Animal health surveillance by quadrant A new intelligent agricultural surveillance system

Abstract Background Effective animal health surveillance systems require reliable, high-quality, and timely data for decision making. In Tanzania, the animal health surveillance system has been relying on a few data sources, which suffer from delays in reporting, underreporting, and high cost of data collection and transmission. The integration of data from multiple sources can enhance early detection and response to animal diseases and facilitate the early control of outbreaks. This study aimed to identify and assess existing and potential data sources for the animal health surveillance system in Tanzania and how they can be better used for early warning surveillance. The study used a mixed-method design to identify and assess data sources. Data were collected through document reviews, internet search, cross-sectional survey, key informant interviews, site visits, and non-participant observation. The assessment was done using pre-defined criteria. Results A total of 13 data sources were identified and assessed. Most surveillance data came from livestock farmers, slaughter facilities, and livestock markets; while animal dip sites were the least used sources. Commercial farms and veterinary shops, electronic surveillance tools like AfyaData and Event Mobile Application (EMA-i) and information systems such as the Tanzania National Livestock Identification and Traceability System (TANLITS) and Agricultural Routine Data System (ARDS) show potential to generate relevant data for the national animal health surveillance system. The common variables found across most sources were: the name of the place (12/13), animal type/species (12/13), syndromes (10/13) and number of affected animals (8/13). The majority of the sources had good surveillance data contents and were accessible with medium to maximum spatial coverage. However, there was significant variation in terms of data frequency, accuracy and cost. There were limited integration and coordination of data flow from the identified sources with minimum to non-existing automated data entry and transmission. Conclusion The study demonstrated how the available data sources have great potential for early warning surveillance in Tanzania. Both existing and potential data sources had complementary strengths and weaknesses; a multi-source surveillance system would be best placed to harness these different strengths.

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The Development of an Abattoir-Based Surveillance System in Lao PDR for the Detection of Zoonoses in Large Ruminants: Q Fever and Brucellosis Seroepidemiology as a Pilot Study

Animals ◽

10.3390/ani11030742 ◽

2021 ◽

Vol 11 (3) ◽

pp. 742

Author(s):

Jarunee Siengsanan-Lamont ◽

Bounlom Douangngeun ◽

Watthana Theppangna ◽

Syseng Khounsy ◽

Phouvong Phommachanh ◽

...

Keyword(s):

Surveillance System ◽

Q Fever ◽

Developing Economies ◽

Animal Health ◽

Lao Pdr ◽

Elisa Test ◽

Health Surveillance ◽

Passive Surveillance System ◽

Large Ruminant ◽

Antibody Elisa

Although animal health surveillance programmes are useful for gaining information to help improve global health and food security, these programmes can be challenging to establish in developing economies with a low-resource base. This study focused on establishing a national surveillance system initiated by the Lao PDR government using a passive surveillance system of abattoir samples as a pilot model, and to gain information on contagious zoonoses, particularly Q fever and brucellosis, in the large ruminant population. A total of 683 cattle and buffalo samples were collected from six selected provinces of Lao PDR between March–December 2019. Out of 271 samples tested, six samples (2.2%, 95% confidence interval (CI) of 1.0, 4.8) were positive in the Q fever antibody ELISA test. Only one sample (out of 683; 0.2%, 95% CI 0.0, 0.8) tested positive to the Brucella antibody ELISA test. Seroprevalence of these important zoonoses in Lao PDR were relatively low in cattle and buffaloes; however, extensive animal movement within the country was identified which could increase risks of spreading transboundary diseases. The study highlights the importance of ongoing animal health surveillance and the need to find cost-effective approaches for its long-term sustainability.

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Evaluation of animal and public health surveillance systems: a systematic review

Epidemiology and Infection ◽

10.1017/s0950268811002160 ◽

2011 ◽

Vol 140 (4) ◽

pp. 575-590 ◽

Cited By ~ 65

Author(s):

J. A. DREWE ◽

L. J. HOINVILLE ◽

A. J. C. COOK ◽

T. FLOYD ◽

K. D. C. STÄRK

Keyword(s):

