Mathematical modeling for estimating influenza vaccine efficacy: A case study of the Valencian Community, Spain.

Vaccine efficacy and its quantification is a crucial concept for the proper design of public health vaccination policies. In this work we proposed a mathematical model to estimate the efficacy of the influenza vaccine in a real-word scenario. In particular, our model is a SEIR-type epidemiological model, which distinguishes vaccinated and unvaccinated populations. Mathematically, its dynamics is governed by a nonlinear system of ordinary differential equations, where the non-linearity arises from the effective contacts between susceptible and infected individuals. Two key aspects of this study is that we use a vaccine distribution over time that is based on real data specific to the elderly people in the Valencian Community and the calibration process takes into account that over one influenza season a specific proportion of the population becomes infected with influenza. To consider the effectiveness of the vaccine, the model incorporates a parameter, the vaccine attenuation factor, which is related with the vaccine efficacy against the influenza virus. With this framework, in order to calibrate the model parameters and to obtain an influenza vaccine efficacy estimation, we considered the 2016-2017 influenza season in the Valencian Community, Spain, using the influenza reported cases of vaccinated and unvaccinated. In order to ensure the model identifiability, we choose to deterministically calibrate the parameters for different scenarios and we find the one with the minimum error in order to determine the vaccine efficacy. The calibration results suggest that the influenza vaccine developed for 2016-2017 influenza season has an efficacy of approximately 76.7%, and that the risk of becoming infected is five times higher for an unvaccinated individual in comparison with a vaccinated one. This estimation partially agrees with some previous studies related to the influenza vaccine. This study presents a new integrated mathematical approach to study the influenza vaccine efficacy and gives further insight into this important public health topic.

On the Elimination of Infections Related to Oncogenic Human Papillomavirus: An Approach Using a Computational Network Model.

Cervical cancer is the fourth most common malignancy in women worldwide, although it is preventable with prophylactic HPV vaccination. HPV transmission-dynamic models can predict the potential for the global elimination of cervical cancer. The random network model is a new approach that allows individuals to be followed, and to implement a given vaccination policy according to their clinical records. We developed an HPV transmission-dynamic model on a lifetime sexual partners network based on individual contacts, also accounting for the sexual behavior of men who have sex with men (MSM). We analyzed the decline in the prevalence of HPV infection in a scenario of 75% and 90% coverage for both sexes. An important herd immunity effect for men and women was observed in the heterosexual network, even with 75% coverage. However, HPV infections are persistent in the MSM population, with sustained circulation of the virus among unvaccinated individuals. Coverage around 75% of both sexes would be necessary to eliminate HPV-related conditions in women within five decades. Nevertheless, the variation in the decline in infection in the long term between a vaccination coverage of 75% and 90% is relatively small, suggesting that reaching coverage of around 70-75% in the heterosexual network may be enough to confer high protection. Nevertheless, HPV elimination may be achieved if men's coverage is strictly controlled. This accurate representation of HPV transmission demonstrates the need to maintain high HPV vaccination coverage, especially in men, for whom the cost-effectiveness of vaccination is questioned.

Impact of a Gender-Neutral HPV Vaccination Program in Men Who Have Sex with Men (MSM).

A major challenge in human papillomavirus (HPV) vaccine programs is the universal gender-neutral recommendation, as well as estimation of its long-term effect. The objective of this study is to predict the added benefit of male vaccination, especially in men who have sex with men (MSM), and to analyze the impact of the program on society. We propose a mathematical model of the HPV infection based on a network paradigm. Data from Spain allowed constructing the sexual network. HPV force of infection was taken from literature. Different scenarios using variable vaccine coverage in both males and females were studied. Strong herd immunity is shown in the heterosexual population, with an important decrease of HPV 6/11 infections both in men and in unvaccinated women with an only-women vaccination at 14 years of age. No impact of this program occurred in the infection incidence in MSM. This group would only benefit from a vaccination program that includes males. However, the impact at short term would be lower than in heterosexual men. The protection of MSM can only be achieved by direct vaccination of males. This may have important consequences for public health.

Analysis of Key Factors of a SARS-CoV-2 Vaccination Program: A Mathematical Modeling Approach.

The administration of vaccines against the coronavirus disease 2019 (COVID-19) started in early December of 2020. Currently, there are only a few approved vaccines, each with different efficacies and mechanisms of action. Moreover, vaccination programs in different regions may vary due to differences in implementation, for instance, simply the availability of the vaccine. In this article, we study the impact of the pace of vaccination and the intrinsic efficacy of the vaccine on prevalence, hospitalizations, and deaths related to the SARS-CoV-2 virus. Then we study different potential scenarios regarding the burden of the COVID-19 pandemic in the near future. We construct a compartmental mathematical model and use computational methodologies to study these different scenarios. Thus, we are able to identify some key factors to reach the aims of the vaccination programs. We use some metrics related to the outcomes of the COVID-19 pandemic in order to assess the impact of the efficacy of the vaccine and the pace of the vaccine inoculation. We found that both factors have a high impact on the outcomes. However, the rate of vaccine administration has a higher impact in reducing the burden of the COVID-19 pandemic. This result shows that health institutions need to focus on increasing the vaccine inoculation pace and create awareness in the population about the importance of COVID-19 vaccines.

