Table 1. Summary of principles of good HIV epidemiology modelling.

Principle	Model Producer Considerations	Model Consumer Considerations
Clear rationale, scope, and objectives	Are the rationale, scope, and objectives clearly stated?	Are the rationale, scope, and objectives understood?
	Is there a statement about why epidemiological modelling is appropriate for this problem?	Is epidemiological modelling appropriate for this problem?
Explicit model structure and key features	Is the model structure completely described, such that all analyses can be reproduced?	Is the model presented comprehensively, such that the inclusion/exclusion of any particular assumption or feature can be identified?
	Is there a description of key model features?	Is the justification for model structure/key assumptions reasonable, considering the primary rationale, scope, and objectives of the study?
	Has a justification for the model structure been provided?
Well-defined and justified model parameters	Is there an understandable and complete listing of the model parameters, their values, and their justification?	Are the implicit inputs upon which the model predictions are made understood, and are they satisfactorily justified?
Alignment of model output with data	Are the model fitting, calibration, and validation approaches with respect to relevant data defined and justified?	Does the model produce, or fail to produce, outputs that can be compared to real world data, and does the model output reflect realistic conditions?
		Does the comparison with real world data increase confidence in the suitability of the model for the current enquiry?
Clear presentation of results, including uncertainty in estimates	Have the uncertainties been captured for all relevant factors included in the model?	Have the uncertainties been captured for all relevant factors included in the model?
	Is the key result of the study robust to that uncertainty?	Are the results sufficiently robust for confident decision-making, or is further analysis or data collection required?
	Are specific recommendations for new data analyses/collections appropriate?
Exploration of model limitations	Are sufficient details provided about limitations of the study, specifically about model structure, parameterization, and application/generalisability?	Are the limitations of the model and its findings clearly understood, including the limits of applicability and generalisability?
		Considering the strength of the evidence, how are the model findings relevant for informing public health decision-making?
Contextualisation with other modelling studies	Have relevant previous studies been referenced and differences/similarities discussed?	Is there an understanding of the overarching conclusion(s) from modelling studies on the topic?
	Is it clearly specified whether a new result versus a confirmation/contradiction of a previous result is presented?	Are the general reasons (assumptions or underlying real world conditions) for why models differ in their conclusions understood?
Application of epidemiological modelling to health economic analyses	Where relevant, are understandable and appropriate estimates of epidemiological impact provided, such that health economic inferences can be made?	Can the model-based estimates be used to infer cost-effectiveness measures of relevant interventions or be extended to health economics?
		Is the degree of uncertainty in estimates relevant to cost-effectiveness understood, particularly with respect to the sensitivity of key parameters?
Clear language	Are model scenarios described in clear formal terms (separate from interpretations about reality) that facilitate technical understanding and evaluation?	Are there clear explanations of intended correspondences between inputs used in the model and key real world conditions such as epidemiological conditions, policy, and programmes?