COVID-19 amplified racial disparities in the US criminal legal system.

The criminal legal system in the USA drives an incarceration rate that is the highest on the planet, with disparities by class and race among its signature features1-3. During the first year of the coronavirus disease 2019 (COVID-19) pandemic, the number of incarcerated people in the USA decreased by at least 17%-the largest, fastest reduction in prison population in American history4. Here we ask how this reduction influenced the racial composition of US prisons and consider possible mechanisms for these dynamics. Using an original dataset curated from public sources on prison demographics across all 50 states and the District of Columbia, we show that incarcerated white people benefited disproportionately from the decrease in the US prison population and that the fraction of incarcerated Black and Latino people sharply increased. This pattern of increased racial disparity exists across prison systems in nearly every state and reverses a decade-long trend before 2020 and the onset of COVID-19, when the proportion of incarcerated white people was increasing amid declining numbers of incarcerated Black people5. Although a variety of factors underlie these trends, we find that racial inequities in average sentence length are a major contributor. Ultimately, this study reveals how disruptions caused by COVID-19 exacerbated racial inequalities in the criminal legal system, and highlights key forces that sustain mass incarceration. To advance opportunities for data-driven social science, we publicly released the data associated with this study at Zenodo6.

Superspreading events in the transmission dynamics of SARS-CoV-2: Opportunities for interventions and control.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the etiological agent of the Coronavirus Disease 2019 (COVID-19) disease, has moved rapidly around the globe, infecting millions and killing hundreds of thousands. The basic reproduction number, which has been widely used-appropriately and less appropriately-to characterize the transmissibility of the virus, hides the fact that transmission is stochastic, often dominated by a small number of individuals, and heavily influenced by superspreading events (SSEs). The distinct transmission features of SARS-CoV-2, e.g., high stochasticity under low prevalence (as compared to other pathogens, such as influenza), and the central role played by SSEs on transmission dynamics cannot be overlooked. Many explosive SSEs have occurred in indoor settings, stoking the pandemic and shaping its spread, such as long-term care facilities, prisons, meat-packing plants, produce processing facilities, fish factories, cruise ships, family gatherings, parties, and nightclubs. These SSEs demonstrate the urgent need to understand routes of transmission, while posing an opportunity to effectively contain outbreaks with targeted interventions to eliminate SSEs. Here, we describe the different types of SSEs, how they influence transmission, empirical evidence for their role in the COVID-19 pandemic, and give recommendations for control of SARS-CoV-2.

A Family of Fitness Landscapes Modeled through Gene Regulatory Networks.

Fitness landscapes are a powerful metaphor for understanding the evolution of biological systems. These landscapes describe how genotypes are connected to each other through mutation and related through fitness. Empirical studies of fitness landscapes have increasingly revealed conserved topographical features across diverse taxa, e.g., the accessibility of genotypes and "ruggedness". As a result, theoretical studies are needed to investigate how evolution proceeds on fitness landscapes with such conserved features. Here, we develop and study a model of evolution on fitness landscapes using the lens of Gene Regulatory Networks (GRNs), where the regulatory products are computed from multiple genes and collectively treated as phenotypes. With the assumption that regulation is a binary process, we prove the existence of empirically observed, topographical features such as accessibility and connectivity. We further show that these results hold across arbitrary fitness functions and that a trade-off between accessibility and ruggedness need not exist. Then, using graph theory and a coarse-graining approach, we deduce a mesoscopic structure underlying GRN fitness landscapes where the information necessary to predict a population's evolutionary trajectory is retained with minimal complexity. Using this coarse-graining, we develop a bottom-up algorithm to construct such mesoscopic backbones, which does not require computing the genotype network and is therefore far more efficient than brute-force approaches. Altogether, this work provides mathematical results of high-dimensional fitness landscapes and a path toward connecting theory to empirical studies.

Socioeconomic bias in influenza surveillance.

Individuals in low socioeconomic brackets are considered at-risk for developing influenza-related complications and often exhibit higher than average influenza-related hospitalization rates. This disparity has been attributed to various factors, including restricted access to preventative and therapeutic health care, limited sick leave, and household structure. Adequate influenza surveillance in these at-risk populations is a critical precursor to accurate risk assessments and effective intervention. However, the United States of America's primary national influenza surveillance system (ILINet) monitors outpatient healthcare providers, which may be largely inaccessible to lower socioeconomic populations. Recent initiatives to incorporate Internet-source and hospital electronic medical records data into surveillance systems seek to improve the timeliness, coverage, and accuracy of outbreak detection and situational awareness. Here, we use a flexible statistical framework for integrating multiple surveillance data sources to evaluate the adequacy of traditional (ILINet) and next generation (BioSense 2.0 and Google Flu Trends) data for situational awareness of influenza across poverty levels. We find that ZIP Codes in the highest poverty quartile are a critical vulnerability for ILINet that the integration of next generation data fails to ameliorate.

