DOI: 10.25338/b8h63b
title: More people, more cats, more parasites: Human population density and temperature variation predict the prevalence of Toxoplasma gondii oocyst shedding in free-ranging domestic and wild felids

description: Aim: Toxoplasma gondii is a ubiquitous zoonotic parasite that can infect
 warm-blooded vertebrates, including humans. Felids, the definitive hosts,
 drive T. gondii infections by shedding the environmentally resistant stage
 of the parasite (oocysts) in their feces. Risk factors for oocyst shedding
 are well-documented in domestic cats under controlled settings, but few
 studies characterize the role of climate and anthropogenic factors in
 oocyst shedding among free-ranging felids, which are responsible for the
 majority of environmental contamination. We aimed to determine how climate
 and anthropogenic factors influence the level of oocyst shedding in
 free-ranging domestic cats and wild felids.  Location: Global
 Time period: 1973-2021 Major taxa studied: Felidae, Toxoplasma gondii
 Methods: We used generalized linear mixed models to determine the
 association between climatic, ecological, and anthropogenic factors and T.
 gondii oocyst shedding in free-ranging felids. T. gondii oocyst shedding
 data from 47 studies were compiled for domestic cats and 6 wild felid
 species, encompassing 256 positive samples out of 9,635 total fecal
 samples.  Results: T. gondii shedding prevalence in domestic cats
 and wild felids was positively associated with human population density at
 the sampling location. Average annual temperature and total precipitation
 were not associated with increased shedding, however, temperature
 variables that reflected fluctuation on a smaller timescale were
 associated with oocyst shedding. Larger mean diurnal range was associated
 with higher T. gondii oocyst shedding prevalence in domestic cats, while
 higher temperatures in the driest quarter were associated with lower
 oocyst shedding in wild felids. Main conclusions: Anthropogenic factors
 associated with increasing human population density and climate change in
 the form of temperature fluctuation can exacerbate environmental
 contamination with the protozoan parasite T. gondii. Direct or indirect
 management of free-ranging domestic cats could lower the burden of
 environmental oocysts due to their large population sizes and close
 affinity with human settlements. 
description: Dataset was collected using systematic review. For studies that
 met inclusion criteria, we extracted metadata including the year of
 publication, type of felid sampled (domestic/wild), country of study,
 continent, diagnostic method, number of positive fecal samples, total
 fecal samples tested, and approximate latitude and longitude of the sample
 site as reported by the authors for each study. We repeated this process
 in studies with multiple species of sampled felids.  Our primary variables of interest were annual mean
 temperature, annual precipitation, and human population density.
 Additionally, we considered other climate variables, such as maximum
 temperature, mean diurnal range and precipitation seasonality, as well as
 human activity variables such as habitat type and species richness for
 inclusion in subsequent models (Table 1). For each study, we used the R
 package ‘raster’ with a World Geodetic System 1984 projection and a 2.5 km
 buffer to obtain location-specific data. Climate data (temperature and
 precipitation variables) was extracted at a 5 km resolution from the
 WorldClim 2.0 (1970-2000) dataset, while human population density and
 human footprint data at a 5 km resolution was extracted from the NASA
 Center for International Earth Science Information Network (CIESIN). Human
 population density was paired to each study by the closest time period
 (2000, 2005, 2010, 2015 and 2020). Habitat type was extracted at a
 resolution of 1 km, and species richness at 110 m from the International
 Union for Conservation of Nature (IUCN) (Jung et al. 2020). 
 WorldClim 2.0 https://www.worldclim.org/data/worldclim21.html NASA CIESIN https://sedac.ciesin.columbia.edu/data/collection/gpw-v4 IUCN Jung et al. 2020 https://zenodo.org/record/3666246#.YroIni9XZpR
description: After data are imported into statistical software such as R or
 Python, it should be transformed and cleaned according to the attached R
 script. Note that all temperature variables from WorldClim are °C * 10 and
 need to be transformed prior to analysis (https://worldclim.org/data/v1.4/formats.html). Updated dataset includes all climate data extracted from WorldClim, NASA, and IUCN such that the user does not have to perform this task on their own.