Repeated introductions and intensive community transmission fueled a mumps virus outbreak in Washington State

  1. Louise H Moncla
  2. Allison Black
  3. Chas DeBolt
  4. Misty Lang
  5. Nicholas R Graff
  6. Ailyn C Pérez-Osorio
  7. Nicola F Müller
  8. Dirk Haselow
  9. Scott Lindquist
  10. Trevor Bedford

  • Curated by eLife

    eLife logo

    Evaluation Summary:

    This interesting phylogenetic analysis of a mumps outbreak in Washington will be of interest to a wide audience, especially those working at the intersection of pathogen genomics and public health. An array of classic and novel phylogenetic approaches supports the conclusions that mumps was introduced several times in Washington during the outbreak, and that the Washington Marshallese community was particularly at risk of mumps infection and transmission despite high vaccination coverage. Inferences regarding the role of age and vaccination status are however less conclusive given the small sample size. Consultation with a community health advocate from the affected communities helps contextualize the results.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

In 2016/2017, Washington State experienced a mumps outbreak despite high childhood vaccination rates, with cases more frequently detected among school-aged children and members of the Marshallese community. We sequenced 166 mumps virus genomes collected in Washington and other US states, and traced mumps introductions and transmission within Washington. We uncover that mumps was introduced into Washington approximately 13 times, primarily from Arkansas, sparking multiple co-circulating transmission chains. Although age and vaccination status may have impacted transmission, our data set could not quantify their precise effects. Instead, the outbreak in Washington was overwhelmingly sustained by transmission within the Marshallese community. Our findings underscore the utility of genomic data to clarify epidemiologic factors driving transmission and pinpoint contact networks as critical for mumps transmission. These results imply that contact structures and historic disparities may leave populations at increased risk for respiratory virus disease even when a vaccine is effective and widely used.

Article activity feed

  1. Version published to 10.7554/elife.66448 on eLife
  2. eLife

    Author Response:

    Reviewer #3 (Public Review):

    1. The authors seem to assume a somewhat random sample throughout Washington state. They state that given a low sampling proportion they do not expect to have captured infection pairs, which seems reasonable. However, they then go onto assume that their sample is primarily comprised of samples from long, successful transmission chains. This is a reasonable assumption if there is no major difference in accessibility of samples from long transmission chains and shorter ones (for example, decreased access to healthcare). Could this impact the assumption of sampling primarily from long transmission chains? It seems from the data collected in this outbreak that this was not the case for mumps in Washington but addressing this assumption clearly (and potential ways to interrogate it) could make their methodology more applicable to other pathogen studies.
    1. There are many examples of phylogenetic analyses that have led to conclusions about pathogen sources and sinks that were later shown to be wrong because of oversampling or other sampling biases. The authors address unequal sampling between clades, but additional contextualization of the problem and how this approach is different may help strengthen the methodology presented in the paper.

    We thank the reviewer for these important points. We have attempted to address these by including an additional paragraph about different types of sampling and their impacts on phylodynamic studies.

    We agree that this is a helpful addition, and have added a new paragraph devoted to a discussion of sampling bias to the discussion on lines 458-484. This paragraph reads:

    “Sampling bias presents a persistent problem for phylodynamic studies that can complicate inference of source-sink dynamics (De Maio et al., 2015; Dudas et al., 2018; Frost et al., 2015; Kühnert et al., 2011; Lemey et al., 2020; Stack et al., 2010). Sampling bias can arise from unequal case detection or from curating a dataset that poorly represents the underlying outbreak. Washington State uses a passive surveillance system for mumps detection and case acquisition, which is known to result in underreporting. Because the WA Department of Health did not perform active mumps surveillance, it is difficult to assess whether different epidemiologic groups have different likelihoods of being sampled. Marshallese individuals are less likely to seek healthcare (Towne et al., 2020), which may have resulted in particularly high rates of underreporting in this group. If the number of cases within the Marshallese community were in fact higher than reported, this would increase the magnitude of the patterns we describe, making our estimates conservative. Given a distribution of cases, composing a dataset for analysis also requires sampling decisions. Uniform sampling regimes in which sampling probability is equal across groups have been shown to perform well for source- sink inferences (Hall et al., 2016). By selecting sequences that matched the overall attributes of the outbreak, including a near 50:50 split between Marshallese and non- Marshallese cases, we adhere to this recommendation. We then specifically employed structured coalescent approaches which have been shown to be robust to sampling differences (Dudas et al., 2018; Müller et al., 2018; Vaughan et al., 2014), rather than using other common approaches that treat sampling intensity as informative of population size (Lemey et al., 2009). Within this framework, we further explore the possibility that unequal sampling within Washington clades could skew internal node reconstruction by forcing the sampling within each Washington clade to be equal between Marshallese and non-Marshallese tips. In doing so, differences within each clade must necessarily be driven by differences in transmission dynamics, rather than sampling. By combining careful sample selection with overlapping approaches to evaluate sampling bias, we were able to mitigate concerns that our source-sink reconstructions are driven by sampling artifacts.”

