Multi-dimensional measures of geography and the opioid epidemic: place, time and context

The opioid crisis has hit the United States hard in recent years. Behavioral patterns and social environments associated with opioid use and misuse vary significantly across communities. It is important to understand the geospatial prevalence of opioid overdoses and other impacts related to the crisis in order to provide a targeted response at different locations. This dissertation contributes a framework for understanding spatial and temporal patterns of drug prevalence, treatment services access and associated socio-environmental factors for opioid use and misuse. This dissertation addresses three main questions related to geography and the opioid epidemic: 1) How did drug poisoning deaths involving heroin evolve over space and time in the U.S. between 2000-2016; 2) How did access to opioid use disorder treatment facilities and emergency medical services vary spatially in New Hampshire during 2015-2016; and 3) What were the relations between socio-environmental factors and numbers of emergency department patients with drug-related health problems over space and time in Maryland during 2016-2018. For the first study, this dissertation developed a spatial and temporal data model to investigate trends of heroin mortality over a 17-year period (2000-2016). The research presented in this dissertation also involved developing a composite index to analyze spatial accessibility to both opioid use disorder treatment facilities and emergency medical services and compared these locations with the locations of deaths involving fentanyl to identify possible gaps in services. In the third study for this dissertation, I utilized socially-sensed data to identify neighborhood characteristics and investigated spatial and temporal relationships with emergency department patients with drug-related health problems admitted to the four hospitals in the western Baltimore area in Maryland during 2016 to 2018, in order to identify the dynamic patterns of the associations in terms of various socio-environmental factors

Modelling the COVID-19 Vaccine Uptake Rates in a Geographical and Socioeconomic Context: A Case Study of England

The global Covid-19 pandemic has posed unprecedented social and economic challenges to many countries, including the United Kingdom. One of the key strategies to contain the pandemic is mass vaccination. The Covid-19 vaccine uptake rate of a population group depends on a range of geographical and socio-economic factors, including accessibility to vaccination, ethnic composition, deprivation levels, etc. However, limited research has been conducted to obtain a quantitative understanding of how these factors are associated with the Covid-19 vaccine uptake rates. This study fills this gap by proposing a beta regression model for the small-area Covid-19 vaccine uptake rates in England. The findings have important implications for the practice and policymaking of advocating vaccination programmes and other healthcare services

Spatial heterogeneity of enteric fever in 2 diverse communities in Nepal

Background: Typhoid fever is endemic in the urban Kathmandu Valley of Nepal; however, there have been no population-based studies of typhoid outside of this community in the past 3 decades. Whether typhoid immunization should be prioritized in periurban and rural communities has been unclear.Methods: We performed population-based surveillance for enteric fever in 1 urban catchment (Kathmandu) and 1 periurban and rural catchment (Kavrepalanchok) as part of the Surveillance for Enteric Fever in Asia Project (SEAP). We recruited individuals presenting to outpatient and emergency departments at 2 study hospitals with suspected enteric fever and performed blood cultures. Additionally, we conducted a household survey in each catchment area to characterize care seeking for febrile illness. We evaluated spatial heterogeneity in febrile illness, care seeking, and enteric fever incidence.Results: Between September 2016 and September 2019, we enrolled 5736 participants with suspected enteric fever at 2 study hospitals. Among these, 304 (5.3%) were culture positive for Salmonella Typhi (249 [81.9%]) or Paratyphi A (55 [18.1%]). Adjusted typhoid incidence in Kathmandu was 484 per 100 000 person-years and in Kavrepalanchok was 615 per 100 000 person-years. While all geographic areas for which estimates could be made had incidence \u3e200 per 100 000 person-years, we observed spatial heterogeneity with up to 10-fold variation in incidence between communities.Conclusions: In urban, periurban, and rural communities in and around Kathmandu, we measured a high but heterogenous incidence of typhoid. These findings provide some support for the introduction of conjugate vaccines in Nepal, including outside urban areas, alongside other measures to prevent enteric fever

Accessibility Assessment of Buildings Based on Multi-Source Spatial Data: Taking Wuhan as a Case Study

The question of whether each building of housing estate has equal access to nearby social service resources (e.g., public transportation service, catering, entertainment, etc.) is a major concern of citizens. This paper takes Wuhan as a case to explore the equality in social service resource sharing of the housing estate at a microscopic level by analyzing the accessibility of each building under different travel patterns. To estimate the accessibility of each building, we developed a novel model with multi-travel modes and residential suitability evaluation of residents. The specific values of the parameters involved in the proposed model were extracted from the multi-source spatial data such as social media data, census data, point of interest, and road network data. These data were acquired from multiple platforms, e.g., Gaode map, OSM (OpenStreetMap), and GeoQ. We chose three types of districts in the city of Wuhan, including the old central district, new central district, and suburban district. We applied the proposed model to assess the accessibility of communities in these districts. Based on the results, we further analyzed whether and to what extent the distribution of each building in urban communities is equitable for social service resource sharing in China

Understanding the spatial heterogeneity of COVID-19 vaccination uptake in England

