Appropriate selection of patients for surgical resection is one the important medical needs in management of PDAC patients. MATERIAL AND METHODS: To this study we enrolled 24 PDAC patients who underwent surgical resection and preoperatively collected their blood plasma specimends. Patients were divided into to two prognostic groups according to their overall survival - 12 patients with poor prognosis (median overall survival 10 months) and 12 patients with good prognosis (median overall survival 25 months). Small RNA sequencing technology was applied to screen for microRNAs (miRNA) with differential levels between both PDAC patients group. cDNA libraries were prepared using QIAseq miRNA Library Kit (Qiaqen) and sequencing by NextSeq500 instrument (Illumina). RESULTS: When miRNA expression profiles of the PDAC patients from good and poor prognostic groups were compared, 61 miRNAs were identified to have significantly different plasma levels between the two groups (p < 0.05). A total of 21 miRNAs showed increased expression and 40 miRNAs showed decreased expression in a group of patients with poor prognosis compared to patients with good prognosis. CONCLUSION: This study demonstrated differences in miRNA expression profiles in preoperative plasma specimens of PDAC patients with short and long overall survival. Our observations indicate that after independent validations plasma miRNAs might become useful biomarkers for identification of PDAC patients having clinical benefit from surgical resection of the tumour. This work was supported by Czech Ministry of Health, grant No. 16-31314A. All rights reserved. The authors declare they have no potential confl icts of interest concerning drugs, products, or services used in the study. The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers. Submitted: 8. 3. 2019 Accepted: 9. 3. 2019.

Bursting endemic bubbles in an adaptive network.

The spread of an infectious disease is known to change people's behavior, which in turn affects the spread of disease. Adaptive network models that account for both epidemic and behavioral change have found oscillations, but in an extremely narrow region of the parameter space, which contrasts with intuition and available data. In this paper we propose a simple susceptible-infected-susceptible epidemic model on an adaptive network with time-delayed rewiring, and show that oscillatory solutions are now present in a wide region of the parameter space. Altering the transmission or rewiring rates reveals the presence of an endemic bubble-an enclosed region of the parameter space where oscillations are observed.

Pairwise approximation for SIR-type network epidemics with non-Markovian recovery.

We present the generalized mean-field and pairwise models for non-Markovian epidemics on networks with arbitrary recovery time distributions. First we consider a hyperbolic partial differential equation (PDE) system, where the population of infective nodes and links are structured by age since infection. We show that the PDE system can be reduced to a system of integro-differential equations, which is analysed analytically and numerically. We investigate the asymptotic behaviour of the generalized model and provide an implicit analytical expression involving the final epidemic size and pairwise reproduction number. As an illustration of the applicability of the general model, we recover known results for the exponentially distributed and fixed recovery time cases. For gamma- and uniformly distributed infectious periods, new pairwise models are derived. Theoretical findings are confirmed by comparing results from the new pairwise model and explicit stochastic network simulation. A major benefit of the generalized pairwise model lies in approximating the time evolution of the epidemic.

[Immunotherapy of Colorectal and Anal Carcinoma]. / Imunoterapie nádoru dolní cásti trávicí trubice.

BACKGROUND: The lower part of the digestive tract includes the large intestine, rectum and anus. Treatment algorithms of cancers in these localities have significant differences in both early and advanced stages. The vast majority of metastatic cases are incurable. A few years ago, it was generally accepted that gastrointestinal tumors are poorly immunogenic and modern immunotherapy would not work in gastrointestinal cancers. The breakthrough has become the recognition of the mismatch repair system (MMR) that affects the microsatellite instability (MSI) and its role in the development of colorectal carcinoma (CRC). Metastatic colorectal carcinoma (mCRC) with defect MMR (dMMR) and MSI-H, resp. is immunogenic and can be a target of modern imunotherapy directed on the PD1/PD-L1 axis. Such a treatment can improve prognosis and life quality od patients with mCRC MSI-H. Immunotherapy effectiveness was shown also in a subgroup of patients with a BRAF mutation where the effectiveness of existing systemic treatment is low. The proven predictive factor is dMMR/MSI-H. PD-1 expression does not have this significance. Results of clinical studies with nivolumab and pembrolizumab result in the inclusion of these drugs in mCRC treatment algorithms. Phase II study shows nivolumab effectiveness also in pretreated metastatic anal cancer. PURPOSE: An overview of basic information on the possibilities of immunotherapy in CRC and anal cancers.Key words: cancer immunotherapy - checkpoint inhibitors - colorectal cancer - anal cancer - nivolumab - pembrolizumab Supported by MH CZ - DRO (MMCI, 00209805) I declare that, in connection with the abovementioned contribution, which I am an author, I have a conflict of interest with the following companies: BMS, Roche, Merck, Amgem and Bayer. The author declares he has no potential conflicts of interest concerning drugs, products, or services used in the study. The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers.Submitted: 7. 9. 2017Accepted: 5. 11. 2017.

