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Accounting for uncertainty during a pandemic
We discuss several issues of statistical design, data collection, analysis, communication, and decision-making that have arisen in recent and ongoing coronavirus studies, focusing on tools for assessment and propagation of uncertainty. This paper does not purport to be a comprehensive survey of the research literature; rather, we use examples to illustrate statistical points that we think are important.
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Coccidioidomycosis and COVID-19 Co-Infection, United States, 2020
We review the interaction between coronavirus disease (COVID-19) and coccidioidomycosis, a respiratory infection caused by inhalation …
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Protective impacts of household-based tuberculosis contact tracing are robust across endemic incidence levels and community contact patterns
Screening household members of newly detected tuberculosis cases is an efficient method for finding previously undiagnosed cases in high-burden settings. Despite the intuitive appeal of this approach, randomized trials examining the population-level effects of these interventions in settings with sustained community transmission have shown mixed results. One explanation for these inconclusive findings is that household transmission is responsible for a varying proportion of overall tuberculosis burden between locations, with the impact of household transmission being a function of both the overall incidence and the relative intensity of disease-transmitting contacts in the community and the household. In this manuscript, we use an individual-based network model to explore how local incidence levels and patterns of community contact impact the effectiveness of household-based approaches for interrupting tuberculosis transmission. Our analyses suggest that protective benefits of household-based interventions are maintained across a wide range of epidemiological settings. Our findings provide evidence for the robustness of household-based interventions and suggest that variable results from trials may be primarily due to implementation challenges rather than inherent limitations of these interventions.
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Measuring the impact of spatial perturbations on the relationship between data privacy and validity of descriptive statistics

Background: Like many scientific fields, epidemiology is addressing issues of research reproducibility. Spatial epidemiology, which …

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Measuring Multiple Dimensions and Indices of Non-Vaccination Clustering in Michigan: 2008-2018
Michigan experienced a significant measles outbreak in 2019 amidst rising rates of non-medical vaccine exemptions (NMEs) and low …
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Racial Disparities in Coronavirus Disease 2019 (COVID-19) Mortality Are Driven by Unequal Infection Risks

Background: As of November 1, 2020, there have been more than 230K deaths and 9M confirmed and probable cases attributable to …

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Fine-scale spatial clustering of measles nonvaccination that increases outbreak potential is obscured by aggregated reporting data
The United States experienced historically high numbers of measles cases in 2019, despite achieving national measles vaccination rates …
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Prenatal and early-life exposure to the Great Chinese Famine increased the risk of tuberculosis in adulthood across two generations
Global food security is a major driver of population health, and food system collapse may have complex and long-lasting effects on …
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Children as sentinels of tuberculosis transmission: disease mapping of programmatic data

Background: Identifying hotspots of tuberculosis transmission can inform spatially targeted active case-finding interventions. While …

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The Impact of Vaccination Efforts on the Spatiotemporal Patterns of the Hepatitis A Outbreak in Michigan, 2016–2018

Background: The United States is currently experiencing the largest hepatitis A virus (HAV) outbreak since the introduction of a …

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