Kebede Amenu1,2,3*
K. Marie McIntyre1,4,5
Nebyou Moje6
Theodore Knight-Jones1,3
Jonathan Rushton1,4
Delia Grace1,7,8- 1Global Burden of Animal Diseases (GBADs) Programme, University of Liverpool, Liverpool, United Kingdom
- 2Department of Microbiology, Immunology and Veterinary, Public Health, College of Veterinary Medicine and Agriculture, Addis Ababa University, Bishoftu, Ethiopia
- 3Animal and Human Health Program, International Livestock Research Institute (ILRI), Addis Ababa, Ethiopia
- 4Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, United Kingdom
- 5Modelling, Evidence and Policy Group, School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
- 6Department of Biomedical Sciences, College of Veterinary Medicine and Agriculture, Addis Ababa University, Bishoftu, Ethiopia
- 7Food and Markets Department, Natural Resources Institute, University of Greenwich, London, United Kingdom
- 8Animal and Human Health Program, International Livestock Research Institute (ILRI), Nairobi, Kenya
This scoping review identifies and describes the methods used to prioritize diseases for resource allocation across disease control, surveillance, and research and the methods used generally in decision-making on animal health policy. Three electronic databases (Medline/PubMed, Embase, and CAB Abstracts) were searched for articles from 2000 to 2021. Searches identified 6, 395 articles after de-duplication, with an additional 64 articles added manually. A total of 6, 460 articles were imported to online document review management software (sysrev.com) for screening. Based on inclusion and exclusion criteria, 532 articles passed the first screening, and after a second round of screening, 336 articles were recommended for full review. A total of 40 articles were removed after data extraction. Another 11 articles were added, having been obtained from cross-citations of already identified articles, providing a total of 307 articles to be considered in the scoping review. The results show that the main methods used for disease prioritization were based on economic analysis, multi-criteria evaluation, risk assessment, simple ranking, spatial risk mapping, and simulation modeling. Disease prioritization was performed to aid in decision-making related to various categories: (1) disease control, prevention, or eradication strategies, (2) general organizational strategy, (3) identification of high-risk areas or populations, (4) assessment of risk of disease introduction or occurrence, (5) disease surveillance, and (6) research priority setting. Of the articles included in data extraction, 50.5% had a national focus, 12.3% were local, 11.9% were regional, 6.5% were sub-national, and 3.9% were global. In 15.2% of the articles, the geographic focus was not specified. The scoping review revealed the lack of comprehensive, integrated, and mutually compatible approaches to disease prioritization and decision support tools for animal health. We recommend that future studies should focus on creating comprehensive and harmonized frameworks describing methods for disease prioritization and decision-making tools in animal health.
Introduction
Livestock production is an economic process in which resources (inputs) are converted into products (outputs) (1). Livestock plays an important economic role across the world, especially in developing countries, as one of the main sources of livelihood (2). However, the livestock sector is constrained by many factors, including disease, which limits livestock production and productivity (3). Diseases negatively influence the conversion of inputs into outputs in the livestock industry, causing direct and indirect costs (4). Direct costs include mortality, reduction in the efficiency of production processes (e.g., reduced feed conversion), and reduced quantity or quality of products. Indirectly, the cost of a disease is associated with additional expenses due to disease management (vaccinate, treat, or control), public health impacts, and suboptimal use of resources, e.g., feed and water, due to infestation by disease vectors in specific localities (5).
Profitable investment in livestock production requires targeted control and prevention strategies, treatment, and surveillance of important diseases (6). Investment in mitigation of livestock disease and improvements in animal health aim to reduce production losses and minimize control costs. However, deciding where best to invest to optimize returns is complex in a livestock system that is often part of more complex systems; decisions for the farm may be made at the household level and across a range of different options at the policy level. Furthermore, there are various sociocultural and non-financial aspects to be considered in both farm- and national-level animal health control activities. A multitude of diseases and pathogens affect animals, including humans, and control efforts must be prioritized, given there are limited available resources (e.g., time, financial resources, etc.), to ensure optimal resource allocation (7, 8). The nature of the impacts of diseases varies with the pathogen and the livestock system affected. In some cases, the indirect costs of livestock diseases, especially zoonotic diseases, through their impacts on other sectors are much greater than the impact on livestock productivity. The costs of zoonoses are mainly due to non-livestock losses (9). The reaction to the presence of non-zoonotic diseases has major effects on the overall burden of disease; for example, the 2001 foot-and-mouth disease (FMD) outbreak in the UK, where there was a significant reduction in income due to shutting down the countryside and loss of tourism (10). Similarly, FMD control measures in Southern Africa had huge impacts on wildlife ecology and marginalized smallholders (11). However, endemic parasitic worm infections impact mostly through direct impacts on productivity and control costs (12), albeit the impacts of these farm-level productivity losses are rarely translated into wider economic impacts that affect downstream actors in the food system and consumers.