Effect of the early use of antivirals on the COVID-19 pandemic. A computational network modeling approach.

It seems that we are far from controlling COVID-19 pandemics, and, consequently, returning to a fully normal life. Until an effective vaccine is found, safety measures as the use of face masks, social distancing, washing hands regularly, etc., have to be taken. Also, the use of appropriate antivirals in order to alleviate the symptoms, to control the severity of the illness and to prevent the transmission, could be a good option that we study in this work. In this paper, we propose a computational random network model to study the transmission dynamics of COVID-19 in Spain. Once the model has been calibrated and validated, we use it to simulate several scenarios where effective antivirals are available. The results show how the early use of antivirals may significantly reduce the incidence of COVID-19 and may avoid a new collapse of the health system.

Evaluating the optimal time for amikacin administration with respect to haemodialysis using an in vitro pharmacodynamic simulation against epidemic nosocomial OXA-48 producing Klebsiella pneumoniae ST405 strains.

OBJECTIVES: Bacterial viability and enrichment of resistance resulting from three different amikacin administration schedules with respect to haemodialysis (HD) were assessed against three OXA-48-producing Klebsiella pneumoniae isolated during an outbreak in a Spanish hospital. METHODS: A previously described two-compartment dynamic system was used. Three possible amikacin administration schedules were simulated: (i) haemodialysis immediately after amikacin infusion (pre-HD); (ii) infusion immediately after haemodialysis (post-HD); and (iii) infusion at 50% interdialytic period. Amikacin standard dose (SD) and double dose (DD) were simulated for each schedule. Values of Cmax/MIC, Cmax/MPC (mutant prevention concentration), AUC0-48h/MIC, AUC0-48h/MPC and %TMSW (percentage of time that the concentration was inside the mutant selection window) were determined with experimental data and were correlated with the area under the bacterial killing curve of the total population and the resistant subpopulation. RESULTS: Both with SD and DD, the pre-HD schedule resulted in increases at 48h in bacterial counts of the total population at the expense of enrichment of pre-existing resistant subpopulations from 12h onwards for all strains. The estimated %TMSW that prevented enrichment of resistant mutants was <61.5%. The AUC0-48h/MPC (with values of ≈40 being associated with countering of increases in resistant subpopulations) was better than the %TMSW as a predictive parameter. CONCLUSION: This study showed that the longest times concentrations were above the MPC (i.e. highest AUC0-48h/MPC, lowest %TMSW), the lowest enrichment of resistant subpopulations. This implies use of the highest possible amikacin dose (limited by toxicity) and post-HD as the best administration schedule.

Random Network Models to Predict the Long-Term Impact of HPV Vaccination on Genital Warts.

The Human papillomaviruses (HPV) vaccine induces a herd immunity effect in genital warts when a large number of the population is vaccinated. This aspect should be taken into account when devising new vaccine strategies, like vaccination at older ages or male vaccination. Therefore, it is important to develop mathematical models with good predictive capacities. We devised a sexual contact network that was calibrated to simulate the Spanish epidemiology of different HPV genotypes. Through this model, we simulated the scenario that occurred in Australia in 2007, where 12-13 year-old girls were vaccinated with a three-dose schedule of a vaccine containing genotypes 6 and 11, which protect against genital warts, and also a catch-up program in women up to 26 years of age. Vaccine coverage were 73 % in girls with three doses and with coverage rates decreasing with age until 52 % for 20-26 year-olds. A fast 59 % reduction in the genital warts diagnoses occurred in the model in the first years after the start of the program, similar to what was described in the literature.

Modelling influenza A(H1N1) 2009 epidemics using a random network in a distributed computing environment.

In this paper we propose the use of a random network model for simulating and understanding the epidemics of influenza A(H1N1). The proposed model is used to simulate the transmission process of influenza A(H1N1) in a community region of Venezuela using distributed computing in order to accomplish many realizations of the underlying random process. These large scale epidemic simulations have recently become an important application of high-performance computing. The network model proposed performs better than the traditional epidemic model based on ordinary differential equations since it adjusts better to the irregularity of the real world data. In addition, the network model allows the consideration of many possibilities regarding the spread of influenza at the population level. The results presented here show how well the SEIR model fits the data for the AH1N1 time series despite the irregularity of the data and returns parameter values that are in good agreement with the medical data regarding AH1N1 influenza virus. This versatile network model approach may be applied to the simulation of the transmission dynamics of several epidemics in human networks. In addition, the simulation can provide useful information for the understanding, prediction and control of the transmission of influenza A(H1N1) epidemics.

