Ashvini Kumar Yadav, Kirti Vishwakarma, Divya Namdeo
et al.
Introduction:
Hepatitis B virus (HBV) infection remains a major public health issue in India, with a significant burden of undiagnosed asymptomatic carriers. Identifying such individuals is essential to achieve the World Health Organization’s goal of HBV elimination by 2030.
Methods:
The objectives of this study were to determine the prevalence of hepatitis B surface antigen (HBsAg) and HBV viral load among asymptomatic healthcare workers and patients undergoing elective surgeries and to evaluate the need for universal HBV screening in such populations. This was a hospital-based cross-sectional study conducted at a tertiary care center in Central India. Blood samples from 13,840 asymptomatic individuals were tested for HBsAg, and positives in HBsAg were further tested for hepatitis B e antigen (HBeAg) by enzyme-linked immunosorbent assay. HBV DNA quantification was performed using a real-time polymerase chain reaction-based method on selected samples.
Results:
Out of 13,840 individuals screened, 355 (2.57%) tested positive for HBsAg. Among these, 37 (10.42%) were HBeAg-positive, all of whom had HBV DNA levels > 2000 IU/ml. Notably, 48.64% of HBeAg-negative individuals also had significant viral loads. The average age of HBsAg-positive individuals was higher than negatives (42.38 ± 16.58 vs. 37.52 ± 18.92; P = 0.008). Males were more frequently infected (P < 0.001).
Conclusion:
The study highlights a significant proportion of asymptomatic individuals with elevated HBV viral loads, particularly among HBeAg-negative cases. These findings support the implementation of universal HBV screening in preoperative and occupational health settings as a vital strategy for early detection, treatment initiation, and achieving national and global HBV elimination targets.
Márcia Pinto Barros de Oliveira, Luisa Frota Chebabo, Monique do Vale da Silveira
et al.
Introduction and objective: Activities developed by multiprofessional teams in infection control are fundamental to ensure safety, quality, prevention, or reduction of harm. A relevant question is how to demonstrate to administrative managers that these actions also result in resource savings. To highlight the financial result of SCIRAS, specialized counseling in antimicrobial use (AEUA) was chosen, since rational use of these medications is essential for safety and quality of care. In contrast, inappropriate use leads to serious consequences, such as increased bacterial resistance, adverse effects for patients, and avoidable cost. This work seeks to estimate, in values, the savings achieved by AEUA. Methods: Study conducted between Oct/24 and Jun/25, in a private healthcare institution with 228 beds, 60 ICU beds, located in the south zone of Rio de Janeiro (RJ). Patients using antimicrobials are identified through a report extracted from medical prescriptions. AEUA is carried out in the institution’s sectors, on business days, by 02 infectious disease physicians from SCIRAS, who perform in-person visits and classify interventions performed in a specific form. Antimicrobials discontinued, reductions in treatment duration, or spectrum reduction resulting from AEUA were considered for analysis. When the medication was replaced with another of narrower spectrum, the difference was counted. When the drug was discontinued or its duration reduced, the initially proposed schedule by the care team was considered for calculating savings. Daily dosage and the value of each drug did not change during the study, despite price adjustments occurring for some medications. Results: Approximately 50% of evaluated patients benefited from prescription adjustments, diagnostic assistance, or follow-up performed through AEUA. Among interventions, 25% of antimicrobials were discontinued or had spectrum or duration reduced, leading to savings of R$ 619,408.65 over the nine months of the study. Conclusion: AEUA provided significant savings for the institution. The reported value is still underestimated, since not all interventions were considered in the calculation. Measuring this savings represents an objective way to demonstrate to administrative managers one of the positive impacts of SCIRAS activities.