Asymptomatic Infection and Transmission of Pertussis in Households: A Systematic Review.

We conducted a systematic review to describe the frequency of mild, atypical, and asymptomatic infection among household contacts of pertussis cases and to explore the published literature for evidence of asymptomatic transmission. We included studies that obtained and tested laboratory specimens from household contacts regardless of symptom presentation and reported the proportion of cases with typical, mild/atypical, or asymptomatic infection. After screening 6789 articles, we included 26 studies. Fourteen studies reported household contacts with mild/atypical pertussis. These comprised up to 46.2% of all contacts tested. Twenty-four studies reported asymptomatic contacts with laboratory-confirmed pertussis, comprising up to 55.6% of those tested. Seven studies presented evidence consistent with asymptomatic pertussis transmission between household contacts. Our results demonstrate a high prevalence of subclinical infection in household contacts of pertussis cases, which may play a substantial role in the ongoing transmission of disease. Our review reveals a gap in our understanding of pertussis transmission.

Asymmetric percolation drives a double transition in sexual contact networks.

Zika virus (ZIKV) exhibits unique transmission dynamics in that it is concurrently spread by a mosquito vector and through sexual contact. Due to the highly asymmetric durations of infectiousness between males and females-it is estimated that males are infectious for periods up to 10 times longer than females-we show that this sexual component of ZIKV transmission behaves akin to an asymmetric percolation process on the network of sexual contacts. We exactly solve the properties of this asymmetric percolation on random sexual contact networks and show that this process exhibits two epidemic transitions corresponding to a core-periphery structure. This structure is not present in the underlying contact networks, which are not distinguishable from random networks, and emerges because of the asymmetric percolation. We provide an exact analytical description of this double transition and discuss the implications of our results in the context of ZIKV epidemics. Most importantly, our study suggests a bias in our current ZIKV surveillance, because the community most at risk is also one of the least likely to get tested.

Food insecure cancer survivors continue to smoke after their diagnosis despite not having enough to eat: implications for policy and clinical interventions.

PURPOSE: This cross-sectional study examined whether food insecurity among cancer survivors is associated with smoking status and quit attempt. METHODS: Data from the 2015 behavioral risk factor surveillance system, social context module on 6,481 adult cancer survivors, were used in this study. Outcome variables were smoking status and quit attempt. Key independent variable was food insecurity. We estimated adjusted odds ratios (AOR) and 95% confidence intervals (CI) using weighted multivariable logistic regression models while controlling for individual-level demographic, socioeconomic, clinical, and behavioral characteristics. RESULTS: About 19.0% of cancer survivors were current smokers, out of whom 60.4% made attempt to quit smoking in the past 12 months, and 26.2% reported experiencing food insecurity in the past 12 months. Food insecurity was significantly associated with smoking status and quit attempt after controlling for individual-level characteristics. The odds of being a current smoker, [AOR 1.45 (95% CI 1.10-2.02)], and making quit attempt, [AOR 1.74 (95% CI 1.10, 2.83)], were higher for food insecure cancer survivors compared to food secure cancer survivors. CONCLUSIONS: Food insecurity, in addition to smoking, may hinder the progress of care and treatment, requiring the development of new policies for routine food insecurity screening among cancer survivors. Efforts should be focused on identifying food insecure cancer survivors, targeting their smoking behavior, and offering them appropriate nutritional and smoking cessation interventions.

The risk of sustained sexual transmission of Zika is underestimated.

Pathogens often follow more than one transmission route during outbreaks-from needle sharing plus sexual transmission of HIV to small droplet aerosol plus fomite transmission of influenza. Thus, controlling an infectious disease outbreak often requires characterizing the risk associated with multiple mechanisms of transmission. For example, during the Ebola virus outbreak in West Africa, weighing the relative importance of funeral versus health care worker transmission was essential to stopping disease spread. As a result, strategic policy decisions regarding interventions must rely on accurately characterizing risks associated with multiple transmission routes. The ongoing Zika virus (ZIKV) outbreak challenges our conventional methodologies for translating case-counts into route-specific transmission risk. Critically, most approaches will fail to accurately estimate the risk of sustained sexual transmission of a pathogen that is primarily vectored by a mosquito-such as the risk of sustained sexual transmission of ZIKV. By computationally investigating a novel mathematical approach for multi-route pathogens, our results suggest that previous epidemic threshold estimates could under-estimate the risk of sustained sexual transmission by at least an order of magnitude. This result, coupled with emerging clinical, epidemiological, and experimental evidence for an increased risk of sexual transmission, would strongly support recent calls to classify ZIKV as a sexually transmitted infection.