MicroRNAs as outcome predictors in patients with metastatic colorectal cancer treated with bevacizumab in combination with FOLFOX.

Bevacizumab is a humanized anti-vascular endothelial growth factor monoclonal antibody, used in combination with a oxaliplatin-based chemotherapy in the treatment of metastatic colorectal cancer (mCRC). The aim of the present study was to identify microRNA (miRNA)-based predictive biomarkers of therapy response in order to avoid unnecessary and costly therapy to non-responding patients. High-throughput miRNA microarray profiling (Affymetrix miRNA array) was performed on a discovery cohort of patients with mCRC. The discovery cohort was (n=20) divided into either responding (n=10) or non-responding (n=10) groups of bevacizumab/5-flourouracil, leucovorin, oxaliplatin (FOLFOX) treatment according to Response Evaluation Criteria in Solid Tumors criteria. Validation of candidate miRNAs was performed on an independent cohort of 41 patients with mCRC using quantitative reverse transcription polymerase chain reaction. Normalized data were subjected to receiver operating characteristic and Kaplan-Meier analyses. In total, 67 miRNAs were identified to be differentially expressed when miRNA expression was compared between responding and non-responding patients to bevacizumab/FOLFOX treatment (P<0.05). A total of 7 miRNAs were chosen for independent validation, which confirmed significantly higher expression of miR-92b-3p, miR-3156-5p, miR-10a-5p and miR-125a-5p (P<0.005) in tumor tissue of responding patients compared with non-reponding patients. Using the combination of miRNAs, the present study identified responders to the therapy with sensitivity 82% and specificity 64% (area under the curve = 0.8015). In conclusion, 4 predictive miRNAs associated with progression-free survival (PFS) were identified in patients with mCRC treated with bevacizumab/FOLFOX. Following further independent validations, detection of these miRNA may enable identification of patients with mCRC who may potentially benefit from the therapy.

Compact pairwise models for epidemics with multiple infectious stages on degree heterogeneous and clustered networks.

This paper presents a compact pairwise model describing the spread of multi-stage epidemics on networks. The multi-stage model corresponds to a gamma-distributed infectious period which interpolates between the classical Markovian models with exponentially distributed infectious period and epidemics with a constant infectious period. We show how the compact approach leads to a system of equations whose size is independent of the range of node degrees, thus significantly reducing the complexity of the model. Network clustering is incorporated into the model to provide a more accurate representation of realistic contact networks, and the accuracy of proposed closures is analysed for different levels of clustering and number of infection stages. Our results support recent findings that standard closure techniques are likely to perform better when the infectious period is constant.

Food additives: Sodium benzoate, potassium sorbate, azorubine, and tartrazine modify the expression of NFκB, GADD45α, and MAPK8 genes.

It has been reported that some of the food additives may cause sensitization, inflammation of tissues, and potentially risk factors in the development of several chronic diseases. Thus, we hypothesized that expressions of common inflammatory molecules - known to be involved in the development of various inflammatory conditions and cancers - are affected by these food additives. We investigated the effects of commonly used food preservatives and artificial food colorants based on the expressions of NFκB, GADD45α, and MAPK8 (JNK1) from the tissues of liver. RNA was isolated based on Trizol protocol and the activation levels were compared between the treated and the control groups. Tartrazine alone could elicit effects on the expressions of NFκB (p = 0.013) and MAPK8 (p = 0.022). Azorubine also resulted in apoptosis according to MAPK8 expression (p = 0.009). Preservatives were anti-apoptotic in high dose. Sodium benzoate (from low to high doses) dose-dependently silenced MAPK8 expression (p = 0.004 to p = 0.002). Addition of the two preservatives together elicited significantly greater expression of MAPK8 at half-fold dose (p = 0.002) and at fivefold dose (p = 0.008). This study suggests that some of the food preservatives and colorants can contribute to the activation of inflammatory pathways.

