The Pharmacists' Role in Disease Outbreaks: Navigating the Dynamics of Uncertainty Before, During, and After Disease Outbreaks.
Ontology highlight
ABSTRACT:
SUBMITTER: Guerci J
PROVIDER: S-EPMC7337136 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:In 2018, the Bill and Melinda Gates Foundation convened over thirty subject matter experts in clinical development, manufacturing, and regulatory assessment to determine how the development and approval of medical countermeasures could be accelerated in the event of Disease X. Disease X is the result of a presently unknown pathogen with epidemic or pandemic potential. A key opportunity to accelerate the scientific assessment and regulatory approval of medical countermeasures exists within efficient navigation of facilitated regulatory pathways. It was identified that not all stakeholders will be able to skillfully navigate the facilitated pathways offered by the various regulatory agencies during a public health emergency. To democratize this knowledge, we have written an overview of the facilitated approaches which have been developed and refined by Stringent Regulatory Authorities and the World Health Organization for the primary assessment of medical products. We discuss the conditions necessary for use of these approaches, scenarios in which certain pathways may be applicable, and the pros and cons of these approaches. We also address opportunities available to developers in, or developers who wish to access, low-income countries that may have nascent regulatory frameworks.
| S-EPMC7584587 | biostudies-literature
Project description:The current COVID-19 pandemic is the most severe pandemic of the 21st century, on track to having a rising death toll. Beyond causing respiratory distress, COVID-19 may also cause mortality by way of suicide. The pathways by which emerging viral disease outbreaks (EVDOs) and suicide are related are complex and not entirely understood. We aimed to systematically review the evidence on the association between EVDOs and suicidal behaviors and/or ideation. An electronic search was conducted using five databases: Medline, Embase, Web of Science, PsycINFO and Scopus in April 2020. A rapid systematic review was carried out, which involved separately and independently extracting quantitative data of selected articles. The electronic search yielded 2480 articles, of which 9 met the inclusion criteria. Most of the data were collected in Hong Kong (n = 3) and the USA (n = 3). Four studies reported a slight but significant increase in deaths by suicide during EVDOs. The increase in deaths by suicide was mainly reported during the peak epidemic and in older adults. Psychosocial factors such as the fear of being infected by the virus or social isolation related to quarantine measures were the most prominent factors associated with deaths by suicide during EVDOs. Overall, we found scarce and weak evidence for an increased risk of deaths by suicide during EVDOs. Our results inform the need to orient public health policies toward suicide prevention strategies targeting the psychosocial effects of EVDOs. High-quality research on suicide risk and prevention are warranted during the current pandemic. Highlights • Few studies assessed the association between suicidal behaviors or ideation and emerging viral outbreaks.• The literature reports weak evidence for increased suicide rates during emerging viral outbreaks.• Psychosocial factors are associated with deaths by suicide during emerging viral outbreaks.• Suicide prevention strategies are needed during emerging viral outbreaks.
| S-EPMC7531915 | biostudies-literature
Project description:Early resolution of uncertainty during an epidemic outbreak can lead to rapid and efficient decision making, provided that the uncertainty affects prioritization of actions. The wide range in caseload projections for the 2014 Ebola outbreak caused great concern and debate about the utility of models. By coding and running 37 published Ebola models with five candidate interventions, we found that, despite this large variation in caseload projection, the ranking of management options was relatively consistent. Reducing funeral transmission and reducing community transmission were generally ranked as the two best options. Value of information (VoI) analyses show that caseloads could be reduced by 11% by resolving all model-specific uncertainties, with information about model structure accounting for 82% of this reduction and uncertainty about caseload only accounting for 12%. Our study shows that the uncertainty that is of most interest epidemiologically may not be the same as the uncertainty that is most relevant for management. If the goal is to improve management outcomes, then the focus of study should be to identify and resolve those uncertainties that most hinder the choice of an optimal intervention. Our study further shows that simplifying multiple alternative models into a smaller number of relevant groups (here, with shared structure) could streamline the decision-making process and may allow for a better integration of epidemiological modeling and decision making for policy.