Comparison of crowd-sourced, electronic health records based, and traditional health-care based influenza-tracking systems at multiple spatial resolutions in the United States of America.

BACKGROUND: Influenza causes an estimated 3000 to 50,000 deaths per year in the United States of America (US). Timely and representative data can help local, state, and national public health officials monitor and respond to outbreaks of seasonal influenza. Data from cloud-based electronic health records (EHR) and crowd-sourced influenza surveillance systems have the potential to provide complementary, near real-time estimates of influenza activity. The objectives of this paper are to compare two novel influenza-tracking systems with three traditional healthcare-based influenza surveillance systems at four spatial resolutions: national, regional, state, and city, and to determine the minimum number of participants in these systems required to produce influenza activity estimates that resemble the historical trends recorded by traditional surveillance systems. METHODS: We compared influenza activity estimates from five influenza surveillance systems: 1) patient visits for influenza-like illness (ILI) from the US Outpatient ILI Surveillance Network (ILINet), 2) virologic data from World Health Organization (WHO) Collaborating and National Respiratory and Enteric Virus Surveillance System (NREVSS) Laboratories, 3) Emergency Department (ED) syndromic surveillance from Boston, Massachusetts, 4) patient visits for ILI from EHR, and 5) reports of ILI from the crowd-sourced system, Flu Near You (FNY), by calculating correlations between these systems across four influenza seasons, 2012-16, at four different spatial resolutions in the US. For the crowd-sourced system, we also used a bootstrapping statistical approach to estimate the minimum number of reports necessary to produce a meaningful signal at a given spatial resolution. RESULTS: In general, as the spatial resolution increased, correlation values between all influenza surveillance systems decreased. Influenza-like Illness rates in geographic areas with more than 250 crowd-sourced participants or with more than 20,000 visit counts for EHR tracked government-lead estimates of influenza activity. CONCLUSIONS: With a sufficient number of reports, data from novel influenza surveillance systems can complement traditional healthcare-based systems at multiple spatial resolutions.

Design Strategies for Efficient Arbovirus Surveillance.

As public health agencies struggle to track and contain emerging arbovirus threats, timely and efficient surveillance is more critical than ever. Using historical dengue data from Puerto Rico, we developed methods for streamlining and designing novel arbovirus surveillance systems with or without historical disease data.

Topological features of a gene co-expression network predict patterns of natural diversity in environmental response.

Molecular interactions affect the evolution of complex traits. For instance, adaptation may be constrained by pleiotropic or epistatic effects, both of which can be reflected in the structure of molecular interaction networks. To date, empirical studies investigating the role of molecular interactions in phenotypic evolution have been idiosyncratic, offering no clear patterns. Here, we investigated the network topology of genes putatively involved in local adaptation to two abiotic stressors-drought and cold-in Arabidopsis thaliana Our findings suggest that the gene-interaction topologies for both cold and drought stress response are non-random, with genes that show genetic variation in drought expression response (eGxE) being significantly more peripheral and cold response genes being significantly more central than genes which do not show GxE. We suggest that the observed topologies reflect different constraints on the genetic pathways involved in environmental response. The approach presented here may inform predictive models linking genetic variation in molecular signalling networks with phenotypic variation, specifically traits involved in environmental response.

On the young age of intraspecific herbaceous taxa.

Dated phylogenies rarely include the divergence times of sister intraspecific taxa, and when they do little is said about this subject. We show that over 90% of the intraspecific plant taxa found in a literature search are estimated to be 5 million yr old or younger, with only 4% of taxa estimated to be over 10 million yr old or older. A Bayesian analysis of intraspecific taxon ages indicates that indeed these taxa are expected to be < 10 million yr old. This result for the young age of intraspecific taxa is consistent with the earlier observation that post-pollination reproductive barriers develop between 5 and 10 million yr after lineage splitting, thus leading to species formation. If lineages have not graduated to the species level of divergence by 10 million yr or so, they are likely to have gone extinct by that time as a result of narrow geographical distributions, narrow niche breadths, and relatively small numbers across populations.

Epidemiological and viral genomic sequence analysis of the 2014 ebola outbreak reveals clustered transmission.

Using Ebolavirus genomic and epidemiological data, we conducted the first joint analysis in which both data types were used to fit dynamic transmission models for an ongoing outbreak. Our results indicate that transmission is clustered, highlighting a potential bias in medical demand forecasts, and provide the first empirical estimate of underreporting.

Asymptomatic transmission and the resurgence of Bordetella pertussis.

