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The Caribbean coral reef ecosystem has experienced a long history of deterioration due to various stressors. For instance, over-fishing of parrotfish – an important grazer of macroalgae that can prevent destructive overgrowth of macroalgae – has threatened reef ecosystems in recent decades and stimulated conservation efforts such as the formation of marine protected areas. Here we develop a mathematical model of coupled socio-ecological interactions between reef dynamics and conservation opinion dynamics to better understand how natural and human factors interact individually and in combination to determine coral reef cover. We find that the coupling opinion and reef systems generates complex dynamics that are difficult to anticipate without use of a model. For instance, instead of converging to a stable state of constant coral cover and conservationist opinion, the system can oscillate between low and high live coral cover as human opinion oscillates in a boom-bust cycle between complacency and concern. Out of various possible parameter manipulations, we also find that raising awareness of coral reef endangerment best avoids counter-productive nonlinear feedbacks and always increases and stabilizes live coral reef cover. In conclusion, an improved understanding of coupled opinion-reef dynamics under anthrogenic stressors is possible using coupled socio-ecological models, and such models should be further researched.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Classical environmental models assume the influence of humans on environmental systems is constant. However, human and environmental systems respond to one another. As such, coupled human-environment systems (CHES) models have been developed and are becoming more widely studied. In this review, we analyze CHES modelling techniques and study systems over a decade (May 2009-April 2019). We utilized the PRISMA method to filter publications from both Web of Knowledge and PUBMED, yielding 92 relevant papers for our review. Publications more than doubled from the 5-year interval May 2009-December 2013 (28/92) to the 5-year interval January 2014-April 2019 (64/92). CHES models typically used either differential equations (DEs) (44/92) or agent-based models (ABMs) (28/92). We organized the included literature with respect to the technique used to represent human behaviour. We noticed a diversity of approaches in this respect, but primarily optimization techniques (28/92) and game theory (34/92). We noticed a substantial increase in publications using more highly structured models in the second 5-year interval. We attribute this to reduced technological barriers to developing more detailed models, and greater data availability. We discuss the realism of the models and their ability to capture real-world dynamics. Finally, we explore avenues for future research, and discuss unconventional routes such as online communities and artificial intelligence modelling to expand representation of human behaviour in CHES models.Competing Interest StatementThe authors have declared no competing interest.

Mathematical models that couple disease dynamics and vaccinating behaviour often assume that the incentive to vaccinate disappears if disease prevalence is zero. Hence, they predict that vaccine refusal should be the rule, and elimination should be difficult or impossible. In reality, countries with non-mandatory vaccination policies have usually been able to maintain elimination or very low incidence of paediatric infectious diseases for long periods of time. Here, we show that including injunctive social norms can reconcile such behaviour-incidence models to observations. Adding social norms to a coupled behaviour-incidence model enables the model to better explain pertussis vaccine uptake and disease dynamics in the UK from 1967 to 2010, in both the vaccine-scare years and the years of high vaccine coverage. The model also illustrates how a vaccine scare can perpetuate suboptimal vaccine coverage long after perceived risk has returned to baseline, pre-vaccine-scare levels. However, at other model parameter values, social norms can perpetuate depressed vaccine coverage during a vaccine scare well beyond the time when the population's baseline vaccine risk perception returns to pre-scare levels. Social norms can strongly suppress vaccine uptake despite frequent outbreaks, as observed in some small communities. Significant portions of the parameter space also exhibit bistability, meaning long-term outcomes depend on the initial conditions. Depending on the context, social norms can either support or hinder immunization goals.

Anti γ aminobutyric acid B(GABA B) receptor encephalitis is a rare form of autoimmune encephalitis. Our aim is to study the clinical characteristics and treatment outcomes of anti GABA B receptor encephalitis. This is a retrospective case series from the Neuroimmunology laboratory of Amrita Institute of Medical Sciences, Kochi, Kerala, India from 2016 to 2021. A total of four cases (two males, two females, age range: 13-80 years) tested positive for GABA B antibody during the study period. The clinical manifestations of anti GABA B receptor encephalitis found in our patients consisted of seizures, cognitive function decline (especially recent memory), and behavioral abnormalities. No malignancies were encountered. Patients were treated with steroids and immunoglobulins and showed an improvement in behavioral and cognitive function. However, one patient succumbed to illness while being treated with plasma exchange, and two other patients died at a later date due to other causes.

Mathematical models that couple disease dynamics and vaccinating behaviour often assume that the incentive to vaccinate disappears if disease prevalence is zero. Hence, they predict that vaccine refusal should be the rule, and elimination should be difficult or impossible. In reality, countries with non-mandatory vaccination policies have usually been able to maintain elimination or very low incidence of paediatric infectious diseases for long periods of time. Here, we show that including injunctive social norms can reconcile such behaviour-incidence models to observations. Adding social norms to a coupled behaviour-incidence model enables the model to better explain pertussis vaccine uptake and disease dynamics in the UK from 1967 to 2010, in both the vaccine-scare years and the years of high vaccine coverage. The model also illustrates how a vaccine scare can perpetuate suboptimal vaccine coverage long after perceived risk has returned to baseline, pre-vaccine-scare levels. However, at other model parameter values, social norms can perpetuate depressed vaccine coverage during a vaccine scare well beyond the time when the population's baseline vaccine risk perception returns to pre-scare levels. Social norms can strongly suppress vaccine uptake despite frequent outbreaks, as observed in some small communities. Significant portions of the parameter space also exhibit bistability, meaning long-term outcomes depend on the initial conditions. Depending on the context, social norms can either support or hinder immunization goals.

Background: Although safe practice guidelines were issued by the Obesity and Metabolic Surgery Society of India (OSSI) in the end of May 2020, surgeons have been in a dilemma about risk of subjecting patients to hospitalisation and bariatric surgery. This survey was conducted with the objective to evaluate the risk of coronavirus disease-19 (COVID-19) infection in peri- and post-operative period after bariatric and metabolic surgery (BMS). Methods: A survey with OSSI members was conducted from 20 July 2020 to 31 August 2020 in accordance with EQUATOR guidelines. Google Form was circulated to all surgeon members through E-mail and WhatsAppTM. In the second phase, clinical details were captured from surgeons who reported positive cases. Results: One thousand three hundred and seven BMS were reported from 1 January 2020 to 15 July 2020. Seventy-eight per cent were performed prior to 31 March 2020 and 276 were performed after 1 April 2020. Of these, 13 (0.99%) patients were reported positive for COVID-19 in the post-operative period. All suffered from a mild disease and there was no mortality. Eighty-seven positive cases were reported from patients who underwent BMS prior to 31 December 2019. Of these, 82.7% of patients had mild disease, 13.7% of patients had moderate symptoms and four patients succumbed to COVID-19. Conclusion: BMS may be considered as a safe treatment option for patients suffering from clinically severe obesity during the COVID-19 pandemic. Due care must be taken to protect patients and healthcare workers and all procedures must be conducted in line with the safe practice guidelines.