Anders Kjellman,1 Min Kim,2 Per-Olof Lundgren,1 Tomas Thiel,1 Anna Thor,1 Helena Thulin,1 David Hägg,3 Vera Ehrenstein4 1Urology Department, Karolinska University Hospital and Karolinska Institutet, Stockholm, Sweden; 2Center for Observational Research, Amgen Inc, Thousand Oaks, CA, USA; 3Department of Medicine Solna, Centre for Pharmacoepidemiology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden; 4Department of Clinical Epidemiology, Department of Clinical Medicine, Center for Population Medicine, Aarhus University and Aarhus University Hospital, Aarhus, DenmarkCorrespondence: Vera Ehrenstein, Department of Clinical Epidemiology, Department of Clinical Medicine, Center for Population Medicine, Aarhus University and Aarhus University Hospital, Olof Palmes Allé 43-45, Aarhus, 8200 N, Denmark, Email ve@clin.au.dkPurpose: To estimate the positive predictive value (PPV) of case ascertainment algorithm for hypocalcemia leading to hospitalization or emergency visit in the Swedish National Patient Register among women with postmenopausal osteoporosis (PMO) treated with antiresorptive agents. This was a regulator-requested validation study to support a multidatabase postauthorisation safety study (PASS) of antiresorptive treatment.Methods: The Swedish part of the PASS was based on data from Swedish population registries. Potential cases of hypocalcemia, identified among women with PMO, included in the PASS in 2010– 2016, were defined based on non-specific International Classification of Diseases, 10th Revision (ICD-10) codes for disorders of calcium metabolism at hospitalization or emergency visit, as recorded in the Swedish Patient Register through 2018. Presence of hypocalcemia among the potential cases was confirmed using a standardized abstraction of medical charts. PPV was estimated as a measure of validity.Results: There were 164 potential cases of hypocalcemia, of which 121 had medical charts with sufficient information available. Among these 121 cases, 19 had confirmed hypocalcemia, PPV 15.7% (95% confidence interval: 10.0 to 23.0).Conclusion: The case-defining algorithm based on the non-specific ICD-10 codes had a low PPV. Reliance on the algorithm may bias results of epidemiologic studies relying it. Limitations include non-response and low precision of some PPV estimates.Keywords: diagnosis code, epidemiology, hypocalcemia, validity
Zhuangzhuang Jia, Hyuk Park, Gökçe Dayanıklı
et al.
Infectious diseases pose major public health challenges to society, highlighting the importance of designing effective policies to reduce economic loss and mortality. In this paper, we propose a framework for sequential decision-making under uncertainty to design fairness-aware disease mitigation policies that incorporate various measures of unfairness. Specifically, our approach learns equitable vaccination and lockdown strategies based on a stochastic multi-group SIR model. To address the challenges of solving the resulting sequential decision-making problem, we adopt the path integral control algorithm as an efficient solution scheme. Through a case study, we demonstrate that our approach effectively improves fairness compared to conventional methods and provides valuable insights for policymakers.
Diego S. Silva, Sara Y. Del Valle, Michael J. Plank
Mathematical models of infectious diseases are frequently used as a tool to support public health policy and decisions around implementation of interventions such as school closures. However, most publications on policy-relevant modelling lack an ethical framework and do not explicitly consider the ethical implications of the work. This creates a risk that unintended consequences of interventions are overlooked or that models are used to justify decisions that are inconsistent with public health ethics. In this article, we focus on the case study of school closures as a commonly modelled intervention against pandemic influenza, COVID-19, and other infectious disease threats. We briefly review some of the key concepts in public health ethics and describe approaches to modelling the effects of school closures. We then identify a series of ethical considerations involved in modelling school closures. These include accounting for population heterogeneity and inequalities; including a diversity of viewpoints and expertise in model design; considering the distribution of benefits and harms; and model transparency and contextualisation. We conclude with some recommendations to ensure that policy-relevant modelling is consistent with some key ethics values.
Infectious diseases continue to pose a serious threat to public health, underscoring the urgent need for effective computational approaches to screen novel anti-infective agents. Oligopeptides have emerged as promising candidates in antimicrobial research due to their structural simplicity, high bioavailability, and low susceptibility to resistance. Despite their potential, computational models specifically designed to predict associations between oligopeptides and infectious diseases remain scarce. This study introduces a prompt-guided graph-based contrastive learning framework (PGCLODA) to uncover potential associations. A tripartite graph is constructed with oligopeptides, microbes, and diseases as nodes, incorporating both structural and semantic information. To preserve critical regions during contrastive learning, a prompt-guided graph augmentation strategy is employed to generate meaningful paired views. A dual encoder architecture, integrating Graph Convolutional Network (GCN) and Transformer, is used to jointly capture local and global features. The fused embeddings are subsequently input into a multilayer perceptron (MLP) classifier for final prediction. Experimental results on a benchmark dataset indicate that PGCLODA consistently outperforms state-of-the-art models in AUROC, AUPRC, and accuracy. Ablation and hyperparameter studies confirm the contribution of each module. Case studies further validate the generalization ability of PGCLODA and its potential to uncover novel, biologically relevant associations. These findings offer valuable insights for mechanism-driven discovery and oligopeptide-based drug development. The source code of PGCLODA is available online at https://github.com/jjnlcode/PGCLODA.