Abstract Background Mass vaccination has been a key strategy in effectively containing global COVID-19 pandemic that posed unprecedented social and economic challenges to many countries. However, vaccination rates vary across space and socio-economic factors, and are likely to depend on the accessibility to vaccination services, which is under-researched in literature. This study aims to empirically identify the spatially heterogeneous relationship between COVID-19 vaccination rates and socio-economic factors in England. Methods We investigated the percentage of over-18 fully vaccinated people at the small-area level across England up to 18 November 2021. We used multiscale geographically weighted regression (MGWR) to model the spatially heterogeneous relationship between vaccination rates and socio-economic determinants, including ethnic, age, economic, and accessibility factors. Results This study indicates that the selected MGWR model can explain 83.2% of the total variance of vaccination rates. The variables exhibiting a positive association with vaccination rates in most areas include proportion of population over 40, car ownership, average household income, and spatial accessibility to vaccination. In contrast, population under 40, less deprived population, and black or mixed ethnicity are negatively associated with the vaccination rates. Conclusions Our findings indicate the importance of improving the spatial accessibility to vaccinations in developing regions and among specific population groups in order to promote COVID-19 vaccination

Event-Based Optimization for Dispatching Policies in Material Handling Systems of General Assembly Lines

assembly line dispatching parts from inventory to working buffers could be complicated and costly to operate. Generally it is extremely difficult to find the optimal dispatching policy due to the complicated system dynamics and the large problem size. In this paper, we formulate the dispatching problem as a Markov decision process (MDP), and use event-based optimization framework to overcome the difficulty caused by problem dimensionality and size. By exploiting the problem structures, we focus on responding to certain events instead of all state transitions, so that the number of aggregated potential function (i.e., value function) is scaled to the square of the system size despite of the exponential growth of the state space. This effectively reduces the computational requirements to a level that is acceptable in practice. We then develop a sample path based algorithm to estimate the potentials, and implement a gradient-based policy optimization procedure. Numerical results demonstrate that the policies obtained by the event-based optimization approach significantly outperform the current dispatching method in production.

DataSheet_1_The incidence risk of breast and gynecological cancer by antidepressant use: A systematic review and dose–response meta-analysis of epidemiological studies involving 160,727 patients.pdf

Background and objectiveAntidepressants are widely prescribed to treat depression and anxiety disorders that may become chronic conditions among women. Epidemiological studies have yielded inconsistent results on the correlation between antidepressant use and the incidence risk of female breast and gynecological cancer, along with uncertain dose–response relationship. Therefore, we performed a systematic review and dose–response meta-analysis to investigate the association.MethodsWeb of Science, Embase, PubMed, The Cochrane Library, and PsycINFO were systematically searched in January 2022, with no language limits. Random-effect models were used to calculate pooled effect sizes and 95% confidence intervals between studies. Linear and non-linear dose–response analyses were performed to evaluate the dose or duration of antidepressant use affecting the incidence risk of female breast and gynecological cancer. Further subgroup analyses were systematically performed by stratifying almost all study characteristics and important potential confounders, in order to further clarify and validate the important potential hypotheses regarding the biological mechanism underlying this association.ResultsBased on a systematic literature search, 34 eligible studies (27 case–control studies and 7 cohort studies) involving 160,727 female breast and gynecological cancer patients found that antidepressant use did not increase the incidence risk of female breast and gynecological cancer (pooled OR: 1.01; 95% CI: 0.97, 1.04, I² = 71.5%, p ConclusionThis systematic review and dose–response meta-analysis found that antidepressant use did not increase the incidence risk of female breast and gynecological cancer and even decreased the incidence risk of ovarian cancer, along with a non-linear or linear dose–response relationship.Systematic Review RegistrationPROSPERO https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=313364, identifier CRD42022313364.</p

The international and intercontinental spread and expansion of antimicrobial-resistant Salmonella Typhi: a genomic epidemiology study

Background: The emergence of increasingly antimicrobial-resistant Salmonella enterica serovar Typhi (S Typhi) threatens to undermine effective treatment and control. Understanding where antimicrobial resistance in S Typhi is emerging and spreading is crucial towards formulating effective control strategies. Methods: In this genomic epidemiology study, we sequenced the genomes of 3489 S Typhi strains isolated from prospective enteric fever surveillance studies in Nepal, Bangladesh, Pakistan, and India (between 2014 and 2019), and combined these with a global collection of 4169 S Typhi genome sequences isolated between 1905 and 2018 to investigate the temporal and geographical patterns of emergence and spread of antimicrobial-resistant S Typhi. We performed non-parametric phylodynamic analyses to characterise changes in the effective population size of fluoroquinolone-resistant, extensively drug-resistant (XDR), and azithromycin-resistant S Typhi over time. We inferred timed phylogenies for the major S Typhi sublineages and used ancestral state reconstruction methods to estimate the frequency and timing of international and intercontinental transfers. Findings: Our analysis revealed a declining trend of multidrug resistant typhoid in south Asia, except for Pakistan, where XDR S Typhi emerged in 2016 and rapidly replaced less-resistant strains. Mutations in the quinolone-resistance determining region (QRDR) of S Typhi have independently arisen and propagated on at least 94 occasions, nearly all occurring in south Asia. Strains with multiple QRDR mutations, including triple mutants with high-level fluoroquinolone resistance, have been increasing in frequency and displacing strains with fewer mutations. Strains containing acrB mutations, conferring azithromycin resistance, emerged in Bangladesh around 2013 and effective population size of these strains has been steadily increasing. We found evidence of frequent international (n=138) and intercontinental transfers (n=59) of antimicrobial-resistant S Typhi, followed by local expansion and replacement of drug-susceptible clades. Interpretation: Independent acquisition of plasmids and homoplastic mutations conferring antimicrobial resistance have occurred repeatedly in multiple lineages of S Typhi, predominantly arising in south Asia before spreading to other regions. Funding: Bill &amp; Melinda Gates Foundation