Research and analysis

International Disease Monitoring Plus (IDM+) tool

Published 21 August 2025

Applies to England, Scotland and Wales

Introduction 

Trade of live animals and products of animal origin (POAO) carries an inherent risk of spreading pathogens. It is essential for any country to have effective early detection and horizon-scanning systems to detect potential entry risks. 

International Disease Monitoring Plus (IDM+) develops these surveillance systems into a generic, semi-quantitative risk assessment tool. The IDM+ tool aims to provide biosecurity assurances that imports of live animals and POAO into Great Britain are safe by assessing the likelihood of entry of animal health diseases through legal, commercial trade. Food safety concerns are not considered in this overview.

Methods 

Model framework 

An overview of the model framework is outlined in figure 1. This represents a risk pathway that could result in a microbial animal health hazard arriving at Great Britain’s border through legal, commercial imports of live animals and POAO. 

IDM+ represents the hazard identification and entry assessment components of a risk assessment. It focusses on 3 main factors to calculate the entry likelihood:  

• country of origin 
• hazard 
• commodity

Figure 1: Simplified model framework

Figure 1 is a simplified model framework, showing how for each ‘hazard-commodity-country’ combination, the data inputs and qualitative risk likelihoods are combined to estimate the final entry likelihood score and model outputs.  

The data inputs include:  

• expert opinion 
• country reported disease status using the World Organisation of Animal Health’s (WOAH) World Animal Health Information System (WAHIS) data 
• commodity trade volumes using His Majesty’s Revenue and Customs (HMRC) UK trade data 

The qualitative risk likelihoods estimated are: 

• pre-export risk mitigation likelihood 
• country status likelihood 
• commodity risk likelihood  

Data inputs  

The following 5 data inputs are required: 

1. Hazards: 125 WOAH-listed animal health hazards. 
2. Countries of origin: 31 EU or EFTA member states and 24 other countries representing a range of geographical locations and disease statuses. 
3. Commodities and commodity categories: 27 commodity categories comprising more than 2,300 individual commodities defined by publicly available combined nomenclature 8-digit level (CN8) codes. 
4. Commodity trade volumes: monthly trade volumes of CN8 imported commodities are extracted from the publicly available HMRC repository of UK trade data. 
5. Country reported disease status: disease status (presence or absence) determined from the number of outbreaks in each country (or inference from surrounding regions) over the last 4 years, as reported to WOAH-WAHIS. 

Model parameters  

The following 4 model parameters are utilised with the data inputs to produce the model outputs: 

1. Country status likelihood: probability that a randomly selected animal in the country of origin will be infected with each hazard, estimated based on the yearly country reported disease status (data input 5).  
2. Pre-export risk mitigation likelihood: estimated from current approvals and restrictions for imports of live animals and POAO to Great Britain combined with an expert opinion elicitation exercise on effectiveness of SPS measures. 
3. Commodity risk likelihood: the likelihood of each identified hazard being present in each product at entry into Great Britain is determined by an expert elicitation exercise. 
4. Entry likelihood: final additive risk score for each ‘country-commodity’ combination (figure 1). 

Model implementation 

Structured query language (SQL) prompts linking likelihood parameters to a large database with the input data combinations are implemented in R (v.4.4.1). 

For each ‘hazard-commodity-country’ combination, the country status, commodity risk, and pre-export risk mitigation likelihoods are combined using a qualitative risk matrix into an overall entry likelihood score. 

A final risk score is generated for each ‘country-commodity’ combination, by aggregating the scores for all hazards associated with that combination.  

The risk scores are:  

• Negligible 
• Very Low 
• Low 
• Medium 
• High  
• Very High 

The model is stored on a private GitHub repository. Public access is not currently provided due to the confidential nature of the code and data.  

Model outputs 

The entry likelihood scores are presented as 2 core model outputs, weighted with and without trade volumes. For each output, the results are aggregated to give 3 different likelihood options:  

• median 
• upper 20th percentile 
• maximum 

Results 

Identifying the likelihood of a hazard arriving at the border of Great Britain involves:  

• more than 550 aggregated individual product types 
• 125 hazards 
• 55 countries 

With multiplicative ‘country × hazard × commodity’ combinations, there are many thousands of combinations for which a likelihood estimation is required. An example of the model output is shown in Table 1. 

Table 1: Example model output

Country of origin	Live animals non-trade-weighted	Live animals trade-weighted	Dairy products non-trade-weighted	Dairy products trade-weighted	Table eggs and egg products non-trade-weighted	Table eggs and egg products trade-weighted	Pork meat and meat products non-trade-weighted	Pork meat and meat products trade-weighted	Porcine by-products non-trade-weighted	Porcine by-products trade-weighted
A	Low	High	Medium	Very Low	Very Low	Very Low	Very Low	Very Low	Very Low	Very Low
B	Medium	NA	Low	Very Low	Low	Very Low	Medium	High	High	Very High
C	Very Low	Prohibited	Very Low	Negligible	Negligible	NA	Medium	Prohibited	Medium	NA

Table 1 is an example model output using hypothetical data for the aggregated entry likelihood assessments: the total annual pathway likelihood (non-trade weighted and trade-weighted aggregations), integrated across all hazards for a selection of example commodity categories and stratified by hypothetical countries.  

‘NA’ means zero-trade volume in that commodity category from that country of origin; ‘prohibited’ means imports are not permitted.

Discussion and conclusion 

The IDM+ model methodology can be used by any country to assess import risks of live animals or POAO. 

IDM+ has several advantages, in that: 

• it is quick to run using a largely automated process, making it a valuable tool that can be used in time-constrained environments 
• it improves cost efficiency by using existing, publicly available data sources for likelihood estimation 
• data inputs can be easily updated, providing ongoing and rapid appraisal of changes in global pathogen distribution and trade volumes 
• its versatile presentation of results allows for trade volume weighting and required likelihood thresholds 
• it is suitable for a variety of purposes, including prioritisation of border inspections and in-country audits; rapid output generation for emergency outbreak assessments; and assessing risk from specific imported consignments 

While it offers higher uncertainty and less detail than traditional, resource-intensive risk assessments, IDM+ is an asset in time-constrained and resource-limited environments. This allows risk managers to effectively target resources, allowing them to respond to import risks under increasingly changeable environmental, epidemiological, and economic pressures. 

A more detailed description of the IDM+ methodology can be found in the following scientific paper: Royden, A. et al. 2025. An international disease monitoring tool to estimate the likelihood of entry of animal health hazards from legal trade of live animals and products of animal origin imported from different countries (IDM+). Microbial Risk Analysis 29, 100338.