Giovanna Deiana, Antonella Arghittu, Marco Dettori
et al.
When we take into account how the boundaries between human, animal, and environmental health are inextricably linked and increasingly intertwined, it comes as no surprise that the One Health approach has assumed an unprecedented level of importance over the past decade [...]
Nicla Gentile, Fernando Carrasquer, Ana Marco-Fuertes
et al.
ABSTRACT: The concept of backyard poultry historically encompassed “food-producing animals.” Nevertheless, a recent shift in livestock production paradigms within developed countries is evident, as backyard poultry owners now raise their birds for purposes beyond self-consumption, raising animals in a familiar way, and fostering emotional bonds with them. Because backyard animals are frequently privately owned, and the resulting products are typically not marketed, very little information is available about the demographic profile of backyard owners and information on flocks’ characteristics, husbandry, and welfare. Thus, this review aims to clarify the characteristics of backyard poultry, highlighting the prevalent infectious diseases and the zoonotic risk to which farmers are exposed. According to the FAO, there are different types of poultry production systems: intensive, sub-intensive, and extensive. The system conditions, requirements, and the resulting performance differ extensively due to the type of breed, feeding practices, prevalence of disease, prevention and control of diseases, flock management, and the interactions among all these factors. The presence and transmission of infectious diseases in avian species is a problem that affects both the animals themselves and public health. Bacterial (Escherichia coli, Salmonella, Campylobacter, and Mycoplasma), parasitic (helminths, louses, and mites), and viral (Avian influenza, Newcastle, Marek, Infectious Bronchitis, Gumboro, Infectious Laringotracheitis, and Fowlpox) are the most important pathogens involved in backyard poultry health. In addition, Avian influenza, Salmonella, Campylobacter, and E. coli, could be a risk for backyard farmers and/or backyard-derived products consumers. Thus, proper biosecurity implementation measures are mandatory to control them. While the principles and practices of on-farm biosecurity may be well-versed among commercial farmers, hobbyists, and backyard farmers might not be familiar with the necessary steps to protect their flocks from infectious diseases and curb their transmission. This sector represents the fourth category of poultry farming, characterized by the lowest biosecurity standards. Consequently, it is imperative to address the legal status of backyard poultry, educate owners about biosecurity measures, and promote proper veterinary care and disease control.
Abstract Background The COVID-19 pandemic has had a significant impact on healthcare systems worldwide, leading to a weakening of surveillance for parasitic diseases during quarantine measures in many countries. In 2022, this effect was observed in the Republic of Kazakhstan, where a significant increase in parasitic diseases was reported. Methods The prediction of parasitic incidence was carried out based on official statistical data on the incidence of the population of Kazakhstan from 2011 to 2022. Exponential smoothing was used for incidence forecasting with 95% CI. Forecasts were carried out for echinococcosis, opisthorchiasis, ascariasis, enterobiasis, and giardiasis. Results In 2022 there was a significant increase in parasitic diseases among the population of the Republic of Kazakhstan, with a total of 9,026 cases registered. Most cases were helminthiasis, accounting for 85% of all cases, while intestinal protozoal invasions accounted for 15%. The most prevalent parasitic diseases were enterobiasis, with an incidence rate of 24.9 per 100,000, followed by giardiasis with a rate of 6.8 per 100,000. Echinococcosis had an incidence rate of 3.9 per 100,000, while ascariasis and opisthorchiasis had rates of 6.4 and 2.5 per 100,000, respectively (Figure 1). However, the expected incidence rates for parasitic diseases in 2023-2025 are projected to be lower than the long-term average incidence. There will be a significant decrease in the incidence rate of opisthorchiasis and enterobiasis. In 2023, the incidence rate of opisthorchiasis is expected to be 1.45 per 100,000, while the incidence rate of enterobiasis will be 12.1 per 100,000. This trend is projected to continue in 2024-2025 (Table 1). Conclusion As negative trends in parasitic diseases are observed, it is crucial to remain vigilant and take proactive measures to prevent the spread of these diseases. Following the results, additional measures were taken in the Republic of Kazakhstan to prevent echinococcosis and opisthorchiasis, such as strengthening the interdepartmental commission and enhancing epidemiological surveillance. It is essential to continue monitoring the situation and take proactive measures to prevent the spread of parasitic diseases. Disclosures All Authors: No reported disclosures
