Mass casualty modelling: a spatial tool to support triage decision making

BACKGROUND:During a mass casualty incident, evacuation of patients to the appropriate health care facility is critical to survival. Despite this, no existing system provides the evidence required to make informed evacuation decisions from the scene of the incident. To mitigate this absence and enable more informed decision making, a web based spatial decision support system (SDSS) was developed. This system supports decision making by providing data regarding hospital proximity, capacity, and treatment specializations to decision makers at the scene of the incident.METHODS:This web-based SDSS utilizes pre-calculated driving times to estimate the actual driving time to each hospital within the inclusive trauma system of the large metropolitan region within which it is situated. In calculating and displaying its results, the model incorporates both road network and hospital data (e.g. capacity, treatment specialties, etc.), and produces results in a matter of seconds, as is required in a MCI situation. In addition, its application interface allows the user to map the incident location and assists in the execution of triage decisions.RESULTS:Upon running the model, driving time from the MCI location to the surrounding hospitals is quickly displayed alongside information regarding hospital capacity and capability, thereby assisting the user in the decision-making process.CONCLUSIONS:The use of SDSS in the prioritization of MCI evacuation decision making is potentially valuable in cases of mass casualty. The key to this model is the utilization of pre-calculated driving times from each hospital in the region to each point on the road network. The incorporation of real-time traffic and hospital capacity data would further improve this model

Spatial Access to Emergency Services in Low- and Middle-Income Countries: A GIS-Based Analysis

Injury is a leading cause of the global disease burden, accounting for 10 percent of all deaths worldwide. Despite 90 percent of these deaths occurring in low and middle-income countries (LMICs), the majority of trauma research and infrastructure development has taken place in high-income settings. Furthermore, although accessible services are of central importance to a mature trauma system, there remains a paucity of literature describing the spatial accessibility of emergency services in LMICs. Using data from the Service Provision Assessment component of the Demographic and Health Surveys of Namibia and Haiti we defined the capabilities of healthcare facilities in each country in terms of their preparedness to provide emergency services. A Geographic Information System-based network analysis method was used to define 5- 10- and 50-kilometer catchment areas for all facilities capable of providing 24-hour care, higher-level resuscitative services or tertiary care. The proportion of a country’s population with access to each level of service was obtained by amalgamating the catchment areas with a population layer. A significant proportion of the population of both countries had poor spatial access to lower level services with 25% of the population of Haiti and 51% of the population of Namibia living further than 50 kilometers from a facility capable of providing 24-hour care. Spatial access to tertiary care was considerably lower with 51% of Haitians and 72% of Namibians having no access to these higher-level services within 50 kilometers. These results demonstrate a significant disparity in potential spatial access to emergency services in two LMICs compared to analogous estimates from high-income settings, and suggest that strengthening the capabilities of existing facilities may improve the equity of emergency services in these countries. Routine collection of georeferenced patient and facility data in LMICs will be important to understanding how spatial access to services influences outcomes

PastoralScape : an environment-driven model of vaccination decision making within pastoralist groups in East Africa

Economic and cultural resilience among pastoralists in East Africa is threatened by the interconnected forces of climate change and contagious diseases spread. A key factor in the resilience of livestock dependent communities is human decision making regarding vaccination against preventable diseases such as Rift Valley fever and Contagious Bovine Pleuropneumonia. The relationship between healthy and productive livestock and economic development of poor households and communities is mediated by human decision making. This paper describes a coupled human and natural systems agent-based model that focuses on One Health. Disease propagation and animal nutritional health are driven by historical GIS data that captures changes in foraging condition. The results of a series of experiments are presented that demonstrate the sensitivity of a transformed Random Field Ising Model of human decision making to changes in human memory and rationality parameters. Results presented communicate that convergence in the splitting of households between vaccinating or not is achieved for combinations of memory and rationality. The interaction of these cognition parameters with public information and social networks of opinions is detailed. This version of the PastoralScape model is intended to form the basis upon which richer economic and human factor models can be built. © 2021, University of Surrey. All rights reserved

A Comparative Analysis of Potential Spatio-Temporal Access to Palliative Care Services in Two Canadian Provinces

