Substantiating freedom from parasitic infection by combining transmission model predictions with disease surveys

Edwin Michael (), Morgan E. Smith, Moses N. Katabarwa, Edson Byamukama, Emily Griswold, Peace Habomugisha, Thomson Lakwo, Edridah Tukahebwa, Emmanuel S. Miri, Abel Eigege, Evelyn Ngige, Thomas R. Unnasch and Frank O. Richards
Additional contact information
Edwin Michael: University of Notre Dame
Morgan E. Smith: University of Notre Dame
Moses N. Katabarwa: One Copenhill
Edson Byamukama: The Carter Center, Uganda
Emily Griswold: One Copenhill
Peace Habomugisha: The Carter Center, Uganda
Thomson Lakwo: Ministry of Health
Edridah Tukahebwa: Ministry of Health
Emmanuel S. Miri: The Carter Center, Nigeria
Abel Eigege: The Carter Center, Nigeria
Evelyn Ngige: Federal Sceretariat
Thomas R. Unnasch: University of South Florida
Frank O. Richards: One Copenhill

Nature Communications, 2018, vol. 9, issue 1, 1-13

Abstract: Abstract Stopping interventions is a critical decision for parasite elimination programmes. Quantifying the probability that elimination has occurred due to interventions can be facilitated by combining infection status information from parasitological surveys with extinction thresholds predicted by parasite transmission models. Here we demonstrate how the integrated use of these two pieces of information derived from infection monitoring data can be used to develop an analytic framework for guiding the making of defensible decisions to stop interventions. We present a computational tool to perform these probability calculations and demonstrate its practical utility for supporting intervention cessation decisions by applying the framework to infection data from programmes aiming to eliminate onchocerciasis and lymphatic filariasis in Uganda and Nigeria, respectively. We highlight a possible method for validating the results in the field, and discuss further refinements and extensions required to deploy this predictive tool for guiding decision making by programme managers.

Date: 2018
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DOI: 10.1038/s41467-018-06657-5

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