Lucille Rudin, Michael M. Bornstein, Viktoriya Shyp
ABSTRACTObjectives To evaluate the effect and mechanism of action of the flavonoid phloretin on the growth and sucrose-dependent biofilm formation of Streptococcus mutans.Methods Minimum inhibitory concentration, viability, and biofilm susceptibility assays were conducted to assess antimicrobial and antibiofilm effect of phloretin. Biofilm composition and structure were analysed with scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM). Water-soluble (WSG) and water-insoluble glucan (WIG) were determined using anthrone method. Lactic acid measurements and acid tolerance assay were performed to assess acidogenicity and aciduricity. Reverse transcription quantitative PCR (RT-qPCR) was used to measure the expression of virulence genes essential for surface attachment, biofilm formation, and quorum sensing.Results Phloretin inhibited S. mutans growth and viability in a dose-dependent manner. Furthermore, it reduced gtfB and gtfC gene expression, correlating with the reduction of extracellular polysaccharides (EPS)/bacteria and WIG/WSG ratio. Inhibition of comED and luxS gene expression, involved in stress tolerance, was associated with compromised acidogenicity and aciduricity of S. mutans.Conclusions Phloretin exhibits antibacterial properties against S. mutans, modulates acid production and tolerance, and reduces biofilm formation.Clinical significance Phloretin is a promising natural compound with pronounced inhibitory effect on key virulence factors of the cariogenic pathogen, S. mutans.
Abstract Background Surgical site infection is an infection occurring within 30 days after surgery. It is recently reported that evidence-based information on the specific time when the majority of surgical site infections would develop is a key to early detect the infection as well as to preventing and early intervene against their pressing and fatal complications. Therefore, the current study aimed to determine the incidence, predictors, and time to development of surgical site infection among general surgery patients at specialized hospitals in the Amhara region. Method An institution-based prospective follow-up study was conducted. The two-stage cluster sampling procedure was used. A systematic sampling technique with a K interval of 2 was applied to prospectively recruit 454 surgical patients. Patients were followed up for 30 days. Data were collected using Epicollect5 v 3.0.5 software. Post-discharge follow-up and diagnosis were done by telephone call follow-up. Data were analyzed using STATA™ version 14.0. Kaplan–Meier curve was used to estimate survival time. Cox proportional regression model was used to determine significant predictors. Variables with a P-value less than 0.05 in the multiple Cox regression models were independent predictors. Result The incidence density was 17.59 per 1000 person-day-observation. The incidence of post-discharge Surgical site infection was 70.3%. The majority of surgical site infections were discovered after discharge between postoperative days 9 to 16. Being male (AHR: 1.98, 95% CI: 1.201 – 3.277, diabetes Mellitus (AHR: 1.819, 95% CI: 1.097 – 3.016), surgical history (AHR: 2.078, 95% CI: 1.345, 3.211), early antimicrobial prophylaxis (AHR: 2.60, 95% CI: 1.676, 4.039), American Society of Anesthesiologists score ≥ III AHR: 6.710, 95% CI: 4.108, 10.960), duration of the surgery (AHR: 1.035 95% CI: 1.001, 1.070), Age (AHR: 1.022 95% CI: 1.000, 1.043), and the number of professionals in the Operation Room (AHR: 1.085 95% CI: 1.037, 1.134) were found to be the predictors of time to development of Surgical site infection. Conclusion The incidence of surgical site infection was higher than the acceptable international range. The majority of infections were detected after hospital discharge between 9 to 16 postoperative days. The main predictors of Surgical site infection were Age, Sex, Diabetes Mellitus, previous surgical history, the timing of Antimicrobial prophylaxis, American Society of Anesthesiologists score, pre-operative hospital stay, duration of surgery, and the number of professionals in the operation room. Hence, hospitals should give great emphasis on pre-operative preparation, post-discharge surveillance, modifiable predictors, and high-risk patients, as they found in this study.