Public Health ◽

Systematic Review ◽

Surveillance System ◽

Animal Health ◽

Evaluation Process ◽

Health Surveillance ◽

Evaluation Framework ◽

Surveillance Systems ◽

Efficient Manner ◽

Wide Range

SUMMARYDisease surveillance programmes ought to be evaluated regularly to ensure they provide valuable information in an efficient manner. Evaluation of human and animal health surveillance programmes around the world is currently not standardized and therefore inconsistent. The aim of this systematic review was to review surveillance system attributes and the methods used for their assessment, together with the strengths and weaknesses of existing frameworks for evaluating surveillance in animal health, public health and allied disciplines. Information from 99 articles describing the evaluation of 101 surveillance systems was examined. A wide range of approaches for assessing 23 different system attributes was identified although most evaluations addressed only one or two attributes and comprehensive evaluations were uncommon. Surveillance objectives were often not stated in the articles reviewed and so the reasons for choosing certain attributes for assessment were not always apparent. This has the potential to introduce misleading results in surveillance evaluation. Due to the wide range of system attributes that may be assessed, methods should be explored which collapse these down into a small number of grouped characteristics by focusing on the relationships between attributes and their links to the objectives of the surveillance system and the evaluation. A generic and comprehensive evaluation framework could then be developed consisting of a limited number of common attributes together with several sets of secondary attributes which could be selected depending on the disease or range of diseases under surveillance and the purpose of the surveillance. Economic evaluation should be an integral part of the surveillance evaluation process. This would provide a significant benefit to decision-makers who often need to make choices based on limited or diminishing resources.

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Mechanisms and Contextual Factors Affecting the Implementation of Animal Health Surveillance in Tanzania: A Process Evaluation

Frontiers in Veterinary Science ◽

10.3389/fvets.2021.790035 ◽

2022 ◽

Vol 8 ◽

Author(s):

Janeth George ◽

Barbara Häsler ◽

Erick V. G. Komba ◽

Mark Rweyemamu ◽

Sharadhuli I. Kimera ◽

...

Keyword(s):

Process Evaluation ◽

Surveillance System ◽

Qualitative Data ◽

Contextual Factors ◽

Animal Health ◽

Complex Interventions ◽

Clinical Signs ◽

Health Surveillance ◽

Observation Data ◽

Cross Sectional Survey

A strong animal health surveillance system is an essential determinant of the health of animal and human population. To ensure its functionality and performance, it needs to be evaluated regularly. Therefore, a process evaluation was conducted in this study to assess animal health surveillance processes, mechanisms and the contextual factors which facilitate or hinder uptake, implementation and sustainability of the system in Tanzania. A mixed-method study design was used to evaluate the national animal health surveillance system guided by a framework for process evaluation of complex interventions developed by Moore and others. The system was assessed against standard guidelines and procedures using the following attributes: fidelity, adherence, exposure, satisfaction, participation rate, recruitment and context. Quantitative and qualitative data were collected using a cross-sectional survey, key informant interviews, document review, site visits and non-participant observation. Data from questionnaires were downloaded, cleaned and analyzed in Microsoft™ Excel. Qualitative data were analyzed following deductive thematic and content analysis methods. Fidelity attribute showed that case identification is mainly based on clinical signs due to limited laboratory services for confirmation. Data collection was not well-coordinated and there were multiple disparate reporting channels. Adherence in terms of the proportion of reports submitted per month was only 61% of the target. District-level animal health officials spent an average of 60% of their weekly time on surveillance-related activities, but only 12% of them were satisfied with the surveillance system. Their dissatisfaction was caused by large area coverage with little to no facilitation, poor communication, and lack of a supporting system. The cost of surveillance data was found to be 1.4 times higher than the annual surveillance budget. The timeliness of the system ranged between 0 and 153 days from the observation date (median = 2 days, mean = 6 days). The study pointed out some deviations in animal health surveillance processes from the standard guidelines and their implication on the system's performance. The system could be improved by developing a user-friendly unified reporting system, the active involvement of subnational level animal health officials, optimization of data sources and an increase in the horizon of the financing mechanism.

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Towards an Integrated Animal Health Surveillance System in Tanzania: Making Better use of Existing and Potential data Sources for Early Warning Surveillance

10.21203/rs.3.rs-106955/v1 ◽

2020 ◽

Author(s):

Janeth George ◽

Barbara Häsler ◽

Erick Komba ◽

Calvin Sindato ◽

Mark Rweyemamu ◽

...

Keyword(s):