    1. The authors present compelling evidence that the mumps outbreak in Washington state was sustained by the Marshallese community, and state that mumps did not transmit efficiently among the general Washington populace. That said, there were several other mumps outbreaks in the United States in the same 2016-2017 time period. Was there something different about Washington state that prevented mumps transmission outside of the Marshallese community? Were there no other close-knit communities (universities, prisons, other cultural communities, etc.) affected? It just seems surprising that the Marshallese community was the only community sustaining transmission at a time where many different types of communities were affected across the United States.

    We thank the reviewers and editor for this comment, and agree that further contextualization would be helpful. We did not make it clear in the initial submission that in 2016/2017, the vast majority of mumps outbreaks in the US were associated with either universities or ethnic communities. We have re-organized a few paragraphs in the discussion section and added information about other 2016/2017 outbreaks. This new paragraph is on lines 499-519, and reads:

    “Our finding that most introductions sparked short transmission chains suggests that mumps did not transmit efficiently among the general Washington populace. We suspect that more diffuse contact patterns may help explain this. Mumps has historically caused outbreaks in communities with strong, interconnected contact patterns (Barskey et al., 2012; Fields et al., 2019; Nelson et al., 2013), and in dense housing environments (Snijders et al., 2012), highlighted most recently by outbreaks in US detention centers (Lo et al., 2021). In 2016, most outbreaks in the US were associated with university settings (Albertson et al., 2016; Bonwitt et al., 2017; Donahue et al., 2017; Golwalkar et al., 2018; Shah et al., 2018; Wohl et al., 2020), including a separate, smaller outbreak in Washington State associated with Greek housing (Bonwitt et al., 2017). Outside of university settings, other outbreaks in 2016 were reported within close-knit ethnic communities (Fields et al., 2019; Marx et al., 2018). We speculate that while waning immunity may promote outbreaks by increasing susceptibility among young adults, outbreaks in younger age groups may be possible in sufficiently high-contact settings. Provision of an outbreak dose of mumps-containing vaccine to high-risk groups may therefore be especially effective for limiting mumps transmission in future outbreaks. Others have reported success in using outbreak dose mumps vaccinations to reduce mumps transmission on college campuses (Cardemil et al., 2017; Shah et al., 2018) and in the US army (Arday et al., 1989; Eick et al., 2008; Green, 2006; Kelley et al., 1991), and the CDC currently recommends providing outbreak vaccine doses to individuals with increased risk due to an outbreak (Marlow et al., 2020). Future work to quantify the interplay between contact rates and vaccine-induced immunity among different age and risk groups should be used to guide updated vaccine recommendations.”

    We also amended lines 42-46 in the introduction to highlight that most other US outbreaks in 2016/2017 were university-associated:

    “Like with other recent mumps outbreaks, most Washington cases in 2016/17 were vaccinated. Unusually though, while most US outbreaks in 2016/2017 were associated with university settings (Albertson et al., 2016; Bonwitt et al., 2017; Donahue et al., 2017; Golwalkar et al., 2018; Shah et al., 2018; Wohl et al., 2020), incidence in Washington was highest among children aged 10-18 years, younger than expected given waning immunity.”

  3. eLife

    Reviewer #3 (Public Review):

    Moncla et al. investigated the transmission of mumps virus in Washington, USA during an outbreak in 2016-2017. They sequenced viral genomes from infected individuals in Washington and elsewhere within the United States and used phylogenetic approaches to understand the origins and patterns of spread exhibited by the virus during the outbreak. They observe a large fraction of cases in individuals who are part of the Marshallese community, and identify a link to a similar outbreak in the Marshallese community in Arkansas. They develop a method for determining the role of the Marshallese community in the Washington outbreak that is robust to sampling bias and size. This method is well thought-out and presented and demonstrates that the outbreak in Washington state was sustained by transmission within this particular community. This paper provides a thoughtful approach to dealing with sampling issues that are often overlooked in phylogenetic studies. By consulting with a public health professional from within the affected (Marshallese) community, the authors are able to contextualize their results and demonstrate the underlying issues that may have contributed to mumps spread within the state.

    Working with public health advocates from affected communities is exceptionally important for long term public health impact, and this paper sets an example that should be followed by others in the pathogen genomics field. The methodology used to determine mumps transmission patterns in Washington is sound and the conclusions are well explained. However, some additional context on the issues and potential pitfalls of source-sink analyses based on phylogenetic inference would help improve this already solid paper. Specifically:

    1. The authors seem to assume a somewhat random sample throughout Washington state. They state that given a low sampling proportion they do not expect to have captured infection pairs, which seems reasonable. However, they then go onto assume that their sample is primarily comprised of samples from long, successful transmission chains. This is a reasonable assumption if there is no major difference in accessibility of samples from long transmission chains and shorter ones (for example, decreased access to healthcare). Could this impact the assumption of sampling primarily from long transmission chains? It seems from the data collected in this outbreak that this was not the case for mumps in Washington but addressing this assumption clearly (and potential ways to interrogate it) could make their methodology more applicable to other pathogen studies.

