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

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

Obstacles to Optimal Antenatal Corticosteroid Administration to Eligible Patients

Background Administration of antenatal corticosteroids (ANCS) is recommended for individuals expected to deliver between 24 and 34 weeks of gestation. Properly timed administration of ANCS achieves maximal benefit. However, more than 50% of individuals receive ANCS outside the recommended window. Objective To examine maternal and hospital factors associated with suboptimal receipt of ANCS among individuals who deliver between 24–34 weeks gestation. Study Design Secondary analysis of the Assessment of Perinatal Excellence (APEX), an observational study of births to 115,502 individuals at 25 hospitals in the US from March 2008–February 2011. Data from 3123 individuals who gave birth to a non-anomalous live-born infant between 240/7 to 340/7 weeks gestation, had prenatal records available at delivery, and data available on the timing of ANCS use were included in this analysis. Eligible individuals’ ANCS status was categorized as optimal (full course completed \u3e24 hours after ANCS but not \u3e7 days before birth) or suboptimal (none, too late, or too early). Maternal and hospital-level variables were compared using optimal as the referent group. Hierarchical multinomial logistic regression models, with site as a random effect, were used to identify maternal and hospital-level characteristics associated with optimal ANCS use. Results Overall, 83.6% (2612/3123) of eligible individuals received any treatment: 1216 (38.9%) optimal and 1907 (61.1%) suboptimal. Within suboptimal group495 (15.9%) received ANCS too late, 901 (28.9%) too early and 511 (16.4%) did not receive any ANCS. Optimal ANCS varied depending on indication for hospital admission (p\u3c0.001). Individuals who were admitted with intent to deliver were less likely to receive optimal ANCS while individuals admitted for hypertensive diseases of pregnancy were most likely to receive optimal ANCS (10% vs 35%). The median gestational age of individuals who received optimal ANCS was 31.0 weeks. Adjusting for hospital factors, hospitals with electronic medical records and who receive transfers had fewer eligible individuals who did not receive ANCS. ANCS administration and timing varied substantially by hospital; optimal frequencies ranged from 9.1 to 51.3%, and none frequencies from 6.1% to 61.8%. When evaluating variation by hospital site, models with maternal and hospital factors, did not explain any of the variation in ANCS use. Conclusions Optimal ANCS use varied by maternal and hospital factors and by hospital site, indicating opportunities for improvement

The Temporal Relationship Between the Coronavirus Disease 2019 (COVID-19) Pandemic and Preterm Birth

OBJECTIVE: To evaluate whether preterm birth rates changed in relation to the onset of the coronavirus disease 2019 (COVID-19) pandemic and whether any change depended on socioeconomic status. METHODS: This is an observational cohort study of pregnant individuals with a singleton gestation who delivered in the years 2019 and 2020 at 1 of 16 U.S. hospitals of the Maternal-Fetal Medicine Units Network. The frequency of preterm birth for those who delivered before the onset of the COVID-19 pandemic (ie, in 2019) was compared with that of those who delivered after its onset (ie, in 2020). Interaction analyses were performed for people of different individual- and community-level socioeconomic characteristics (ie, race and ethnicity, insurance status, Social Vulnerability Index (SVI) of a person\u27s residence). RESULTS: During 2019 and 2020, 18,526 individuals met inclusion criteria. The chance of preterm birth before the COVID-19 pandemic was similar to that after the onset of the pandemic (11.7% vs 12.5%, adjusted relative risk 0.94, 95% CI 0.86-1.03). In interaction analyses, race and ethnicity, insurance status, and the SVI did not modify the association between the epoch and the chance of preterm birth before 37 weeks of gestation (all interaction P \u3e.05). CONCLUSION: There was no statistically significant difference in preterm birth rates in relation to the COVID-19 pandemic onset. This lack of association was largely independent of socioeconomic indicators such as race and ethnicity, insurance status, or SVI of the residential community in which an individual lived