Hypersensitivity reactions to synthetic haemodialysis membranes.

Undergoing a haemodialysis (HD) session poses a certain risk of hypersensitivity adverse reactions as large quantities of blood are in contact with various synthetic materials. Hypersensitivity reactions to ethylene oxide and non-biocompatible membranes, such as cuprophane, have been described in HD. Cases of hypersensitivity with biocompatible membranes, such as polysulfone, and even polysulfone-polyvinylpyrrolidone, have also been reported. In this article we describe six cases of mostly early-stage hypersensitivity reactions to HD occurring in our department, characterised by malaise, desaturation, bronchospasm and arterial hypotension, with good response to the session’s temporary suspension and with reappearance in subsequent sessions that used a synthetic dialyser. No hypersensitivity reactions reappeared in successive observations when the sessions were carried out using a cellulose membrane.

Optimizing strategies for meningococcal C disease vaccination in Valencia (Spain).

BACKGROUND: Meningococcal C (MenC) conjugate vaccines have controlled invasive diseases associated with this serogroup in countries where they are included in National Immunization Programs and also in an extensive catch-up program involving subjects up to 20 years of age. Catch-up was important, not only because it prevented disease in adolescents and young adults at risk, but also because it decreased transmission of the bacteria, since it was in this age group where the organism was circulating. Our objective is to develop a new vaccination schedule to achieve maximum seroprotection in these groups. METHODS: A recent study has provided detailed age-structured information on the seroprotection levels against MenC in Valencia (Spain), where vaccination is routinely scheduled at 2 months and 6 months, with a booster dose at 18 months of age. A complementary catch-up campaign was also carried out in n for children from 12 months to 19 years of age. Statistical analyses of these data have provided an accurate picture on the evolution of seroprotection in the last few years. RESULTS: An agent-based model has been developed to study the future evolution of the seroprotection histogram. We have shown that the optimum strategy for achieving high protection levels in all infants, toddlers and adolescents is a change to a 2 months, 12 months and 12 years of age vaccination pattern. If the new schedule were implemented in January 2014, high-risk subjects between 15-19 years of age would have very low seroprotection for the next 6 years, thereby threatening the program. CONCLUSIONS: High protection levels and a low incidence of meningococcal C disease can be achieved in the future by means of a cost-free change in vaccination program. However, we recommend a new catch-up program simultaneous to the change in regular vaccination program.

epiModel: a system to build automatically systems of differential equations of compartmental type-epidemiological models.

In this paper we describe epiModel, a code developed in Mathematica that facilitates the building of systems of differential equations corresponding to type-epidemiological linear or quadratic models whose characteristics are defined in text files following an easy syntax. It includes the possibility of obtaining the equations of models involving age and/or sex groups.

An age structured model for obesity prevalence dynamics in populations

Objective. Modeling the correlation of the development of obesity in a population with age and time and predict the dynamics of the correlation of the development of obesity in a population with age and time under different scenarios in Valencia (Spain). Materials and methods. An age structured mathematical model is used to describe the future dynamics of obesity prevalence for different ages in human population with excess weight. Simulation of the model with parameters estimated using the Health Survey of the Region of Valencia 2000 (4.319 interviews) and Health Survey of the Region of Valencia 2005 (4.012 interviews). The model considers only overweight and obese populations since these subpopulations are the most relevant on obesity health concern. Results. The model allows predicting and studying the prevalence of obesity for each age. Results showed an increasing trend of obesity in the following years in well accordance with the trend observed in several countries. Conclusions. Based on the numerical simulations it is possible to conclude that the age structured mathematical model is suitable to forecast the obesity epidemic in each age group in different countries. Additionally, this type of models may be applied to study other characteristics of other populations such animal populations.

[Prokinetic agents as a cause of granulomatous interstitial nephritis]. / Procinéticos como causantes de nefritis intersticial granulomatosa.

Granulomatous interstitial nephritides are uncommon entities in routine clinical practice. These entities are usually associated with infectious diseases such as tuberculosis, or immune diseases, such as sarcoidosis, systemic lupus erythematosus or cryoglobulinemia. However, these diseases are most frequently associated with drug intake, especially antibiotics, proton pump inhibitors and nonsteroidal anti inflammatory drugs. An association with prokinetic agents has not previously been reported. We report the case of a 64-year-old woman who developed acute renal failure with this histological pattern after taking the motility promoter cinitapride without her physician's knowledge.