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Timescale reverses the relationship between host density and infection risk

Cite this dataset

Stewart Merrill, Tara et al. (2022). Timescale reverses the relationship between host density and infection risk [Dataset]. Dryad.


Host density shapes infection risk through two opposing phenomena. First, when infective stages are subdivided among multiple hosts, greater host densities decrease infection risk through “safety in numbers”. Hosts, however, represent resources for parasites, and greater host availability also fuels parasite reproduction. Hence, host density increases infection risk through “density-dependent transmission”. Theory proposes that these phenomena are not disparate outcomes but occur over different timescales. That is, higher host densities may reduce short-term infection risk, but because they support parasite reproduction, may increase long-term risk. We tested this theory in a zooplankton-disease system with laboratory experiments and field observations. Supporting theory, we found that negative density-risk relationships (‘safety in numbers’) sometimes emerged over short timescales, but these relationships reversed to ‘density-dependent transmission’ within two generations. By allowing parasite numerical responses to play out, time can shift the consequences of host density, from reduced immediate risk to amplified future risk.


All methods related to the present data can be found in the methods and supplementary materials of Stewart Merrill et al. 2022 Proc R Soc B.

Usage notes

All files can be opened in Excel and contain a "metadata" tab with additional information regarding the column headers and notes for interpretation. The files (which follow the order of the methods and results in the manuscript) include:

master_SIN_lab infection prevalence.xlsx: The dataset containing infection statuses of Daphnia to experimentally assess how host density influences infection risk over time.

master_SIN_spore counts.xlsx: The dataset containing spore counts following Metschnikowia reproduction to assess the parasite's numerical response over time.

master_SIN_microscopic evaluations.xlsx: The dataset in which individual Daphnia were assessed under high magnification to groundtruth assumptions regarding safety in numbers.

master_SIN_field density and prevalence.xlsx: The dataset containing field infections used to explore safety in numbers and density-dependent transmission in the natural environment.


National Science Foundation, Award: NSF 1420273

National Science Foundation, Award: 1144245

National Science Foundation, Award: 1354407

National Science Foundation, Award: 1701515