When an infectious disease propagates throughout society, the incidence function may rise at first due to an increase in pathogenicity and then decrease due to inhibitory effects until it reaches saturation. Effective vaccination and treatment are very helpful for controlling the effects of such infectious diseases. To analyze the impacts of these diseases, we proposed a new compartmental model with a generalized non-linear incidence function, vaccination function, and treatment function, along with time delays in the respective functions, which show how its monotonic features influence the stability of the model. Fundamental properties of a model, such as positivity, boundedness, and the existence of equilibria, are examined in this work. The basic reproduction number has been computed, and correlative studies for local stability in view of the basic reproduction number have been examined at the disease-free and endemic equilibrium points. A delay-independent global stability result has been established, and to be more precise, we explicitly derived the result on global stability by restricting delay parameters within a very specific range. Furthermore, numerical simulations and some examples based on COVID-19 real-time data are pointed out to emphasize the significance of how the disease's dynamical behavior is characterized by various functions for controlling the spread of disease in a population and to justify the mathematical conclusions.
What is the long term dynamics of the Covid-19 pandemic? How will it end? Here we constructed an infectious disease model with testing and analyzed the existence and stability of its endemic states. For a large parameter set, including those relevant to the SARS-CoV-2 virus, we demonstrated the existence of one endemic equilibrium without testing and one endemic equilibrium with testing and proved their local and global stabilities for some cases. Our results suggest that the pandemic is to end with a testing-less endemic state through a novel and surprising mechanism called stochastic trapping.
Luciane Beatriz Kern, Thaís Raupp Azevedo, Ivaine Tais Sauthier Sartor
et al.
Introdução/Objetivo: Os fatores associados ao risco de hospitalização por COVID19 não são completamente conhecidos. O objetivo deste estudo foi descrever o risco de hospitalização dos participantes ambulatoriais com diagnóstico exclusivo para rinovírus, SARS-CoV-2 e codetecção entre esses dois agentes, durante a pandemia no sul do Brasil. Métodos: Participantes ambulatoriais (> 18 anos) com sinais agudos de tosse, febre ou dor de garganta foram recrutados prospectivamente nas tendas de atendimento do Hospital Moinhos de Vento e Hospital Restinga e Extremo Sul, entre maio e novembro de 2020, e foram acompanhados por 28 dias através de entrevistas telefônicas. Para a detecção de SARS-CoV-2 bem como para o painel respiratório, foi utilizada a técnica de RT-PCR. Para detecção de SARS-CoV-2 foi utilizado kit TaqManTM 2019-nCoV Assay Kit v1 (genes S, N e ORF1ab) a partir de swabs orofaríngeo e nasofaríngeo bilateral. Em coleta de outro swab nasofaríngeo foi realizado painel respiratório para detecção de: Bordetella pertussis; Chlamydophila pneumoniae; Mycoplasma pneumoniae; adenovírus; bocavírus; coronavírus tipos HKU1, 229E, NL63 e OC43; vírus influenza A tipos H1 e H3; vírus influenza B; enterovírus humano; metapneumovírus humano; vírus parainfluenza tipos 1, 2 e 3; RSV tipos A e B; e rinovírus). Todas as amostras foram analisadas no Laboratório de Biologia Molecular do Hospital Moinhos de Vento. Resultados: Foram recrutados 609 participantes, com idade mediana de 36 anos, sendo a maioria mulheres (63,2%). 282 (46,4%) participantes tiveram detectado apenas rinovírus, seguido por 234 (38,4%) com SARS-CoV-2 exclusivamente. A codetecção entre estes dois agentes ocorreu em 93 (15,3%) dos 608 participantes. Deste total, 26 (4,3%) participantes necessitaram hospitalização após a busca por atendimento ambulatorial. Participantes com codetecção viral apresentaram maior proporção de hospitalização quando comparados aos participantes com SARS-CoV-2 e rinovírus detectados como agentes únicos (9,7% (9/93) vs 6,8% (16/234) vs 0,4% (1/282), p < 0.001). Entretanto, quando comparadas as proporções de coinfecção com SARS-CoV-2 (como agente único), a diferença não é significativa (9,7% (9/93) vs 6,8% (16/234), p = 0.373). Conclusão: O rinovírus foi o principal patógeno detectado em adultos, e apesar da alta prevalência não foi associado ao aumento na hospitalização, sendo o maior risco atribuído à detecção de SARS-CoV-2 nessa população.