Background Access to health services such as palliative care is determined not only by health policy but a number of legacies linked to geography and settlement patterns. We use GIS to calculate potential spatio-temporal access to palliative care services. In addition, we combine qualitative data with spatial analysis to develop a unique mixed-methods approach. Methods Inpatient health care facilities with dedicated palliative care beds were sampled in two Canadian provinces: Newfoundland and Saskatchewan. We then calculated one-hour travel time catchments to palliative health services and extended the spatial model to integrate available beds as well as documented wait times. Results 26 facilities with dedicated palliative care beds in Newfoundland and 69 in Saskatchewan were identified. Spatial analysis of one-hour travel times and palliative beds per 100,000 population in each province showed distinctly different geographical patterns. In Saskatchewan, 96.7 % of the population living within a-1 h of drive to a designated palliative care bed. In Newfoundland, 93.2 % of the population aged 65+ were living within a-1 h of drive to a designated palliative care bed. However, when the relationship between wait time and bed availability was examined for each facility within these two provinces, the relationship was found to be weak in Newfoundland (R2 = 0.26) and virtually nonexistent in Saskatchewan (R2 = 0.01). Conclusions Our spatial analysis shows that when wait times are incorporated as a way to understand potential spatio-temporal access to dedicated palliative care beds, as opposed to spatial access alone, the picture of access changes

Spatial Relationships between Small-Holder Farms Coupled With Livestock Management Practices Are Correlated With the Distribution of Antibiotic Resistant Bacteria in Northern Tanzania

We examined the spatial distribution of antibiotic-resistant coliform bacteria amongst livestock from three distinct cultural groups, where group-level differences in practices (e.g., antibiotic use) may influence the magnitude of antibiotic resistance, while livestock interactions (e.g., mixing herds, shared markets) between these locations may reduce heterogeneity in the distribution of antibiotic resistant bacteria. Data was collected as part of a larger study of antibiotic-resistance in northern Tanzania. Simple regression and generalized linear regression were used to assess livestock management and care practices in relation to the prevalence of multidrug-resistant (MDR) coliform bacteria. Simple and multivariable logistic regression were then used to identify how different management practices affected the odds of households being found within MDR “hotspots.” Households that had a higher median neighbourhood value within a 3000 m radius showed a significant positive correlation with livestock MDR prevalence (β = 4.33, 95% CI: 2.41–6.32). Households were more likely to be found within hotspots if they had taken measures to avoid disease (Adjusted Odds Ratio (AOR) 1.53, CI: 1.08—2.18), and if they reported traveling less than a day to reach the market (AOR 2.66, CI: 1.18—6.01). Hotspot membership was less likely when a greater number of livestock were kept at home (AOR 0.81, CI: 0.69–0.95), if livestock were vaccinated (AOR 0.32, CI: 0.21—0.51), or if distance to nearest village was greater (AOR 0.46, CI: 0.36–0.59). The probability of MDR increases when herds are mixed, consistent with evidence for passive transmission of resistant bacteria between animals. Reduced MDR with vaccination is consistent with many studies showing reduced antibiotic use with less disease burden. The neighbourhood effect has implications for design of intervention studies

Media literacy's role in the mitigation of disinformation effects on substance misuse

Objective: Misinformation and substance use both increased substantially during the COVID-19 pandemic. This study examined potential links between misinformation beliefs and substance use among adults, along with the potential for media literacy to mitigate misinformation's influences on problematic use of widely available substances of misuse.Method: Structural equation modeling (SEM) was used to test a theoretical model of media literacy's effects on substance use, fully mediated by disinformation beliefs, with a nationally representative sample of U.S. adults recruited through a Qualtrics panel of adults using census-based quotas for geographic region, population density, ethnic diversity and gender (N = 1264). The sample was 51.5% male (N = 651); 46.7% female (N = 591); 1.1% nonbinary (N = 13); and 0.7% (N = 9) not reporting.Results: Media literacy for source of news positively associated with media literacy for content of news (b = 0.814, p < 0.001). Media literacy for content of news then positively associated with science media literacy (b = 0.192, p < 0.001). Science media literacy then negatively associated with disinformation beliefs (b = -0.586, p < 0.001), and COVID-19 disinformation beliefs associated with an increase in substance use (b = 0.466, p < 0.001). Disinformation beliefs also associated with alcohol and sleep medication co-use (odds = 1.956, p < 0.05).Conclusions: Results demonstrate media literacy's value for substance misuse prevention and effective public health messaging

