Report on the evaluation of surveillance systems relevant to zoonotic diseases in Kenya, 2015: A basis for design of an integrated human–livestock surveillance system

The Zoonoses in Livestock in Kenya (ZooLinK) is a project that seeks to enable Kenya develop an effective surveillance programme for zoonotic diseases (infectious diseases transmissible between animals and human beings). The surveillance programme will be integrated across both human and animal health sectors. To achieve this goal the project will work in close collaboration with Kenyan government departments in responsible for animal and human health. As a prelude to the start of the project, an evaluation of the existing surveillance systems for human and animal health was carried out. The evaluation focused on the national surveillance system and the systems at the western part of Kenya (Busia county, Kakamega county and Bungoma county) where the initial programme will be developed. In conducting the evaluation the investigators used key informant interviews, focused group discussion participant questionnaires, audio recordings and observation for data collection. Data analysis for the qualitative data focused on generating themes or theory around the responses obtained in the key informants interviews and focused group discussions. Univariate analysis was performed by use of simple proportions in calculation for surveillance system attributes like sensitivity, completeness, PVP and Timeliness for the human health surveillance systems. The findings of the evaluation revealed that there was poor linkage between animal health surveillance and the human health surveillance systems. None of the systems had surveillance structures dedicated to zoonotic diseases. Most practitioners used clinical signs for diagnosis of diseases with little reference to acceptable case definitions. Laboratory diagnosis in animal health services focused more on suspected notifiable diseases as opposed to being a standard operating procedure for diagnosis. In Human health services the health care facilities that had laboratory within the facility conducted laboratory diagnosis for cases referred by the clinicians. However, some clinicians preferred using clinical signs for diagnosis to avoid the wait or turn-around time in the laboratory. For effective surveillance of zoonoses to be realized it would be advisable to establish surveillance structures specific to zoonoses and the necessary resources allocated to the surveillance activities. In addition, an integrated approach that incorporated both human and animal disease surveillance should be employed in the surveillance of zoonoses

Effects of Surveillance on Intrinsic Motivation

Previous research indicates that explicit surveillance should induce subjects to attribute their performance at a task to the surveillance; hence, such subjects should persist to a lesser extent than subjects not exposed to such surveillance. Two forms of explicit surveillance were utilized: human and camera, as well as the appropriate opposites (human non- and camera non-surveillance). Subjects were directed to perform a model construction task, then were unobtrusively observed during a post-task “waiting period.” No difference in persistence was found for type of surveillance utilized. However, as predicted, subjects exposed to surveillance persisted less with the task materials than subjects not exposed

Melanoma Surveillance

According to the CDC, in 2015 the rate of melanoma of the skin was 22.1 per 100 thousand people, the sixth most common cancer. In Vermont this rate was 35.8 per 100 thousand, higher than the national average. In Berlin, VT, it was noted that patients often are concerned about their nevi, but often do not know when it is appropriate to bring them to their physician\u27s attention. A pamphlet was developed to assist physicians in educating patients on the characteristics of melanocytic nevi and encourage patients to speak to their physician when they find moles which meet these characteristics.https://scholarworks.uvm.edu/fmclerk/1512/thumbnail.jp

Systems approaches to animal disease surveillance and resource allocation: methodological frameworks for behavioral analysis

While demands for animal disease surveillance systems are growing, there has been little applied research that has examined the interactions between resource allocation, cost-effectiveness, and behavioral considerations of actors throughout the livestock supply chain in a surveillance system context. These interactions are important as feedbacks between surveillance decisions and disease evolution may be modulated by their contextual drivers, influencing the cost-effectiveness of a given surveillance system. This paper identifies a number of key behavioral aspects involved in animal health surveillance systems and reviews some novel methodologies for their analysis. A generic framework for analysis is discussed, with exemplar results provided to demonstrate the utility of such an approach in guiding better disease control and surveillance decisions

Success Factors of European Syndromic Surveillance Systems: A Worked Example of Applying Qualitative Comparative Analysis

Introduction: Syndromic surveillance aims at augmenting traditional public health surveillance with timely information. To gain a head start, it mainly analyses existing data such as from web searches or patient records. Despite the setup of many syndromic surveillance systems, there is still much doubt about the benefit of the approach. There are diverse interactions between performance indicators such as timeliness and various system characteristics. This makes the performance assessment of syndromic surveillance systems a complex endeavour. We assessed if the comparison of several syndromic surveillance systems through Qualitative Comparative Analysis helps to evaluate performance and identify key success factors. Materials and Methods: We compiled case-based, mixed data on performance and characteristics of 19 syndromic surveillance systems in Europe from scientific and grey literature and from site visits. We identified success factors by applying crisp-set Qualitative Comparative Analysis. We focused on two main areas of syndromic surveillance application: seasonal influenza surveillance and situational awareness during different types of potentially health threatening events. Results: We found that syndromic surveillance systems might detect the onset or peak of seasonal influenza earlier if they analyse non-clinical data sources. Timely situational awareness during different types of events is supported by an automated syndromic surveillance system capable of analysing multiple syndromes. To our surprise, the analysis of multiple data sources was no key success factor for situational awareness. Conclusions: We suggest to consider these key success factors when designing or further developing syndromic surveillance systems. Qualitative Comparative Analysis helped interpreting complex, mixed data on small-N cases and resulted in concrete and practically relevant findings