scholarly journals Evaluation of Probabilistic Disease Forecasts

2017 ◽  
Vol 107 (10) ◽  
pp. 1136-1143 ◽  
Author(s):  
Gareth Hughes ◽  
Fiona J. Burnett
Keyword(s):  
Disease Management ◽  
Statistical Evaluation ◽  
Disease Status ◽  
Scoring Rules ◽  
Management Decision ◽  
Predictive Values ◽  
Clinical Literature ◽  
Probabilistic Forecasts ◽  
Management Decision Making ◽  
Plant Disease Management

The statistical evaluation of probabilistic disease forecasts often involves calculation of metrics defined conditionally on disease status, such as sensitivity and specificity. However, for the purpose of disease management decision making, metrics defined conditionally on the result of the forecast—predictive values—are also important, although less frequently reported. In this context, the application of scoring rules in the evaluation of probabilistic disease forecasts is discussed. An index of separation with application in the evaluation of probabilistic disease forecasts, described in the clinical literature, is also considered and its relation to scoring rules illustrated. Scoring rules provide a principled basis for the evaluation of probabilistic forecasts used in plant disease management. In particular, the decomposition of scoring rules into interpretable components is an advantageous feature of their application in the evaluation of disease forecasts.

scholarly journals Priority selection of agro-meteorological parameters for integrated plant diseases management through analytical hierarchy process

2022 ◽  
Vol 12 (1) ◽  
pp. 649
Author(s):  
Rutuja Rajendra Patil ◽  
Sumit Kumar
Keyword(s):  
Decision Making ◽  
Disease Management ◽  
Plant Disease ◽  
Meteorological Parameters ◽  
Plant Diseases ◽  
Heat Index ◽  
Management Decision ◽  
Factors Affecting ◽  
Management Decision Making ◽  
Plant Disease Management

To understand the influence of agro-meteorological parameters to take decisions related to various factors in an integrated plant disease management, it becomes vital to carry out scientific studies on the factors affecting it. The different agro-meteorological parameters namely temperature, humidity, moisture, rain, phenological week, cropping season, soil type, location, precipitation, heat index, and cloud coverage have been considered for this study. Each parameter has been allocated the ranking by using a technique called analytical hierarchical process (AHP). The parameter priorities are determined by calculating the Eigenvalues. This helps to make decisions related to integrated plant disease management where the prediction of plant disease occurrence, yield prediction, irrigation requirements, and fertilization recommendations can be taken. To take these decisions which parameters are good indicators can be identified using this method. The parameters majorly contribute to plant diseases and pest management decision making while delivers minor contribution in irrigation and fertilizer management related decision making. The manual results are compared with software generated results which indicates that both the results correlate with each other. Therefore, AHP technique can be successfully implemented for prioritizing agro-meteorological parameters for integrated plant diseases management as the results for both levels are consistent (consistency ratio < 0.1).

scholarly journals Cooperation and Coordination in Plant Disease Management

2019 ◽  
Vol 109 (10) ◽  
pp. 1720-1731 ◽  
Author(s):  
Jennifer Sherman ◽  
Jordan M. Burke ◽  
David H. Gent
Keyword(s):  
Disease Management ◽  
Collective Action ◽  
Information Sharing ◽  
Best Management Practices ◽  
Management Practices ◽  
Disease Risk ◽  
Disease Status ◽  
Best Management ◽  
Trust And Reciprocity ◽  
Plant Disease Management

Scaling of management efforts beyond the boundaries of individual farms may require that individuals act collectively. Such approaches have been suggested several times in plant pathology contexts but rarely have been implemented, in part because the institutional structures that enable successful collective action are poorly understood. In this research, we conducted in-depth interviews with hop producers in Oregon and Washington State to identify their motivations for and barriers to collective action regarding communication of disease levels, coordination of management practices, and sharing of best management practices and other data for powdery mildew (caused by Podosphaera macularis). Growers were generally open to and engaged in communication with neighbors and others on disease status in their hop yards and some evidence of higher levels of information sharing on management practices was found. However, growers who had developed extensive knowledge and databases were reluctant to share information viewed as proprietary. Relationships, trust, and reciprocity were facilitating factors for communication and information sharing, whereas lack of these factors and social norms of independence and pride in portions of the grower community were identified as impediments. Given the heterogeneity of trust, lack of confidence in reciprocity, and weak shared norms, communication of disease risk and coordinated management may be most successful if directed at a smaller scale as a series of neighborhood-based partnerships of growers and their immediate neighbors. Developing a disease reporting system and coordinated disease management efforts with more producers and at larger spatial extents would require formalized structures and rules that would provide assurance that there is consistency in disease data collection and reporting, reciprocation, and sanctions for those who use the information for marketing purposes against other growers. Given the analyses presented here, we believe there is potential for collective action in disease management but with limitations on the scope and nature of the actions.