    2. There are many examples of phylogenetic analyses that have led to conclusions about pathogen sources and sinks that were later shown to be wrong because of oversampling or other sampling biases. The authors address unequal sampling between clades, but additional contextualization of the problem and how this approach is different may help strengthen the methodology presented in the paper.

    3. The authors present compelling evidence that the mumps outbreak in Washington state was sustained by the Marshallese community, and state that mumps did not transmit efficiently among the general Washington populace. That said, there were several other mumps outbreaks in the United States in the same 2016-2017 time period. Was there something different about Washington state that prevented mumps transmission outside of the Marshallese community? Were there no other close-knit communities (universities, prisons, other cultural communities, etc.) affected? It just seems surprising that the Marshallese community was the only community sustaining transmission at a time where many different types of communities were affected across the United States.

  4. eLife

    Reviewer #2 (Public Review):

    In this manuscript, Moncla et al. undertake a large sequencing and phylogenetic study to investigate the underlying epidemiology of the 2016-2017 Washington State Mumps epidemic. The authors generate 110 sequences and include 166 novel sequences in their analysis. This data set represents over a quarter of the publicly available Mumps genomes from North America.

    They then apply a mixture of phylogenetic methods and intuitive data analyses to uncover, that i) Mumps was imported into Washington at least 13 times. ii) A disproportionate amount of transmission occurred in the Marshallese community in WA with limited transmission in the non-Marshallese community. iii) These heterologous transmission dynamics might be explained by historical and current health disparities within the community, but are not due to low vaccination coverage.

    These conclusions are supported by a wide array of carefully controlled phylogenetic methods. The authors explore the sensitivity of their findings to sampling bias. Additionally, the conclusion that transmission occurred disproportionally within the Marshallese community is supported by multiple implementations of the structured coalescent as well as, more coarse but intuitive methods such as the rarefaction analysis and the "descendent" analysis in Figure 4. The "descendent" analysis complements the structured coalescent models and highlights how tips that are close to internal nodes inform the "state" of those unsampled ancestors. Each internal node represents an unsampled ancestor, and if transmission rates are higher in one population, then samples from that population are more likely to be close to those ancestors. The approach captures these processes; however, calling downstream tips "descendants" is unfortunate, as it is unknown if the tips that have "descendants" are direct ancestors of their "descendants" in the transmission chain. Inferring transmission dynamics from divergence trees is difficult, and variants of this approach are likely to be useful in other systems.

    The finding that transmission disproportionally occurred in the Marshallese community leads the authors to propose several possibilities for why this may be. The authors should be commended for reaching out to Marshallese health advocates in this process and including the community in their study. This context is a major strength of the study.

    Both the data generation and data analysis are achievements that advance our understanding of the epidemiology of Mumps. As can be seen in the tree in Figure 1 the 2016-2017 epidemic in North America was seeded by at least two divergent lineages that appear to have all contributed to the same outbreak. The large number of sequences contributed by this study will help future work uncover the dynamics that drive Mumps epidemics at larger scales. The findings also highlight how large outbreaks can persist in highly vaccinated populations and how an array of phylogenetic approaches can be employed to uncover the underlying population heterogeneity behind an outbreak. To have both of these achievements in the same manuscript sets this work apart.

  5. eLife

    Reviewer #1 (Public Review):

    In this study, Moncla et al. used genomic data to analyse a mumps outbreak in Washington, in order to draw inferences about the epidemiological factors driving the outbreak. Some important strengths of the analysis include sophisticated sequencing and modeling techniques to reconstruct chains of transmission during the outbreak, which support the conclusions that the mumps virus was introduced several times in Washington from other North American regions during the outbreak, and that the Washington Marshallese community was particularly at risk of mumps infection and transmission during this time. Limitations of the analysis include potential for sampling bias, where the sample may not be entirely representative of mumps outbreak cases, and a sample size that is too low to allow sufficient statistical power to assess the impacts of age and vaccination status on transmission. The work has potential public health impacts in terms of identification of a vulnerable community and points to social networks as the primary risk factor for potential future respiratory virus outbreaks. The analysis methods could be potentially applied for the phylodynamic analysis of other infectious disease outbreaks.

  6. eLife

    Evaluation Summary:

    This interesting phylogenetic analysis of a mumps outbreak in Washington will be of interest to a wide audience, especially those working at the intersection of pathogen genomics and public health. An array of classic and novel phylogenetic approaches supports the conclusions that mumps was introduced several times in Washington during the outbreak, and that the Washington Marshallese community was particularly at risk of mumps infection and transmission despite high vaccination coverage. Inferences regarding the role of age and vaccination status are however less conclusive given the small sample size. Consultation with a community health advocate from the affected communities helps contextualize the results.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

  7. Version published to 10.1101/2020.10.19.20215442v2 on medRxiv
  8. Version published to 10.1101/2020.10.19.20215442v1 on medRxiv