Past, present, and future: a situational analysis of infectious disease modelling in Thailand

Abstract

Infectious disease modelling (IDM) is a useful tool supporting evidence to inform policies on disease outbreaks. Understanding situation, existing capacities and needs will enable countries to prepare and use the evidence derived from IDM for future outbreaks. This report maps Thailan's IDM landscape, identifies key stakeholders, and provides recommendations to develop a supportive ecosystem. We found that there is a moderate capacity to conduct and use IDM in Thailand. Users of IDM are spread across ministries and government level, while IDM evidence suppliers operate in departments in a few universities. Key challenges concern availability and quality of data, human resource capacity, integration of initiatives and communication mechanisms between evidence users and providers, and sustainable funding for IDM activities. Investing in human and data infrastructure, including IDM ecosystem development, could enhance Thailand's capacity to synthesise and use evidence for future outbreak preparedness, while also contributing to regional efforts in health security and outbreak response.

Funding: This study was supported by a grant from the Rockefeller Foundation [2022 ARO 004] and the National Science, Research and Innovation Fund, Thailand Science Research and Innovation (TSRI).

Keywords: Infectious diseases; Mathematical modelling; SWOT; Situational analysis; Thailand.

Fig. 1

Overview of the process flow for modelling work addressing diseases of human health. Light yellow indicates needs where modelling work could help address. Dark blue represents the demand side or users of evidence from modelling. Purple denotes the supply side, including entities involved in evidence synthesis and provision. Orange highlights interactions with the public and/or broader stakeholders. ∗This can be a sub-committee established for certain outbreaks.

Fig. 2

Overview of the process flow for modelling work addressing diseases of animal health. Light yellow indicates needs where modelling work could help address. Dark blue represents the demand side or users of evidence from modelling. Purple denotes the supply side, including entities involved in evidence synthesis and provision. Orange highlights interactions with the public and/or broader stakeholders.

Fig. 3

A graph illustrating the overall number of dynamic modelling studies published in international databases between 1970 and 2023 (the search teams available inSupplementary 1).