A multi-criteria framework for disease surveillance site selection: Case study for Plasmodium knowlesi malaria in Indonesia

Lucinda E. Harrison, Jennifer A. Flegg, Ruarai Tobin, Inke N.D. Lubis, Rintis Noviyanti, Matthew J. Grigg, Freya M. Shearer, David J. Price

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Abstract

Disease surveillance aims to collect data at different times or locations, to assist public health authorities to respond appropriately. Surveillance of the simian malaria parasite, Plasmodium knowlesi, is sparse in some endemic areas and the spatial extent of transmission is uncertain. Zoonotic transmission of Plasmodium knowlesi has been demonstrated throughout Southeast Asia and represents a major hurdle to regional malaria elimination efforts. Given an arbitrary spatial prediction of relative disease risk, we develop a flexible framework for surveillance site selection, drawing on principles from multi-criteria decision-making. To demonstrate the utility of our framework, we apply it to the case study of Plasmodium knowlesi malaria surveillance site selection in western Indonesia. We demonstrate how statistical predictions of relative disease risk can be quantitatively incorporated into public health decision-making, with specific application to active human surveillance of zoonotic malaria. This approach can be used in other contexts to extend the utility of modelling outputs.

Original languageEnglish
Article number230641
JournalRoyal Society Open Science
Volume11
Issue number1
DOIs
Publication statusPublished - 10 Jan 2024

Bibliographical note

Funding Information:
This study was supported through funding provided by the Australian Centre for International Agricultural Research (ACIAR) and the Indo-Pacific Centre For Health Security, DFAT, Australian Government, as part of the project: ‘Evaluating zoonotic malaria transmission and agricultural and forestry land use in Indonesia (ZOOMAL)’ (LS/2019/116). Further support was provided by the National Health and Medical Research Council of Australia through its Centres of Research Excellence (ACREME, GNT1134989). F.M.S. was supported by the National Health and Medical Research Council of Australia Investigator Grant Scheme (Emerging Leader Fellowship, 2021/GNT2010051). J.A.F. was supported by the Australian Research Council (ARC, FT210100034 and DP200100747). L.E.H. was supported by a Melbourne Research Scholarship from the University of Melbourne. M.J.G. was supported by the National Health and Medical Research Council of Australia Investigator Grant Scheme (Emerging Leader 2 Fellowship, 2023/GNT2017436).

Publisher Copyright:
© 2024 The Authors.

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