| S-EPMC5465899 | biostudies-other
Project description:Internists are well-positioned to play significant roles in recognizing and responding to epidemics, outbreaks, and bioterrorist attacks. They see large numbers of patients with various health problems and may be the patients' only interaction with the medical community for symptoms resulting from infectious diseases and injuries from radiation, chemicals, and/or burns. Therefore, Internists must understand early warning signs of different bioterrorist and infectious agents, proper reporting channels and measures, various ways that they can assist the public health response, and roles of different local, state, and federal agencies. In addition, it is important to understand effects of a public health disaster on clinic operations and relevant legal consequences.
| S-EPMC1824729 | biostudies-other
Project description:The mass mortality of acroporid corals has transformed Caribbean reefs from coral- to macroalgal-dominated habitats since systematic monitoring began in the 1970s. Declines have been attributed to overfishing, pollution, sea urchin and coral disease, and climate change, but the mechanisms are unresolved due to the dearth of pre-1970s data. We used paleoecological, historical, and survey data to track Acropora presence and dominance throughout the Caribbean from the prehuman period to present. Declines in dominance from prehuman values first occurred in the 1950s for Acropora palmata and the 1960s for Acropora cervicornis, decades before outbreaks of acroporid disease or bleaching. We compared trends in Acropora dominance since 1950 to potential regional and local drivers. Human population negatively affected and consumption of fertilizer for agriculture positively affected A. palmata dominance, the latter likely due to lower human presence in agricultural areas. The earlier, local roots of Caribbean Acropora declines highlight the urgency of mitigating local human impacts.
| S-EPMC7176417 | biostudies-literature
Project description:In the event of a new infectious disease outbreak, mathematical and simulation models are commonly used to inform policy by evaluating which control strategies will minimize the impact of the epidemic. In the early stages of such outbreaks, substantial parameter uncertainty may limit the ability of models to provide accurate predictions, and policymakers do not have the luxury of waiting for data to alleviate this state of uncertainty. For policymakers, however, it is the selection of the optimal control intervention in the face of uncertainty, rather than accuracy of model predictions, that is the measure of success that counts. We simulate the process of real-time decision-making by fitting an epidemic model to observed, spatially-explicit, infection data at weekly intervals throughout two historical outbreaks of foot-and-mouth disease, UK in 2001 and Miyazaki, Japan in 2010, and compare forward simulations of the impact of switching to an alternative control intervention at the time point in question. These are compared to policy recommendations generated in hindsight using data from the entire outbreak, thereby comparing the best we could have done at the time with the best we could have done in retrospect. Our results show that the control policy that would have been chosen using all the data is also identified from an early stage in an outbreak using only the available data, despite high variability in projections of epidemic size. Critically, we find that it is an improved understanding of the locations of infected farms, rather than improved estimates of transmission parameters, that drives improved prediction of the relative performance of control interventions. However, the ability to estimate undetected infectious premises is a function of uncertainty in the transmission parameters. Here, we demonstrate the need for both real-time model fitting and generating projections to evaluate alternative control interventions throughout an outbreak. Our results highlight the use of using models at outbreak onset to inform policy and the importance of state-dependent interventions that adapt in response to additional information throughout an outbreak.
| S-EPMC6075790 | biostudies-literature
Project description:BackgroundClinical pharmacists have an important role in inter-professional healthcare collaboration for epilepsy management. However, the pharmacy practices of managing epilepsy are still limited in Vietnam, deterring pharmacists from routine adjustments of antiepileptic drugs, which could decrease the patients' quality of life. This study aimed to assess the effectiveness of pharmacist interventions in epilepsy treatment at a Vietnamese general hospital.MethodsA before-and-after study was conducted from January 2016 to December 2018. All patients with a diagnosis of epilepsy and being treated at the investigated hospital were recruited and screened for eligibility and exclusion criteria. The primary outcome was the proportion of patients in good control of their epilepsy (with two seizures or less in a year). The secondary outcome was the number of patients maintaining optimized concentrations within the therapeutic range of carbamazepine (4-12 mg/L), phenytoin (10-20 mg/L), or valproic acid (50-100 mg/L). Collected data were analyzed using two proportions Z-test or Chi-square test.ResultsA total of 141 participants were enrolled in the study. While most patients were given lower prescribed daily doses than the recommendations from the World Health Organization, over 56% of the participants still experienced adverse drug effects. More than half of the patients received at least one pharmacists' intervention, which increased by 25.0% the effectiveness of the therapy (p < 0.001) and by 14.6% the number of patients with optimized drug concentrations (p = 0.018).ConclusionEpilepsy management requires a multiple-stepped and comprehensive approach, with a focus on the health and safety of the patients. As part of the healthcare team, pharmacists need to engage at every stage to monitor the patient's response and determine the most effective treatment with the fewest adverse drug reactions. Trial registration ClinicalTrials.gov, NCT04967326. Registered July 19, 2021-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT04967326.
