Examining the Neighborhood Attributes of Recently Housed Partner Violence Survivors in Rapid Rehousing

Survivors’ considerations for re-housing following intimate partner violence (IPV) are understudied despite likely neighborhood-level influences on women’s safety. We assess housing priorities and predictors of re-housing location among recent IPV survivors (n = 54) in Rapid Re-housing (RRH) in the Baltimore-Washington Metropolitan Area. Choropleth maps depict residential location relative to census tract characteristics (neighborhood deprivation index (NDI) and residential segregation) derived from American Community Survey data (2013–2017). Linear regression measured associations between women’s individual, economic, and social factors and NDI and segregation. In-depth interviews (n = 16) contextualize quantitative findings. Overall, survivors re-housed in significantly more deprived and racially segregated census tracts within their respective regions. In adjusted models, trouble securing housing (B = 0.74, 95% CI: 0.13, 1.34), comfortability with proximity to loved ones (B = 0.75, 95% CI: 0.02, 1.48), and being unsure (vs unlikely) about IPV risk (B = −0.76, 95% CI: −1.39, −0.14) were significantly associated with NDI. Economic dependence on an abusive partner (B = −0.31, 95% CI: −0.56, −0.06) predicted re-housing in segregated census tracts; occasional stress about housing affordability (B = 0.39, 95% CI: 0.04, 0.75) predicted re-housing in less segregated census tracts. Qualitative results contextualize economic (affordability), safety, and social (familiarity) re-housing considerations and process impacts (inspection delays). Structural racism, including discriminatory housing practices, intersect with gender, exacerbating challenges among survivors of severe IPV. This mixed-methods study further highlights the significant economic tradeoffs for safety and stability, where the prioritization of safety may exacerbate economic devastation for IPV survivors. Findings will inform programmatic policies for RRH practices among survivors.

A flexible COVID-19 model to assess mitigation, reopening, virus mutation and other changes

The COVID-19 epidemic which began in China last year has expanded worldwide. A flexible SEIRD epidemiological model with time-dependent parameters is applied to modeling the pandemic. The value of the effective reproduction ratio is varied to quantify the impact of quarantines and social distancing on the number of infections and deaths, on their daily changes. and on the maxima in these daily rates expected during the epidemic. The effect of changing Reff is substantial. It ought to inform policy decisions around resource allocation, mitigation strategies and their duration, and economic tradeoffs. The model can also calculate the impact of changes in infectiousness or morbidity as the virus mutates, or the expected effects of a new therapy or vaccine assumed to arrive at a future date. The paper concludes with a discussion of a potential endemic end of COVID-19, which might involve times of about 100 years.

Agronomic and economic tradeoffs between alternative cover crop and organic soybean sequences

Organic grain producers are interested in reducing tillage to conserve soil and decrease labor and fuel costs. We examined agronomic and economic tradeoffs associated with alternative strategies for reducing tillage frequency and intensity in a cover crop–soybean (Glycine max L. Merr.) sequence within a corn (Zea mays L.)–soybean–spelt (Triticum spelta L.) organic cropping system experiment in Pennsylvania. Tillage-based soybean production preceded by a cover crop mixture of annual ryegrass (Lolium perenne L. ssp. multiflorum), orchardgrass (Dactylis glomerata L.) and forage radish (Raphanus sativus L.) interseeded into corn grain (Z. mays L.) was compared with reduced-tillage soybean production preceded by roller-crimped cereal rye (Secale cereale L.) that was sown after corn silage. Total aboveground weed biomass did not differ between soybean production strategies. Each strategy, however, was characterized by high inter-annual variability in weed abundance. Tillage-based soybean production marginally increased grain yield by 0.28 Mg ha−1 compared with reduced-tillage soybean. A path model of soybean yield indicated that soybean stand establishment and weed biomass were primary drivers of yield, but soybean production strategy had a measurable effect on yields due to factors other than within-season weed–crop competition. Cumulative tillage frequency and intensity were quantified for each cover crop—sequence using the Soil Tillage Intensity Rating (STIR) index. The reduced-tillage soybean sequence resulted in 50% less soil disturbance compared to tillage-based soybean sequence across study years. Finally, enterprise budget comparisons showed that the reduced-tillage soybean sequence resulted in lower input costs than the tillage-based soybean sequence but was approximately $114 ha−1 less profitable because of lower average yields.