Author: Lloyd A. C. Chapman; Simon E. F. Spencer; Timothy M. Pollington; Chris P. Jewell; Dinesh Mondal; Jorge Alvar; T. Deirdre Hollingsworth; Mary M. Cameron; Caryn Bern; Graham F. Medley
Title: Inferring transmission trees to guide targeting of interventions against visceral leishmaniasis and post-kala-azar dermal leishmaniasis Document date: 2020_2_25
ID: nqn1qzcu_90
Snippet: To assess the fit of the model and simulate hypothetical interventions against PKDL, we create a stochastic simulation version of 520 the individual-level spatiotemporal transmission model described above. We follow standard stochastic simulation methodology 521 for discrete-time individual-level transmission models (47), converting infection event rates into probabilities in order to 522 determine who gets infected in each month. We assume that .....
Document: To assess the fit of the model and simulate hypothetical interventions against PKDL, we create a stochastic simulation version of 520 the individual-level spatiotemporal transmission model described above. We follow standard stochastic simulation methodology 521 for discrete-time individual-level transmission models (47), converting infection event rates into probabilities in order to 522 determine who gets infected in each month. We assume that an individual's progression through di erent infection states 523 following infection occurs independently of the rest of the epidemic (i.e. is either governed by internal biological processes or 524 random external processes of detection), which enables the simulation of an individual's full infection history from the point of 525 infection.
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