Influence of risk-taking health behaviours of adolescents on cervical cancer prevention: a Hungarian survey.

An anonymous questionnaire survey was conducted among the Hungarian adolescents to establish their use of tobacco, alcohol and drugs in relation to sexual behaviours, knowledge of human papillomavirus (HPV) and cervical cancer, and beliefs and attitudes towards screening and vaccination. Results indicated that adolescent risk-taking health behaviours correlate with risky sexual behaviours. As risk-taking behaviours do not correlate with a better awareness of the risk associated with HPV infection, it is of crucial importance that HPV/cervical cancer preventing educational programmes shall be sensitive to this 'vulnerable' population and draw the attention of these adolescents to their increased risk of sexually transmitted diseases and undesired pregnancies. Well-designed behavioural change interventions may be effective when in addition to providing adolescents (both men and women) with clear information about the implications of an HPV infection, they also aim to improve safer sex behaviours: consistent condom usage, limiting the number of sex partners, as well as encouraging regular participation in gynaecological screenings and uptake of the HPV vaccine. As this study population demonstrated positive attitudes towards the primary and secondary prevention of cervical cancer, the free HPV vaccination for the 12-13-year-old girls in Autumn 2014 will hopefully increase the currently low uptake of the vaccine in Hungary.

The significance of micro- and macrovascular biomarkers on cardiovascular outcome in chronic kidney disease: a prospective cohort study.

Measures of small and large artery dysfunction have not been investigated in a single cohort for the prediction of cardiovascular (CV) events in patients with nondialysed (ND) chronic kidney disease (CKD). This prospective cohort study aimed to determine whether central pulse wave velocity (cPWV), central pulse pressure (CPP) or microvascular post-occlusive reactive hyperaemia area (PORHHA) independently predict CV events and mortality in CKD-ND. A total of 94 stage 1-5 CKD-ND (65.3±13.1 years; estimated glomerular filtration rate 35.3 (22.8-49.4) ml min(-1) per 1.73 m(2)) patients were followed-up for a median of 52 (36-65) months and had baseline cPWV and CPP measured by applanation tonometry and PORHHA by laser Doppler flowmetry. Multiple failure time Cox regression models were used to determine the predictive role of vascular parameters on CV mortality and events. Based on multiple linear regressions, baseline age, diabetes, CV disease, and systolic blood pressure (SBP) were independently related to cPWV (R(2)=0.3), SBP and PORHHA to CPP (R(2)=0.45), whereas CPP was the only parameter independently related to PORHHA (R(2)=0.16, all P<0.05). During follow-up, 41 CV events occurred (14 CV deaths). In univariate analyses, cPWV (1.07 (1.02-1.13) per m s(-1)), CPP (1.04 (1.01-1.07) per mm Hg) and lnPORHHA (0.70 (0.58-0.85) per ln(PU × s)) were all related to the outcome. Baseline diabetes (HR 3.07 (1.65-5.68)), lnFGF23 (fibroblast growth factor-23; 1.86 (1.13-3.06) per RU ml(-1)) and CPP (1.04 (1.01-1.07) per mm Hg) were independent predictors of CV events. The impaired pulsatile component of large arteries (CPP) independently of other vascular markers (cPWV, PORHHA) predicted CV outcomes in CKD-ND. CPP may integrate the information provided by cPWV and PORHHA.

Dynamics of Multi-stage Infections on Networks.

This paper investigates the dynamics of infectious diseases with a non-exponentially distributed infectious period. This is achieved by considering a multi-stage infection model on networks. Using pairwise approximation with a standard closure, a number of important characteristics of disease dynamics are derived analytically, including the final size of an epidemic and a threshold for epidemic outbreaks, and it is shown how these quantities depend on disease characteristics, as well as the number of disease stages. Stochastic simulations of dynamics on networks are performed and compared to output of pairwise models for several realistic examples of infectious diseases to illustrate the role played by the number of stages in the disease dynamics. These results show that a higher number of disease stages results in faster epidemic outbreaks with a higher peak prevalence and a larger final size of the epidemic. The agreement between the pairwise and simulation models is excellent in the cases we consider.