Socio Economic Status and Traumatic Brain Injury amongst Pediatric Populations: A Spatial Analysis in Greater Vancouver

Introduction: Within Canada, injuries are the leading cause of death amongst children fourteen years of age and younger, and also one of the leading causes of morbidity. Low Socio Economic Status (SES) seems to be a strong indicator of a higher prevalence of injuries. This study aims to identify hotspots for pediatric Traumatic Brain Injury (TBI) and examines the relationship between SES and pediatric TBI rates in greater Vancouver, British Columbia (BC), Canada. Methods: Pediatric TBI data from the BC Trauma Registry (BCTR) was used to identify all pediatric TBI patients admitted to BC hospitals between the years 2000 and 2013. Spatial analysis was used to identify hotspots for pediatric TBI. Multivariate analysis was used to distinguish census variables that were correlated with rates of injury. Results: Six hundred and fifty three severe pediatric TBI injuries occurred within the BC Lower Mainland between 2000 and 2013. High rates of injury were concentrated in the East, while low rate clusters were most common in the West of the region (more affluent neighborhoods). A low level of education was the main predictor of a high rate of injury (OR = 1.13, 95% CI = 1.03–1.23, p-Value 0.009). Conclusion: While there was a clear relationship between different SES indicators and pediatric TBI rates in greater Vancouver, income-based SES indicators did not serve as good predictors within this region

Spatial Epidemiology of Child and Youth Injury

Injury is one of the leading causes of death amongst Canadian children. Every year, it is estimated that approximately 25000 children will be hospitalized because of unintentional injuries – of these 25000, nearly 400 are likely to die. However, not all children are equally at risk. Studies have shown that children from socio-economically deprived families are at higher risk of morbidity and mortality as a result of injuries. In fact, despite a steady decrease in total rates of injury within the Western world, the difference in rates of pediatric injury between rich and poor has actually broadened in recent decades. In addition, injury has been shown to have a geographical gradient, whereby populations residing in rural areas experience worse outcomes compared to urban dwellers. This is primarily attributable to the reduced access to pediatric trauma centres amongst rural populations, as rapid access to pediatric trauma centres have been shown to produce superior outcomes with severely injured patients. This dissertation encompasses an analysis of pediatric trauma centre access and socioeconomic status within specific regions of Canada and Israel. Its two principal objectives involve: 1) an analysis of the geographical distribution of major traumas within the child and youth population; and 2) an assessment of the effectiveness of pediatric trauma systems in dealing with these injuries within both of the countries under observation. On a more granular level, the project aims to describe the hotspots for child and youth injury, to identify disadvantaged populations and high risk injury mechanisms and patterns, and to explore the barriers that impede access to appropriate care in both of the study regions. It is also intended to improve the methodology available to researchers in dealing with locational error within injury data. The results will assist decision makers in prioritizing the delivery of health care services and will help direct scarce prevention-related public health resources to high risk populations

A web- based model to support triage location allocation in mass casualty situations

Many aspects of life in North America changed in the aftermath of the terrorist attacks that took place in the United States on September 11, 2001. In addition to the implementation of new security protocols and the strengthening of those already in existence, there were also more subtle changes. Within the medical community, for example, it became evident that existing strategies for managing mass casualty incidents (MCI) were insufficient when dealing with large-scale terrorist attacks (Frykberg 2002; Frykberg 2003). In a position statement made by the American College of Surgeons (2003), it was acknowledged that a smoother integration of rescue, decontamination, triage, stabilization, evacuation and definitive treatment of casualties was required in order to enable the system to provide the best care to the greatest number of casualties in a mass casualty situation (American College of Surgeons 2003; American College of Surgeons 2010). This thesis introduces a web based spatial decision support system (SDSS) intended to assist health care providers at the scene of an MCI in determining the appropriate hospital to which critically injured patients should be evacuated. The model decision-making process utilizes the following factors in determining the evacuation hospital: proximity of the hospital to the MCI, hospital capability and real time bed capacity. The analysis and visualization associated with the SDSS incorporates spatial network analysis as well as specialized algorithms for calculating travel times. This is the first known SDSS to target and attempt to optimize decision-making processes during critical stages of evacuation