scholarly journals On the Binormal Predictive Receiver Operating Characteristic Curve for the Joint Assessment of Positive and Negative Predictive Values

Entropy ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. 593 ◽  
Author(s):  
Gareth Hughes
Keyword(s):  
Receiver Operating Characteristic ◽  
Roc Curve ◽  
Operating Characteristic ◽  
Statistical Evaluation ◽  
Characteristic Curve ◽  
Disease Status ◽  
Curve Analysis ◽  
Roc Curve Analysis ◽  
Predictive Values ◽  
Receiver Operating

The predictive receiver operating characteristic (PROC) curve is a diagrammatic format with application in the statistical evaluation of probabilistic disease forecasts. The PROC curve differs from the more well-known receiver operating characteristic (ROC) curve in that it provides a basis for evaluation using metrics defined conditionally on the outcome of the forecast rather than metrics defined conditionally on the actual disease status. Starting from the binormal ROC curve formulation, an overview of some previously published binormal PROC curves is presented in order to place the PROC curve in the context of other methods used in statistical evaluation of probabilistic disease forecasts based on the analysis of predictive values; in particular, the index of separation (PSEP) and the leaf plot. An information theoretic perspective on evaluation is also outlined. Five straightforward recommendations are made with a view to aiding understanding and interpretation of the sometimes-complex patterns generated by PROC curve analysis. The PROC curve and related analyses augment the perspective provided by traditional ROC curve analysis. Here, the binormal ROC model provides the exemplar for investigation of the PROC curve, but potential application extends to analysis based on other distributional models as well as to empirical analysis.

scholarly journals A qualitative inquiry on self-management decision making among rural African Americans with type 2 diabetes

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 693-693
Author(s):  
Idethia Shevon Harvey
Keyword(s):  
Type 2 Diabetes ◽  
Decision Making ◽  
African Americans ◽  
Disease Management ◽  
Developmental Process ◽  
Qualitative Inquiry ◽  
Self Management ◽  
Management Decision ◽  
Management Decision Making

Abstract Living in a rural area has been recognized as a unique health disparity associated with higher rates of chronic disease. It is further compounded for those who are the most structurally vulnerable complicating access to care and negatively affecting health outcomes. Barriers to type 2 diabetes (T2DM) self-management remain a growing concern, particularly among minority communities living in underserved geographical areas. Much of the self-management research focused on compliance with medication regimens and modification of lifestyle choices. A less well-understood but arguably more critical aspect is the social factors in disease management decision-making. Purposive sampling was used to identify rural African Americans (n = 34). The mean age of participants was 65.9 years (SD = 12.3), and T2DM diagnosis was 15 years (SD = 12.4). The study utilized the consensual qualitative research methodology and the "Sort and Sift, Think and Shift" approach to identify themes. The participants reported an alternative way of integrating glucose monitoring through a "feedback loop" of body sensing. The longer they live with the condition (i.e., knowing my body), the more they can interpret whether they are hypoglycemic or hyperglycemic (i.e., deciphering the cues) to create and navigate their disease management strategy (i.e., body sensing). Self-management decision-making is a complex developmental process that includes disease trajectory and cultural and environmental factors. Findings from this study may provide a conceptual framework for ongoing inquiry and may provide insights to help T2DM educators and clinicians fully understand the complexity of long-term disease management among rural African Americans.

Centralization and Effectiveness of Reward Management in Multinational Enterprises

2018 ◽  
Vol 17 (2) ◽  
pp. 55-65 ◽  
Author(s):  
Michael Tekieli ◽  
Marion Festing ◽  
Xavier Baeten
Keyword(s):  
Decision Making ◽  
Social Identity Theory ◽  
Multinational Enterprises ◽  
Role Identity ◽  
Management Decision ◽  
Role Identities ◽  
Management Decision Making ◽  
New Perspective ◽  
Subsidiary Managers ◽  
The Relationship

Abstract. Based on responses from 158 reward managers located at the headquarters or subsidiaries of multinational enterprises, the present study examines the relationship between the centralization of reward management decision making and its perceived effectiveness in multinational enterprises. Our results show that headquarters managers perceive a centralized approach as being more effective, while for subsidiary managers this relationship is moderated by the manager’s role identity. Referring to social identity theory, the present study enriches the standardization versus localization debate through a new perspective focusing on psychological processes, thereby indicating the importance of in-group favoritism in headquarters and the influence of subsidiary managers’ role identities on reward management decision making.

Emergency management decision-making during severe weather

2006 ◽  
Author(s):  
Leigh A. Baumgart ◽  
Ellen J. Bass ◽  
Brenda Philips ◽  
Kevin Kloesel
Keyword(s):  
Decision Making ◽  
Emergency Management ◽  
Severe Weather ◽  
Management Decision ◽  
Management Decision Making
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