The basic principle of prioritizing different diseases within animal health is to maximize net benefits from allocating resources compared with the opportunity costs of alternative resource use (8). This ensures appropriate resource allocation within targeted actions, maximizing the potential benefits to animal health, public health, and the economy. The development and use of prioritization methods within human healthcare started formally several decades ago; infectious disease control and surveillance measures were targeted under the condition that not all diseases should be given equal weights for prevention and control (13). In animal health, various methods have been developed for disease priority setting and resource allocation programs. These include quantitative and qualitative approaches, such as decision tree analysis, expert opinion elicitation, risk-based assessment, semi-quantitative and quantitative scoring frameworks, and multi-criteria decision tools (8, 14–18).
However, despite its importance, the broad topic of disease prioritization for animal health priority setting lacks structure, and it exists as a range of ad hoc disparate tools and projects. This scoping review aims to collect the approaches used in disease prioritization and tools for animal decision-making processes. The concept of this study was developed with a view to designing a comprehensive framework for animal health decision-making and resource allocation.
Methods
A scoping review investigating methodological approaches to animal health priority setting and decision-making tools was carried out according to the updated Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-SLR) extension for Scoping Reviews (19). In the review, prioritization was considered a process to decide the relative importance of animal health issues (e.g., the importance of diseases and their pathogenic causes, strategies for prevention, surveillance, control or research, drug treatment choices, etc.). In addition, studies that generated evidence to support decision-making, such as economic analysis, risk assessment, and spatial mapping regarding animal diseases, were also included. Therefore, the review included studies that actually or potentially assisted decisions to optimize resource use for animal disease mitigation.
Information sources and search strategy of articles
Major bibliographic databases were systematically searched using a specific syntax for the articles retrieved. Three electronic databases (Medline/PubMed, Embase, and CAB Abstracts) were examined using the search syntax (Supplementary material 1). Keywords for the searches were identified by a detailed review of the contents of selected articles. Keywords were refined by searching for synonyms and formatted using Boolean operators. Initially, language filters were not applied, but English language literature was targeted during data extraction, and other languages were also included where articles had abstracts available in English.
Eligibility criteria (exclusion and inclusion criteria)
Eligibility criteria defining articles to be included or excluded were developed and applied. Studies had to report “real-life” (not theoretical) application of prioritization methodologies for animal diseases, generating evidence for prioritization or decision-making by targeting the strategies identified for disease control, prevention, or surveillance at various levels (single organization or farm, local, sub-national, national, or international). Publications written in English from 1 January 2000 to 13 August 2021 (last date of search) were included. Discussion papers, reviews, and commentaries not addressing a “real-life” prioritization exercise and not implicating prioritization methods directly were not included. Studies focusing on theoretical prioritization issues (e.g., methodology development without presenting a case study on the application of the developed methods) were excluded. Prioritization studies of purely human diseases (including zoonotic diseases originating in animals but currently transmitting from human to human such as HIV/AIDS) were excluded. However, articles presenting a mix of animal and purely human diseases were considered, taking into account the animal aspects as inclusion criteria.
Literature screening based on inclusion/exclusion criteria
Literature screening was based on the article title and abstract and was carried out by two independent reviewers, with disagreements resolved by discussion. If article abstracts were not available, the full text was screened. During the first-round screening of literature, the aforementioned eligibility criteria were used. Additionally, the geographic range covered was recorded (local, sub-national, national, and global).
In the second round of screening, retained articles were categorized based on (1) the prioritization or priority setting methods used (economic-based, simple ranking of diseases, multi-criteria, qualitative risk assessment, quantitative risk analysis, spatial (geographic) risk mapping, mix of different prioritization techniques, and other) and (2) the prioritization purpose—what the prioritization was designed to assess (disease control and prevention strategies, general importance of diseases or animal health issues, risk of disease prioritization, spatial risk mapping or analysis, disease surveillance, and research priority settings).