| S-EPMC8686354 | biostudies-literature
Project description:BackgroundThe present study assessed the impact of time-out on vancomycin use and compared the strategy's efficacy when led by pharmacists versus infectious disease (ID) physicians at a tertiary care center.MethodsTime-out, consisting of a telephone call to inpatient providers and documentation of vancomycin use >72 hours, was performed by ID physicians and clinical pharmacists in the Departments of Medicine and Surgery/Critical Care. Patients in the Department of Medicine were assigned to the clinical pharmacist-led arm, and patients in the Department of Surgery/Critical Care were assigned to the ID physician-led arm in the initial, 6-month phase and were switched in the second, 6-month phase. The primary outcome was the change in weekly days of therapy (DOT) per 1000 patient-days (PD), and vancomycin use was compared using interrupted time-series analysis.ResultsOf 587 patients receiving vancomycin, 132 participated, with 79 and 53 enrolled in the first and second phases, respectively. Overall, vancomycin use decreased, although the difference was statistically nonsignificant (change in slope, -0.25 weekly DOT per 1000 PD; 95% confidence interval [CI], -0.68 to 0.18; P = .24). The weekly vancomycin DOT per 1000 PD remained unchanged during phase 1 but decreased significantly in phase 2 (change in slope, -0.49; 95% CI, -0.84 to -0.14; P = .007). Antimicrobial use decreased significantly in the surgery/critical care patients in the pharmacist-led arm (change in slope, -0.77; 95% CI, -1.33 to -0.22; P = .007).ConclusionsVancomycin time-out was moderately effective, and clinical pharmacist-led time-out with surgery/critical care patients substantially reduced vancomycin use.
| S-EPMC8232390 | biostudies-literature
Project description:Mathematical models provide a quantitative framework with which scientists can assess hypotheses on the potential underlying mechanisms that explain patterns in the observed data at different spatial and temporal scales, generate estimates of key kinetic parameters, assess the impact of interventions, optimize the impact of control strategies, and generate forecasts. We review and illustrate a simple data assimilation framework for calibrating mathematical models based on ordinary differential equation models to time series data describing the temporal progression of case counts relating to population growth or infectious disease transmission dynamics. In contrast to Bayesian estimation approaches that always raise the question of how to set priors for the parameters, this frequentist approach relies on modeling the error structure in the data. We discuss issues related to parameter identifiability, uncertainty quantification and propagation as well as model performance and forecasts along examples based on phenomenological and mechanistic models parameterized using simulated and real datasets.
| S-EPMC5726591 | biostudies-literature
Project description:Background: The widespread use of social media represents an unprecedented opportunity for health promotion. We have more information and evidence-based health related knowledge, for instance about healthy habits or possible risk behaviors. However, these tools also carry some disadvantages since they also open the door to new social and health risks, in particular during health emergencies. This systematic review aims to study the determinants of infodemics during disease outbreaks, drawing on both quantitative and qualitative methods. Methods: We searched research articles in PubMed, Scopus, Medline, Embase, CINAHL, Sociological abstracts, Cochrane Library, and Web of Science. Additional research works were included by searching bibliographies of electronically retrieved review articles. Results: Finally, 42 studies were included in the review. Five determinants of infodemics were identified: (1) information sources; (2) online communities' structure and consensus; (3) communication channels (i.e., mass media, social media, forums, and websites); (4) messages content (i.e., quality of information, sensationalism, etc.,); and (5) context (e.g., social consensus, health emergencies, public opinion, etc.). Studied selected in this systematic review identified different measures to combat misinformation during outbreaks. Conclusion: The clarity of the health promotion messages has been proven essential to prevent the spread of a particular disease and to avoid potential risks, but it is also fundamental to understand the network structure of social media platforms and the emergency context where misinformation might dynamically evolve. Therefore, in order to prevent future infodemics, special attention will need to be paid both to increase the visibility of evidence-based knowledge generated by health organizations and academia, and to detect the possible sources of mis/disinformation.
| S-EPMC8039137 | biostudies-literature