Fine-scale spatial patterns of wildlife disease are common and understudied

Abstract

All pathogens are heterogeneous in space, yet little is known about the prevalence and scale of this spatial variation, particularly in wild animal systems. To address this question, we conducted a broad literature search to identify datasets involving diseases of wild mammals in spatially distributed contexts. Across 31 such final datasets featuring 89 replicates and 71 host-parasite combinations, only 51% had previously been used to test spatial hypotheses. We analysed these datasets for spatial dependence within a standardised modelling framework using Bayesian linear models. We detected spatial autocorrelation in 44/89 model replicates (54%) across 21/31 datasets (68%), spread across parasites of all groups and transmission modes. Surprisingly, although larger sampling areas more easily detected spatial patterns, even some very small study areas (under 0.01km2) exhibited substantial spatial heterogeneity. Parasites of all transmission modes had easily detectable spatial patterns, implying that structured contact networks and susceptibility effects are likely as important in spatially structuring disease as are environmental drivers of transmission efficiency. Our findings imply that fine-scale spatial patterns of infection often manifest in wild animal systems, whether or not the aim of the study is to examine environmentally varying processes. Given the widespread nature of these findings, studies should more frequently record and analyse spatial data, facilitating development and testing of spatial hypotheses in disease ecology.

Unifying spatial and social network analysis in disease ecology

“…For example, if certain areas lend themselves to fighting or mating grounds for Tasmanian devils Sarcophilus harrisii , this would create an enduring spatial variation in the prevalence of Tasmanian devil facial tumour disease despite strictly direct transmission (Figure 1; Hamede et al., 2009). According to a recent meta‐analysis, directly transmitted pathogens may exhibit spatial autocorrelation at least as often as environmentally transmitted ones (Albery, Sweeny, et al., 2020). Therefore, known transmission mode is not sufficient to predict whether space is worth investigating in a given host‐parasite system, and researchers will benefit from measuring both.…”

“…Unfortunately, little consensus is available on which systems and environments are most likely to exhibit spatial‐social correlations due to the rarity of cross‐system synthesis. Recent studies have integrated social networks across a range of animals to make strong comparative conclusions (Sah, Mann, et al., 2018), and a recent meta‐analysis found that spatial variation in wildlife disease is widespread across host–pathogen systems and could not be predicted based on any host, pathogen or sampling traits (Albery, Sweeny, et al., 2020). As such, it is difficult to predict a priori which systems and sampling regimes will exhibit the most spatial‐social confounding.…”

Examining Prevalence and Diversity of Tick-Borne Pathogens in Questing Ixodes pacificus Ticks in California

“…These nuances can be important for treatment, control and educational opportunities. In addition, zoonotic disease systems often exhibit fine-scale spatial patterns and sharing these data at the site level may help future studies examining disease ecology and environmental drivers (33). Similarly, prevalence patterns of Borrelia likely will vary across time even at the same sites (34,35).…”

How does host social behavior drive parasite non-selective evolution from the within-host to the landscape-scale?

“…At a time where social distancing is widely recognized for its importance in limiting transmission among individuals and between populations, the ecological and evolutionary consequences of these behaviors for infectious parasites that extend beyond selection need to be investigated (Stockmaier et al 2021). Fine-scale spatial patterns in parasite infection are common across wildlife parasites of social organisms, even within very small areas (under 0.01 km 2 ) yet the mechanism which generates these patterns, and their ecological and evolutionary consequences are extremely understudied (Albery et al 2020). Several recent reviews have called for integrating animal behavior, spatial analysis, and parasite transmission data to better understand parasite ecology and evolution in wild systems (He et al 2019;Albery et al 2020Albery et al , 2021.…”

“…Fine-scale spatial patterns in parasite infection are common across wildlife parasites of social organisms, even within very small areas (under 0.01 km 2 ) yet the mechanism which generates these patterns, and their ecological and evolutionary consequences are extremely understudied (Albery et al 2020). Several recent reviews have called for integrating animal behavior, spatial analysis, and parasite transmission data to better understand parasite ecology and evolution in wild systems (He et al 2019;Albery et al 2020Albery et al , 2021. These data are required to understand emerging infectious diseases in wildlife and human systems (Townsend et al 2020).…”