Article selection process and data extraction process
The information extracted from the articles included the full bibliographic citation of the retrieved article (including authors, titles, year of publication, and journal), types of prioritizations or types of studies for evidence generation (ranging from economic, multi-criteria, spatial, risk assessment, mathematical modeling, or simple ranking), the continent of the article covered (when specified), and the geographic ranges of the focus of the articles (local to global). The different categories and sub-categories of the prioritization techniques were identified during screening and the extraction of information from the initial articles when preparing a template for full data extraction. The outputs in line with the purposes or objectives of the prioritization or evidence generation for decision-making were classified into various groups, which include general disease importance, assessment of risks (new introduction or spatial risk), and research priority setting. Species of animals and diseases or health issues mentioned in each article were also extracted. The categorization was carried out to determine how the outputs will inform users and influence decision-makers in the sense of what the prioritization process or analysis ultimately answers. The diseases, pathogens, or general health issues under consideration in each article have been extracted and presented as priorities in the form of study outputs. Species of animals considered in each article were also extracted when specified as a single species or a group of animals (e.g., ruminants, wildlife, small ruminants, equine, etc.). Species of animals described in the articles were extracted when applicable, if not presented as animals or livestock in general. The study could be focused on general livestock, specific animal species, or multiple species. Some health situations were described without mentioning diseases.
Data extraction was carried out using a form prepared in Kobotoolbox (www.kobotoolbox.org, an online data collection tool). A template for extraction was developed and pre-tested on 2–3 articles in each of the different categories. The online data capturing tool was used instead of a spreadsheet (Excel) due to its convenience for designing the formats using logics (e.g., skip patterns) and adding entries collaboratively. The online tool can accommodate complex formats, including uploading files to the system. Finally, the extracted data were exported into a spreadsheet and managed.
Results
Retrieved and screened articles
The online search identified 6, 726 articles, and upon manual searching, an additional 64 articles were added and 330 were removed due to duplicates. A total of 6, 460 articles were finally imported into online systematic review management software (20) for screening. Based on inclusion and exclusion criteria, 532 articles passed the first screening, and after a second round of screening, 336 were recommended for full review. In the preparation for data extraction, upon downloading the articles, 40 articles were excluded due to lack of full text, and 11 articles were added by snowballing from the reference lists of already identified articles. Thus, the total number of articles for final inclusion and full review was 307 (Figure 1).
Figure 1. Preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram depicting the number of articles retrieved and screened sequentially (selected for full-text download, data extraction, and quality check) describing animal disease prioritization methods and processes (n = 307).
Categories of disease or animal health issues prioritization methods, yearly publication, and continental geographic distribution
Of the 307 retained articles that were fully reviewed, the results were presented under the following methods categories: (a) 96 articles on economic analysis (21–116), (b) 59 articles on multi-criteria prioritization (14, 117–173), (c) 57 articles on risk assessment (174–230), (d) 38 articles on spatial analysis (231–268), (e) 27 articles on the simple ranking of disease or animal health issues (269–295), (f) 17 articles on mathematical modeling (296–312), and (g) 13 other articles (313–325) (Table 1).
Table 1. Categories of disease or animal health issue prioritization methods in retained papers (n = 307).
The annual number of publications relevant to this review increased over time, with articles using multi-criteria prioritization methods available from 2010 onward and economic analyses more evenly distributed over the duration of the two decades of publication (Figure 2).
Figure 2. Annual (2000–2021) distribution of the articles included for data extraction disaggregated by animal health (disease) prioritization method (n = 307); *(decision tree, H-index, and combinations of different methods).
The geographic focus of the articles was Europe (35.8%), followed by Africa (18.9%) and then North America (13.0%). European disease prioritization and evidence for decision-making studies focused on risk assessment (52.6%), and African studies mostly (63.0%) used simple ranking of diseases or health problems. Half of the articles (50.8%) focused on national-level prioritization or evidence generation for decision-making, and this figure increased to nearly 60% when multi-criteria methods were used. For articles describing spatial analysis methods, 47.5% of them focused on the national level. The number of articles describing global-level prioritizations was very limited (n = 13) (Table 2).
Table 2. Number of articles and methods used for prioritization disaggregated by continent and geographic focus.
Purposes of prioritization
Of the 307 articles reviewed, 39.1% were focused on prioritizations to help target disease control, prevention, or eradication strategies, and 23.0% were to aid in the identification of priority diseases to inform general organizational strategy (Table 3).
Table 3. The purposes of the prioritizations described in the articles presented in this scoping review (n = 307).
Sub-categories of the methods of multi-criteria prioritization and economic analysis
This part of our study describes the sub-categories of prioritization and evidence-generating studies (economic analysis, multi-criteria prioritization, and risk assessment). Different sub-types of multi-criteria prioritization studies largely based on weighting techniques were identified (Table 4). The common technique applied was the Phylum applied in studies in eastern African countries. The brief definitions of the different sub-categories are described in Supplementary material 2.
Table 4. The types of multi-criteria prioritization methods (n = 59).
