Modelling mass drug administration strategies for reducing scabies burden in Monrovia, Liberia.

Liberia agent-based modelling mass drug administration scabies transmission

Journal

Epidemiology and infection
ISSN: 1469-4409
Titre abrégé: Epidemiol Infect
Pays: England
ID NLM: 8703737

Informations de publication

Date de publication:
18 08 2023
Historique:
medline: 26 9 2023
pubmed: 18 8 2023
entrez: 18 8 2023
Statut: epublish

Résumé

Scabies is a parasitic infestation with high global burden. Mass drug administrations (MDAs) are recommended for communities with a scabies prevalence of >10%. Quantitative analyses are needed to demonstrate the likely effectiveness of MDA recommendations. In this study, we developed an agent-based model of scabies transmission calibrated to demographic and epidemiological data from Monrovia. We used this model to compare the effectiveness of MDA scenarios for achieving scabies elimination and reducing scabies burden, as measured by time until recrudescence following delivery of an MDA and disability-adjusted-life-years (DALYs) averted. Our model showed that three rounds of MDA delivered at six-month intervals and reaching 80% of the population could reduce prevalence below 2% for three years following the final round, before recrudescence. When MDAs were followed by increased treatment uptake, prevalence was maintained below 2% indefinitely. Increasing the number of and coverage of MDA rounds increased the probability of achieving elimination and the number of DALYs averted. Our results suggest that acute reduction of scabies prevalence by MDA can support a transition to improved treatment access. This study demonstrates how modelling can be used to estimate the expected impact of MDAs by projecting future epidemiological dynamics and health gains under alternative scenarios.

Identifiants

pubmed: 37593956
doi: 10.1017/S0950268823001310
pii: S0950268823001310
pmc: PMC10548539
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e153

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Auteurs

Nefel Tellioglu (N)

School of Computing and Information Systems, The University of Melbourne, Melbourne, VIC, Australia.

Rebecca H Chisholm (RH)

Department of Mathematical and Physical Sciences, La Trobe University, Bundoora, VIC, Australia.
Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.

Patricia Therese Campbell (PT)

Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
Department of Infectious Diseases, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia.

Shelui Collinson (S)

Clinical Research Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK.

Joseph Timothy (J)

Department of Disease Control, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK.

Karsor Kollie (K)

Ministry of Health, Monrovia, Liberia.

Samuel Zayzay (S)

Ministry of Health, Monrovia, Liberia.

Angela Devine (A)

Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
Global and Tropical Health Division, Menzies School of Health Research, Charles Darwin University, Darwin, NT, Australia.

Jodie McVernon (J)

Department of Infectious Diseases, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia.
Victorian Infectious Diseases Reference Laboratory, The Royal Melbourne Hospital at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia.

Michael Marks (M)

Clinical Research Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Hospital for Tropical Diseases, University College London Hospital, London, UK.
Division of Infection and Immunity, University College London, London, UK.

Nicholas Geard (N)

School of Computing and Information Systems, The University of Melbourne, Melbourne, VIC, Australia.

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Classifications MeSH