Semantic Conceptual Framework for Environmental Monitoring and Surveillance—A Case Study on Forest Fire Video Monitoring and Surveillance

This paper presents a semantic conceptual framework and definition of environmental monitoring and surveillance and demonstrates an ontology implementation of the framework. This framework is defined in a mathematical formulation and is built upon and focused on the notation of observation systems. This formulation is utilized in the analysis of the observation system. Three taxonomies are presented, namely, the taxonomy of (1) the sampling method, (2) the value format and (3) the functionality. The definition of concepts and their relationships in the conceptual framework clarifies the task of querying for information related to the state of the environment or conditions related to specific events. This framework aims to make the observation system more queryable and therefore more interactive for users or other systems. Using the proposed semantic conceptual framework, we derive definitions of the distinguished tasks of monitoring and surveillance. Monitoring is focused on the continuous assessment of an environment state and surveillance is focused on the collection of all data relevant for specific events. The proposed mathematical formulation is implemented in the format of the computer readable ontology. The presented ontology provides a general framework for the semantic retrieval of relevant environmental information. For the implementation of the proposed framework, we present a description of the Intelligent Forest Fire Video Monitoring and Surveillance system in Croatia. We present the implementation of the tasks of monitoring and surveillance in the application domain of forest fire management.

Pyoderma Gangrenosum Induced by BNT162b2 COVID-19 Vaccine in a Healthy Adult

(1) Background: Pyoderma gangrenosum (PG) is a rare neutrophilic dermatosis of unknown etiology. Coronavirus disease 2019 (COVID-19) vaccines can cause a variety of adverse cutaneous manifestations. PG associated with mRNA vaccines has not previously been described. This case study reports on the first patient to develop PG after receiving BNT162b2. (2) Case Presentation: An otherwise-healthy 27-year-old man developed multiple skin lesions 24 h after receiving the first dose of the messenger RNA-based Pfizer/BioNTech BNT162b2 COVID-19 vaccine. When in hospital, he developed a new painful ulcerative lesion on his right hand. Skin ulcer edge biopsy showed severe epidermal neutrophilic infiltrate with epidermal and dermal edema, underlying superficial dermal necrosis, and characteristic undermining with extensive mixed inflammatory infiltration of the dermis and abscess formation consistent with an ulcer with mixed dermal inflammation compatible with pyoderma gangrenosum. The lesion showed rapid improvement after the initiation of immunosuppressive therapy. (3) Conclusions: PG may be a rare adverse event related to the BNT162b2 vaccine, which could be more frequently encountered with the wide-scale use of mRNA vaccines. The continuous monitoring and surveillance of skin manifestations post-vaccination is essential.

Health surveillance and development of children with congenital Zika Virus syndrome: an integrative literature review

ABSTRACT Objective: To identify scientific knowledge about the attention to health surveillance and development of Brazilian children under the age of three years involving the Congenital Zika virus (ZIKV) Syndrome. Data sources: This is an integrative literature review of primary studies with Brazilian children under three years of age from 2015 to 2019. The searches were carried out in the databases Latin American and Caribbean Literature in Health Sciences (LILACS), US National Library of Medicine (PubMed), Cumulative Index to Nursing and Allied Health Literature (CINAHL), SCOPUS and Web of Science. It was carried out by crossing the keywords in English (child, child development and Zika virus) and in Portuguese (criança, desenvolvimento infantil e Zika vírus), with the combination of the Boolean operator “AND”. Data synthesis: The knowledge produced is related to the specific health and development problems of children affected by the Congenital ZIKV Syndrome, with clinical characteristics, care demands, multiprofessional performance, health monitoring and surveillance needs. Conclusions: This integrative review synthesized scientific knowledge by adding aspects that reinforce the relevance of appropriate approaches to assess and care for children, linked to the engagement of caregivers, the need to document, evaluate and track the situations of children in early childhood and long-term, management coordination of care and its challenges in the context of primary health care.

Evolution of Non-communicable Disease Programs in Kerala: Lessons Learnt and the Way Forward

Addressing the double burden of disease in a country like India is a massive challenge, especially when the system is tuned to do monitoring and surveillance of mainly communicable diseases. Achieving the sustainable development goal target 3.4 to bring down the premature mortality from non-communicable diseases (NCDs) to one-third will need to consider the requirement of robust indicators at the national level to keep track of the prevalence of NCD and its risk factors among its population. The state of Kerala in contrast has a strong primary health care system that it can build on to address the rising NCD burden.

Intelligent Waterflood Optimization Advisory System – A Step Change Towards Digital Transformation