BACKGROUND: The recent increase in whooping cough incidence (primarily caused by Bordetella pertussis) presents a challenge to both public health practitioners and scientists trying to understand the mechanisms behind its resurgence. Three main hypotheses have been proposed to explain the resurgence: 1) waning of protective immunity from vaccination or natural infection over time, 2) evolution of B. pertussis to escape protective immunity, and 3) low vaccine coverage. Recent studies have suggested a fourth mechanism: asymptomatic transmission from individuals vaccinated with the currently used acellular B. pertussis vaccines. METHODS: Using wavelet analyses of B. pertussis incidence in the United States (US) and United Kingdom (UK) and a phylodynamic analysis of 36 clinical B. pertussis isolates from the US, we find evidence in support of asymptomatic transmission of B. pertussis. Next, we examine the clinical, public health, and epidemiological consequences of asymptomatic B. pertussis transmission using a mathematical model. RESULTS: We find that: 1) the timing of changes in age-specific attack rates observed in the US and UK are consistent with asymptomatic transmission; 2) the phylodynamic analysis of the US sequences indicates more genetic diversity in the overall bacterial population than would be suggested by the observed number of infections, a pattern expected with asymptomatic transmission; 3) asymptomatic infections can bias assessments of vaccine efficacy based on observations of B. pertussis-free weeks; 4) asymptomatic transmission can account for the observed increase in B. pertussis incidence; and 5) vaccinating individuals in close contact with infants too young to receive the vaccine ("cocooning" unvaccinated children) may be ineffective. CONCLUSIONS: Although a clear role for the previously suggested mechanisms still exists, asymptomatic transmission is the most parsimonious explanation for many of the observations surrounding the resurgence of B. pertussis in the US and UK. These results have important implications for B. pertussis vaccination policy and present a complicated scenario for achieving herd immunity and B. pertussis eradication.

Epigenetic transgenerational inheritance of altered stress responses.

Ancestral environmental exposures have previously been shown to promote epigenetic transgenerational inheritance and influence all aspects of an individual's life history. In addition, proximate life events such as chronic stress have documented effects on the development of physiological, neural, and behavioral phenotypes in adulthood. We used a systems biology approach to investigate in male rats the interaction of the ancestral modifications carried transgenerationally in the germ line and the proximate modifications involving chronic restraint stress during adolescence. We find that a single exposure to a common-use fungicide (vinclozolin) three generations removed alters the physiology, behavior, metabolic activity, and transcriptome in discrete brain nuclei in descendant males, causing them to respond differently to chronic restraint stress. This alteration of baseline brain development promotes a change in neural genomic activity that correlates with changes in physiology and behavior, revealing the interaction of genetics, environment, and epigenetic transgenerational inheritance in the shaping of the adult phenotype. This is an important demonstration in an animal that ancestral exposure to an environmental compound modifies how descendants of these progenitor individuals perceive and respond to a stress challenge experienced during their own life history.

Evolution of a genetic incompatibility in the genus Xiphophorus.

Genetic incompatibilities are commonly observed between hybridizing species. Although this type of isolating mechanism has received considerable attention, we have few examples describing how genetic incompatibilities evolve. We investigated the evolution of two loci involved in a classic example of a Bateson-Dobzhansky-Muller (BDM) incompatibility in Xiphophorus, a genus of freshwater fishes from northern Central America. Hybrids develop a lethal melanoma due to the interaction of two loci, an oncogene and its repressor. We cloned and sequenced the putative repressor locus in 25 Xiphophorus species and an outgroup species, and determined the status of the oncogene in those species from the literature. Using phylogenetic analyses, we find evidence that a repeat region in the proximal promoter of the repressor is coevolving with the oncogene. The data support a hypothesis that departs from the standard BDM model: it appears the alleles that cause the incompatibilities have coevolved simultaneously within lineages, rather than in allopatric or temporal isolation.

About PAR: the distinct evolutionary dynamics of the pseudoautosomal region.

Sex chromosomes differ from other chromosomes in the striking divergence they often show in size, structure, and gene content. Not only do they possess genes controlling sex determination that are restricted to either the X or Y (or Z or W) chromosomes, but in many taxa they also include recombining regions. In these 'pseudoautosomal regions' (PARs), sequence homology is maintained by meiotic pairing and exchange in the heterogametic sex. PARs are unique genomic regions, exhibiting some features of autosomes, but they are also influenced by their partial sex linkage. Here we review the distribution and structure of PARs among animals and plants, the theoretical predictions concerning their evolutionary dynamics, the reasons for their persistence, and the diversity and content of genes that reside within them. It is now clear that the evolution of the PAR differs in important ways from that of genes in either the non-recombining regions of sex chromosomes or the autosomes.