For economic analysis, cost-benefit analysis was the most commonly used economic analysis method for prioritization (48 articles), followed by cost-effectiveness analysis (34 articles). The use of partial budget analysis was reported in 12 articles, respectively (Table 5).
Table 5. Common economic analytical methods in animal health (n = 96).
Out of the total articles dealing with risk assessment, 29, 21, and 7 articles used qualitative, quantitative, and both (qualitative and quantitative), respectively.
Prioritized diseases
The importance of different diseases was examined in prioritization exercises involving different methods (Table 6). Paratuberculosis was most commonly examined (10 out of 96 articles) within economic analyses, with rabies, brucellosis, and FMD commonly assessed in multi-criteria prioritizations. African swine fever and FMD were most often assessed in risk assessments. FMD was also the most considered disease using simple ranking methods (Table 6).
Table 6. The top three diseases or health (with some described by their pathogenic causes) commonly targeted using different disease prioritization methods*.
For all articles combined, FMD (54 articles), bovine brucellosis (40 articles), and rabies (39 articles) were the common diseases considered in the articles. From the total articles, 20 assessed general animal health situations without mentioning specific diseases (Supplementary material 3).
Table 7 depicts the type of animal species or group of species considered in the articles included in the present scoping review. Accordingly, cattle are the most common animals considered by the articles, followed by pigs (Table 7).
Table 7. Animal species (type) considered in the articles included in the scoping review.
Discussion
This scoping review examined published literature describing the prioritization of animal and zoonotic diseases by reviewing a total of 307 published articles. The context of prioritization in the review was taken as studies that either explicitly prioritized the relative importance of diseases, those that prioritized animal health interventions based on one or more criteria, or those generating evidence for wider decision-making. Studies generating evidence used economic analysis, risk assessment (adverse effects of diseases assessed), spatial analysis (risk or disease distribution mapping), or modeling approaches.
In the reviewed articles, those describing economic analysis were dominant, followed by multi-criteria-based prioritizations. Disease prioritization is a complex decision-making process (8), and prioritization based on single approaches such as economic analysis and disease burden estimates may not be rigorous and inclusive enough (326). Health issues are inherently complex, involving an understanding of the economic, social, ethical, and cultural aspects of various stakeholders. These aspects need to be captured in the decision-making process. However, how these different aspects are all considered together, e.g., in multi-criteria prioritization and decision analysis, relies on arbitrary weightings of them; such analytical systems incur costs of time and understanding.
Economic analysis was widely used in prioritization studies by means of a range of approaches. Cost-benefit analysis and cost-effectiveness analysis are most commonly used in animal health, as reported in this and other studies (327). Cost-effectiveness analysis is often used for health interventions that do not have an agreed monetary value, such as human lives or animal welfare. We would expect cost-effectiveness analysis to be used more for zoonoses and diseases with high welfare implications. As an example, cost-effectiveness analysis was not used in any non-zoonotic diseases such as African swine fever, Peste des petits ruminants, and African horse sickness. However, it was used in brucellosis (11.8%), bovine tuberculosis (17.5%), and rabies (17.5%) (Supplementary material 4, raw dataset). Multi-criteria analysis was the second most common approach used for disease prioritization. Developed in the 1960s to aid complex decision-making processes within the environmental, engineering, finance, and management sciences (328, 329), multi-criteria decision analysis combines multiple, often conflicting, alternatives in order to reach a consensus on a given issue (330). The criteria for decision analysis can be measured qualitatively or quantitatively, and the technique has been relatively recently applied within animal health and, particularly, disease control (139). Multi-criteria decision analysis involves multiple steps: (1) identification of pathogens or diseases; (2) selection, weighting, and scoring of criteria; and (3) decision analysis (163). The selection and weighting of criteria according to the views of stakeholders is crucial for outputs to be appropriate (330). Within this study, the weighting methods were Preference Ranking Organization Method Enrichment of Evaluations (PROMETHEE) and Conjoint Analysis (CA) in four articles each; the specific methods used were not explicitly stated for many (34) articles.
Studies dealing with disease prioritization and those generating evidence for decision-making are increasing. This indicates the importance of such approaches in the optimization of resources for animal health and production investment. The finding that most disease prioritization studies are focused disproportionately on developed countries illustrates differences between countries in their capacities to undertake disease prioritization exercises. Several of the disease prioritization methods require expertise and resources in terms of time to complete. Available data to be used as inputs in prioritization methods can also be a reason that most studies come from developed countries. For reliable disease prioritization for resource allocation and decision-making, timely and high-quality data are required. Animal health information systems for developing countries are not well organized, constraining the practice of priority setting in animal health and the overall decision-making process.
