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Impact of the tree prior on estimating clock rates during epidemic outbreaks.

ABSTRACT: Bayesian phylogenetics aims at estimating phylogenetic trees together with evolutionary and population dynamic parameters based on genetic sequences. It has been noted that the clock rate, one of the evolutionary parameters, decreases with an increase in the sampling period of sequences. In particular, clock rates of epidemic outbreaks are often estimated to be higher compared with the long-term clock rate. Purifying selection has been suggested as a biological factor that contributes to this phenomenon, since it purges slightly deleterious mutations from a population over time. However, other factors such as methodological biases may also play a role and make a biological interpretation of results difficult. In this paper, we identify methodological biases originating from the choice of tree prior, that is, the model specifying epidemiological dynamics. With a simulation study we demonstrate that a misspecification of the tree prior can upwardly bias the inferred clock rate and that the interplay of the different models involved in the inference can be complex and nonintuitive. We also show that the choice of tree prior can influence the inference of clock rate on real-world Ebola virus (EBOV) datasets. While commonly used tree priors result in very high clock-rate estimates for sequences from the initial phase of the epidemic in Sierra Leone, tree priors allowing for population structure lead to estimates agreeing with the long-term rate for EBOV.

SUBMITTER: Moller S

PROVIDER: S-EPMC5910814 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Impact of the tree prior on estimating clock rates during epidemic outbreaks.

Möller Simon S du Plessis Louis L Stadler Tanja T

Proceedings of the National Academy of Sciences of the United States of America 20180402 16

Bayesian phylogenetics aims at estimating phylogenetic trees together with evolutionary and population dynamic parameters based on genetic sequences. It has been noted that the clock rate, one of the evolutionary parameters, decreases with an increase in the sampling period of sequences. In particular, clock rates of epidemic outbreaks are often estimated to be higher compared with the long-term clock rate. Purifying selection has been suggested as a biological factor that contributes to this ph ...[more]

PMID: 29610334

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Project description:BackgroundNovel coronaviruses have emerged and caused major epidemics and pandemics in the past 2 decades, including SARS-CoV-1, MERS-CoV, and SARS-CoV-2, which led to the current COVID-19 pandemic. These coronaviruses are marked by their potential to produce disproportionally large transmission clusters from superspreading events (SSEs). As prompt action is crucial to contain and mitigate SSEs, real-time epidemic size estimation could characterize the transmission heterogeneity and inform timely implementation of control measures.ObjectiveThis study aimed to estimate the epidemic size of SSEs to inform effective surveillance and rapid mitigation responses.MethodsWe developed a statistical framework based on back-calculation to estimate the epidemic size of ongoing coronavirus SSEs. We first validated the framework in simulated scenarios with the epidemiological characteristics of SARS, MERS, and COVID-19 SSEs. As case studies, we retrospectively applied the framework to the Amoy Gardens SARS outbreak in Hong Kong in 2003, a series of nosocomial MERS outbreaks in South Korea in 2015, and 2 COVID-19 outbreaks originating from restaurants in Hong Kong in 2020.ResultsThe accuracy and precision of the estimation of epidemic size of SSEs improved with longer observation time; larger SSE size; and more accurate prior information about the epidemiological characteristics, such as the distribution of the incubation period and the distribution of the onset-to-confirmation delay. By retrospectively applying the framework, we found that the 95% credible interval of the estimates contained the true epidemic size after 37% of cases were reported in the Amoy Garden SARS SSE in Hong Kong, 41% to 62% of cases were observed in the 3 nosocomial MERS SSEs in South Korea, and 76% to 86% of cases were confirmed in the 2 COVID-19 SSEs in Hong Kong.ConclusionsOur framework can be readily integrated into coronavirus surveillance systems to enhance situation awareness of ongoing SSEs.

Project description:At least 10% of the world's tree species are threatened with extinction and pathogens are increasingly implicated in tree threats. Coextinction and threats to affiliates as a consequence of the loss or decline of their host trees is a poorly understood phenomenon. Ash dieback is an emerging infectious disease causing severe dieback of common ash Fraxinus excelsior throughout Europe. We utilized available empirical data on affiliate epiphytic lichen diversity (174 species and 17,800 observations) among 20 ash dieback infected host tree populations of F. excelsior on the island Gotland in the Baltic Sea, Sweden. From this, we used structured scenario projections scaled with empirical data of ash dieback disease to generate probabilistic models for estimating local and regional lichen coextinction risks. Average coextinction probabilities (Ā) were 0.38 (95% CI ± 0.09) for lichens occurring on F. excelsior and 0.14 (95% CI ± 0.03) when considering lichen persistence on all tree species. Ā was strongly linked to local disease incidence levels and generally increasing with lichen host specificity to F. excelsior and decreasing population size. Coextinctions reduced affiliate community viability, with significant local reductions in species richness and shifts in lichen species composition. Affiliates were projected to become locally extirpated before their hosts, illuminating the need to also consider host tree declines. Traditionally managed open wooded meadows had the highest incidence of ash dieback disease and significantly higher proportions of affiliate species projected to go extinct, compared with unmanaged closed forests and semi-open grazed sites. Most cothreatened species were not previously red-listed, which suggest that tree epidemics cause many unforeseen threats to species. Our analysis shows that epidemic tree deaths represent an insidious, mostly overlooked, threat to sessile affiliate communities in forested environments. Current conservation and management strategies must account for secondary extinctions associated with epidemic tree death.

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Impact of the tree prior on estimating clock rates during epidemic outbreaks.

Publications

Impact of the tree prior on estimating clock rates during epidemic outbreaks.

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