Latent Self-Exciting Point Process Model for Spatial-Temporal Networks

We propose a latent self-exciting point process model that describes geographically distributed interactions between pairs of entities. In contrast to most existing approaches that assume fully observable interactions, here we consider a scenario where certain interaction events lack information about participants. Instead, this information needs to be inferred from the available observations. We develop an efficient approximate algorithm based on variational expectation-maximization to infer unknown participants in an event given the location and the time of the event. We validate the model on synthetic as well as real-world data, and obtain very promising results on the identity-inference task. We also use our model to predict the timing and participants of future events, and demonstrate that it compares favorably with baseline approaches.Comment: 20 pages, 6 figures (v3); 11 pages, 6 figures (v2); previous version appeared in the 9th Bayesian Modeling Applications Workshop, UAI'1

Gang-related crime in Los Angeles remained stable following COVID-19 social distancing orders

Research Summary The onset of extreme social distancing measures is expected to have a dramatic impact on crime. Here, we examine the impact of mandated, city‐wide social distancing orders aimed at limiting the spread of COVID‐19 on gang‐related crime in Los Angeles. We hypothesize that the unique subcultural processes surrounding gangs may supersede calls to shelter in place and allow gang‐related crime to persist. If the normal guardianship of people and property is also disrupted by social distancing, then we expect gang violence to increase. Using autoregressive time series models, we show that gang‐related crime remained stable and crime hot spots largely stationary following the onset of shelter in place. Policy Implications In responding to disruptions to social and economic life on the scale of the present pandemic, both police and civilian organizations need to anticipate continued demand, all while managing potential reductions to workforce. Police are faced with this challenge across a wide array of crime types. Civilian interventionists tasked with responding to gang‐related crime need to be prepared for continued peacekeeping and violence interruption activities, but also an expansion of responsibilities to deal with “frontline” or “street‐level” management of public health needs

Impact of social distancing during COVID-19 pandemic on crime in Los Angeles and Indianapolis

Governments have implemented social distancing measures to address the ongoing COVID-19 pandemic. The measures include instructions that individuals maintain social distance when in public, school closures, limitations on gatherings and business operations, and instructions to remain at home. Social distancing may have an impact on the volume and distribution of crime. Crimes such as residential burglary may decrease as a byproduct of increased guardianship over personal space and property. Crimes such as domestic violence may increase because of extended periods of contact between potential offenders and victims. Understanding the impact of social distancing on crime is critical for ensuring the safety of police and government capacity to deal with the evolving crisis. Understanding how social distancing policies impact crime may also provide insights into whether people are complying with public health measures. Examination of the most recently available data from both Los Angeles, CA, and Indianapolis, IN, shows that social distancing has had a statistically significant impact on a few specific crime types. However, the overall effect is notably less than might be expected given the scale of the disruption to social and economic life

Human group formation in online guilds and offline gangs driven by common team dynamic

Quantifying human group dynamics represents a unique challenge. Unlike animals and other biological systems, humans form groups in both real (offline) and virtual (online) spaces -- from potentially dangerous street gangs populated mostly by disaffected male youths, through to the massive global guilds in online role-playing games for which membership currently exceeds tens of millions of people from all possible backgrounds, age-groups and genders. We have compiled and analyzed data for these two seemingly unrelated offline and online human activities, and have uncovered an unexpected quantitative link between them. Although their overall dynamics differ visibly, we find that a common team-based model can accurately reproduce the quantitative features of each simply by adjusting the average tolerance level and attribute range for each population. By contrast, we find no evidence to support a version of the model based on like-seeking-like (i.e. kinship or `homophily')

Adjunctive Azithromycin Prophylaxis for Cesarean Delivery

The addition of azithromycin to standard regimens for antibiotic prophylaxis before cesarean delivery may further reduce the rate of postoperative infection. We evaluated the benefits and safety of azithromycin-based extended-spectrum prophylaxis in women undergoing nonelective cesarean section

Risk Factors for Postcesarean Maternal Infection in a Trial of Extended-Spectrum Antibiotic Prophylaxis

To identify maternal clinical risk factors for postcesarean maternal infection in a randomized clinical trial of preincision extended-spectrum antibiotic prophylaxis

Association of Recorded Estimated Fetal Weight and Cesarean Delivery in Attempted Vaginal Delivery at Term:

To evaluate the association between documentation of estimated fetal weight, and its value, with cesarean delivery

The Effect of Urban Street Gang Densities on Small Area Homicide Incidence in a Large Metropolitan County, 1994–2002

The presence of street gangs has been hypothesized as influencing overall levels of violence in urban communities through a process of gun–drug diffusion and cross-type homicide. This effect is said to act independently of other known correlates of violence, i.e., neighborhood poverty. To test this hypothesis, we independently assessed the impact of population exposure to local street gang densities on 8-year homicide rates in small areas of Los Angeles County, California. Homicide data from the Los Angeles County Coroners Office were analyzed with original field survey data on street gang locations, while controlling for the established covariates of community homicide rates. Bivariate and multivariate regression analyses explicated strong relationships between homicide rates, gang density, race/ethnicity, and socioeconomic structure. Street gang densities alone had cumulative effects on small area homicide rates. Local gang densities, along with high school dropout rates, high unemployment rates, racial and ethnic concentration, and higher population densities, together explained 90% of the variation in local 8-year homicide rates. Several other commonly considered covariates were insignificant in the model. Urban environments with higher densities of street gangs exhibited higher overall homicide rates, independent of other community covariates of homicide. The unique nature of street gang killings and their greater potential to influence future local rates of violence suggests that more direct public health interventions are needed alongside traditional criminal justice mechanisms to combat urban violence and homicides