In this paper, we discuss the development of an end-to-end waterflood optimization solution that provides monitoring and surveillance dashboards with artificial intelligence (AI) and machine learning (ML) components to generate and assess insights into waterflood operational efficiency in an automated manner. The solution allows for fast screening of waterflood performance at diverse levels (reservoir, sector, pattern, well) enabling prompt identification of opportunities for immediate uptake into an opportunity management process and for evaluation in AI-driven production forecast solution and/or a reservoir simulator. The process starts with the integration of a wide range of production and reservoir engineering data types from multiple sources. Following this, a series of monitoring and surveillance dashboards of key units and elements of the entire waterflood operations are created. The workflows in these dashboards are framed with key waterflood reservoir and production engineering concepts in mind. The optimization opportunity insights are then extracted using automated traditional and AI/ML algorithms. The identified opportunities are consolidated in an optimization action list. This list is passed to an AI-driven production forecast solution and/or a reservoir simulator to assess the impact of each scenario. The system is designed to improve the business-time decision-making cycle, resulting in increased operational performance and lower waterflood operating costs by consolidating end-to-end optimization workflows in one platform. It incorporates both surface and subsurface aspects of the waterflood and provides a comprehensive understanding of waterflood operations from top-down field, reservoir, sector, pattern and well levels. Its AI/ML components facilitate understanding of producer-injector relationships, injector dynamic performance, underperformance of patterns in the sector as well as evaluating the impact of different optimization scenarios on incremental oil production. The data-driven production forecast component consists of several ML models and is tailored to assess their impact on oil production of different scenarios such as changes in voidage replacement ratio (VRR) in reservoir, sector, pattern and well levels. Opportunities are also converted into reservoir simulator compatible format in an automated manner to assess the impact of different scenarios using more rigorous numerical methods. The scenarios that yield the highest impact are passed to the field operations team for execution. The solution is expected to serve as a benchmark, upon successful implementation, for optimizing injection schemas in any field or reservoir. The novelty of the system lies in automating the insights generation process, in addition to integrating with an AI/ML production forecasting solution and/or a reservoir simulator to assess different optimization scenarios. It is an end-to-end solution for waterflood optimization because of the integration of various components that allow for the identification and assessment of opportunities all in one environment.

Dampak Trichinella sp. dalam Daging Babi Terhadap Kesehatan Masyarakat

Trichinellosis/Trichinosis is one of the most common zoonotic parasites in the world caused by infection with Trichinella nematodes. The infection occurs after the larvae have been eaten in the muscles of the infected animal. Due to its spread and spread, several outbreaks of trichinosis have occurred around the world, which has caused serious public health problems. The main risk factor for trichinosis is the consumption of raw or undercooked meat from pigs and hunted meat. In the first stage of infection, adults nematode in the intestine can cause transient gastroenteritis, but the most serious symptoms are associated with the larval formation and muscle migration. a study conducted in India to investigate at the clinical and biochemical profile of Trichinella infection stated that clinical symptoms first appeared at 2-3 weeks after consuming pork and the symptoms would gradually disappear at 4-5 weeks, but there were also some who experienced myalgia. Supervision and implementing proper biosecurity in livestock areas by monitoring and surveillance of the risk of Trichinella infection in pig products and their derivatives as well as preventing transmission to humans.

Klebsiella pneumoniae Complex Harboring mcr-1, mcr-7, and mcr-8 Isolates from Slaughtered Pigs in Thailand

Dissemination of the mobile colistin resistance gene mcr in Enterobacterales among humans, animals, and the environment is a public health issue. We characterized mcr genes in the Klebsiella pneumoniae complex (KpnC) isolated from slaughtered pigs in Thailand. The 280 KpnCs consisted of K. pneumoniae (85%), Klebsiella quasipneumoniae (8.21%), and Klebsiella variicola (6.79%). mcr genes were detected in 6.79% (19/280) of KpnC isolates, consisting of mcr-8 (n = 9; 3.21%), mcr-7 (n = 7; 2.50%), mcr-7 + mcr-8 (n = 2; 0.71%), and mcr-1 + mcr-7 (n = 1; 0.36%). K. pneumoniae predominantly carried the mcr-7 and mcr-8 genes, while K. variicola and K. quasipneumoniae harbored mcr-7 and mcr-8, respectively. Six of the nineteen mcr-harboring KpnC isolates exhibited colistin resistance, and five had mcr-1 or mcr-8 transferable to an Escherichia coli recipient. Antimicrobial susceptibility analysis revealed that all mcr-carrying KpnC isolates were susceptible to carbapenems, cefotaxime, cefepime, amoxicillin/clavulanic acid, piperacillin/tazobactam, amikacin, and fosfomycin, and had high resistance to azithromycin. Multilocus sequence analysis demonstrated that the mcr-harboring KpnC isolates were genetically diverse. A ‘One-Health’ approach is useful to combat antimicrobial-resistant bacteria through coordinating the human, animal, and environmental sectors. Hence, continuous monitoring and surveillance of mcr-carrying KpnCs throughout the pork supply chain is crucial for ensuring public health.

Strategy for a rapid screening and surveillance of SARS-CoV-2 variants by real time RT-PCR: a key tool that allowed control and delay in Delta spread in Cordoba, Argentina

Background: SARS-CoV-2 variants of concern (VOC) and interest (VOI) present mutations in reference to the original virus, being more transmissible. We implemented a rapid strategy for the screening of SARS-CoV-2 VOC/VOIs using real time RT-PCR and performed monitoring and surveillance of the variants in our region. Methods: consecutive real-time RT-PCRs for detection of the relevant mutations/deletions present in the Spike protein in VOC/VOIs (TaqMan SARS-CoV-2 Mutation Panel, Applied Biosystems) were implemented. An algorithm was established and 3941 SARS-CoV-2 RNA samples (Cts<30) obtained from oropharyngeal swabs from infected individuals in Cordoba, Argentina, between January and October 2021, were analyzed. Results: the strategy of choice included a first screening of 3 mutations (N501Y, E484K, L452R) followed by the detection of other mutations/deletions based on the results. The analyses of the samples showed introductions of VOCs Alpha and Gamma in February and March 2021, respectively. Since then, Alpha presented a low to moderate circulation (1.7% of the SARS-CoV-2 currently detected). Gamma showed an exponential increase, with a peak of detection in July (72%), until reaching a current frequency of 41.1%. VOC Delta was first detected in July in travellers and currently represents 35% of detections in the community. VOI Lambda presented a gradual increase, showing a current frequency of 29%. Conclusions: we report a useful tool for VOC/VOI detection, innovative for Argentina, capable to quickly and cost-effectively monitor currently recognized variants. It was key in the early detection of Delta, being able to implement measures to delay its dissemination.