The levels of analysis related to geographic or political administrative boundaries of the studies included in the present literature review showed that approximately half of the studies were at the national level, with minor global coverage. There are several highly infectious animal diseases that pose a global threat (transboundary diseases), potentially causing negative socioeconomic and public health consequences beyond national boundaries. This means that the burden and consequences of animal disease go beyond national boundaries; resource allocation for actions should consider such situations. In contrast, endemic diseases are often of local importance, and resources need to be allocated accordingly. This reflects the need for customizable disease prioritization and resource allocation tools that can be used in various scenarios to provide evidence-based decision-making processes for the efficient utilization of animal resources. The present scoping review showed that more complex tools (e.g., risk analysis, modeling, and economic analysis) are commonly used in more economically developed countries (e.g., Europe) compared to simple disease ranking tools being more often used in Africa. This indicates a need to build capacity for the use of complex tools in developing countries.
Various reasons behind the delivery of disease prioritization exercises were mentioned in the reviewed articles. The intention to design control, prevention, or eradication strategies by targeting single or multiple diseases was the most common reason. Overall, the ultimate intent or purpose of disease prioritization is to ensure the allocation of limited resources toward achieving the greatest benefit in improving and maintaining human and animal health (8). Apart from the relatively substantial number of articles identified in the present scoping review, the prioritization tools developed by various organizations and used for practical purposes targeting animal diseases, including zoonoses, were not commonly cited in the peer-reviewed publications identified in this review. Diseases or pathogens targeted in different studies included in the present review were quite diverse. Economic assessment was largely targeted at endemic diseases, of which, for example, paratuberculosis was the most common.
Conclusion
The present scoping review covered various approaches to disease prioritization, including those supporting decision-making in animal health. Some studies focused on explicit disease prioritization, and the remaining studies generated evidence. The scoping review revealed the lack of comprehensive, integrated, and mutually compatible approaches to disease prioritization and decision support tools for animal health; this could lead to sub-optimal resource allocation. It can be concluded that there is neither a dominant tool or sets of data being used nor a comprehensive understanding of how to prioritize actions to control specific diseases. Notably, there was more variation in prioritization analysis than in economic analysis. By far, the most popular approach was cost-benefit analysis (followed by cost-effectiveness analysis) in its true meaning. There is also a complete absence of studies on what investment is needed for the livestock sector in terms of research, education, and coordination. Accordingly, this demands further work to improve disease prioritization through the integration of existing or new approaches that could be related to disease impacts as a result of generic disease risks, spatial distribution, economic impacts, and public health impacts. In the present scoping review, only published articles in English were included, and this can be a limitation of the present study. All disease prioritization outputs may not be found in published formats, and the inclusion of gray literature in possible future studies is recommended.
Data availability statement
The original contributions presented in the study are included in the article/Supplementary material. Further inquiries can be directed to the corresponding author.
Author contributions
KA, KM, and DG conceptualized the study. KA and KM prepared the data retrieval query protocol. TK-J, DG, and JR reviewed the data retrieval protocol. KA and NM extracted data. KA drafted the initial manuscript. All authors made critical contributions in revising the manuscript and approved the final version.
Funding
This study was part of the Global Burden of Animal Diseases Programme (GBADs) funded by the Bill and Melinda Gates Foundation (BMGF) and Foreign, Commonwealth and Development Office (FCDO) UK (Grant number INV 005366).
Acknowledgments
We thank Dr. Vittoria Lutje who helped us to improve the review protocol and search criteria, translated the search strategies for the different electronic databases, ran the searches, and de-duplicated the results.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fvets.2023.1231711/full#supplementary-material
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Keywords: priority setting, animal health economics, resource allocation, risk assessment, spatial analysis, animal health investment, decision-making
Citation: Amenu K, McIntyre KM, Moje N, Knight-Jones T, Rushton J and Grace D (2023) Approaches for disease prioritization and decision-making in animal health, 2000–2021: a structured scoping review. Front. Vet. Sci. 10:1231711. doi: 10.3389/fvets.2023.1231711
Received: 30 May 2023; Accepted: 06 September 2023;
Published: 06 October 2023.
Edited by:
Paola Scaramozzino, Institute of Experimental Zooprophylactic of the Lazio and Tuscany Regions (IZSLT), ItalyReviewed by:
Sara Savic, Scientific Veterinary Institute Novi Sad, SerbiaBiswajit Bhowmick, The University of Tennessee, Knoxville, United States
Jordi Casal, Autonomous University of Barcelona, Spain
Copyright © 2023 Amenu, McIntyre, Moje, Knight-Jones, Rushton and Grace. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Kebede Amenu, k.amenu@cgiar.org