ASF Shiny app: An interactive web application for exploring premovement active surveillance scenarios for early African Swine Fever detection

Sasidhar Malladi; Peter J. Bonney; Sylvia Wanzala Martin; Amos Ssematimba; Kaitlyn St. Charles; Kathleen C. O'Hara; Marta D. Remmenga; Michelle Leonard; Holden C. Hutchinson; Cesar A. Corzo; Marie R. Culhane

doi:10.1016/j.softx.2025.102105

ASF Shiny app: An interactive web application for exploring premovement active surveillance scenarios for early African Swine Fever detection

Sasidhar Malladi, Peter J. Bonney, Sylvia Wanzala Martin, Amos Ssematimba, Kaitlyn St. Charles, Kathleen C. O'Hara, Marta D. Remmenga, Michelle Leonard, Holden C. Hutchinson, Cesar A. Corzo, Marie R. Culhane

Research output: Contribution to journal › Article › peer-review

Abstract

African Swine Fever (ASF) is a deadly, viral, swine disease with serious socio-economic impacts across the globe. Developing effective active surveillance strategies is critical, given the relatively long herd level incubation period for ASF. We developed an interactive web application that interfaces with a heterogeneous within-herd disease transmission model and enables rapid exploration of various ASF transmission scenarios and premovement surveillance options for finisher swine herds. The application demonstrates the effects of various surveillance design aspects and illustrates the benefit of an enhanced targeted biosecurity interval before movement. Developing such interactive tools can help translate complex mathematical models, and advance communication of ASF risk and surveillance strategies.

Original language	English (US)
Article number	102105
Journal	SoftwareX
Volume	30
DOIs	https://doi.org/10.1016/j.softx.2025.102105
State	Published - May 2025

Bibliographical note

Publisher Copyright:
© 2025

Keywords

Active surveillance
African Swine Fever
Disease transmission dynamics
R Shiny
Simulation models

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.softx.2025.102105

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Malladi, S., Bonney, P. J., Martin, S. W., Ssematimba, A., St. Charles, K., O'Hara, K. C., Remmenga, M. D., Leonard, M., Hutchinson, H. C., Corzo, C. A., & Culhane, M. R. (2025). ASF Shiny app: An interactive web application for exploring premovement active surveillance scenarios for early African Swine Fever detection. SoftwareX, 30, Article 102105. https://doi.org/10.1016/j.softx.2025.102105

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title = "ASF Shiny app: An interactive web application for exploring premovement active surveillance scenarios for early African Swine Fever detection",

abstract = "African Swine Fever (ASF) is a deadly, viral, swine disease with serious socio-economic impacts across the globe. Developing effective active surveillance strategies is critical, given the relatively long herd level incubation period for ASF. We developed an interactive web application that interfaces with a heterogeneous within-herd disease transmission model and enables rapid exploration of various ASF transmission scenarios and premovement surveillance options for finisher swine herds. The application demonstrates the effects of various surveillance design aspects and illustrates the benefit of an enhanced targeted biosecurity interval before movement. Developing such interactive tools can help translate complex mathematical models, and advance communication of ASF risk and surveillance strategies.",

keywords = "Active surveillance, African Swine Fever, Disease transmission dynamics, R Shiny, Simulation models",

author = "Sasidhar Malladi and Bonney, {Peter J.} and Martin, {Sylvia Wanzala} and Amos Ssematimba and {St. Charles}, Kaitlyn and O'Hara, {Kathleen C.} and Remmenga, {Marta D.} and Michelle Leonard and Hutchinson, {Holden C.} and Corzo, {Cesar A.} and Culhane, {Marie R.}",

note = "Publisher Copyright: {\textcopyright} 2025",

year = "2025",

month = may,

doi = "10.1016/j.softx.2025.102105",

language = "English (US)",

volume = "30",

journal = "SoftwareX",

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AU - Malladi, Sasidhar

AU - Bonney, Peter J.

AU - Martin, Sylvia Wanzala

AU - Ssematimba, Amos

AU - St. Charles, Kaitlyn

AU - O'Hara, Kathleen C.

AU - Remmenga, Marta D.

AU - Leonard, Michelle

AU - Hutchinson, Holden C.

AU - Corzo, Cesar A.

AU - Culhane, Marie R.

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AB - African Swine Fever (ASF) is a deadly, viral, swine disease with serious socio-economic impacts across the globe. Developing effective active surveillance strategies is critical, given the relatively long herd level incubation period for ASF. We developed an interactive web application that interfaces with a heterogeneous within-herd disease transmission model and enables rapid exploration of various ASF transmission scenarios and premovement surveillance options for finisher swine herds. The application demonstrates the effects of various surveillance design aspects and illustrates the benefit of an enhanced targeted biosecurity interval before movement. Developing such interactive tools can help translate complex mathematical models, and advance communication of ASF risk and surveillance strategies.

KW - Active surveillance

KW - African Swine Fever

KW - Disease transmission dynamics

KW - R Shiny

KW - Simulation models

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ASF Shiny app: An interactive web application for exploring premovement active surveillance scenarios for early African Swine Fever detection

Abstract

Bibliographical note

Keywords

UN SDGs

Publisher link

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