Hemophagocytic lymphohistiocytosis (HLH) is an uncommon hyperinflammatory syndrome characterized by excessive activation of macrophages and T-cells with high cytokines levels, causing multiorgan dysfunction.HLH has been associated with variable infectious etiologies, such as tuberculosis(TB). TB-associated HLH (TB-HLH) is a rare condition, but it is fatal if not treated. The diagnosis of TB-HLH is challenging and might be missed if not highly considered. The classic manifestations of HLH include pancytopenia, organomegaly, lymphadenopathy, and coagulopathy. Herein, we present a young immunocompetent adult diagnosed with disseminated TB complicated by HLH. Our patient responded well to the combination of antituberculosis therapy(ATT), corticosteroid, and intravenous immunoglobulin(IVIG). This case highlights the importance of considering this fatal complication in TB patients.
Emmanuelle A. Dankwa, Andrew F. Brouwer, Christl A. Donnelly
If model identifiability is not confirmed, inferences from infectious disease transmission models may not be reliable, so they might lead to misleading recommendations. Structural identifiability analysis characterizes whether it is possible to obtain unique solutions for all unknown model parameters, given the model structure. In this work, we studied the structural identifiability of some typical deterministic compartmental models for infectious disease transmission, focusing on the influence of the data type considered as model output on the identifiability of unknown model parameters, including initial conditions. We defined 26 model versions, each having a unique combination of underlying compartmental structure and data type(s) considered as model output(s). Four compartmental model structures and three common data types in disease surveillance (incidence, prevalence and detected vector counts) were studied. The structural identifiability of some parameters varied depending on the type of model output. In general, models with multiple data types as outputs had more structurally identifiable parameters, than did models with a single data type as output. This study highlights the importance of a careful consideration of data types as an integral part of the inference process with compartmental infectious disease transmission models.
This paper focus on the diffusive eco-epidemiological prey-predator model with infectious diseases in prey, and with the homogeneous Neumann and Dirichlet boundary conditions, respectively. When boundary conditions are homogeneous Neumann boundary conditions, we give a complete conclusion about the stabilities of nonnegative constant equilibrium solutions. The results show that such a problem has neither periodic solutions nor Turing patterns. When boundary conditions are homogeneous Dirichlet boundary conditions, we first establish the necessary and sufficient conditions for the existence of positive equilibrium solutions, and prove that the positive equilibrium solution is unique when it exists. Then we study the global asymptotic stabilities of trivial and semi-trivial nonnegative equilibrium solutions.
Automatic infectious disease classification from images can facilitate needed medical diagnoses. Such an approach can identify diseases, like tuberculosis, which remain under-diagnosed due to resource constraints and also novel and emerging diseases, like monkeypox, which clinicians have little experience or acumen in diagnosing. Avoiding missed or delayed diagnoses would prevent further transmission and improve clinical outcomes. In order to understand and trust neural network predictions, analysis of learned representations is necessary. In this work, we argue that automatic discovery of concepts, i.e., human interpretable attributes, allows for a deep understanding of learned information in medical image analysis tasks, generalizing beyond the training labels or protocols. We provide an overview of existing concept discovery approaches in medical image and computer vision communities, and evaluate representative methods on tuberculosis (TB) prediction and monkeypox prediction tasks. Finally, we propose NMFx, a general NMF formulation of interpretability by concept discovery that works in a unified way in unsupervised, weakly supervised, and supervised scenarios.
Enrique C. Gabrick, Elaheh Sayari, Paulo R. Protachevicz
et al.
In this work, we study the unpredictability of seasonal infectious diseases considering a SEIRS model with seasonal forcing. To investigate the dynamical behaviour, we compute bifurcation diagrams type hysteresis and their respective Lyapunov exponents. Our results from bifurcations and the largest Lyapunov exponent show bistable dynamics for all the parameters of the model. Choosing the inverse of latent period as control parameter, over 70% of the interval comprises the coexistence of periodic and chaotic attractors, bistable dynamics. Despite the competition between these attractors, the chaotic ones are preferred. The bistability occurs in two wide regions. One of these regions is limited by periodic attractors, while periodic and chaotic attractors bound the other. As the boundary of the second bistable region is composed of periodic and chaotic attractors, it is possible to interpret these critical points as tipping points. In other words, depending on the latent period, a periodic attractor (predictability) can evolve to a chaotic attractor (unpredictability). Therefore, we show that unpredictability is associated with bistable dynamics preferably chaotic, and, furthermore, there is a tipping point associated with unpredictable dynamics.