Inference of malaria reproduction numbers in three elimination settings by combining temporal data and distance metrics.

ABSTRACT: Individual-level geographic information about malaria cases, such as the GPS coordinates of residence or health facility, is often collected as part of surveillance in near-elimination settings, but could be more effectively utilised to infer transmission dynamics, in conjunction with additional information such as symptom onset time and genetic distance. However, in the absence of data about the flow of parasites between populations, the spatial scale of malaria transmission is often not clear. As a result, it is important to understand the impact of varying assumptions about the spatial scale of transmission on key metrics of malaria transmission, such as reproduction numbers. We developed a method which allows the flexible integration of distance metrics (such as Euclidian distance, gen

SUBMITTER: Routledge I 

PROVIDER: S-EPMC8280212 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature