Thu, Aug 18, 2022: 10:30 AM-10:45 AM
514C
Background/Question/MethodsDisease outbreaks have strong seasonal patterns, which are often linked to spatial and temporal heterogeneity in transmission. Many parasites are not transmitted directly from one host to another but, instead, are transmitted by transmission stages (“spores”) that remain infective for extended periods of time in environmental reservoirs. If these spores are unevenly distributed in the environment, there may be “hotspots” with heightened exposure risk for hosts, which may have major implications for disease dynamics (e.g., influencing the timing and location of outbreaks, virulence evolution of parasites, and host behavior). While it traditionally has been difficult to track transmission stages in the environment, their detection and quantification is now much more feasible with improved molecular methods. We are now poised to understand the fate of transmission stages in the environment, which may help us predict when and where epidemics occur. To investigate this, we used digital PCR to quantify transmission stage concentrations of five common Daphnia parasites in water samples collected across a spatial gradient within six lakes in southeastern Michigan at twelve time points. We simultaneously collected data on infection prevalence, host densities, and abiotic conditions (especially thermal stratification) to identify factors driving transmission stage distribution and disease outbreaks.
Results/ConclusionsThe distribution of transmission stages of common Daphnia parasites was uneven throughout the water column and changed over time. For example, in one lake high concentrations of transmission stages of two parasites (Pasteuria ramosa and Metschnikowia bicuspidata) were detected at similar depths in August but at different depths in October. Moreover, the M. bicuspidata spore concentration was nearly three times higher in October than in August. Thus, the spatiotemporal dynamics of transmission stage distribution introduces seasonal variation in exposure risk for hosts.Thermistor chains in the deep basin of six lakes captured thermal signatures of mixing events (e.g., an intense rainstorm on September 22-23, 2021 and seasonal turnover in October, 2021). We had predicted outbreaks of M. bicuspidata would follow mixing events due to resuspension of spores from sediments. However, based on the timing of mixing and detection of infected hosts, the initial M. bicuspidata outbreak began before the intense storm and before turnover. Ongoing analyses will allow for finer scale comparisons of mixing events, spore concentration, and infection prevalence in hosts. By linking the spatiotemporal dynamics of transmission stages with infection prevalence, we expand our understanding of the seasonality of diseases and improve our ability to anticipate outbreaks.
Results/ConclusionsThe distribution of transmission stages of common Daphnia parasites was uneven throughout the water column and changed over time. For example, in one lake high concentrations of transmission stages of two parasites (Pasteuria ramosa and Metschnikowia bicuspidata) were detected at similar depths in August but at different depths in October. Moreover, the M. bicuspidata spore concentration was nearly three times higher in October than in August. Thus, the spatiotemporal dynamics of transmission stage distribution introduces seasonal variation in exposure risk for hosts.Thermistor chains in the deep basin of six lakes captured thermal signatures of mixing events (e.g., an intense rainstorm on September 22-23, 2021 and seasonal turnover in October, 2021). We had predicted outbreaks of M. bicuspidata would follow mixing events due to resuspension of spores from sediments. However, based on the timing of mixing and detection of infected hosts, the initial M. bicuspidata outbreak began before the intense storm and before turnover. Ongoing analyses will allow for finer scale comparisons of mixing events, spore concentration, and infection prevalence in hosts. By linking the spatiotemporal dynamics of transmission stages with infection prevalence, we expand our understanding of the seasonality of diseases and improve our ability to anticipate outbreaks.