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Modelling gambiense human African trypanosomiasis infection in villages of the Democratic Republic of Congo using Kolmogorov forward equations.
J R Soc Interface. 2021 10; 18(183):20210419.JR

Abstract

Stochastic methods for modelling disease dynamics enable the direct computation of the probability of elimination of transmission. For the low-prevalence disease of human African trypanosomiasis (gHAT), we develop a new mechanistic model for gHAT infection that determines the full probability distribution of the gHAT infection using Kolmogorov forward equations. The methodology allows the analytical investigation of the probabilities of gHAT elimination in the spatially connected villages of different prevalence health zones of the Democratic Republic of Congo, and captures the uncertainty using exact methods. Our method provides a more realistic approach to scaling the probability of elimination of infection between single villages and much larger regions, and provides results comparable to established models without the requirement of detailed infection structure. The novel flexibility allows the interventions in the model to be implemented specific to each village, and this introduces the framework to consider the possible future strategies of test-and-treat or direct treatment of individuals living in villages where cases have been found, using a new drug.

Authors+Show Affiliations

Mathematics Institute, University of Warwick, Coventry CV4 7AL, UK. Zeeman Institute (SBIDER), University of Warwick, Coventry CV4 7AL, UK.Mathematics Institute, University of Warwick, Coventry CV4 7AL, UK. Zeeman Institute (SBIDER), University of Warwick, Coventry CV4 7AL, UK. School of Life Sciences, University of Warwick, Coventry CV4 7AL, UK.Mathematics Institute, University of Warwick, Coventry CV4 7AL, UK. Zeeman Institute (SBIDER), University of Warwick, Coventry CV4 7AL, UK.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

34610258

Citation

Davis, Christopher N., et al. "Modelling Gambiense Human African Trypanosomiasis Infection in Villages of the Democratic Republic of Congo Using Kolmogorov Forward Equations." Journal of the Royal Society, Interface, vol. 18, no. 183, 2021, p. 20210419.
Davis CN, Keeling MJ, Rock KS. Modelling gambiense human African trypanosomiasis infection in villages of the Democratic Republic of Congo using Kolmogorov forward equations. J R Soc Interface. 2021;18(183):20210419.
Davis, C. N., Keeling, M. J., & Rock, K. S. (2021). Modelling gambiense human African trypanosomiasis infection in villages of the Democratic Republic of Congo using Kolmogorov forward equations. Journal of the Royal Society, Interface, 18(183), 20210419. https://doi.org/10.1098/rsif.2021.0419
Davis CN, Keeling MJ, Rock KS. Modelling Gambiense Human African Trypanosomiasis Infection in Villages of the Democratic Republic of Congo Using Kolmogorov Forward Equations. J R Soc Interface. 2021;18(183):20210419. PubMed PMID: 34610258.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Modelling gambiense human African trypanosomiasis infection in villages of the Democratic Republic of Congo using Kolmogorov forward equations. AU - Davis,Christopher N, AU - Keeling,Matt J, AU - Rock,Kat S, Y1 - 2021/10/06/ PY - 2021/10/5/entrez PY - 2021/10/6/pubmed PY - 2021/10/30/medline KW - African sleeping sickness KW - African trypanosomiasis KW - Kolmogorov forward equations KW - mathematical model SP - 20210419 EP - 20210419 JF - Journal of the Royal Society, Interface JO - J R Soc Interface VL - 18 IS - 183 N2 - Stochastic methods for modelling disease dynamics enable the direct computation of the probability of elimination of transmission. For the low-prevalence disease of human African trypanosomiasis (gHAT), we develop a new mechanistic model for gHAT infection that determines the full probability distribution of the gHAT infection using Kolmogorov forward equations. The methodology allows the analytical investigation of the probabilities of gHAT elimination in the spatially connected villages of different prevalence health zones of the Democratic Republic of Congo, and captures the uncertainty using exact methods. Our method provides a more realistic approach to scaling the probability of elimination of infection between single villages and much larger regions, and provides results comparable to established models without the requirement of detailed infection structure. The novel flexibility allows the interventions in the model to be implemented specific to each village, and this introduces the framework to consider the possible future strategies of test-and-treat or direct treatment of individuals living in villages where cases have been found, using a new drug. SN - 1742-5662 UR - https://www.unboundmedicine.com/medline/citation/34610258/Modelling_gambiense_human_African_trypanosomiasis_infection_in_villages_of_the_Democratic_Republic_of_Congo_using_Kolmogorov_forward_equations_ DB - PRIME DP - Unbound Medicine ER -