Early Warning ◽

Surveillance System ◽

Animal Health ◽

Health Surveillance ◽

Surveillance Data ◽

Data Sources ◽

Surveillance Systems ◽

Cross Sectional Survey ◽

Traceability System ◽

Spatial Coverage

Abstract Background: Effective animal health surveillance systems require reliable, quality, and timely data for decision-making. The animal health surveillance system in Tanzania has been relying on a few data sources, which suffer from delays in reporting, underreporting, and high cost of data collection and transmission. The integration of data from multiple sources can enhance early detection and response to animal diseases and consequently facilitate the early control of outbreaks. The study aimed to identify and assess the existing and potential data sources for animal health surveillance system in Tanzania and how they can better be used for early warning surveillance. The study used mixed-method design to identify and assess data sources. Data were collected through document reviews, internet search, cross-sectional survey, key informant interviews, site visits, and non-participant observation. The assessment was done using pre-defined criteria.Results: A total of 13 data sources were identified and assessed. Most surveillance data came from livestock farmers, slaughter facilities, and livestock markets, while animal dip sites were the least used sources. Commercial farms and veterinary shops, electronic surveillance tools like AfyaData and Event Mobile Application (EMA-i) and information systems such as Tanzania National Livestock Identification and Traceability System (TANLITS) and Agricultural Routine Data System (ARDS) show potential to generate relevant data for the national animal health surveillance system. The common variables found across most sources were: the name of the place (12/13), animal type/species (12/13), syndromes (10/13) and number of affected animals (8/13). The majority of the sources had good surveillance data contents and were accessible with medium to maximum spatial coverage. However, there was significant variation in terms of data frequency, accuracy and cost. There were limited integration and coordination of data flow from the identified sources with minimum to non-automated data entry and transmission. Conclusion: The study demonstrated how the available data sources have great potential for early warning surveillance in Tanzania. Both existing and potential data sources had complementary strengths and weaknesses; a multi-source surveillance system would be best placed to harness these different strengths.

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Sykdomspulsen One Health - A real time surveillance system in an infrastructure coping with half a million analysis a day

ARPHA Conference Abstracts ◽

10.3897/aca.4.e68891 ◽

2021 ◽

Vol 4 ◽

Author(s):

Clemence Koren ◽

David Swanson ◽

Gry Grøneng ◽

Gunnar Rø ◽

Petter Hopp ◽

...

Keyword(s):

Public Health ◽

Real Time ◽

Surveillance System ◽

One Health ◽

Animal Health ◽

Cost Effective ◽

Health Surveillance ◽

Weather Data ◽

Joint Project ◽

R Shiny

Sykdomspulsen is a real time surveillance system developed by the Norwegian Institute of Public Health (NIPH) for One Health surveillance and the surveillance of other infectious diseases in humans like respiratory diseases and lately covid-19. The One Health surveillance comprise of Campylobacter data from humans and chicken farms and also includes diagnosis codes from doctor appointments and weather data with analysis forecasting outbreaks in Norway. It is a joint project between the Norwegian Institute of Public Health (NIPH) and the Norwegian Veterinary Institute (NVI), under the framework of the OHEJP NOVA (Novel approaches for design and evaluation of cost-effective surveillance across the food chain) and MATRIX (Connecting dimensions in One-Health surveillance) projects. The system relies on two pillars, the first being an analytics infrastructure which in real time retrieves data from tens of sources, cleans and harmonizes it, then runs over half a million analyses each day and produces over 20 000 000 rows of results to be used every day. The analytics infrastructure is based on R. Results are notably being used by NIPH for the monitoring of covid-19 development and the surveillance of other transmittable diseases such as influenza and gastro-intestinal illness. The analytics framework also generates hundreds of reports every day, directed at dissemination to municipal health authorities. This framework is not currently publicly available, but an open-source release is expected by the end of 2021. The second pilar is an interactive R Shiny dashboard platform, which is used for communicating the data and the model results to partner organisations. It allows for the easy creation of a website where public and animal health researchers and food safety experts can view real time analyses. This dashboard combines the powerful data visualisation and analysis strength of R with the accessibility, flexibility, structure and interactivity of web-based platforms. The result is a real time interactive surveillance system, that is supported by a solid infrastructure and streamlined data flow, and shared with actors through a beautiful and user-friendly website, based entirely on R.

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Proceedings of the International Workshop ‘Integration of International Expertise in the Development of a Mental Health Surveillance System in Germany’

BMC Proceedings ◽

10.1186/s12919-020-00186-0 ◽

2020 ◽

Vol 14 (S4) ◽

Keyword(s):

Mental Health ◽

Surveillance System ◽

International Workshop ◽

Health Surveillance

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Understanding the pharmaceutical approach to pain management in canine osteoarthritis

Companion Animal ◽

10.12968/coan.2021.0039 ◽

2021 ◽

Vol 26 (6) ◽

pp. 73-80

Author(s):

Hannah Capon

Keyword(s):

Surveillance System ◽

Best Practice ◽

Animal Health ◽

Management Strategies ◽

Companion Animal ◽

Multimodal Approach ◽

Pharmaceutical Management ◽

Veterinary Surgeons ◽

Canine Population ◽

Canine Osteoarthritis

Canine osteoarthritis was recently reclassified as a welfare concern by the Veterinary Companion Animal Surveillance System (VetCompass), an initiative run by the Royal College of Veterinary Surgeons, focused on improving companion animal health. This condition is a common cause for consultation in first opinion practice, with an estimated 35% of the canine population being affected. Chronic pain is complex and a multimodal approach is best for management, which includes pharmaceuticals employed in a methodical manner. This article provides an overview of the types of pain associated with canine osteoarthritis, as well as how to recognise them. Making reference to hypothetical cases, the appropriate pharmaceutical management is described. Further management strategies, as part of a multimodal approach, are summarised to ensure best practice.

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